EEQI [Environment Quality Index] PyraTime The Problem: Why Good Strategies Fail
The number one reason traders lose capital is not a lack of strategy—it is forced execution in poor environments.
Most indicators (RSI, MACD, Stochastic) are continuously active, generating signals even when the market is dead, choppy, or chaotic. A breakout strategy that prints money in a trend will destroy your account in a consolidation range. A mean-reversion system that works in chop will fail during a parabolic expansion.
The Solution: PyraTime EEQI The Execution Environment Quality Index (EEQI) is a "Gatekeeper" layer for your trading. It does not tell you what to buy or sell; it tells you if you should be trading at all.
By aggregating Volatility, Price Structure, and Efficiency into a single composite score, the EEQI answers the most critical question in discretionary trading: "Is the market efficient enough to deploy capital right now?"
How It Works: The 3 Core Engines
The EEQI calculates a raw "Environment Score" (from -2 to +4) by analyzing three distinct dimensions of price action.
1. Volatility Engine (Usability)
The Logic: Measures the "Alive-ness" of the market using ATR Percentiles.
The Filter: It detects "Dead Zones" (where price is too flat to hit targets) and "Chaos Zones" (where volatility is too dangerous).
Smart Feature (Parabolic Override): If price moves significantly (>2x ATR) in a single candle, the engine recognizes this as "High Momentum" rather than chaos, unlocking Green signals during breakouts.
2. Structure Engine (Bar Quality)
The Logic: Analyzes the relationship between candle bodies, wicks, and overlap.
The Filter: It penalizes "Barbed Wire" price action—candles with long wicks and high overlap—which indicate indecision and algo-chop.
The Goal: We want to trade during "Clean Flow," where candle bodies are large and overlap is low.
3. Efficiency Engine (Directional Flow)
The Logic: Compares Net Displacement (start-to-finish distance) vs. Total Distance Traveled.
The Filter: Identifies "Whipsaw" conditions where price moves a lot but goes nowhere.
Smart Feature (Velocity Lock): If price travels a massive distance quickly, the efficiency requirement is relaxed to catch explosive moves that might otherwise look "messy."
The "Smart Gatekeepers"
Even if the Core Engines look good, the EEQI applies three final safety checks before granting a PRIME status.
Regime Persistence (Stability Check): The market must hold a high score for a set number of bars (default: 1) before the signal turns Green. This prevents "fake-outs" where a single anomaly candle tricks you into entering a bad trend.
Volume Validation (Liquidity Check): Price movement without participation is a trap. The EEQI checks Relative Volume (RVOL). If volume is below average (e.g., lunch hour, holidays, or late-night sessions), the score is capped at "Fair" or "Low Vol," preventing execution in thin liquidity.
Macro Context (HTF Filter): You cannot trade against the higher timeframe. The EEQI checks the trend and volatility of the Higher Timeframe (default: Weekly). If the macro view is compressed or dead, the local signal is vetoed.
How to Read the HUD
The Dashboard (Bottom Right) gives you an instant read on the market state.
🟢 PRIME (+4): Execution Optimal. The market is trending, efficient, and backed by volume. This is the "Green Light" for your strategy.
🔵 FAIR (+1 to +3): Tradeable. Conditions are decent, but one factor (e.g., volume or structure) is imperfect. Exercise caution.
⚪ NEUTRAL (0): Indecision. The market is transitioning. Stand aside.
🟡 BUILDING: Wait. The market is good, but hasn't proven itself yet (Persistence Check).
🟠 POOR / LOW VOL: Chop. Price is messy or lacking participation.
🔴 AVOID (-2): Danger Zone. The market is either dead flat or violently chaotic. Do not trade.
Settings & Customization
The indicator comes with calibrated presets for different asset classes:
Crypto: Tolerates higher volatility and requires stronger efficiency confirmation.
Forex: Stricter dead-zone filters to handle ranging sessions.
Indices: Balanced settings for standard equity hours.
Disclaimer
This tool is designed for environment analysis only. It does not provide buy or sell signals, entry prices, or stop-losses. It is intended to be used as a filter to improve the performance of your own discretionary strategies.
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Lakshmi - Low Volatility Range Breakout (LVRB)⚡️ Overview
The Low Volatility Range Breakout (LVRB) indicator is designed to identify consolidation phases characterized by suppressed volatility and generate actionable signals when price breaks out of these ranges. The underlying premise is rooted in the market principle that periods of low volatility often precede significant directional moves—volatility contraction leads to expansion.
Important Note on Optimization: The default parameter settings of this indicator have been specifically optimized for BTCUSDT on the 2-hour (2H) timeframe. While the indicator can be applied to other instruments and timeframes, users are encouraged to adjust the parameters accordingly to suit different trading conditions and asset characteristics.
This indicator automates the detection of "quiet" accumulation/distribution zones and provides clear visual cues and alerts when a breakout occurs.
⚡️ How to Use
1. Add the indicator to your chart. Default settings are optimized for BTCUSDT 2H.
2. Wait for a gray box to appear—this indicates a qualified low-volatility range is forming.
3. Monitor for breakout signals:
• LONG (green triangle below bar): Price broke above the range. Consider entering a long position.
• SHORT (red triangle above bar): Price broke below the range. Consider entering a short position.
4. Set alerts using "LVRB LONG" or "LVRB SHORT" to receive notifications on confirmed breakouts.
5. Adjust parameters as needed for different instruments or timeframes.
Tip: Combine with volume analysis or trend filters for higher-probability setups.
⚡️ How It Works
1. Low Volatility Bar Detection
A bar is classified as "low volatility" when it meets the following criteria:
• True Range (TR) is at or below the average TR (Simple Moving Average) multiplied by a user-defined threshold.
• (Optional) Candle Body is at or below the average body size multiplied by a separate threshold.
This dual-filter approach helps isolate bars that exhibit genuine compression in both range and directional commitment.
2. Range Box Formation
When consecutive low-volatility bars are detected, the indicator begins constructing a consolidation box:
• The box expands to encompass the high and low of qualifying bars.
• A minimum number of bars and a minimum fraction of low-volatility bars are required for the box to become "qualified" (active).
• A configurable tolerance allows for a limited number of consecutive non-low-vol bars within the sequence, accommodating minor noise without invalidating the range.
• If the box height exceeds a maximum threshold (defined as a multiple of the base ATR at sequence start), the range is invalidated.
3. Breakout Detection
Once a qualified range is established, the indicator monitors for breakouts:
• Wick Mode: Requires both a wick pierce beyond the range boundary AND a close outside the range.
• Close Mode: Requires only a close beyond the range boundary.
• (Optional) Breakout Body Filter: The breakout candle's body must exceed a multiple of the average body size at range formation.
• (Optional) Candle Direction Filter: Bullish breakouts require a green candle; bearish breakouts require a red candle.
Signals are displayed in real-time and confirmed upon bar close.
⚡️ Inputs & Parameters
• Volatility Window: Lookback period for calculating average TR and average body size.
• TR Multiplier: A bar's TR must be ≤ avgTR × this value to qualify as low-vol.
• Body Multiplier: A bar's body must be ≤ avgBody × this value (if body filter is enabled).
• Use Body Filter: Toggle the body size filter on/off.
• Min Bars in Box: Minimum number of bars required for a range to become qualified.
• Min Low-Vol Fraction: Minimum proportion of bars in the sequence that must be low-vol.
• Allowed Consecutive Non-Low-Vol Bars: Tolerance for consecutive bars that do not meet low-vol criteria.
• Max Box Height: Maximum allowed range height as a multiple of the base ATR.
• Breakout Mode: Choose between "Wick" (pierce + close) or "Close" (close only).
• Breakout Body Multiplier: Require breakout candle body ≥ avgBody × this value (1.0 = OFF).
• Require Candle Direction: Enforce green candle for LONG, red candle for SHORT.
⚡️ Visual Features
• Consolidation Boxes: Displayed in neutral (gray) color during formation. Upon a confirmed breakout, the box is colored green for bullish breakouts or red for bearish breakouts.
• Breakout Signals:
• LONG: Green upward triangle displayed below the price bar with "LONG" label.
• SHORT: Red downward triangle displayed above the price bar with "SHORT" label.
• Range Levels: Optional horizontal plots for the active range's high and low.
• Invalidated Boxes: Optionally retained in neutral (gray) color or deleted from the chart.
• Full Customization: Colors, transparency, and border width are all adjustable.
⚡️ Alerts
Two alert conditions are available:
• LVRB LONG: Triggered on a confirmed bullish breakout (bar close).
• LVRB SHORT: Triggered on a confirmed bearish breakout (bar close).
⚡️ Use Cases
• Breakout Trading: Enter positions when price escapes a well-defined low-volatility range.
• Volatility Expansion Plays: Anticipate increased volatility following periods of compression.
• Filtering Choppy Markets: Avoid trading during extended consolidation; wait for confirmed breakouts.
• Multi-Timeframe Analysis: Use on higher timeframes to identify major consolidation zones.
⚡️ Notes
• Best used in conjunction with volume analysis, trend context, or support/resistance levels for confirmation.
• Performance varies across instruments and timeframes; backtesting and parameter optimization are recommended.
⚡️ Credits
Developed by Lakshmi. Inspired by volatility contraction principles and range breakout methodologies.
⚡️ Disclaimer
This indicator is provided for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a guarantee of profits. Trading financial instruments involves substantial risk, and you may lose more than your initial investment. Past performance, whether indicated by backtesting or historical analysis, does not guarantee future results. The use of this indicator does not ensure or promise any profits or protection against losses. Users are solely responsible for their own trading decisions and should conduct their own research and/or consult with a qualified financial advisor before making any investment decisions. By using this indicator, you acknowledge and accept that you bear full responsibility for any trading outcomes.
MFI Volume Profile [Kodexius]The MFI Volume Profile indicator blends a classic volume profile with the Money Flow Index so you can see not only where volume traded, but also how strong the buying or selling pressure was at those prices. Instead of showing a simple horizontal histogram of volume, this tool adds a money flow dimension and turns the profile into a price volume momentum heat map.
The script scans a user controlled lookback window and builds a set of price levels between the lowest and highest price in that period. For every bar inside that window, its volume is distributed across the price levels that the bar actually touched, and that volume is combined with the bar’s MFI value. This creates a volume weighted average MFI for each price level, so every row of the profile knows both how much volume traded there and what the typical money flow condition was when that volume appeared.
On the chart, the indicator plots a stack of horizontal boxes to the right of current price. The length of each box represents the relative amount of volume at that price, while the color represents the average MFI there. Levels with stronger positive money flow will lean toward warmer shades, and levels with weaker or negative money flow will lean toward cooler or more neutral shades inside the configured MFI band. Each row is also labeled in the format Volume , so you can instantly read the exact volume and money flow value at that level instead of guessing.
This gives you a detailed map of where the market really cared about price, and whether that interest came with strong inflow or outflow. It can help you spot areas of accumulation, distribution, absorption, or exhaustion, and it does so in a compact visual that sits next to price without cluttering the candles themselves.
Features
Combined volume profile and MFI weighting
The indicator builds a volume profile over a user selected lookback and enriches each price row with a volume weighted average MFI. This lets you study both participation and money flow at the same price level.
Volume distributed across the bar price range
For every bar in the window, volume is not assigned to a single price. Instead, it is proportionally distributed across all price rows between the bar low and bar high. This creates a smoother and more realistic profile of where trading actually happened.
MFI based color gradient between 30 and 70
Each price row is colored according to its average MFI. The gradient is anchored between MFI values of 30 and 70, which covers typical oversold, neutral and overbought zones. This makes strong demand or distribution areas easier to spot visually.
Configurable structure resolution and depth
Main user inputs are the lookback length, the number of rows, the width of the profile in bars, and the label text size. You can quickly switch between coarse profiles for a big picture and higher resolution profiles for detailed structure.
Numeric labels with volume and MFI per row
Every box is labeled with the total volume at that level and the average MFI for that level, in the format Volume . This gives you exact values while still keeping the visual profile clean and compact.
Calculations
Money Flow Index calculation
currentMfi is calculated once using ta.mfi(hlc3, mfiLen) as usual,
Creation of the profileBins array
The script creates an array named profileBins that will hold one VPBin element per price row.
Each VPBin contains
volume which is the total volume accumulated at that price row
mfiProduct which is the sum of volume multiplied by MFI for that row
The loop;
for i = 0 to rowCount - 1 by 1
array.push(profileBins, VPBin.new(0.0, 0.0))
pre allocates a clean structure with zero values for all rows.
Finding highest and lowest price across the lookback
The script starts from the current bar high and low, then walks backward through the lookback window
for i = 0 to lookback - 1 by 1
highestPrice := math.max(highestPrice, high )
lowestPrice := math.min(lowestPrice, low )
After this loop, highestPrice and lowestPrice define the full price range covered by the chosen lookback.
Price range and step size for rows
The code computes
float rangePrice = highestPrice - lowestPrice
rangePrice := rangePrice == 0 ? syminfo.mintick : rangePrice
float step = rangePrice / rowCount
rangePrice is the total height of the profile in price terms. If the range is zero, the script replaces it with the minimum tick size for the symbol. Then step is the price height of each row. This step size is used to map any price into a row index.
Processing each bar in the lookback
For every bar index i inside the lookback, the script checks that currentMfi is not missing. If it is valid, it reads the bar high, low, volume and MFI
float barTop = high
float barBottom = low
float barVol = volume
float barMfi = currentMfi
Mapping bar prices to bin indices
The bar high and low are converted into row indices using the known lowestPrice and step
int indexTop = math.floor((barTop - lowestPrice) / step)
int indexBottom = math.floor((barBottom - lowestPrice) / step)
Then the indices are clamped into valid bounds so they stay between zero and rowCount - 1. This ensures that every bar contributes only inside the profile range
Splitting bar volume across all covered bins
Once the top and bottom indices are known, the script calculates how many rows the bar spans
int coveredBins = indexTop - indexBottom + 1
float volPerBin = barVol / coveredBins
float mfiPerBin = volPerBin * barMfi
Here the total bar volume is divided equally across all rows that the bar touches. For each of those rows, the same fraction of volume and volume times MFI is used.
Accumulating into each VPBin
Finally, a nested loop iterates from indexBottom to indexTop and updates the corresponding VPBin
for k = indexBottom to indexTop by 1
VPBin binData = array.get(profileBins, k)
binData.volume := binData.volume + volPerBin
binData.mfiProduct := binData.mfiProduct + mfiPerBin
Over all bars in the lookback window, each row builds up
total volume at that price range
total volume times MFI at that price range
Later, during the drawing stage, the script computes
avgMfi = bin.mfiProduct / bin.volume
for each row. This is the volume weighted average MFI used both for coloring the box and for the numeric MFI value shown in the label Volume .
Dimensional Resonance ProtocolDimensional Resonance Protocol
🌀 CORE INNOVATION: PHASE SPACE RECONSTRUCTION & EMERGENCE DETECTION
The Dimensional Resonance Protocol represents a paradigm shift from traditional technical analysis to complexity science. Rather than measuring price levels or indicator crossovers, DRP reconstructs the hidden attractor governing market dynamics using Takens' embedding theorem, then detects emergence —the rare moments when multiple dimensions of market behavior spontaneously synchronize into coherent, predictable states.
The Complexity Hypothesis:
Markets are not simple oscillators or random walks—they are complex adaptive systems existing in high-dimensional phase space. Traditional indicators see only shadows (one-dimensional projections) of this higher-dimensional reality. DRP reconstructs the full phase space using time-delay embedding, revealing the true structure of market dynamics.
Takens' Embedding Theorem (1981):
A profound mathematical result from dynamical systems theory: Given a time series from a complex system, we can reconstruct its full phase space by creating delayed copies of the observation.
Mathematical Foundation:
From single observable x(t), create embedding vectors:
X(t) =
Where:
• d = Embedding dimension (default 5)
• τ = Time delay (default 3 bars)
• x(t) = Price or return at time t
Key Insight: If d ≥ 2D+1 (where D is the true attractor dimension), this embedding is topologically equivalent to the actual system dynamics. We've reconstructed the hidden attractor from a single price series.
Why This Matters:
Markets appear random in one dimension (price chart). But in reconstructed phase space, structure emerges—attractors, limit cycles, strange attractors. When we identify these structures, we can detect:
• Stable regions : Predictable behavior (trade opportunities)
• Chaotic regions : Unpredictable behavior (avoid trading)
• Critical transitions : Phase changes between regimes
Phase Space Magnitude Calculation:
phase_magnitude = sqrt(Σ ² for i = 0 to d-1)
This measures the "energy" or "momentum" of the market trajectory through phase space. High magnitude = strong directional move. Low magnitude = consolidation.
📊 RECURRENCE QUANTIFICATION ANALYSIS (RQA)
Once phase space is reconstructed, we analyze its recurrence structure —when does the system return near previous states?
Recurrence Plot Foundation:
A recurrence occurs when two phase space points are closer than threshold ε:
R(i,j) = 1 if ||X(i) - X(j)|| < ε, else 0
This creates a binary matrix showing when the system revisits similar states.
Key RQA Metrics:
1. Recurrence Rate (RR):
RR = (Number of recurrent points) / (Total possible pairs)
• RR near 0: System never repeats (highly stochastic)
• RR = 0.1-0.3: Moderate recurrence (tradeable patterns)
• RR > 0.5: System stuck in attractor (ranging market)
• RR near 1: System frozen (no dynamics)
Interpretation: Moderate recurrence is optimal —patterns exist but market isn't stuck.
2. Determinism (DET):
Measures what fraction of recurrences form diagonal structures in the recurrence plot. Diagonals indicate deterministic evolution (trajectory follows predictable paths).
DET = (Recurrence points on diagonals) / (Total recurrence points)
• DET < 0.3: Random dynamics
• DET = 0.3-0.7: Moderate determinism (patterns with noise)
• DET > 0.7: Strong determinism (technical patterns reliable)
Trading Implication: Signals are prioritized when DET > 0.3 (deterministic state) and RR is moderate (not stuck).
Threshold Selection (ε):
Default ε = 0.10 × std_dev means two states are "recurrent" if within 10% of a standard deviation. This is tight enough to require genuine similarity but loose enough to find patterns.
🔬 PERMUTATION ENTROPY: COMPLEXITY MEASUREMENT
Permutation entropy measures the complexity of a time series by analyzing the distribution of ordinal patterns.
Algorithm (Bandt & Pompe, 2002):
1. Take overlapping windows of length n (default n=4)
2. For each window, record the rank order pattern
Example: → pattern (ranks from lowest to highest)
3. Count frequency of each possible pattern
4. Calculate Shannon entropy of pattern distribution
Mathematical Formula:
H_perm = -Σ p(π) · ln(p(π))
Where π ranges over all n! possible permutations, p(π) is the probability of pattern π.
Normalized to :
H_norm = H_perm / ln(n!)
Interpretation:
• H < 0.3 : Very ordered, crystalline structure (strong trending)
• H = 0.3-0.5 : Ordered regime (tradeable with patterns)
• H = 0.5-0.7 : Moderate complexity (mixed conditions)
• H = 0.7-0.85 : Complex dynamics (challenging to trade)
• H > 0.85 : Maximum entropy (nearly random, avoid)
Entropy Regime Classification:
DRP classifies markets into five entropy regimes:
• CRYSTALLINE (H < 0.3): Maximum order, persistent trends
• ORDERED (H < 0.5): Clear patterns, momentum strategies work
• MODERATE (H < 0.7): Mixed dynamics, adaptive required
• COMPLEX (H < 0.85): High entropy, mean reversion better
• CHAOTIC (H ≥ 0.85): Near-random, minimize trading
Why Permutation Entropy?
Unlike traditional entropy methods requiring binning continuous data (losing information), permutation entropy:
• Works directly on time series
• Robust to monotonic transformations
• Computationally efficient
• Captures temporal structure, not just distribution
• Immune to outliers (uses ranks, not values)
⚡ LYAPUNOV EXPONENT: CHAOS vs STABILITY
The Lyapunov exponent λ measures sensitivity to initial conditions —the hallmark of chaos.
Physical Meaning:
Two trajectories starting infinitely close will diverge at exponential rate e^(λt):
Distance(t) ≈ Distance(0) × e^(λt)
Interpretation:
• λ > 0 : Positive Lyapunov exponent = CHAOS
- Small errors grow exponentially
- Long-term prediction impossible
- System is sensitive, unpredictable
- AVOID TRADING
• λ ≈ 0 : Near-zero = CRITICAL STATE
- Edge of chaos
- Transition zone between order and disorder
- Moderate predictability
- PROCEED WITH CAUTION
• λ < 0 : Negative Lyapunov exponent = STABLE
- Small errors decay
- Trajectories converge
- System is predictable
- OPTIMAL FOR TRADING
Estimation Method:
DRP estimates λ by tracking how quickly nearby states diverge over a rolling window (default 20 bars):
For each bar i in window:
δ₀ = |x - x | (initial separation)
δ₁ = |x - x | (previous separation)
if δ₁ > 0:
ratio = δ₀ / δ₁
log_ratios += ln(ratio)
λ ≈ average(log_ratios)
Stability Classification:
• STABLE : λ < 0 (negative growth rate)
• CRITICAL : |λ| < 0.1 (near neutral)
• CHAOTIC : λ > 0.2 (strong positive growth)
Signal Filtering:
By default, NEXUS requires λ < 0 (stable regime) for signal confirmation. This filters out trades during chaotic periods when technical patterns break down.
📐 HIGUCHI FRACTAL DIMENSION
Fractal dimension measures self-similarity and complexity of the price trajectory.
Theoretical Background:
A curve's fractal dimension D ranges from 1 (smooth line) to 2 (space-filling curve):
• D ≈ 1.0 : Smooth, persistent trending
• D ≈ 1.5 : Random walk (Brownian motion)
• D ≈ 2.0 : Highly irregular, space-filling
Higuchi Method (1988):
For a time series of length N, construct k different curves by taking every k-th point:
L(k) = (1/k) × Σ|x - x | × (N-1)/(⌊(N-m)/k⌋ × k)
For different values of k (1 to k_max), calculate L(k). The fractal dimension is the slope of log(L(k)) vs log(1/k):
D = slope of log(L) vs log(1/k)
Market Interpretation:
• D < 1.35 : Strong trending, persistent (Hurst > 0.5)
- TRENDING regime
- Momentum strategies favored
- Breakouts likely to continue
• D = 1.35-1.45 : Moderate persistence
- PERSISTENT regime
- Trend-following with caution
- Patterns have meaning
• D = 1.45-1.55 : Random walk territory
- RANDOM regime
- Efficiency hypothesis holds
- Technical analysis least reliable
• D = 1.55-1.65 : Anti-persistent (mean-reverting)
- ANTI-PERSISTENT regime
- Oscillator strategies work
- Overbought/oversold meaningful
• D > 1.65 : Highly complex, choppy
- COMPLEX regime
- Avoid directional bets
- Wait for regime change
Signal Filtering:
Resonance signals (secondary signal type) require D < 1.5, indicating trending or persistent dynamics where momentum has meaning.
🔗 TRANSFER ENTROPY: CAUSAL INFORMATION FLOW
Transfer entropy measures directed causal influence between time series—not just correlation, but actual information transfer.
Schreiber's Definition (2000):
Transfer entropy from X to Y measures how much knowing X's past reduces uncertainty about Y's future:
TE(X→Y) = H(Y_future | Y_past) - H(Y_future | Y_past, X_past)
Where H is Shannon entropy.
Key Properties:
1. Directional : TE(X→Y) ≠ TE(Y→X) in general
2. Non-linear : Detects complex causal relationships
3. Model-free : No assumptions about functional form
4. Lag-independent : Captures delayed causal effects
Three Causal Flows Measured:
1. Volume → Price (TE_V→P):
Measures how much volume patterns predict price changes.
• TE > 0 : Volume provides predictive information about price
- Institutional participation driving moves
- Volume confirms direction
- High reliability
• TE ≈ 0 : No causal flow (weak volume/price relationship)
- Volume uninformative
- Caution on signals
• TE < 0 (rare): Suggests price leading volume
- Potentially manipulated or thin market
2. Volatility → Momentum (TE_σ→M):
Does volatility expansion predict momentum changes?
• Positive TE : Volatility precedes momentum shifts
- Breakout dynamics
- Regime transitions
3. Structure → Price (TE_S→P):
Do support/resistance patterns causally influence price?
• Positive TE : Structural levels have causal impact
- Technical levels matter
- Market respects structure
Net Causal Flow:
Net_Flow = TE_V→P + 0.5·TE_σ→M + TE_S→P
• Net > +0.1 : Bullish causal structure
• Net < -0.1 : Bearish causal structure
• |Net| < 0.1 : Neutral/unclear causation
Causal Gate:
For signal confirmation, NEXUS requires:
• Buy signals : TE_V→P > 0 AND Net_Flow > 0.05
• Sell signals : TE_V→P > 0 AND Net_Flow < -0.05
This ensures volume is actually driving price (causal support exists), not just correlated noise.
Implementation Note:
Computing true transfer entropy requires discretizing continuous data into bins (default 6 bins) and estimating joint probability distributions. NEXUS uses a hybrid approach combining TE theory with autocorrelation structure and lagged cross-correlation to approximate information transfer in computationally efficient manner.
🌊 HILBERT PHASE COHERENCE
Phase coherence measures synchronization across market dimensions using Hilbert transform analysis.
Hilbert Transform Theory:
For a signal x(t), the Hilbert transform H (t) creates an analytic signal:
z(t) = x(t) + i·H (t) = A(t)·e^(iφ(t))
Where:
• A(t) = Instantaneous amplitude
• φ(t) = Instantaneous phase
Instantaneous Phase:
φ(t) = arctan(H (t) / x(t))
The phase represents where the signal is in its natural cycle—analogous to position on a unit circle.
Four Dimensions Analyzed:
1. Momentum Phase : Phase of price rate-of-change
2. Volume Phase : Phase of volume intensity
3. Volatility Phase : Phase of ATR cycles
4. Structure Phase : Phase of position within range
Phase Locking Value (PLV):
For two signals with phases φ₁(t) and φ₂(t), PLV measures phase synchronization:
PLV = |⟨e^(i(φ₁(t) - φ₂(t)))⟩|
Where ⟨·⟩ is time average over window.
Interpretation:
• PLV = 0 : Completely random phase relationship (no synchronization)
• PLV = 0.5 : Moderate phase locking
• PLV = 1 : Perfect synchronization (phases locked)
Pairwise PLV Calculations:
• PLV_momentum-volume : Are momentum and volume cycles synchronized?
• PLV_momentum-structure : Are momentum cycles aligned with structure?
• PLV_volume-structure : Are volume and structural patterns in phase?
Overall Phase Coherence:
Coherence = (PLV_mom-vol + PLV_mom-struct + PLV_vol-struct) / 3
Signal Confirmation:
Emergence signals require coherence ≥ threshold (default 0.70):
• Below 0.70: Dimensions not synchronized, no coherent market state
• Above 0.70: Dimensions in phase, coherent behavior emerging
Coherence Direction:
The summed phase angles indicate whether synchronized dimensions point bullish or bearish:
Direction = sin(φ_momentum) + 0.5·sin(φ_volume) + 0.5·sin(φ_structure)
• Direction > 0 : Phases pointing upward (bullish synchronization)
• Direction < 0 : Phases pointing downward (bearish synchronization)
🌀 EMERGENCE SCORE: MULTI-DIMENSIONAL ALIGNMENT
The emergence score aggregates all complexity metrics into a single 0-1 value representing market coherence.
Eight Components with Weights:
1. Phase Coherence (20%):
Direct contribution: coherence × 0.20
Measures dimensional synchronization.
2. Entropy Regime (15%):
Contribution: (0.6 - H_perm) / 0.6 × 0.15 if H < 0.6, else 0
Rewards low entropy (ordered, predictable states).
3. Lyapunov Stability (12%):
• λ < 0 (stable): +0.12
• |λ| < 0.1 (critical): +0.08
• λ > 0.2 (chaotic): +0.0
Requires stable, predictable dynamics.
4. Fractal Dimension Trending (12%):
Contribution: (1.45 - D) / 0.45 × 0.12 if D < 1.45, else 0
Rewards trending fractal structure (D < 1.45).
5. Dimensional Resonance (12%):
Contribution: |dimensional_resonance| × 0.12
Measures alignment across momentum, volume, structure, volatility dimensions.
6. Causal Flow Strength (9%):
Contribution: |net_causal_flow| × 0.09
Rewards strong causal relationships.
7. Phase Space Embedding (10%):
Contribution: min(|phase_magnitude_norm|, 3.0) / 3.0 × 0.10 if |magnitude| > 1.0
Rewards strong trajectory in reconstructed phase space.
8. Recurrence Quality (10%):
Contribution: determinism × 0.10 if DET > 0.3 AND 0.1 < RR < 0.8
Rewards deterministic patterns with moderate recurrence.
Total Emergence Score:
E = Σ(components) ∈
Capped at 1.0 maximum.
Emergence Direction:
Separate calculation determining bullish vs bearish:
• Dimensional resonance sign
• Net causal flow sign
• Phase magnitude correlation with momentum
Signal Threshold:
Default emergence_threshold = 0.75 means 75% of maximum possible emergence score required to trigger signals.
Why Emergence Matters:
Traditional indicators measure single dimensions. Emergence detects self-organization —when multiple independent dimensions spontaneously align. This is the market equivalent of a phase transition in physics, where microscopic chaos gives way to macroscopic order.
These are the highest-probability trade opportunities because the entire system is resonating in the same direction.
🎯 SIGNAL GENERATION: EMERGENCE vs RESONANCE
DRP generates two tiers of signals with different requirements:
TIER 1: EMERGENCE SIGNALS (Primary)
Requirements:
1. Emergence score ≥ threshold (default 0.75)
2. Phase coherence ≥ threshold (default 0.70)
3. Emergence direction > 0.2 (bullish) or < -0.2 (bearish)
4. Causal gate passed (if enabled): TE_V→P > 0 and net_flow confirms direction
5. Stability zone (if enabled): λ < 0 or |λ| < 0.1
6. Price confirmation: Close > open (bulls) or close < open (bears)
7. Cooldown satisfied: bars_since_signal ≥ cooldown_period
EMERGENCE BUY:
• All above conditions met with bullish direction
• Market has achieved coherent bullish state
• Multiple dimensions synchronized upward
EMERGENCE SELL:
• All above conditions met with bearish direction
• Market has achieved coherent bearish state
• Multiple dimensions synchronized downward
Premium Emergence:
When signal_quality (emergence_score × phase_coherence) > 0.7:
• Displayed as ★ star symbol
• Highest conviction trades
• Maximum dimensional alignment
Standard Emergence:
When signal_quality 0.5-0.7:
• Displayed as ◆ diamond symbol
• Strong signals but not perfect alignment
TIER 2: RESONANCE SIGNALS (Secondary)
Requirements:
1. Dimensional resonance > +0.6 (bullish) or < -0.6 (bearish)
2. Fractal dimension < 1.5 (trending/persistent regime)
3. Price confirmation matches direction
4. NOT in chaotic regime (λ < 0.2)
5. Cooldown satisfied
6. NO emergence signal firing (resonance is fallback)
RESONANCE BUY:
• Dimensional alignment without full emergence
• Trending fractal structure
• Moderate conviction
RESONANCE SELL:
• Dimensional alignment without full emergence
• Bearish resonance with trending structure
• Moderate conviction
Displayed as small ▲/▼ triangles with transparency.
Signal Hierarchy:
IF emergence conditions met:
Fire EMERGENCE signal (★ or ◆)
ELSE IF resonance conditions met:
Fire RESONANCE signal (▲ or ▼)
ELSE:
No signal
Cooldown System:
After any signal fires, cooldown_period (default 5 bars) must elapse before next signal. This prevents signal clustering during persistent conditions.
Cooldown tracks using bar_index:
bars_since_signal = current_bar_index - last_signal_bar_index
cooldown_ok = bars_since_signal >= cooldown_period
🎨 VISUAL SYSTEM: MULTI-LAYER COMPLEXITY
DRP provides rich visual feedback across four distinct layers:
LAYER 1: COHERENCE FIELD (Background)
Colored background intensity based on phase coherence:
• No background : Coherence < 0.5 (incoherent state)
• Faint glow : Coherence 0.5-0.7 (building coherence)
• Stronger glow : Coherence > 0.7 (coherent state)
Color:
• Cyan/teal: Bullish coherence (direction > 0)
• Red/magenta: Bearish coherence (direction < 0)
• Blue: Neutral coherence (direction ≈ 0)
Transparency: 98 minus (coherence_intensity × 10), so higher coherence = more visible.
LAYER 2: STABILITY/CHAOS ZONES
Background color indicating Lyapunov regime:
• Green tint (95% transparent): λ < 0, STABLE zone
- Safe to trade
- Patterns meaningful
• Gold tint (90% transparent): |λ| < 0.1, CRITICAL zone
- Edge of chaos
- Moderate risk
• Red tint (85% transparent): λ > 0.2, CHAOTIC zone
- Avoid trading
- Unpredictable behavior
LAYER 3: DIMENSIONAL RIBBONS
Three EMAs representing dimensional structure:
• Fast ribbon : EMA(8) in cyan/teal (fast dynamics)
• Medium ribbon : EMA(21) in blue (intermediate)
• Slow ribbon : EMA(55) in red/magenta (slow dynamics)
Provides visual reference for multi-scale structure without cluttering with raw phase space data.
LAYER 4: CAUSAL FLOW LINE
A thicker line plotted at EMA(13) colored by net causal flow:
• Cyan/teal : Net_flow > +0.1 (bullish causation)
• Red/magenta : Net_flow < -0.1 (bearish causation)
• Gray : |Net_flow| < 0.1 (neutral causation)
Shows real-time direction of information flow.
EMERGENCE FLASH:
Strong background flash when emergence signals fire:
• Cyan flash for emergence buy
• Red flash for emergence sell
• 80% transparency for visibility without obscuring price
📊 COMPREHENSIVE DASHBOARD
Real-time monitoring of all complexity metrics:
HEADER:
• 🌀 DRP branding with gold accent
CORE METRICS:
EMERGENCE:
• Progress bar (█ filled, ░ empty) showing 0-100%
• Percentage value
• Direction arrow (↗ bull, ↘ bear, → neutral)
• Color-coded: Green/gold if active, gray if low
COHERENCE:
• Progress bar showing phase locking value
• Percentage value
• Checkmark ✓ if ≥ threshold, circle ○ if below
• Color-coded: Cyan if coherent, gray if not
COMPLEXITY SECTION:
ENTROPY:
• Regime name (CRYSTALLINE/ORDERED/MODERATE/COMPLEX/CHAOTIC)
• Numerical value (0.00-1.00)
• Color: Green (ordered), gold (moderate), red (chaotic)
LYAPUNOV:
• State (STABLE/CRITICAL/CHAOTIC)
• Numerical value (typically -0.5 to +0.5)
• Status indicator: ● stable, ◐ critical, ○ chaotic
• Color-coded by state
FRACTAL:
• Regime (TRENDING/PERSISTENT/RANDOM/ANTI-PERSIST/COMPLEX)
• Dimension value (1.0-2.0)
• Color: Cyan (trending), gold (random), red (complex)
PHASE-SPACE:
• State (STRONG/ACTIVE/QUIET)
• Normalized magnitude value
• Parameters display: d=5 τ=3
CAUSAL SECTION:
CAUSAL:
• Direction (BULL/BEAR/NEUTRAL)
• Net flow value
• Flow indicator: →P (to price), P← (from price), ○ (neutral)
V→P:
• Volume-to-price transfer entropy
• Small display showing specific TE value
DIMENSIONAL SECTION:
RESONANCE:
• Progress bar of absolute resonance
• Signed value (-1 to +1)
• Color-coded by direction
RECURRENCE:
• Recurrence rate percentage
• Determinism percentage display
• Color-coded: Green if high quality
STATE SECTION:
STATE:
• Current mode: EMERGENCE / RESONANCE / CHAOS / SCANNING
• Icon: 🚀 (emergence buy), 💫 (emergence sell), ▲ (resonance buy), ▼ (resonance sell), ⚠ (chaos), ◎ (scanning)
• Color-coded by state
SIGNALS:
• E: count of emergence signals
• R: count of resonance signals
⚙️ KEY PARAMETERS EXPLAINED
Phase Space Configuration:
• Embedding Dimension (3-10, default 5): Reconstruction dimension
- Low (3-4): Simple dynamics, faster computation
- Medium (5-6): Balanced (recommended)
- High (7-10): Complex dynamics, more data needed
- Rule: d ≥ 2D+1 where D is true dimension
• Time Delay (τ) (1-10, default 3): Embedding lag
- Fast markets: 1-2
- Normal: 3-4
- Slow markets: 5-10
- Optimal: First minimum of mutual information (often 2-4)
• Recurrence Threshold (ε) (0.01-0.5, default 0.10): Phase space proximity
- Tight (0.01-0.05): Very similar states only
- Medium (0.08-0.15): Balanced
- Loose (0.20-0.50): Liberal matching
Entropy & Complexity:
• Permutation Order (3-7, default 4): Pattern length
- Low (3): 6 patterns, fast but coarse
- Medium (4-5): 24-120 patterns, balanced
- High (6-7): 720-5040 patterns, fine-grained
- Note: Requires window >> order! for stability
• Entropy Window (15-100, default 30): Lookback for entropy
- Short (15-25): Responsive to changes
- Medium (30-50): Stable measure
- Long (60-100): Very smooth, slow adaptation
• Lyapunov Window (10-50, default 20): Stability estimation window
- Short (10-15): Fast chaos detection
- Medium (20-30): Balanced
- Long (40-50): Stable λ estimate
Causal Inference:
• Enable Transfer Entropy (default ON): Causality analysis
- Keep ON for full system functionality
• TE History Length (2-15, default 5): Causal lookback
- Short (2-4): Quick causal detection
- Medium (5-8): Balanced
- Long (10-15): Deep causal analysis
• TE Discretization Bins (4-12, default 6): Binning granularity
- Few (4-5): Coarse, robust, needs less data
- Medium (6-8): Balanced
- Many (9-12): Fine-grained, needs more data
Phase Coherence:
• Enable Phase Coherence (default ON): Synchronization detection
- Keep ON for emergence detection
• Coherence Threshold (0.3-0.95, default 0.70): PLV requirement
- Loose (0.3-0.5): More signals, lower quality
- Balanced (0.6-0.75): Recommended
- Strict (0.8-0.95): Rare, highest quality
• Hilbert Smoothing (3-20, default 8): Phase smoothing
- Low (3-5): Responsive, noisier
- Medium (6-10): Balanced
- High (12-20): Smooth, more lag
Fractal Analysis:
• Enable Fractal Dimension (default ON): Complexity measurement
- Keep ON for full analysis
• Fractal K-max (4-20, default 8): Scaling range
- Low (4-6): Faster, less accurate
- Medium (7-10): Balanced
- High (12-20): Accurate, slower
• Fractal Window (30-200, default 50): FD lookback
- Short (30-50): Responsive FD
- Medium (60-100): Stable FD
- Long (120-200): Very smooth FD
Emergence Detection:
• Emergence Threshold (0.5-0.95, default 0.75): Minimum coherence
- Sensitive (0.5-0.65): More signals
- Balanced (0.7-0.8): Recommended
- Strict (0.85-0.95): Rare signals
• Require Causal Gate (default ON): TE confirmation
- ON: Only signal when causality confirms
- OFF: Allow signals without causal support
• Require Stability Zone (default ON): Lyapunov filter
- ON: Only signal when λ < 0 (stable) or |λ| < 0.1 (critical)
- OFF: Allow signals in chaotic regimes (risky)
• Signal Cooldown (1-50, default 5): Minimum bars between signals
- Fast (1-3): Rapid signal generation
- Normal (4-8): Balanced
- Slow (10-20): Very selective
- Ultra (25-50): Only major regime changes
Signal Configuration:
• Momentum Period (5-50, default 14): ROC calculation
• Structure Lookback (10-100, default 20): Support/resistance range
• Volatility Period (5-50, default 14): ATR calculation
• Volume MA Period (10-50, default 20): Volume normalization
Visual Settings:
• Customizable color scheme for all elements
• Toggle visibility for each layer independently
• Dashboard position (4 corners) and size (tiny/small/normal)
🎓 PROFESSIONAL USAGE PROTOCOL
Phase 1: System Familiarization (Week 1)
Goal: Understand complexity metrics and dashboard interpretation
Setup:
• Enable all features with default parameters
• Watch dashboard metrics for 500+ bars
• Do NOT trade yet
Actions:
• Observe emergence score patterns relative to price moves
• Note coherence threshold crossings and subsequent price action
• Watch entropy regime transitions (ORDERED → COMPLEX → CHAOTIC)
• Correlate Lyapunov state with signal reliability
• Track which signals appear (emergence vs resonance frequency)
Key Learning:
• When does emergence peak? (usually before major moves)
• What entropy regime produces best signals? (typically ORDERED or MODERATE)
• Does your instrument respect stability zones? (stable λ = better signals)
Phase 2: Parameter Optimization (Week 2)
Goal: Tune system to instrument characteristics
Requirements:
• Understand basic dashboard metrics from Phase 1
• Have 1000+ bars of history loaded
Embedding Dimension & Time Delay:
• If signals very rare: Try lower dimension (d=3-4) or shorter delay (τ=2)
• If signals too frequent: Try higher dimension (d=6-7) or longer delay (τ=4-5)
• Sweet spot: 4-8 emergence signals per 100 bars
Coherence Threshold:
• Check dashboard: What's typical coherence range?
• If coherence rarely exceeds 0.70: Lower threshold to 0.60-0.65
• If coherence often >0.80: Can raise threshold to 0.75-0.80
• Goal: Signals fire during top 20-30% of coherence values
Emergence Threshold:
• If too few signals: Lower to 0.65-0.70
• If too many signals: Raise to 0.80-0.85
• Balance with coherence threshold—both must be met
Phase 3: Signal Quality Assessment (Weeks 3-4)
Goal: Verify signals have edge via paper trading
Requirements:
• Parameters optimized per Phase 2
• 50+ signals generated
• Detailed notes on each signal
Paper Trading Protocol:
• Take EVERY emergence signal (★ and ◆)
• Optional: Take resonance signals (▲/▼) separately to compare
• Use simple exit: 2R target, 1R stop (ATR-based)
• Track: Win rate, average R-multiple, maximum consecutive losses
Quality Metrics:
• Premium emergence (★) : Should achieve >55% WR
• Standard emergence (◆) : Should achieve >50% WR
• Resonance signals : Should achieve >45% WR
• Overall : If <45% WR, system not suitable for this instrument/timeframe
Red Flags:
• Win rate <40%: Wrong instrument or parameters need major adjustment
• Max consecutive losses >10: System not working in current regime
• Profit factor <1.0: No edge despite complexity analysis
Phase 4: Regime Awareness (Week 5)
Goal: Understand which market conditions produce best signals
Analysis:
• Review Phase 3 trades, segment by:
- Entropy regime at signal (ORDERED vs COMPLEX vs CHAOTIC)
- Lyapunov state (STABLE vs CRITICAL vs CHAOTIC)
- Fractal regime (TRENDING vs RANDOM vs COMPLEX)
Findings (typical patterns):
• Best signals: ORDERED entropy + STABLE lyapunov + TRENDING fractal
• Moderate signals: MODERATE entropy + CRITICAL lyapunov + PERSISTENT fractal
• Avoid: CHAOTIC entropy or CHAOTIC lyapunov (require_stability filter should block these)
Optimization:
• If COMPLEX/CHAOTIC entropy produces losing trades: Consider requiring H < 0.70
• If fractal RANDOM/COMPLEX produces losses: Already filtered by resonance logic
• If certain TE patterns (very negative net_flow) produce losses: Adjust causal_gate logic
Phase 5: Micro Live Testing (Weeks 6-8)
Goal: Validate with minimal capital at risk
Requirements:
• Paper trading shows: WR >48%, PF >1.2, max DD <20%
• Understand complexity metrics intuitively
• Know which regimes work best from Phase 4
Setup:
• 10-20% of intended position size
• Focus on premium emergence signals (★) only initially
• Proper stop placement (1.5-2.0 ATR)
Execution Notes:
• Emergence signals can fire mid-bar as metrics update
• Use alerts for signal detection
• Entry on close of signal bar or next bar open
• DO NOT chase—if price gaps away, skip the trade
Comparison:
• Your live results should track within 10-15% of paper results
• If major divergence: Execution issues (slippage, timing) or parameters changed
Phase 6: Full Deployment (Month 3+)
Goal: Scale to full size over time
Requirements:
• 30+ micro live trades
• Live WR within 10% of paper WR
• Profit factor >1.1 live
• Max drawdown <15%
• Confidence in parameter stability
Progression:
• Months 3-4: 25-40% intended size
• Months 5-6: 40-70% intended size
• Month 7+: 70-100% intended size
Maintenance:
• Weekly dashboard review: Are metrics stable?
• Monthly performance review: Segmented by regime and signal type
• Quarterly parameter check: Has optimal embedding/coherence changed?
Advanced:
• Consider different parameters per session (high vs low volatility)
• Track phase space magnitude patterns before major moves
• Combine with other indicators for confluence
💡 DEVELOPMENT INSIGHTS & KEY BREAKTHROUGHS
The Phase Space Revelation:
Traditional indicators live in price-time space. The breakthrough: markets exist in much higher dimensions (volume, volatility, structure, momentum all orthogonal dimensions). Reading about Takens' theorem—that you can reconstruct any attractor from a single observation using time delays—unlocked the concept. Implementing embedding and seeing trajectories in 5D space revealed hidden structure invisible in price charts. Regions that looked like random noise in 1D became clear limit cycles in 5D.
The Permutation Entropy Discovery:
Calculating Shannon entropy on binned price data was unstable and parameter-sensitive. Discovering Bandt & Pompe's permutation entropy (which uses ordinal patterns) solved this elegantly. PE is robust, fast, and captures temporal structure (not just distribution). Testing showed PE < 0.5 periods had 18% higher signal win rate than PE > 0.7 periods. Entropy regime classification became the backbone of signal filtering.
The Lyapunov Filter Breakthrough:
Early versions signaled during all regimes. Win rate hovered at 42%—barely better than random. The insight: chaos theory distinguishes predictable from unpredictable dynamics. Implementing Lyapunov exponent estimation and blocking signals when λ > 0 (chaotic) increased win rate to 51%. Simply not trading during chaos was worth 9 percentage points—more than any optimization of the signal logic itself.
The Transfer Entropy Challenge:
Correlation between volume and price is easy to calculate but meaningless (bidirectional, could be spurious). Transfer entropy measures actual causal information flow and is directional. The challenge: true TE calculation is computationally expensive (requires discretizing data and estimating high-dimensional joint distributions). The solution: hybrid approach using TE theory combined with lagged cross-correlation and autocorrelation structure. Testing showed TE > 0 signals had 12% higher win rate than TE ≈ 0 signals, confirming causal support matters.
The Phase Coherence Insight:
Initially tried simple correlation between dimensions. Not predictive. Hilbert phase analysis—measuring instantaneous phase of each dimension and calculating phase locking value—revealed hidden synchronization. When PLV > 0.7 across multiple dimension pairs, the market enters a coherent state where all subsystems resonate. These moments have extraordinary predictability because microscopic noise cancels out and macroscopic pattern dominates. Emergence signals require high PLV for this reason.
The Eight-Component Emergence Formula:
Original emergence score used five components (coherence, entropy, lyapunov, fractal, resonance). Performance was good but not exceptional. The "aha" moment: phase space embedding and recurrence quality were being calculated but not contributing to emergence score. Adding these two components (bringing total to eight) with proper weighting increased emergence signal reliability from 52% WR to 58% WR. All calculated metrics must contribute to the final score. If you compute something, use it.
The Cooldown Necessity:
Without cooldown, signals would cluster—5-10 consecutive bars all qualified during high coherence periods, creating chart pollution and overtrading. Implementing bar_index-based cooldown (not time-based, which has rollover bugs) ensures signals only appear at regime entry, not throughout regime persistence. This single change reduced signal count by 60% while keeping win rate constant—massive improvement in signal efficiency.
🚨 LIMITATIONS & CRITICAL ASSUMPTIONS
What This System IS NOT:
• NOT Predictive : NEXUS doesn't forecast prices. It identifies when the market enters a coherent, predictable state—but doesn't guarantee direction or magnitude.
• NOT Holy Grail : Typical performance is 50-58% win rate with 1.5-2.0 avg R-multiple. This is probabilistic edge from complexity analysis, not certainty.
• NOT Universal : Works best on liquid, electronically-traded instruments with reliable volume. Struggles with illiquid stocks, manipulated crypto, or markets without meaningful volume data.
• NOT Real-Time Optimal : Complexity calculations (especially embedding, RQA, fractal dimension) are computationally intensive. Dashboard updates may lag by 1-2 seconds on slower connections.
• NOT Immune to Regime Breaks : System assumes chaos theory applies—that attractors exist and stability zones are meaningful. During black swan events or fundamental market structure changes (regulatory intervention, flash crashes), all bets are off.
Core Assumptions:
1. Markets Have Attractors : Assumes price dynamics are governed by deterministic chaos with underlying attractors. Violation: Pure random walk (efficient market hypothesis holds perfectly).
2. Embedding Captures Dynamics : Assumes Takens' theorem applies—that time-delay embedding reconstructs true phase space. Violation: System dimension vastly exceeds embedding dimension or delay is wildly wrong.
3. Complexity Metrics Are Meaningful : Assumes permutation entropy, Lyapunov exponents, fractal dimensions actually reflect market state. Violation: Markets driven purely by random external news flow (complexity metrics become noise).
4. Causation Can Be Inferred : Assumes transfer entropy approximates causal information flow. Violation: Volume and price spuriously correlated with no causal relationship (rare but possible in manipulated markets).
5. Phase Coherence Implies Predictability : Assumes synchronized dimensions create exploitable patterns. Violation: Coherence by chance during random period (false positive).
6. Historical Complexity Patterns Persist : Assumes if low-entropy, stable-lyapunov periods were tradeable historically, they remain tradeable. Violation: Fundamental regime change (market structure shifts, e.g., transition from floor trading to HFT).
Performs Best On:
• ES, NQ, RTY (major US index futures - high liquidity, clean volume data)
• Major forex pairs: EUR/USD, GBP/USD, USD/JPY (24hr markets, good for phase analysis)
• Liquid commodities: CL (crude oil), GC (gold), NG (natural gas)
• Large-cap stocks: AAPL, MSFT, GOOGL, TSLA (>$10M daily volume, meaningful structure)
• Major crypto on reputable exchanges: BTC, ETH on Coinbase/Kraken (avoid Binance due to manipulation)
Performs Poorly On:
• Low-volume stocks (<$1M daily volume) - insufficient liquidity for complexity analysis
• Exotic forex pairs - erratic spreads, thin volume
• Illiquid altcoins - wash trading, bot manipulation invalidates volume analysis
• Pre-market/after-hours - gappy, thin, different dynamics
• Binary events (earnings, FDA approvals) - discontinuous jumps violate dynamical systems assumptions
• Highly manipulated instruments - spoofing and layering create false coherence
Known Weaknesses:
• Computational Lag : Complexity calculations require iterating over windows. On slow connections, dashboard may update 1-2 seconds after bar close. Signals may appear delayed.
• Parameter Sensitivity : Small changes to embedding dimension or time delay can significantly alter phase space reconstruction. Requires careful calibration per instrument.
• Embedding Window Requirements : Phase space embedding needs sufficient history—minimum (d × τ × 5) bars. If embedding_dimension=5 and time_delay=3, need 75+ bars. Early bars will be unreliable.
• Entropy Estimation Variance : Permutation entropy with small windows can be noisy. Default window (30 bars) is minimum—longer windows (50+) are more stable but less responsive.
• False Coherence : Phase locking can occur by chance during short periods. Coherence threshold filters most of this, but occasional false positives slip through.
• Chaos Detection Lag : Lyapunov exponent requires window (default 20 bars) to estimate. Market can enter chaos and produce bad signal before λ > 0 is detected. Stability filter helps but doesn't eliminate this.
• Computation Overhead : With all features enabled (embedding, RQA, PE, Lyapunov, fractal, TE, Hilbert), indicator is computationally expensive. On very fast timeframes (tick charts, 1-second charts), may cause performance issues.
⚠️ RISK DISCLOSURE
Trading futures, forex, stocks, options, and cryptocurrencies involves substantial risk of loss and is not suitable for all investors. Leveraged instruments can result in losses exceeding your initial investment. Past performance, whether backtested or live, is not indicative of future results.
The Dimensional Resonance Protocol, including its phase space reconstruction, complexity analysis, and emergence detection algorithms, is provided for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security or instrument.
The system implements advanced concepts from nonlinear dynamics, chaos theory, and complexity science. These mathematical frameworks assume markets exhibit deterministic chaos—a hypothesis that, while supported by academic research, remains contested. Markets may exhibit purely random behavior (random walk) during certain periods, rendering complexity analysis meaningless.
Phase space embedding via Takens' theorem is a reconstruction technique that assumes sufficient embedding dimension and appropriate time delay. If these parameters are incorrect for a given instrument or timeframe, the reconstructed phase space will not faithfully represent true market dynamics, leading to spurious signals.
Permutation entropy, Lyapunov exponents, fractal dimensions, transfer entropy, and phase coherence are statistical estimates computed over finite windows. All have inherent estimation error. Smaller windows have higher variance (less reliable); larger windows have more lag (less responsive). There is no universally optimal window size.
The stability zone filter (Lyapunov exponent < 0) reduces but does not eliminate risk of signals during unpredictable periods. Lyapunov estimation itself has lag—markets can enter chaos before the indicator detects it.
Emergence detection aggregates eight complexity metrics into a single score. While this multi-dimensional approach is theoretically sound, it introduces parameter sensitivity. Changing any component weight or threshold can significantly alter signal frequency and quality. Users must validate parameter choices on their specific instrument and timeframe.
The causal gate (transfer entropy filter) approximates information flow using discretized data and windowed probability estimates. It cannot guarantee actual causation, only statistical association that resembles causal structure. Causation inference from observational data remains philosophically problematic.
Real trading involves slippage, commissions, latency, partial fills, rejected orders, and liquidity constraints not present in indicator calculations. The indicator provides signals at bar close; actual fills occur with delay and price movement. Signals may appear delayed due to computational overhead of complexity calculations.
Users must independently validate system performance on their specific instruments, timeframes, broker execution environment, and market conditions before risking capital. Conduct extensive paper trading (minimum 100 signals) and start with micro position sizing (5-10% intended size) for at least 50 trades before scaling up.
Never risk more capital than you can afford to lose completely. Use proper position sizing (0.5-2% risk per trade maximum). Implement stop losses on every trade. Maintain adequate margin/capital reserves. Understand that most retail traders lose money. Sophisticated mathematical frameworks do not change this fundamental reality—they systematize analysis but do not eliminate risk.
The developer makes no warranties regarding profitability, suitability, accuracy, reliability, fitness for any particular purpose, or correctness of the underlying mathematical implementations. Users assume all responsibility for their trading decisions, parameter selections, risk management, and outcomes.
By using this indicator, you acknowledge that you have read, understood, and accepted these risk disclosures and limitations, and you accept full responsibility for all trading activity and potential losses.
📁 DOCUMENTATION
The Dimensional Resonance Protocol is fundamentally a statistical complexity analysis framework . The indicator implements multiple advanced statistical methods from academic research:
Permutation Entropy (Bandt & Pompe, 2002): Measures complexity by analyzing distribution of ordinal patterns. Pure statistical concept from information theory.
Recurrence Quantification Analysis : Statistical framework for analyzing recurrence structures in time series. Computes recurrence rate, determinism, and diagonal line statistics.
Lyapunov Exponent Estimation : Statistical measure of sensitive dependence on initial conditions. Estimates exponential divergence rate from windowed trajectory data.
Transfer Entropy (Schreiber, 2000): Information-theoretic measure of directed information flow. Quantifies causal relationships using conditional entropy calculations with discretized probability distributions.
Higuchi Fractal Dimension : Statistical method for measuring self-similarity and complexity using linear regression on logarithmic length scales.
Phase Locking Value : Circular statistics measure of phase synchronization. Computes complex mean of phase differences using circular statistics theory.
The emergence score aggregates eight independent statistical metrics with weighted averaging. The dashboard displays comprehensive statistical summaries: means, variances, rates, distributions, and ratios. Every signal decision is grounded in rigorous statistical hypothesis testing (is entropy low? is lyapunov negative? is coherence above threshold?).
This is advanced applied statistics—not simple moving averages or oscillators, but genuine complexity science with statistical rigor.
Multiple oscillator-type calculations contribute to dimensional analysis:
Phase Analysis: Hilbert transform extracts instantaneous phase (0 to 2π) of four market dimensions (momentum, volume, volatility, structure). These phases function as circular oscillators with phase locking detection.
Momentum Dimension: Rate-of-change (ROC) calculation creates momentum oscillator that gets phase-analyzed and normalized.
Structure Oscillator: Position within range (close - lowest)/(highest - lowest) creates a 0-1 oscillator showing where price sits in recent range. This gets embedded and phase-analyzed.
Dimensional Resonance: Weighted aggregation of momentum, volume, structure, and volatility dimensions creates a -1 to +1 oscillator showing dimensional alignment. Similar to traditional oscillators but multi-dimensional.
The coherence field (background coloring) visualizes an oscillating coherence metric (0-1 range) that ebbs and flows with phase synchronization. The emergence score itself (0-1 range) oscillates between low-emergence and high-emergence states.
While these aren't traditional RSI or stochastic oscillators, they serve similar purposes—identifying extreme states, mean reversion zones, and momentum conditions—but in higher-dimensional space.
Volatility analysis permeates the system:
ATR-Based Calculations: Volatility period (default 14) computes ATR for the volatility dimension. This dimension gets normalized, phase-analyzed, and contributes to emergence score.
Fractal Dimension & Volatility: Higuchi FD measures how "rough" the price trajectory is. Higher FD (>1.6) correlates with higher volatility/choppiness. FD < 1.4 indicates smooth trends (lower effective volatility).
Phase Space Magnitude: The magnitude of the embedding vector correlates with volatility—large magnitude movements in phase space typically accompany volatility expansion. This is the "energy" of the market trajectory.
Lyapunov & Volatility: Positive Lyapunov (chaos) often coincides with volatility spikes. The stability/chaos zones visually indicate when volatility makes markets unpredictable.
Volatility Dimension Normalization: Raw ATR is normalized by its mean and standard deviation, creating a volatility z-score that feeds into dimensional resonance calculation. High normalized volatility contributes to emergence when aligned with other dimensions.
The system is inherently volatility-aware—it doesn't just measure volatility but uses it as a full dimension in phase space reconstruction and treats changing volatility as a regime indicator.
CLOSING STATEMENT
DRP doesn't trade price—it trades phase space structure . It doesn't chase patterns—it detects emergence . It doesn't guess at trends—it measures coherence .
This is complexity science applied to markets: Takens' theorem reconstructs hidden dimensions. Permutation entropy measures order. Lyapunov exponents detect chaos. Transfer entropy reveals causation. Hilbert phases find synchronization. Fractal dimensions quantify self-similarity.
When all eight components align—when the reconstructed attractor enters a stable region with low entropy, synchronized phases, trending fractal structure, causal support, deterministic recurrence, and strong phase space trajectory—the market has achieved dimensional resonance .
These are the highest-probability moments. Not because an indicator said so. Because the mathematics of complex systems says the market has self-organized into a coherent state.
Most indicators see shadows on the wall. DRP reconstructs the cave.
"In the space between chaos and order, where dimensions resonate and entropy yields to pattern—there, emergence calls." DRP
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Chop + MSS/FVG Retest (Ace v1.6) – IndicatorWhat this indicator does
Name: Chop + MSS/FVG Retest (Ace v1.6) – Indicator
This is an entry model helper, not just a BOS/MSS marker.
It looks for clean trend-side setups by combining:
MSS (Market Structure Shift) using swing highs/lows
3-bar ICT Fair Value Gaps (FVG)
First retest back into the FVG
A built-in chop / trend filter based on ATR and a moving average
When everything lines up, it plots:
L below the candle = Long candidate
S above the candle = Short candidate
You pair this with a higher-timeframe filter (like the Chop Meter 1H/30M/15M) to avoid pressing the button in garbage environments.
How it works (simple explanation)
Chop / Trend filter
Computes ATR and compares each bar’s range to ATR.
If the bar is small vs ATR → more likely CHOP.
If the bar is big vs ATR → more likely TREND.
Uses a moving average:
Above MA + TREND → trendLong zone
Below MA + TREND → trendShort zone
MSS (Market Structure Shift)
Uses swing highs/lows (left/right bars) to track the last significant high/low.
Bullish MSS: close breaks above last swing high with displacement.
Bearish MSS: close breaks below last swing low with displacement.
Those events are marked as tiny triangles (MSS up/down).
A MSS only stays “valid” for a certain number of bars (Bars after MSS allowed).
3-bar ICT FVG
Bullish FVG: low > high
→ gap between bar 3 high and bar 2 low.
Bearish FVG: high < low
→ gap between bar 3 low and bar 2 high.
The indicator stores the FVG boundaries (top/bottom).
Retest of FVG
Watches for price to trade back into that gap (first touch).
That retest is the “entry zone” after the MSS.
Final Long / Short condition
Long (L) prints when:
Recent bullish MSS
Bullish FVG has formed
Price retests the bullish FVG
Environment = trendLong (ATR + above MA)
Not CHOP
Short (S) prints when:
Recent bearish MSS
Bearish FVG has formed
Price retests the bearish FVG
Environment = trendShort (ATR + below MA)
Not CHOP
So the L/S markers are “model-approved entry candles”, not just any random BOS.
Inputs / Settings
Key inputs you’ll see:
ATR length (chop filter)
How many bars to use for ATR in the chop / trend filter.
Lower = more sensitive, twitchy
Higher = smoother, slower to change
Max chop ratio
If barRange / ATR is below this → treat as CHOP.
Min trend ratio
If barRange / ATR is above this → treat as TREND.
Hide MSS/BOS marks in CHOP?
ON = MSS triangles disappear when the bar is classified as CHOP
Keeps your chart cleaner in consolidation
Swing left / right bars
Controls how tight or wide the swing highs/lows are for MSS:
Smaller = more sensitive, more MSS points
Larger = fewer, more significant swings
Bars after MSS allowed
How many bars after a MSS the indicator will still allow FVG entries.
Small value (e.g. 10) = MSS must deliver quickly or it’s ignored.
Larger (e.g. 20) = MSS idea stays “in play” longer.
Visual RR (for info only)
Just for plotting relative risk-reward in your head.
This is not a strategy tester; it doesn’t manage positions.
What you see on the chart
Small green triangle up = Bullish MSS
Small red triangle down = Bearish MSS
“L” triangle below a bar = Long idea (MSS + FVG retest + trendLong + not chop)
“S” triangle above a bar = Short idea (MSS + FVG retest + trendShort + not chop)
Faint circle plots on price:
When the filter sees CHOP
When it sees Trend Long zone
When it sees Trend Short zone
You do not have to trade every L or S.
They’re there to show “this is where the model would have considered an entry.”
How to use it in your trading
1. Use it with a higher-timeframe filter
Best practice:
Use this with the Chop Meter 1H/30M/15M or some other HTF filter.
Only consider L/S when:
Chop Meter = TRADE / NORMAL, and
This indicator prints L or S in the right location (premium/discount, near OB/FVG, etc.)
If higher-timeframe says NO TRADE, you ignore all L/S.
2. Location > Signal
Treat L/S as confirmation, not the whole story.
For shorts (S):
Look for premium zones (previous highs, OBs, fair value ranges above mid).
Want purge / raid of liquidity + MSS down + bearish FVG retest → then S.
For longs (L):
Look for discount zones (previous lows, OBs/FVGs below mid).
Want stop raid / purge low + MSS up + bullish FVG retest → then L.
If you see L/S firing in the middle of a bigger range, that’s where you skip and let it go.
3. Instrument presets (example)
You can tune the ATR/chop settings per instrument:
MNQ (noisy, 1m chart):
ATR length: 21
Max chop ratio: 0.90
Min trend ratio: 1.40
Bars after MSS allowed: 10
GOLD (cleaner, 3m chart):
ATR length: 14
Max chop ratio: 0.80
Min trend ratio: 1.30
Bars after MSS allowed: 20
You can save those as presets in the TV settings for quick switching.
4. How to practice with it
Open replay on a couple of days.
Check Chop Meter → if NO TRADE, just observe.
When Chop Meter says TRADE:
Mark where L/S printed.
Ask:
Was this in premium/discount?
Was there SMT / purge on HTF?
Did the move actually deliver, or did it die?
Screenshot the A+ L/S and the ugly ones; refine:
ATR length
Chop / trend thresholds
MSS lookback
Your goal is to get it to where:
The L/S marks show up mostly in the same places your eye already likes,
and you ignore the rest.
MA SMART Angle
### 📊 WHAT IS MA SMART ANGLE?
**MA SMART Angle** is an advanced momentum and trend detection indicator that analyzes the angles (slopes) of multiple moving averages to generate clear, non-repainting BUY and SELL signals.
**Original Concept Credit:** This indicator builds upon the "MA Angles" concept originally created by **JD** (also known as Duyck). The core angle calculation methodology and Jurik Moving Average (JMA) implementation by **Everget** are preserved from the original open-source work. The angle calculation formula was contributed by **KyJ**. This enhanced version is published with respect to the open-source nature of the original indicator.
Original indicator reference: "ma angles - JD" by Duyck
---
## 🎯 ORIGINALITY & VALUE PROPOSITION
### **What Makes This Different from the Original:**
While the original "MA Angles" by **JD** provided excellent angle visualization, it lacked actionable entry signals. **MA SMART Angle** addresses this by adding:
**1. Clear Entry/Exit Signals**
- Explicit BUY/SELL arrows based on angle crossovers, momentum confirmation, and MA alignment
- No guessing when to enter trades - the indicator tells you exactly when conditions align
**2. Non-Repainting Logic**
- All signals use confirmed historical data (shifted by 2 bars minimum)
- Critical for backtesting reliability and live trading confidence
- Original indicator could repaint signals on current bar
**3. Dual Signal System**
- **Simple Mode:** More frequent signals based on angle crossovers + momentum (for active traders)
- **Strict Mode:** Requires full multi-MA alignment + momentum confirmation (for conservative traders)
- Adaptable to different trading styles and risk tolerances
**4. Smart Signal Filtering**
- **Anti-spam cooldown:** Prevents duplicate signals within configurable bar count
- **No-trade zone detection:** Filters out low-conviction sideways markets automatically
- **Multi-timeframe MA alignment:** Ensures all moving averages agree on direction before signaling
**5. Enhanced Visualization**
- Large, clear BUY/SELL arrows with descriptive labels
- Color-coded backgrounds for market states (trending vs. ranging)
- Momentum histogram showing acceleration/deceleration in real-time
- Live status table displaying trend strength, angle value, momentum, and MA alignment
**6. Professional Alert System**
- Four distinct alert conditions: BUY Signal, SELL Signal, Strong BUY, Strong SELL
- Enables automated trade notifications and strategy integration
**7. Modified MA Periods**
- Original used EMA(27), EMA(83), EMA(278)
- Enhanced version uses faster EMA(3), EMA(8), EMA(13) for more responsive signals
- Better suited for modern volatile markets and shorter timeframes
---
## 📐 HOW IT WORKS - TECHNICAL EXPLANATION
### **Core Methodology:**
The indicator calculates angles (slopes) for five key moving averages:
- **JMA (Jurik Moving Average)** - Smooth, lag-reduced trend line (original implementation by **Everget**)
- **JMA Fast** - Responsive momentum indicator with higher power parameter
- **MA27 (EMA 3)** - Primary fast-moving average for signal generation
- **MA83 (EMA 8)** - Medium-term trend confirmation
- **MA278 (EMA 13)** - Slower trend filter
### **Angle Calculation Formula (by KyJ):**
```
angle = arctan((MA - MA ) / ATR(14)) × (180 / π)
```
**Why ATR normalization?**
- Makes angles comparable across different instruments (forex, stocks, crypto)
- Makes angles comparable across different timeframes
- Accounts for volatility - a 10-point move in different assets has different significance
**Angle Interpretation:**
- **> 15°** = Strong trend (momentum accelerating)
- **0° to 15°** = Weak trend (momentum present but moderate)
- **-2° to +2°** = No-trade zone (sideways/choppy market)
- **< -15°** = Strong downtrend
### **Signal Generation Logic:**
#### **BUY Signal Conditions:**
1. MA27 angle crosses above 0° (upward momentum initiates)
2. All three EMAs (3, 8, 13) pointing upward (trend alignment confirmed)
3. Momentum is positive for 2+ bars (acceleration, not deceleration)
4. Angle exceeds minimum threshold (not in no-trade zone)
5. Cooldown period passed (prevents signal spam)
#### **SELL Signal Conditions:**
1. MA27 angle crosses below 0° (downward momentum initiates)
2. All three EMAs pointing downward (downtrend alignment)
3. Momentum is negative for 2+ bars
4. Angle below negative threshold (not in no-trade zone)
5. Cooldown period passed
#### **Strong BUY+ / SELL+ Signals:**
Additional entry opportunities when JMA Fast crosses JMA Slow while maintaining strong directional angle - indicates momentum acceleration within established trend.
---
## 🔧 HOW TO USE
### **Recommended Settings by Trading Style:**
**Scalpers / Day Traders:**
- Signal Type: **Simple**
- Minimum Angle: **3-5°**
- Cooldown Bars: **3-5 bars**
- Timeframes: 1m, 5m, 15m
**Swing Traders:**
- Signal Type: **Strict**
- Minimum Angle: **7-10°**
- Cooldown Bars: **8-12 bars**
- Timeframes: 1H, 4H, Daily
**Position Traders:**
- Signal Type: **Strict**
- Minimum Angle: **10-15°**
- Cooldown Bars: **15-20 bars**
- Timeframes: Daily, Weekly
### **Parameter Descriptions:**
**1. Source** (default: OHLC4)
- Price data used for MA calculations
- OHLC4 provides smoothest angles
- Close is more responsive but noisier
**2. Threshold for No-Trade Zones** (default: 2°)
- Angles below this are considered sideways/ranging
- Increase for stricter filtering of choppy markets
- Decrease to allow signals in quieter trending periods
**3. Signal Type** (Simple vs. Strict)
- **Simple:** Angle crossover OR (trend + momentum)
- **Strict:** Angle crossover AND all MAs aligned AND momentum confirmed
- Start with Simple, switch to Strict if too many false signals
**4. Minimum Angle for Signal** (default: 5°)
- Only generate signals when angle exceeds this threshold
- Higher values = stronger trends required
- Lower values = more sensitive to momentum changes
**5. Cooldown Bars** (default: 5)
- Minimum bars between consecutive signals
- Prevents spam during volatile chop
- Scale with your timeframe (higher TF = more bars)
**6. Color Bars** (default: true)
- Colors chart bars based on signal state
- Green = bullish conditions, Red = bearish conditions
- Can disable if you prefer clean price bars
**7. Background Colors**
- **Yellow background** = No-trade zone (low angle, ranging market)
- **Green flash** = BUY signal generated
- **Red flash** = SELL signal generated
- All customizable or can be disabled
---
## 📊 INTERPRETING THE INDICATOR
### **Visual Elements:**
**Main Chart Window:**
- **Thick Lime/Fuchsia Line** = MA27 angle (primary signal line)
- **Medium Green/Red Line** = MA83 angle (trend confirmation)
- **Thin Green/Red Line** = MA278 angle (slow trend filter)
- **Aqua/Orange Line** = JMA Fast (momentum detector)
- **Green/Red Area** = JMA slope (overall trend context)
- **Blue/Purple Histogram** = Momentum (angle acceleration/deceleration)
**Signal Arrows:**
- **Large Green ▲ "BUY"** = Primary buy signal (all conditions met)
- **Small Green ▲ "BUY+"** = Strong momentum buy (JMA fast cross)
- **Large Red ▼ "SELL"** = Primary sell signal (all conditions met)
- **Small Red ▼ "SELL+"** = Strong momentum sell (JMA fast cross)
**Status Table (Top Right):**
- **Angle:** Current MA27 angle in degrees
- **Trend:** Classification (STRONG UP/DOWN, UP/DOWN, FLAT)
- **Momentum:** Acceleration state (ACCEL UP/DN, Up/Down)
- **MAs:** Alignment status (ALL UP/DOWN, Mixed)
- **Zone:** Trading zone status (ACTIVE vs. NO TRADE)
- **Last:** Bars since last signal
### **Trading Strategies:**
**Strategy 1: Pure Signal Following**
- Enter LONG on BUY signal
- Exit on SELL signal
- Use stop-loss at recent swing low/high
- Works best on trending instruments
**Strategy 2: Confirmation with Price Action**
- Wait for BUY signal + bullish candlestick pattern
- Wait for SELL signal + bearish candlestick pattern
- Increases win rate by filtering premature signals
- Recommended for beginners
**Strategy 3: Momentum Acceleration**
- Use BUY+/SELL+ signals for adding to positions
- Only take these in direction of primary signal
- Scalp quick moves during momentum spikes
- For experienced traders
**Strategy 4: Mean Reversion in No-Trade Zones**
- When status shows "NO TRADE", fade extremes
- Wait for angle to exit no-trade zone for reversal
- Contrarian approach for range-bound markets
- Requires tight stops
---
## ⚠️ LIMITATIONS & DISCLAIMERS
**What This Indicator DOES:**
✅ Measures momentum direction and strength via angle analysis
✅ Generates signals when multiple conditions align
✅ Filters out low-conviction sideways markets
✅ Provides visual clarity on trend state
**What This Indicator DOES NOT:**
❌ Predict future price movements with certainty
❌ Guarantee profitable trades (no indicator can)
❌ Work equally well on all instruments/timeframes
❌ Replace proper risk management and position sizing
**Known Limitations:**
- **Lagging Nature:** Like all moving averages, signals occur after momentum begins
- **Whipsaw Risk:** Can generate false signals in volatile, directionless markets
- **Optimization Required:** Parameters need adjustment for different assets
- **Not a Complete System:** Should be combined with risk management, position sizing, and other analysis
**Best Performance Conditions:**
- Strong trending markets (crypto bull runs, stock breakouts)
- Liquid instruments (major forex pairs, large-cap stocks)
- Appropriate timeframe selection (match to trading style)
- Used alongside support/resistance and volume analysis
---
## 🔔 ALERT SETUP
The indicator includes four alert conditions:
**1. BUY SIGNAL**
- Message: "MA SMART Angle: BUY SIGNAL! Angle crossed up with momentum"
- Use for: Primary long entries
**2. SELL SIGNAL**
- Message: "MA SMART Angle: SELL SIGNAL! Angle crossed down with momentum"
- Use for: Primary short entries or long exits
**3. Strong BUY**
- Message: "MA SMART Angle: Strong BUY momentum - JMA fast crossed up"
- Use for: Adding to longs or aggressive entries
**4. Strong SELL**
- Message: "MA SMART Angle: Strong SELL momentum - JMA fast crossed down"
- Use for: Adding to shorts or aggressive exits
**Setting Up Alerts:**
1. Right-click indicator → "Add Alert on MA SMART Angle"
2. Select desired condition from dropdown
3. Choose notification method (popup, email, webhook)
4. Set alert expiration (typically "Once Per Bar Close")
---
## 📚 EDUCATIONAL VALUE
This indicator serves as an excellent learning tool for understanding:
**1. Angle-Based Momentum Analysis**
- Traditional indicators show MA crossovers
- This shows the *rate of change* (velocity) of MAs
- Teaches traders to think in terms of momentum acceleration
**2. Multi-Timeframe Confirmation**
- Shows how fast, medium, and slow MAs interact
- Demonstrates importance of trend alignment
- Helps develop patience for high-probability setups
**3. Signal Quality vs. Quantity Tradeoff**
- Simple mode = more signals, more noise
- Strict mode = fewer signals, higher quality
- Teaches discretionary filtering skills
**4. Market State Recognition**
- Visual distinction between trending and ranging markets
- Helps traders avoid trading choppy conditions
- Develops "market context" awareness
---
## 🔄 DIFFERENCES FROM OTHER MA INDICATORS
**vs. Traditional MA Crossovers:**
- Measures momentum (angle) rather than just price crossing MA
- Provides earlier signals as angles change before price crosses
- Filters better for sideways markets using no-trade zones
**vs. MACD:**
- Uses multiple MAs instead of just two
- ATR normalization makes it universal across instruments
- Visual angle representation more intuitive than histogram
**vs. Supertrend:**
- Not based on ATR bands but on MA slope analysis
- Provides graduated strength indication (not just binary trend)
- Less prone to whipsaw in low volatility
**vs. Original "MA Angles" by JD:**
- Adds explicit entry/exit signals (original had none)
- Implements no-repaint logic for reliability
- Includes signal filtering and quality controls
- Provides dual signal systems (Simple/Strict)
- Enhanced visualization and status monitoring
- Uses faster MA periods (3/8/13 vs 27/83/278) for modern markets
---
## 📖 CODE STRUCTURE (for Pine Script learners)
This indicator demonstrates:
**Advanced Pine Script Techniques:**
- Custom function implementation (JMA, angle calculation)
- Var declarations for stateful tracking
- Table creation for HUD display
- Multi-condition signal logic
- Alert system integration
- Proper use of historical references for no-repaint
**Code Organization:**
- Modular function definitions (JMA, angle)
- Clear separation of concerns (inputs, calculations, plotting, alerts)
- Extensive commenting for maintainability
- Best practices for Pine Script v5
**Learning Resources:**
- Study the JMA function to understand adaptive smoothing
- Examine angle calculation for ATR normalization technique
- Review signal logic for multi-condition confirmation patterns
- Analyze anti-spam filtering for state management
The code is open-source - feel free to study, modify, and improve upon it!
---
## 🙏 CREDITS & ATTRIBUTION
**Original Concepts:**
- **"ma angles - JD" by JD (Duyck)** - Core angle calculation methodology and indicator concept
Original open-source indicator on TradingView Community Scripts
- **JMA (Jurik Moving Average) implementation by Everget** - Smooth, low-lag moving average function
Acknowledged in original JD indicator code
- **Angle Calculation formula by KyJ** - Mathematical formula for converting MA slope to degrees using ATR normalization
Acknowledged in original JD indicator code comments
**Enhancements in This Version:**
- Signal generation logic - Original implementation for this indicator
- No-repaint confirmation system - Original implementation
- Dual signal modes (Simple/Strict) - Original implementation
- Visual enhancements and status table - Original implementation
- Alert system and signal filtering - Original implementation
- Modified MA periods (3/8/13 instead of 27/83/278) - Optimization for modern markets
**Open Source Philosophy:**
This indicator follows the open-source spirit of TradingView and the Pine Script community. The original "ma angles - JD" by JD (Duyck) was published as open-source, enabling this enhanced version. Similarly, this code is published as open-source to allow further community improvements.
---
## ⚡ QUICK START GUIDE
**For New Users:**
1. Add indicator to chart
2. Start with default settings (Simple mode)
3. Wait for BUY signal (green arrow)
4. Observe how price behaves after signal
5. Check status table to understand market state
6. Adjust parameters based on your instrument/timeframe
**For Experienced Traders:**
1. Switch to Strict mode for higher quality signals
2. Increase cooldown bars to reduce frequency
3. Raise minimum angle threshold for stronger trends
4. Combine with your existing strategy for confirmation
5. Set up alerts for desired signal types
6. Backtest on your preferred instruments
---
## 🎓 RECOMMENDED COMBINATIONS
**Works Well With:**
- **Volume Analysis:** Confirm signals with volume spikes
- **Support/Resistance:** Take signals near key levels
- **RSI/Stochastic:** Avoid overbought/oversold extremes
- **ATR:** Size positions based on volatility
- **Price Action:** Wait for candlestick confirmation
**Complementary Indicators:**
- Order Flow / Footprint (for institutional confirmation)
- Volume Profile (for identifying value areas)
- VWAP (for intraday mean reversion reference)
- Fibonacci Retracements (for target setting)
---
## 📈 PERFORMANCE EXPECTATIONS
**Realistic Win Rates:**
- Simple Mode: 45-55% (higher frequency, moderate accuracy)
- Strict Mode: 55-65% (lower frequency, higher accuracy)
- Combined with price action: 60-70%
**Best Asset Classes:**
1. **Cryptocurrencies** (strong trends, clear signals)
2. **Forex Major Pairs** (smooth price action, good angles)
3. **Large-Cap Stocks** (trending behavior, liquid)
4. **Index Futures** (trending instruments)
**Challenging Conditions:**
- Low volatility consolidation periods
- News-driven erratic movements
- Thin/illiquid instruments
- Counter-trending markets
---
## 🛡️ RISK DISCLAIMER
**IMPORTANT LEGAL NOTICE:**
This indicator is for **educational and informational purposes only**. It is **NOT financial advice** and does not constitute a recommendation to buy or sell any financial instrument.
**Trading Risks:**
- Trading carries substantial risk of loss
- Past performance does not guarantee future results
- No indicator can predict market movements with certainty
- You can lose more than your initial investment (especially with leverage)
**User Responsibilities:**
- Conduct your own research and due diligence
- Understand the instruments you trade
- Never risk more than you can afford to lose
- Use proper position sizing and risk management
- Consider consulting a licensed financial advisor
**Indicator Limitations:**
- Signals are based on historical data only
- No guarantee of accuracy or profitability
- Parameters must be optimized for your specific use case
- Results vary significantly by market conditions
By using this indicator, you acknowledge and accept all trading risks. The author is not responsible for any financial losses incurred through use of this indicator.
---
## 📧 SUPPORT & FEEDBACK
**Found a bug?** Please report it in the comments with:
- Chart symbol and timeframe
- Parameter settings used
- Description of unexpected behavior
- Screenshot if possible
**Have suggestions?** Share your ideas for improvements!
**Enjoying the indicator?** Leave a like and follow for updates!
Smart VWAP FVG SystemSmart VWAP FVG System - Professional Multi-Filter Trading Indicator
📊 OVERVIEW
The Smart VWAP FVG System is an advanced multi-layered trading indicator that combines institutional volume analysis, multi-timeframe VWAP trend confirmation, and Fair Value Gap detection to identify high-probability trade entries. This indicator uses a sophisticated filtering mechanism where signals appear only when multiple independent confirmation criteria align simultaneously.
Recommended Timeframe: 5-minute (M5) or higher. The indicator works best on M5, M15, and M30 charts for intraday trading.
🎯 ORIGINALITY & PURPOSE
This indicator is original because it combines three distinct analytical methods into a unified decision-making system:
Market Profile Volume Analysis - Identifies institutional accumulation/distribution zones
Dual VWAP Filtering - Confirms trend direction using two independent VWAP calculations
Fair Value Gap Detection - Validates institutional interest through price inefficiency zones
The key innovation is the directional filter system: the primary Market Profile generates BUY-ONLY or SELL-ONLY states based on higher timeframe value area reversals, which then controls which signals from the main system are displayed. This creates a multi-timeframe confluence that significantly reduces false signals.
Unlike simple indicator mashups, each component serves a specific purpose:
Market Profile → Direction bias (trend filter)
Primary VWAP (Session) → Short-term trend confirmation
Secondary VWAP (Week) → Medium-term trend confirmation
FVG Detection → Institutional activity validation
🔧 HOW IT WORKS
1. Primary Market Profile Filter (Higher Timeframe)
The indicator calculates Market Profile on a higher timeframe (default: 1 hour) to determine the overall market structure:
Value Area High (VAH): Top 70% of volume distribution
Value Area Low (VAL): Bottom 70% of volume distribution
Point of Control (POC): Price level with highest volume
When price reaches VAH and reverses down → SELL-ONLY mode activated
When price reaches VAL and reverses up → BUY-ONLY mode activated
This higher timeframe filter ensures you're trading in the direction of institutional flow.
2. Dual VWAP System
Two independent VWAP calculations provide multi-timeframe trend confirmation:
Primary VWAP (Session-based): Resets daily, tracks intraday momentum
Secondary VWAP (Week-based): Resets weekly, confirms longer-term trend
Filter Logic:
BUY signals require: Price > Primary VWAP AND Price > Secondary VWAP
SELL signals require: Price < Primary VWAP AND Price < Secondary VWAP
This dual confirmation prevents counter-trend trades during ranging conditions.
3. Fair Value Gap (FVG) Detection
FVG zones identify price inefficiencies where institutional orders were executed rapidly:
Bullish FVG: Gap between candle .high and candle .low (upward imbalance)
Bearish FVG: Gap between candle .high and candle .low (downward imbalance)
The indicator monitors recent FVG formation (lookback: 50 bars) and requires:
Bullish FVG present for BUY signals
Bearish FVG present for SELL signals
FVG zones are displayed as colored boxes and automatically marked as "mitigated" when price fills the gap.
4. Main Trading Signal Logic
The secondary Market Profile (default: 1 hour) generates the actual trading signals:
BUY Signal Conditions:
Price reaches Value Area Low
Reversal pattern confirmed (minimum 1 bar)
Price > Primary VWAP
Price > Secondary VWAP (if filter enabled)
Recent Bullish FVG detected (if filter enabled)
Primary MP Filter = BUY-ONLY or NEUTRAL
SELL Signal Conditions:
Price reaches Value Area High
Reversal pattern confirmed (minimum 1 bar)
Price < Primary VWAP
Price < Secondary VWAP (if filter enabled)
Recent Bearish FVG detected (if filter enabled)
Primary MP Filter = SELL-ONLY or NEUTRAL
All conditions must be TRUE simultaneously for a signal to appear.
📈 VISUAL ELEMENTS
On Chart:
🟢 Green Triangle (▲) = BUY Signal
🔴 Red Triangle (▼) = SELL Signal
🟦 Blue horizontal lines = Value Area zones
🟡 Yellow line = Point of Control (POC)
🟩 Green boxes = Bullish FVG zones
🟥 Red boxes = Bearish FVG zones
🔵 Blue line = Primary VWAP (Session)
⚪ White line = Secondary VWAP (Week)
Info Panel (Top Right):
Real-time status display showing:
Filter Direction (BUY ONLY / SELL ONLY / NEUTRAL)
Active timeframes for both MP filters
FVG filter status and count
VWAP positions (ABOVE/BELOW)
Signal enablement status
Alert status
⚙️ KEY SETTINGS
MP/TPO Filter Settings (Primary Indicator)
MP Filter Time Frame: 60 minutes (controls directional bias)
Filter Value Area %: 70% (standard Market Profile calculation)
Filter Alert Distance: 1 bar
Filter Min Bars for Reversal: 1 bar
Filter Alert Zone Margin: 0.01 (1%)
FVG Filter Settings
Use FVG Filter: Enabled (toggle on/off)
FVG Timeframe: 60 minutes (1 hour)
FVG Filter Mode: Both (require bullish FVG for BUY, bearish for SELL)
FVG Lookback Period: 50 bars (how far back to search)
Show FVG Formation Signals: Optional visual markers
Max FVG on Chart: 50 zones
Show Mitigated FVG: Display filled gaps
Market Profile Settings
Higher Time Frame: 60 minutes (for main signals)
Percent for Value Area: 70%
Show POC Line: Enabled
Keep Old MPs: Enabled (maintain historical profiles)
Primary VWAP Filter
Use Primary VWAP Filter: Enabled
Primary VWAP Anchor Period: Session (resets daily)
Primary VWAP Source: HLC3 (typical price)
Secondary VWAP Filter
Use Secondary VWAP Filter: Enabled
Secondary VWAP Anchor Period: Week (resets weekly)
Secondary VWAP Filter Mode: Both
Secondary VWAP Line Color: White
Trading Signals
Show Trading Signals on Chart: Enabled
Show SELL Signals: Enabled
Show BUY Signals: Enabled
Alert Distance: 1 bar
Min Bars for Reversal: 1 bar
Alert Zone Margin: 0.01 (1%)
Retest Search Period: 20 bars
Min Bars Between Retests: 5 bars
Show Only Retests: Disabled
Alert Settings
Enable Trading Notifications: Enabled
VAH Reversal Alert: Enabled (SELL signals)
VAL Reversal Alert: Enabled (BUY signals)
Time Filter Settings
Filter Alerts By Time: Optional (exclude specific hours)
⚠️ IMPORTANT WARNINGS & LIMITATIONS
1. Repainting Behavior
CRITICAL: This indicator uses lookahead=barmerge.lookahead_on to access higher timeframe data immediately for FVG detection. This is necessary to provide real-time FVG zone visualization but has the following implications:
FVG zones may shift slightly until the higher timeframe candle closes
FVG detection signals are preliminary until HTF bar confirmation
The main trading signals (triangles) appear on confirmed bars and do not repaint
Best Practice: Always wait for the current timeframe bar to close before acting on signals. The filter status and FVG zones are informational but may adjust as new data arrives.
2. Minimum Timeframe
Do NOT use on timeframes below 5 minutes (M5)
Recommended: M5, M15, M30 for intraday trading
Higher timeframes (H1, H4) can also be used but will generate fewer signals
3. Multiple Filters Can Block Signals
By design, this indicator is conservative. When all filters are enabled:
Signals appear ONLY when all conditions align
You may see extended periods with no signals
This is intentional to reduce false positives
If you see no signals:
Check the Info Panel to see which filters are failing
Consider adjusting FVG lookback period
Temporarily disable FVG filter to test
Verify VWAP filters match current market trend
4. Market Profile Limitations
Market Profile requires sufficient volume data
Low-volume instruments may produce unreliable profiles
Value Areas update only on higher timeframe bar close
Works best on liquid markets (major forex pairs, indices, crypto)
📖 HOW TO USE
Step 1: Add to Chart
Apply indicator to M5 or higher timeframe chart
Ensure chart shows volume data
Use standard candles (NOT Heikin Ashi, Renko, etc.)
Step 2: Configure Settings
Primary MP Filter TF: Set to 60 (1 hour) minimum, or 240 (4 hour) for swing trading
Main MP TF: Set to 60 (1 hour) for intraday signals
FVG Timeframe: Match or exceed main MP timeframe
Leave other settings at default initially
Step 3: Understand the Info Panel
Monitor the top-right panel:
FILTER STATUS: Shows current directional bias
NEUTRAL = Both signals allowed
BUY ONLY = Only green triangles will appear
SELL ONLY = Only red triangles will appear
FVG Filter: Shows if bullish/bearish gaps detected recently
VWAP positions: Confirms trend alignment
Step 4: Take Signals
For BUY Signal (Green Triangle ▲):
Wait for green triangle to appear
Check Info Panel shows ✓ for BUY signals
Confirm current bar has closed
Enter long position
Stop loss: Below recent VAL or swing low
Target: Previous Value Area High or 1.5-2× risk
For SELL Signal (Red Triangle ▼):
Wait for red triangle to appear
Check Info Panel shows ✓ for SELL signals
Confirm current bar has closed
Enter short position
Stop loss: Above recent VAH or swing high
Target: Previous Value Area Low or 1.5-2× risk
Step 5: Risk Management
Risk per trade: Maximum 1-2% of account equity
Position sizing: Adjust based on stop loss distance
Avoid trading: During major news events or time filter periods
Multiple confirmations: Look for confluence with price action (support/resistance, trendlines)
🎓 UNDERLYING CONCEPTS
Market Profile Theory
Developed by J. Peter Steidlmayer in the 1980s, Market Profile organizes price and volume data to identify:
Value Areas: Where 70% of trading activity occurred
POC: Price level with highest acceptance (most volume)
Imbalances: When price moves away from value quickly
This indicator uses TPO (Time Price Opportunity) calculation method to build the volume profile distribution.
VWAP (Volume Weighted Average Price)
VWAP represents the average price weighted by volume, showing where institutional traders are positioned:
Price above VWAP = Bullish (institutions accumulated lower)
Price below VWAP = Bearish (institutions distributed higher)
Using dual VWAP (Session + Week) creates multi-timeframe trend alignment.
Fair Value Gaps (FVG)
Also known as "imbalance" or "inefficiency," FVG occurs when:
Price moves so rapidly that a gap forms in the candlestick structure
Indicates institutional order flow (large market orders)
Price often returns to "fill" these gaps (rebalance)
The 3-candle FVG pattern (gap between candle and candle ) is widely used in ICT (Inner Circle Trader) methodology and Smart Money Concepts.
🔍 CREDITS & CODE ATTRIBUTION
This indicator builds upon established technical analysis concepts and combines multiple methodologies:
1. Market Profile / TPO Calculation
Concept Origin: J. Peter Steidlmayer (Chicago Board of Trade, 1980s)
Code Inspiration: TradingView's public domain Market Profile examples
Modifications: Custom filtering logic for directional bias, dual timeframe implementation
2. VWAP Calculation
Concept Origin: Standard financial instrument (widely used since 1980s)
Code Base: TradingView built-in ta.vwap() function (public domain)
Modifications: Dual VWAP system with independent anchor periods, custom filtering modes
3. Fair Value Gap Detection
Concept Origin: Inner Circle Trader (ICT) / Smart Money Concepts methodology
Code Implementation: Original implementation based on 3-candle gap pattern
Features: Multi-timeframe detection, automatic mitigation tracking, visual zone display
4. Pine Script Framework
Language: Pine Script v6 (TradingView)
Built-in Functions Used:
ta.vwap() - Volume weighted average price
request.security() - Higher timeframe data access
ta.change() - Period detection
ta.cum() - Cumulative volume
time() - Timestamp functions
Note: All code is original implementation. While concepts are based on established trading methodologies, the combination, filtering logic, and execution are unique to this indicator.
📊 RECOMMENDED INSTRUMENTS
Best Performance:
Major Forex Pairs (EURUSD, GBPUSD, USDJPY)
Stock Indices (ES, NQ, SPX, DAX)
Major Cryptocurrencies (BTCUSD, ETHUSD)
Liquid Stocks (high daily volume)
Avoid:
Low-volume altcoins
Illiquid stocks
Exotic forex pairs with wide spreads
⚡ PERFORMANCE TIPS
Start Conservative: Enable all filters initially
Reduce Filters Gradually: If too few signals, disable Secondary VWAP filter first
Match Timeframes: Keep MP Filter TF and FVG TF at same value
Backtest First: Review historical performance on your preferred instrument/timeframe
Combine with Price Action: Look for support/resistance confluence
Use Time Filter: Avoid low-liquidity hours (optional setting)
🚫 WHAT THIS INDICATOR DOES NOT DO
Does not guarantee profits - No trading system is 100% accurate
Does not predict the future - Based on historical patterns
Does not replace risk management - Always use stop losses
Does not work on all instruments - Requires volume data and liquidity
Does not provide exact entry/exit prices - Signals are zones, not precise levels
Does not account for fundamentals - Purely technical analysis
📜 DISCLAIMER
This indicator is provided for educational and informational purposes only. It is not financial advice, and past performance does not guarantee future results.
Trading Risk Warning:
All trading involves risk of loss
You can lose more than your initial investment (leverage products)
Only trade with capital you can afford to lose
Always use appropriate position sizing and risk management
Consider seeking advice from a licensed financial advisor
Technical Limitations:
Indicator may repaint FVG zones until HTF bar closes
Signals are based on historical patterns that may not repeat
Market conditions change and no system works in all environments
Volume data quality varies by exchange/broker
By using this indicator, you acknowledge these risks and agree that the author bears no responsibility for trading losses.
📞 SUPPORT & UPDATES
Questions? Comment on this publication
Issues? Describe the problem with chart screenshot
Feature Requests? Suggest improvements in comments
Updates: Will be published as new versions using TradingView's update feature
📝 VERSION HISTORY
Version 1.0 (Current)
Initial public release
Multi-filter system: MP + Dual VWAP + FVG
Directional bias filter
Real-time info panel
Comprehensive alert system
Time-based filtering
Thank you for using Smart VWAP FVG System!
Happy Trading! 📈
Multi-Timeframe SFP (Swing Failure Pattern)How to Use
1. Set Pivot Timeframe: Choose the timeframe for identifying major swing points (e.g., 'D' for Daily pivots).
2. Set SFP Timeframe: Choose the timeframe to find the SFP candle (e.g., '240' for the 4-Hour chart).
3. Set Confirmation Bars: Set how many SFP Timeframe bars must pass without invalidating the level. A value of '0' confirms immediately on the SFP bar's close. A value of '1' waits for one more bar to close.
4. Adjust Filters (Optional): Enable the 'Wick % Filter' to add a quality check for strong rejections.
5. Watch & Wait: The indicator will draw lines and labels and fire alerts for fully confirmed signals.
In-Depth Explanation
1. Overview
The Dynamic Pivot SFP Engine is a multi-timeframe tool designed to identify and validate Swing Failure Patterns (SFPs) at significant price levels.
An SFP is a common price action pattern where price briefly trades beyond a previous swing high or low (sweeping liquidity) but then fails to hold those new prices, closing back inside the previous range. This "failure" often signals a reversal.
This indicator enhances SFP detection by separating the Pivot (Liquidity) from the SFP (Rejection), allowing you to monitor them on different timeframes.
2. The Core Multi-Timeframe Logic
The indicator's power comes from two key inputs:
• Pivot Timeframe (Pivot Timeframe)
This is the "high timeframe" used to establish significant support and resistance levels. The script finds standard pivots (swing highs and lows) on this timeframe based on the Pivot Left Strength and Pivot Right Strength inputs. These pivots are the "liquidity" levels the SFP will target. The Pivot Lookback input controls how long (in Pivot Timeframe bars) a pivot remains active and monitored.
• SFP Timeframe (SFP Timeframe)
This is the "execution timeframe" where the script looks for the actual SFP. On every new bar of this timeframe, the script checks if price has swept and rejected any of the active pivots.
Example Setup:
You might set Pivot Timeframe to 'D' (Daily) to find major daily swing points. You then set SFP Timeframe to '240' (4-Hour) to find a 4-hour candle that sweeps a daily pivot and closes back below/above it.
3. The SFP Confirmation Process
An SFP is not confirmed instantly. It must pass a rigorous, multi-step validation process.
Step 1: The SFP Candle (The Sweep)
A potential SFP is identified when an SFP Timeframe bar does the following:
• Bearish SFP: The bar's high trades above an active pivot high, but the bar closes below that same pivot high.
• Bullish SFP: The bar's low trades below an active pivot low, but the bar closes above that same pivot low.
Step 2: The Wick Filter (Optional Quality Check)
If Enable Wick % Filter is checked, the SFP candle from Step 1 is also measured.
• For a bearish SFP, the upper wick (from the high to the open/close) must be at least Min. Wick % of the entire candle's range (high-to-low).
• For a bullish SFP, the lower wick (from the low to the open/close) must meet the same percentage requirement.
If the SFP candle fails this test, it is discarded, even if it met the sweep/close criteria.
Step 3: The Validation Window (The Confirmation)
This is the most critical feature, controlled by Confirmation Bars.
• If Confirmation Bars = 0: The SFP is confirmed immediately on the SFP candle's close (assuming it passed the optional wick check). The label, line, and alert are triggered at this moment.
• If Confirmation Bars > 0: The SFP enters a "pending" state. The script will wait for $N$ more SFP Timeframe bars to close.
o Invalidation: If, during this waiting period, any bar closes back across the pivot (e.g., a close above the pivot for a bearish SFP), the SFP is considered failed and invalidated. All pending plots are deleted.
o Confirmation: If the $N$ confirmation bars all complete without invalidating the level, the SFP is finally confirmed. The label, line, and alert are only triggered after this entire process is complete. This adds a significant layer of robustness, ensuring the rejection holds for a period of time.
4. Visuals & Alerts
• Lines: A horizontal line is drawn from the original pivot to the SFP bar, showing which level was targeted. Note: These lines will only be drawn on chart timeframes equal to or lower than the 'SFP Timeframe'.
• Labels: A label is placed at the SFP's extreme (the high/low of the SFP bar). The label text conveniently includes the Ticker, Pivot TF, SFP TF, and Confirmation bar settings (e.g., "Bearish SFP BTCUSD / Pivot: 1D / SFP: 4H | Conf: 1").
• MTF Boxes (Show SFP Box, Show Conf. Boxes): These boxes highlight the SFP and confirmation bars. Crucially, they are only visible when your chart timeframe is lower than the SFP Timeframe. For example, if your SFP Timeframe is '240' (4H), you will only see these boxes on the 1H, 15M, 5M, etc., charts. This allows you to see the higher-timeframe SFP unfolding on your lower-timeframe chart.
• Alerts (Enable Alerts): An alert is fired only when an SFP is fully confirmed (i.e., after the Confirmation Bars have passed successfully). For efficient, real-time monitoring, it is highly recommended to run this indicator server-side by creating an alert on TradingView set to trigger on "Any alert() function call".
Relative Strength Index Remastered [CHE]Relative Strength Index Remastered — Enhanced RSI with robust divergence detection using price-based pivots and line-of-sight validation to reduce false signals compared to the standard RSI indicator.
Summary
RSI Remastered builds on the classic Relative Strength Index by adding a more reliable divergence detection system that relies on price pivots rather than RSI pivots alone, incorporating a line-of-sight check to ensure the RSI path between points remains clear. This approach filters out many false divergences that occur in the original RSI indicator due to its volatile pivot detection on the RSI line itself. Users benefit from clearer reversal and continuation signals, especially in noisy markets, with optional hidden divergence support for trend confirmation. The core RSI calculation and smoothing options remain familiar, but the divergence logic provides materially fewer alerts while maintaining sensitivity.
Motivation: Why this design?
The standard RSI indicator often generates misleading divergence signals because it detects pivots directly on the RSI values, which can fluctuate erratically in volatile conditions, leading to frequent false positives that confuse traders during ranging or choppy price action. RSI Remastered addresses this by shifting pivot detection to the underlying price highs and lows, which are more stable, and adding a validation step that confirms the RSI line does not cross the direct path between pivot points. This design targets the real problem of over-signaling in the original, promoting more actionable insights without altering the RSI's core momentum measurement.
What’s different vs. standard approaches?
- Reference baseline: The classical TradingView RSI indicator, which uses simple RSI-based pivot detection for divergences.
- Architecture differences:
- Pivot identification on price extremes (highs and lows) instead of RSI values, extracting RSI levels at those points for comparison.
- Addition of a line-of-sight validation that checks the RSI path bar by bar between pivots to prevent signals where the line is interrupted.
- Inclusion of hidden divergence types alongside regular ones, using the same robust framework.
- Configurable drawing of connecting lines between validated pivot RSI points for visual clarity.
- Practical effect: Charts show fewer but higher-quality divergence markers and lines, reducing clutter from the original's frequent RSI pivot triggers; this matters for avoiding whipsaws in intraday trading, where the standard version might flag dozens of invalid setups per session.
Key Comparison Aspects
Aspect: Title/Shorttitle
Original RSI: "Relative Strength Index" / "RSI"
Robust Variant: "Relative Strength Index Remastered " / "RSI RM"
Aspect: Max. Lines/Labels
Original RSI: No specification (Standard: 50/50)
Robust Variant: max_lines_count=200, max_labels_count=200 (for more lines/markers in divergences)
Aspect: RSI Calculation & Plots
Original RSI: Identical: RSI with RMA, Plots (line, bands, gradient fills)
Robust Variant: Identical: RSI with RMA, Plots (line, bands, gradient fills)
Aspect: Smoothing (MA)
Original RSI: Identical: Inputs for MA types (SMA, EMA etc.), Bollinger Bands optional
Robust Variant: Identical: Inputs for MA types (SMA, EMA etc.), Bollinger Bands optional
Aspect: Divergence Activation
Original RSI: input.bool(false, "Calculate Divergence") (disabled by default)
Robust Variant: input.bool(true, "Calculate Divergence") (enabled by default, with tooltip)
Aspect: Pivot Calculation
Original RSI: Pivots on RSI (ta.pivotlow/high on RSI values)
Robust Variant: Pivots on price (ta.pivotlow/high on low/high), RSI values then extracted
Aspect: Lookback Values
Original RSI: Fixed: lookbackLeft=5, lookbackRight=5
Robust Variant: Input: L=5 (Pivot Left), R=5 (Pivot Right), adjustable (min=1, max=50)
Aspect: Range Between Pivots
Original RSI: Fixed: rangeUpper=60, rangeLower=5 (via _inRange function)
Robust Variant: Input: rangeUpper=60 (Max Bars), rangeLower=5 (Min Bars), adjustable (min=1–6, max=100–300)
Aspect: Divergence Types
Original RSI: Only Regular Bullish/Bearish: - Bull: Price LL + RSI HL - Bear: Price HH + RSI LH
Robust Variant: Regular + Hidden (optional via showHidden=true): - Regular Bull: Price LL + RSI HL - Regular Bear: Price HH + RSI LH - Hidden Bull: Price HL + RSI LL - Hidden Bear: Price LH + RSI HH
Aspect: Validation
Original RSI: No additional check (only pivot + range check)
Robust Variant: Line-of-Sight Check: RSI line must not cross the connecting line between pivots (line_clear function with slope calculation and loop for each bar in between)
Aspect: Signals (Plots/Shapes)
Original RSI: - Plot of pivot points (if divergence) - Shapes: "Bull"/"Bear" at RSI value, offset=-5
Robust Variant: - No pivot plots, instead shapes at RSI , offset=-R (adjustable) - Shapes: "Bull"/"Bear" (Regular), "HBull"/"HBear" (Hidden) - Colors: Lime/Red (Regular), Teal/Orange (Hidden)
Aspect: Line Drawing
Original RSI: No lines
Robust Variant: Optional (showLines=true): Lines between RSI pivots (thick for regular, dashed/thin for hidden), extend=none
Aspect: Alerts
Original RSI: Only Regular Bullish/Bearish (with pivot lookback reference)
Robust Variant: Regular Bullish/Bearish + Hidden Bullish/Bearish (specific "at latest pivot low/high")
Aspect: Robustness
Original RSI: Simple, prone to false signals (RSI pivots can be volatile)
Robust Variant: Higher: Price pivots are more stable, line-of-sight filters "broken" divergences, hidden support for trend continuations
Aspect: Code Length/Structure
Original RSI: ~100 lines, simple if-blocks for bull/bear
Robust Variant: ~150 lines, extended helper functions (e.g., inRange, line_clear), var group for inputs
How it works (technical)
The indicator first computes the core RSI value based on recent price changes, separating upward and downward movements over the specified length and smoothing them to derive a momentum reading scaled between zero and one hundred. This value is then plotted in a separate pane with fixed upper and lower reference lines at seventy and thirty, along with optional gradient fills to highlight overbought and oversold zones.
For smoothing, a moving average type is applied to the RSI if enabled, with an option to add bands around it based on the variability of recent RSI values scaled by a multiplier. Divergence detection activates on confirmed price pivots: lows for bullish checks and highs for bearish. At each new pivot, the system retrieves the bar index and values (price and RSI) for the current and prior pivot, ensuring they fall within a configurable bar range to avoid unrelated points.
Comparisons then assess whether the price has made a lower low (or higher high) while the RSI at those points moves in the opposite direction—higher for bullish regular, lower for bearish regular. For hidden types, the directions reverse to capture trend strength. The line-of-sight check calculates the straight path between the two RSI points and verifies that the actual RSI values in between stay entirely above (for bullish) or below (for bearish) that path, breaking the signal if any bar violates it. Valid signals trigger shapes at the RSI level of the new pivot and optional lines connecting the points. Initialization uses built-in functions to track prior occurrences, with states persisting across bars for accurate historical comparisons. No higher timeframe data is used, so confirmation occurs after the right pivot bars close, minimizing live-bar repaints.
Parameter Guide
Length — Controls the period for measuring price momentum changes — Default: 14 — Trade-offs/Tips: Shorter values increase responsiveness but add noise and more false signals; longer smooths trends but delays entries in fast markets.
Source — Selects the price input for RSI calculation — Default: Close — Trade-offs/Tips: Use high or low for volatility focus, but close works best for most assets; mismatches can skew overbought/oversold reads.
Calculate Divergence — Enables the enhanced divergence logic — Default: True — Trade-offs/Tips: Disable for pure RSI view to save computation; essential for signal reliability over the standard method.
Type (Smoothing) — Chooses the moving average applied to RSI — Default: SMA — Trade-offs/Tips: None for raw RSI; EMA for quicker adaptation, but SMA reduces whipsaws; Bollinger Bands option adds volatility context at cost of added lines.
Length (Smoothing) — Period for the smoothing average — Default: 14 — Trade-offs/Tips: Match RSI length for consistency; shorter boosts signal speed but amplifies noise in the smoothed line.
BB StdDev — Multiplier for band width around smoothed RSI — Default: 2.0 — Trade-offs/Tips: Lower narrows bands for tighter signals, risking more touches; higher widens for fewer but stronger breakouts.
Pivot Left — Bars to the left for confirming price pivots — Default: 5 — Trade-offs/Tips: Increase for stricter pivots in noisy data, reducing signals; too high delays confirmation excessively.
Pivot Right — Bars to the right for confirming price pivots — Default: 5 — Trade-offs/Tips: Balances with left for symmetry; longer right ensures maturity but shifts signals backward.
Max Bars Between Pivots — Upper limit on distance for valid pivot pairs — Default: 60 — Trade-offs/Tips: Tighten for short-term trades to focus recent action; widen for swing setups but risks unrelated comparisons.
Min Bars Between Pivots — Lower limit to avoid clustered pivots — Default: 5 — Trade-offs/Tips: Raise to filter micro-moves; too low invites overlapping signals like the original RSI.
Detect Hidden — Includes trend-continuation hidden types — Default: True — Trade-offs/Tips: Enable for full trend analysis; disable simplifies to reversals only, akin to basic RSI.
Draw Lines — Shows connecting lines between valid pivots — Default: True — Trade-offs/Tips: Turn off for cleaner charts; helps visually confirm line-of-sight in backtests.
Reading & Interpretation
The main RSI line oscillates between zero and one hundred, crossing above fifty suggesting building momentum and below indicating weakness; touches near seventy or thirty flag potential extremes. The optional smoothed line and bands provide a filtered view—price above the upper band on the RSI pane hints at overextension. Divergence shapes appear as upward labels for bullish (lime for regular, teal for hidden) and downward for bearish (red regular, orange hidden) at the pivot's RSI level, signaling a mismatch only after validation. Connecting lines, if drawn, slope between points without RSI interference, their color matching the shape type; a dashed style denotes hidden. Fewer shapes overall compared to the standard RSI mean higher conviction, but always confirm with price structure.
Practical Workflows & Combinations
- Trend following: Enter longs on regular bullish shapes near support with higher highs in price; filter hidden bullish for pullback buys in uptrends, pairing with a rising smoothed RSI above fifty.
- Exits/Stops: Use bearish regular as reversal warnings to tighten stops; hidden bearish in downtrends confirms continuation—exit if lines show RSI crossing the path.
- Multi-asset/Multi-TF: Defaults suit forex and stocks on one-hour charts; for crypto volatility, widen pivot ranges to ten; scale min/max bars proportionally on daily for swings, avoiding the original's intraday spam.
Behavior, Constraints & Performance
Signals confirm only after the right pivot bars close, so live bars may show tentative pivots that vanish on close, unlike the standard RSI's immediate RSI-pivot triggers—plan for this delay in automation. No higher timeframe calls, so no security-related repaints. Resources include up to two hundred lines and labels for dense charts, with a loop in validation scanning up to three hundred bars between pivots, which is efficient but could slow on very long histories. Known limits: Slight lag at pivot confirmation in trending markets; volatile RSI might rarely miss fine path violations; not ideal for gap-heavy assets where pivots skip.
Sensible Defaults & Quick Tuning
Start with defaults for balanced momentum and divergence on most timeframes. For too many signals (like the original), raise pivot left/right to eight and min bars to ten to filter noise. If sluggish in trends, shorten RSI length to nine and enable EMA smoothing for faster adaptation. In high-volatility assets, widen max bars to one hundred but disable hidden to focus essentials. For clean reversal hunts, set smoothing to none and lines on.
What this indicator is—and isn’t
RSI Remastered serves as a refined momentum and divergence visualization tool, enhancing the standard RSI for better signal quality in technical analysis setups. It is not a standalone trading system, nor does it predict price moves—pair it with volume, structure breaks, and risk rules for decisions. Use alongside position sizing and broader context, not in isolation.
Disclaimer
The content provided, including all code and materials, is strictly for educational and informational purposes only. It is not intended as, and should not be interpreted as, financial advice, a recommendation to buy or sell any financial instrument, or an offer of any financial product or service. All strategies, tools, and examples discussed are provided for illustrative purposes to demonstrate coding techniques and the functionality of Pine Script within a trading context.
Any results from strategies or tools provided are hypothetical, and past performance is not indicative of future results. Trading and investing involve high risk, including the potential loss of principal, and may not be suitable for all individuals. Before making any trading decisions, please consult with a qualified financial professional to understand the risks involved.
By using this script, you acknowledge and agree that any trading decisions are made solely at your discretion and risk.
Do not use this indicator on Heikin-Ashi, Renko, Kagi, Point-and-Figure, or Range charts, as these chart types can produce unrealistic results for signal markers and alerts.
Best regards and happy trading
Chervolino
Luxy Momentum, Trend, Bias and Breakout Indicators V7
TABLE OF CONTENTS
This is Version 7 (V7) - the latest and most optimized release. If you are using any older versions (V6, V5, V4, V3, etc.), it is highly recommended to replace them with V7.
Why This Indicator is Different
Who Should Use This
Core Components Overview
The UT Bot Trading System
Understanding the Market Bias Table
Candlestick Pattern Recognition
Visual Tools and Features
How to Use the Indicator
Performance and Optimization
FAQ
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### CREDITS & ATTRIBUTION
This indicator implements proven trading concepts using entirely original code developed specifically for this project.
### CONCEPTUAL FOUNDATIONS
• UT Bot ATR Trailing System
- Original concept by @QuantNomad: (search "UT-Bot-Strategy"
- Our version is a complete reimplementation with significant enhancements:
- Volume-weighted momentum adjustment
- Composite stop loss from multiple S/R layers
- Multi-filter confirmation system (swing, %, 2-bar, ZLSMA)
- Full integration with multi-timeframe bias table
- Visual audit trail with freeze-on-touch
- NOTE: No code was copied - this is a complete reimplementation with enhancements.
• Standard Technical Indicators (Public Domain Formulas):
- Supertrend: ATR-based trend calculation with custom gradient fills
- MACD: Gerald Appel's formula with separation filters
- RSI: J. Welles Wilder's formula with pullback zone logic
- ADX/DMI: Custom trend strength formula inspired by Wilder's directional movement concept, reimplemented with volume weighting and efficiency metrics
- ZLSMA: Zero-lag formula enhanced with Hull MA and momentum prediction
### Custom Implementations
- Trend Strength: Inspired by Wilder's ADX concept but using volume-weighted pressure calculation and efficiency metrics (not traditional +DI/-DI smoothing)
- All code implementations are original
### ORIGINAL FEATURES (70%+ of codebase)
- Multi-Timeframe Bias Table with live updates
- Risk Management System (R-multiple TPs, freeze-on-touch)
- Opening Range Breakout tracker with session management
- Composite Stop Loss calculator using 6+ S/R layers
- Performance optimization system (caching, conditional calcs)
- VIX Fear Index integration
- Previous Day High/Low auto-detection
- Candlestick pattern recognition with interactive tooltips
- Smart label and visual management
- All UI/UX design and table architecture
### DEVELOPMENT PROCESS
**AI Assistance:** This indicator was developed over 2+ months with AI assistance (ChatGPT/Claude) used for:
- Writing Pine Script code based on design specifications
- Optimizing performance and fixing bugs
- Ensuring Pine Script v6 compliance
- Generating documentation
**Author's Role:** All trading concepts, system design, feature selection, integration logic, and strategic decisions are original work by the author. The AI was a coding tool, not the system designer.
**Transparency:** We believe in full disclosure - this project demonstrates how AI can be used as a powerful development tool while maintaining creative and strategic ownership.
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1. WHY THIS INDICATOR IS DIFFERENT
Most traders use multiple separate indicators on their charts, leading to cluttered screens, conflicting signals, and analysis paralysis. The Suite solves this by integrating proven technical tools into a single, cohesive system.
Key Advantages:
All-in-One Design: Instead of loading 5-10 separate indicators, you get everything in one optimized script. This reduces chart clutter and improves TradingView performance.
Multi-Timeframe Bias Table: Unlike standard indicators that only show the current timeframe, the Bias Table aggregates trend signals across multiple timeframes simultaneously. See at a glance whether 1m, 5m, 15m, 1h are aligned bullish or bearish - no more switching between charts.
Smart Confirmations: The indicator doesn't just give signals - it shows you WHY. Every entry has multiple layers of confirmation (MA cross, MACD momentum, ADX strength, RSI pullback, volume, etc.) that you can toggle on/off.
Dynamic Stop Loss System: Instead of static ATR stops, the SL is calculated from multiple support/resistance layers: UT trailing line, Supertrend, VWAP, swing structure, and MA levels. This creates more intelligent, price-action-aware stops.
R-Multiple Take Profits: Built-in TP system calculates targets based on your initial risk (1R, 1.5R, 2R, 3R). Lines freeze when touched with visual checkmarks, giving you a clean audit trail of partial exits.
Educational Tooltips Everywhere: Every single input has detailed tooltips explaining what it does, typical values, and how it impacts trading. You're not guessing - you're learning as you configure.
Performance Optimized: Smart caching, conditional calculations, and modular design mean the indicator runs fast despite having 15+ features. Turn off what you don't use for even better performance.
No Repainting: All signals respect bar close. Alerts fire correctly. What you see in history is what you would have gotten in real-time.
What Makes It Unique:
Integrated UT Bot + Bias Table: No other indicator combines UT Bot's ATR trailing system with a live multi-timeframe dashboard. You get precision entries with macro trend context.
Candlestick Pattern Recognition with Interactive Tooltips: Patterns aren't just marked - hover over any emoji for a full explanation of what the pattern means and how to trade it.
Opening Range Breakout Tracker: Built-in ORB system for intraday traders with customizable session times and real-time status updates in the Bias Table.
Previous Day High/Low Auto-Detection: Automatically plots PDH/PDL on intraday charts with theme-aware colors. Updates daily without manual input.
Dynamic Row Labels in Bias Table: The table shows your actual settings (e.g., "EMA 10 > SMA 20") not generic labels. You know exactly what's being evaluated.
Modular Filter System: Instead of forcing a fixed methodology, the indicator lets you build your own strategy. Start with just UT Bot, add filters one at a time, test what works for your style.
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2. WHO WHOULD USE THIS
Designed For:
Intermediate to Advanced Traders: You understand basic technical analysis (MAs, RSI, MACD) and want to combine multiple confirmations efficiently. This isn't a "one-click profit" system - it's a professional toolkit.
Multi-Timeframe Traders: If you trade one asset but check multiple timeframes for confirmation (e.g., enter on 5m after checking 15m and 1h alignment), the Bias Table will save you hours every week.
Trend Followers: The indicator excels at identifying and following trends using UT Bot, Supertrend, and MA systems. If you trade breakouts and pullbacks in trending markets, this is built for you.
Intraday and Swing Traders: Works equally well on 5m-1h charts (day trading) and 4h-D charts (swing trading). Scalpers can use it too with appropriate settings adjustments.
Discretionary Traders: This isn't a black-box system. You see all the components, understand the logic, and make final decisions. Perfect for traders who want tools, not automation.
Works Across All Markets:
Stocks (US, international)
Cryptocurrency (24/7 markets supported)
Forex pairs
Indices (SPY, QQQ, etc.)
Commodities
NOT Ideal For :
Complete Beginners: If you don't know what a moving average or RSI is, start with basics first. This indicator assumes foundational knowledge.
Algo Traders Seeking Black Box: This is discretionary. Signals require context and confirmation. Not suitable for blind automated execution.
Mean-Reversion Only Traders: The indicator is trend-following at its core. While VWAP bands support mean-reversion, the primary methodology is trend continuation.
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3. CORE COMPONENTS OVERVIEW
The indicator combines these proven systems:
Trend Analysis:
Moving Averages: Four customizable MAs (Fast, Medium, Medium-Long, Long) with six types to choose from (EMA, SMA, WMA, VWMA, RMA, HMA). Mix and match for your style.
Supertrend: ATR-based trend indicator with unique gradient fill showing trend strength. One-sided ribbon visualization makes it easier to see momentum building or fading.
ZLSMA : Zero-lag linear-regression smoothed moving average. Reduces lag compared to traditional MAs while maintaining smooth curves.
Momentum & Filters:
MACD: Standard MACD with separation filter to avoid weak crossovers.
RSI: Pullback zone detection - only enter longs when RSI is in your defined "buy zone" and shorts in "sell zone".
ADX/DMI: Trend strength measurement with directional filter. Ensures you only trade when there's actual momentum.
Volume Filter: Relative volume confirmation - require above-average volume for entries.
Donchian Breakout: Optional channel breakout requirement.
Signal Systems:
UT Bot: The primary signal generator. ATR trailing stop that adapts to volatility and gives clear entry/exit points.
Base Signals: MA cross system with all the above filters applied. More conservative than UT Bot alone.
Market Bias Table: Multi-timeframe dashboard showing trend alignment across 7 timeframes plus macro bias (3-day, weekly, monthly, quarterly, VIX).
Candlestick Patterns: Six major reversal patterns auto-detected with interactive tooltips.
ORB Tracker: Opening range high/low with breakout status (intraday only).
PDH/PDL: Previous day levels plotted automatically on intraday charts.
VWAP + Bands : Session-anchored VWAP with up to three standard deviation band pairs.
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4. THE UT BOT TRADING SYSTEM
The UT Bot is the heart of the indicator's signal generation. It's an advanced ATR trailing stop that adapts to market volatility.
Why UT Bot is Superior to Fixed Stops:
Traditional ATR stops use a fixed multiplier (e.g., "stop = entry - 2×ATR"). UT Bot is smarter:
It TRAILS the stop as price moves in your favor
It WIDENS during high volatility to avoid premature stops
It TIGHTENS during consolidation to lock in profits
It FLIPS when price breaks the trailing line, signaling reversals
Visual Elements You'll See:
Orange Trailing Line: The actual UT stop level that adapts bar-by-bar
Buy/Sell Labels: Aqua triangle (long) or orange triangle (short) when the line flips
ENTRY Line: Horizontal line at your entry price (optional, can be turned off)
Suggested Stop Loss: A composite SL calculated from multiple support/resistance layers:
- UT trailing line
- Supertrend level
- VWAP
- Swing structure (recent lows/highs)
- Long-term MA (200)
- ATR-based floor
Take Profit Lines: TP1, TP1.5, TP2, TP3 based on R-multiples. When price touches a TP, it's marked with a checkmark and the line freezes for audit trail purposes.
Status Messages: "SL Touched ❌" or "SL Frozen" when the trade leg completes.
How UT Bot Differs from Other ATR Systems:
Multiple Filters Available: You can require 2-bar confirmation, minimum % price change, swing structure alignment, or ZLSMA directional filter. Most UT implementations have none of these.
Smart SL Calculation: Instead of just using the UT line as your stop, the indicator suggests a better SL based on actual support/resistance. This prevents getting stopped out by wicks while keeping risk controlled.
Visual Audit Trail: All SL/TP lines freeze when touched with clear markers. You can review your trades weeks later and see exactly where entries, stops, and targets were.
Performance Options: "Draw UT visuals only on bar close" lets you reduce rendering load without affecting logic or alerts - critical for slower machines or 1m charts.
Trading Logic:
UT Bot flips direction (Buy or Sell signal appears)
Check Bias Table for multi-timeframe confirmation
Optional: Wait for Base signal or candlestick pattern
Enter at signal bar close or next bar open
Place stop at "Suggested Stop Loss" line
Scale out at TP levels (TP1, TP2, TP3)
Exit remaining position on opposite UT signal or stop hit
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5. UNDERSTANDING THE MARKET BIAS TABLE
This is the indicator's unique multi-timeframe intelligence layer. Instead of looking at one chart at a time, the table aggregates signals across seven timeframes plus macro trend bias.
Why Multi-Timeframe Analysis Matters:
Professional traders check higher and lower timeframes for context:
Is the 1h uptrend aligning with my 5m entry?
Are all short-term timeframes bullish or just one?
Is the daily trend supportive or fighting me?
Doing this manually means opening multiple charts, checking each indicator, and making mental notes. The Bias Table does it automatically in one glance.
Table Structure:
Header Row:
On intraday charts: 1m, 5m, 15m, 30m, 1h, 2h, 4h (toggle which ones you want)
On daily+ charts: D, W, M (automatic)
Green dot next to title = live updating
Headline Rows - Macro Bias:
These show broad market direction over longer periods:
3 Day Bias: Trend over last 3 trading sessions (uses 1h data)
Weekly Bias: Trend over last 5 trading sessions (uses 4h data)
Monthly Bias: Trend over last 30 daily bars
Quarterly Bias: Trend over last 13 weekly bars
VIX Fear Index: Market regime based on VIX level - bullish when low, bearish when high
Opening Range Breakout: Status of price vs. session open range (intraday only)
These rows show text: "BULLISH", "BEARISH", or "NEUTRAL"
Indicator Rows - Technical Signals:
These evaluate your configured indicators across all active timeframes:
Fast MA > Medium MA (shows your actual MA settings, e.g., "EMA 10 > SMA 20")
Price > Long MA (e.g., "Price > SMA 200")
Price > VWAP
MACD > Signal
Supertrend (up/down/neutral)
ZLSMA Rising
RSI In Zone
ADX ≥ Minimum
These rows show emojis: GREEB (bullish), RED (bearish), GRAY/YELLOW (neutral/NA)
AVG Column:
Shows percentage of active timeframes that are bullish for that row. This is the KEY metric:
AVG > 70% = strong multi-timeframe bullish alignment
AVG 40-60% = mixed/choppy, no clear trend
AVG < 30% = strong multi-timeframe bearish alignment
How to Use the Table:
For a long trade:
Check AVG column - want to see > 60% ideally
Check headline bias rows - want to see BULLISH, not BEARISH
Check VIX row - bullish market regime preferred
Check ORB row (intraday) - want ABOVE for longs
Scan indicator rows - more green = better confirmation
For a short trade:
Check AVG column - want to see < 40% ideally
Check headline bias rows - want to see BEARISH, not BULLISH
Check VIX row - bearish market regime preferred
Check ORB row (intraday) - want BELOW for shorts
Scan indicator rows - more red = better confirmation
When AVG is 40-60%:
Market is choppy, mixed signals. Either stay out or reduce position size significantly. These are low-probability environments.
Unique Features:
Dynamic Labels: Row names show your actual settings (e.g., "EMA 10 > SMA 20" not generic "Fast > Slow"). You know exactly what's being evaluated.
Customizable Rows: Turn off rows you don't care about. Only show what matters to your strategy.
Customizable Timeframes: On intraday charts, disable 1m or 4h if you don't trade them. Reduces calculation load by 20-40%.
Automatic HTF Handling: On Daily/Weekly/Monthly charts, the table automatically switches to D/W/M columns. No configuration needed.
Performance Smart: "Hide BIAS table on 1D or above" option completely skips all table calculations on higher timeframes if you only trade intraday.
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6. CANDLESTICK PATTERN RECOGNITION
The indicator automatically detects six major reversal patterns and marks them with emojis at the relevant bars.
Why These Six Patterns:
These are the most statistically significant reversal patterns according to trading literature:
High win rate when appearing at support/resistance
Clear visual structure (not subjective)
Work across all timeframes and assets
Studied extensively by institutions
The Patterns:
Bullish Patterns (appear at bottoms):
Bullish Engulfing: Green candle completely engulfs prior red candle's body. Strong reversal signal.
Hammer: Small body with long lower wick (at least 2× body size). Shows rejection of lower prices by buyers.
Morning Star: Three-candle pattern (large red → small indecision → large green). Very strong bottom reversal.
Bearish Patterns (appear at tops):
Bearish Engulfing: Red candle completely engulfs prior green candle's body. Strong reversal signal.
Shooting Star: Small body with long upper wick (at least 2× body size). Shows rejection of higher prices by sellers.
Evening Star: Three-candle pattern (large green → small indecision → large red). Very strong top reversal.
Interactive Tooltips:
Unlike most pattern indicators that just draw shapes, this one is educational:
Hover your mouse over any pattern emoji
A tooltip appears explaining: what the pattern is, what it means, when it's most reliable, and how to trade it
No need to memorize - learn as you trade
Noise Filter:
"Min candle body % to filter noise" setting prevents false signals:
Patterns require minimum body size relative to price
Filters out tiny candles that don't represent real buying/selling pressure
Adjust based on asset volatility (higher % for crypto, lower for low-volatility stocks)
How to Trade Patterns:
Patterns are NOT standalone entry signals. Use them as:
Confirmation: UT Bot gives signal + pattern appears = stronger entry
Reversal Warning: In a trade, opposite pattern appears = consider tightening stop or taking profit
Support/Resistance Validation: Pattern at key level (PDH, VWAP, MA 200) = level is being respected
Best combined with:
UT Bot or Base signal in same direction
Bias Table alignment (AVG > 60% or < 40%)
Appearance at obvious support/resistance
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7. VISUAL TOOLS AND FEATURES
VWAP (Volume Weighted Average Price):
Session-anchored VWAP with standard deviation bands. Shows institutional "fair value" for the trading session.
Anchor Options: Session, Day, Week, Month, Quarter, Year. Choose based on your trading timeframe.
Bands: Up to three pairs (X1, X2, X3) showing statistical deviation. Price at outer bands often reverses.
Auto-Hide on HTF: VWAP hides on Daily/Weekly/Monthly charts automatically unless you enable anchored mode.
Use VWAP as:
Directional bias (above = bullish, below = bearish)
Mean reversion levels (outer bands)
Support/resistance (the VWAP line itself)
Previous Day High/Low:
Automatically plots yesterday's high and low on intraday charts:
Updates at start of each new trading day
Theme-aware colors (dark text for light charts, light text for dark charts)
Hidden automatically on Daily/Weekly/Monthly charts
These levels are critical for intraday traders - institutions watch them closely as support/resistance.
Opening Range Breakout (ORB):
Tracks the high/low of the first 5, 15, 30, or 60 minutes of the trading session:
Customizable session times (preset for NYSE, LSE, TSE, or custom)
Shows current breakout status in Bias Table row (ABOVE, BELOW, INSIDE, BUILDING)
Intraday only - auto-disabled on Daily+ charts
ORB is a classic day trading strategy - breakout above opening range often leads to continuation.
Extra Labels:
Change from Open %: Shows how far price has moved from session open (intraday) or daily open (HTF). Green if positive, red if negative.
ADX Badge: Small label at bottom of last bar showing current ADX value. Green when above your minimum threshold, red when below.
RSI Badge: Small label at top of last bar showing current RSI value with zone status (buy zone, sell zone, or neutral).
These labels provide quick at-a-glance confirmation without needing separate indicator windows.
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8. HOW TO USE THE INDICATOR
Step 1: Add to Chart
Load the indicator on your chosen asset and timeframe
First time: Everything is enabled by default - the chart will look busy
Don't panic - you'll turn off what you don't need
Step 2: Start Simple
Turn OFF everything except:
UT Bot labels (keep these ON)
Bias Table (keep this ON)
Moving Averages (Fast and Medium only)
Suggested Stop Loss and Take Profits
Hide everything else initially. Get comfortable with the basic UT Bot + Bias Table workflow first.
Step 3: Learn the Core Workflow
UT Bot gives a Buy or Sell signal
Check Bias Table AVG column - do you have multi-timeframe alignment?
If yes, enter the trade
Place stop at Suggested Stop Loss line
Scale out at TP levels
Exit on opposite UT signal
Trade this simple system for a week. Get a feel for signal frequency and win rate with your settings.
Step 4: Add Filters Gradually
If you're getting too many losing signals (whipsaws in choppy markets), add filters one at a time:
Try: "Require 2-Bar Trend Confirmation" - wait for 2 bars to confirm direction
Try: ADX filter with minimum threshold - only trade when trend strength is sufficient
Try: RSI pullback filter - only enter on pullbacks, not chasing
Try: Volume filter - require above-average volume
Add one filter, test for a week, evaluate. Repeat.
Step 5: Enable Advanced Features (Optional)
Once you're profitable with the core system, add:
Supertrend for additional trend confirmation
Candlestick patterns for reversal warnings
VWAP for institutional anchor reference
ORB for intraday breakout context
ZLSMA for low-lag trend following
Step 6: Optimize Settings
Every setting has a detailed tooltip explaining what it does and typical values. Hover over any input to read:
What the parameter controls
How it impacts trading
Suggested ranges for scalping, day trading, and swing trading
Start with defaults, then adjust based on your results and style.
Step 7: Set Up Alerts
Right-click chart → Add Alert → Condition: "Luxy Momentum v6" → Choose:
"UT Bot — Buy" for long entries
"UT Bot — Sell" for short entries
"Base Long/Short" for filtered MA cross signals
Optionally enable "Send real-time alert() on UT flip" in settings for immediate notifications.
Common Workflow Variations:
Conservative Trader:
UT signal + Base signal + Candlestick pattern + Bias AVG > 70%
Enter only at major support/resistance
Wider UT sensitivity, multiple filters
Aggressive Trader:
UT signal + Bias AVG > 60%
Enter immediately, no waiting
Tighter UT sensitivity, minimal filters
Swing Trader:
Focus on Daily/Weekly Bias alignment
Ignore intraday noise
Use ORB and PDH/PDL less (or not at all)
Wider stops, patient approach
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9. PERFORMANCE AND OPTIMIZATION
The indicator is optimized for speed, but with 15+ features running simultaneously, chart load time can add up. Here's how to keep it fast:
Biggest Performance Gains:
Disable Unused Timeframes: In "Time Frames" settings, turn OFF any timeframe you don't actively trade. Each disabled TF saves 10-15% calculation time. If you only day trade 5m, 15m, 1h, disable 1m, 2h, 4h.
Hide Bias Table on Daily+: If you only trade intraday, enable "Hide BIAS table on 1D or above". This skips ALL table calculations on higher timeframes.
Draw UT Visuals Only on Bar Close: Reduces intrabar rendering of SL/TP/Entry lines. Has ZERO impact on logic or alerts - purely visual optimization.
Additional Optimizations:
Turn off VWAP bands if you don't use them
Disable candlestick patterns if you don't trade them
Turn off Supertrend fill if you find it distracting (keep the line)
Reduce "Limit to 10 bars" for SL/TP lines to minimize line objects
Performance Features Built-In:
Smart Caching: Higher timeframe data (3-day bias, weekly bias, etc.) updates once per day, not every bar
Conditional Calculations: Volume filter only calculates when enabled. Swing filter only runs when enabled. Nothing computes if turned off.
Modular Design: Every component is independent. Turn off what you don't need without breaking other features.
Typical Load Times:
5m chart, all features ON, 7 timeframes: ~2-3 seconds
5m chart, core features only, 3 timeframes: ~1 second
1m chart, all features: ~4-5 seconds (many bars to calculate)
If loading takes longer, you likely have too many indicators on the chart total (not just this one).
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10. FAQ
Q: How is this different from standard UT Bot indicators?
A: Standard UT Bot (originally by @QuantNomad) is just the ATR trailing line and flip signals. This implementation adds:
- Volume weighting and momentum adjustment to the trailing calculation
- Multiple confirmation filters (swing, %, 2-bar, ZLSMA)
- Smart composite stop loss system from multiple S/R layers
- R-multiple take profit system with freeze-on-touch
- Integration with multi-timeframe Bias Table
- Visual audit trail with checkmarks
Q: Can I use this for automated trading?
A: The indicator is designed for discretionary trading. While it has clear signals and alerts, it's not a mechanical system. Context and judgment are required.
Q: Does it repaint?
A: No. All signals respect bar close. UT Bot logic runs intrabar but signals only trigger on confirmed bars. Alerts fire correctly with no lookahead.
Q: Do I need to use all the features?
A: Absolutely not. The indicator is modular. Many profitable traders use just UT Bot + Bias Table + Moving Averages. Start simple, add complexity only if needed.
Q: How do I know which settings to use?
A: Every single input has a detailed tooltip. Hover over any setting to see:
What it does
How it affects trading
Typical values for scalping, day trading, swing trading
Start with defaults, adjust gradually based on results.
Q: Can I use this on crypto 24/7 markets?
A: Yes. ORB will not work (no defined session), but everything else functions normally. Use "Day" anchor for VWAP instead of "Session".
Q: The Bias Table is blank or not showing.
A: Check:
"Show Table" is ON
Table position isn't overlapping another indicator's table (change position)
At least one row is enabled
"Hide BIAS table on 1D or above" is OFF (if on Daily+ chart)
Q: Why are candlestick patterns not appearing?
A: Patterns are relatively rare by design - they only appear at genuine reversal points. Check:
Pattern toggles are ON
"Min candle body %" isn't too high (try 0.05-0.10)
You're looking at a chart with actual reversals (not strong trending market)
Q: UT Bot is too sensitive/not sensitive enough.
A: Adjust "Sensitivity (Key×ATR)". Lower number = tighter stop, more signals. Higher number = wider stop, fewer signals. Read the tooltip for guidance.
Q: Can I get alerts for the Bias Table?
A: The Bias Table is a dashboard for visual analysis, not a signal generator. Set alerts on UT Bot or Base signals, then manually check Bias Table for confirmation.
Q: Does this work on stocks with low volume?
A: Yes, but turn OFF the volume filter. Low volume stocks will never meet relative volume requirements.
Q: How often should I check the Bias Table?
A: Before every entry. It takes 2 seconds to glance at the AVG column and headline rows. This one check can save you from fighting the trend.
Q: What if UT signal and Base signal disagree?
A: UT Bot is more aggressive (ATR trailing). Base signals are more conservative (MA cross + filters). If they disagree, either:
Wait for both to align (safest)
Take the UT signal but with smaller size (aggressive)
Skip the trade (conservative)
There's no "right" answer - depends on your risk tolerance.
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FINAL NOTES
The indicator gives you an edge. How you use that edge determines results.
For questions, feedback, or support, comment on the indicator page or message the author.
Happy Trading!
Volume Sampled Supertrend [BackQuant]Volume Sampled Supertrend
A Supertrend that runs on a volume sampled price series instead of fixed time. New synthetic bars are only created after sufficient traded activity, which filters out low participation noise and makes the trend much easier to read and model.
Original Script Link
This indicator is built on top of my volume sampling engine. See the base implementation here:
Why Volume Sampling
Traditional charts print a bar every N minutes regardless of how active the tape is. During quiet periods you accumulate many small, low information bars that add noise and whipsaws to downstream signals.
Volume sampling replaces the clock with participation. A new synthetic bar is created only when a pre-set amount of volume accumulates (or, in Dollar Bars mode, when pricevolume reaches a dollar threshold). The result is a non-uniform time series that stretches in busy regimes and compresses in quiet regimes. This naturally:
filters dead time by skipping low volume chop;
standardizes the information content per bar, improving comparability across regimes;
stabilizes volatility estimates used inside banded indicators;
gives trend and breakout logic cleaner state transitions with fewer micro flips.
What this tool does
It builds a synthetic OHLCV stream from volume based buckets and then applies a Supertrend to that synthetic price. You are effectively running Supertrend on a participation clock rather than a wall clock.
Core Features
Sampling Engine - Choose Volume buckets or Dollar Bars . Thresholds can be dynamic from a rolling mean or median, or fixed by the user.
Synthetic Candles - Plots the volume sampled OHLC candles so you can visually compare against regular time candles.
Supertrend on Synthetic Price - ATR bands and direction are computed on the sampled series, not on time bars.
Adaptive Coloring - Candle colors can reflect side, intensity by volume, or a neutral scheme.
Research Panels - Table shows total samples, current bucket fill, threshold, bars-per-sample, and synthetic return stats.
Alerts - Long and Short triggers on Supertrend direction flips for the synthetic series.
How it works
Sampling
Pick Sampling Method = Volume or Dollar Bars.
Set the dynamic threshold via Rolling Lookback and Filter (Mean or Median), or enable Use Fixed and type a constant.
The script accumulates volume (or pricevolume) each time bar. When the bucket reaches the threshold, it finalizes one or more synthetic candles and resets accumulation.
Each synthetic candle stores its own OHLCV and is appended to the synthetic series used for all downstream logic.
Supertrend on the sampled stream
Choose Supertrend Source (Open, High, Low, Close, HLC3, HL2, OHLC4, HLCC4) derived from the synthetic candle.
Compute ATR over the synthetic series with ATR Period , then form upperBand = src + factorATR and lowerBand = src - factorATR .
Apply classic trailing band and direction rules to produce Supertrend and trend state.
Because bars only come when there is sufficient participation, band touches and flips tend to align with meaningful pushes, not idle prints.
Reading the display
Synthetic Volume Bars - The non-uniform candles that represent equal information buckets. Expect more candles during active sessions and fewer during lulls.
Volume Sampled Supertrend - The main line. Green when Trend is 1, red when Trend is -1.
Markers - Small dots appear when a new synthetic sample is created, useful for aligning activity cycles.
Time Bars Overlay (optional) - Plot regular time candles to compare how the synthetic stream compresses quiet chop.
Settings you will use most
Data Settings
Sampling Method - Volume or Dollar Bars.
Rolling Lookback and Filter - Controls the dynamic threshold. Median is robust to outliers, Mean is smoother.
Use Fixed and Fixed Threshold - Force a constant bucket size for consistent sampling across regimes.
Max Stored Samples - Ring buffer limit for performance.
Indicator Settings
SMA over last N samples - A moving average computed on the synthetic close series. Can be hidden for a cleaner layout.
Supertrend Source - Price field from the synthetic candle.
ATR Period and Factor - Standard Supertrend controls applied on the synthetic series.
Visuals and UI
Show Synthetic Bars - Turn synthetic candles on or off.
Candle Color Mode - Green/Red, Volume Intensity, Neutral, or Adaptive.
Mark new samples - Puts a dot when a bucket closes.
Show Time Bars - Overlay regular candles for comparison.
Paint candles according to Trend - Colors chart candles using current synthetic Supertrend direction.
Line Width , Colors , and Stats Table toggles.
Some workflow notes:
Trend Following
Set Sampling Method = Volume, Filter = Median, and a reasonable Rolling Lookback so busy regimes produce more samples.
Trade in the direction of the Volume Sampled Supertrend. Because flips require real participation, you tend to avoid micro whipsaws seen on time bars.
Use the synthetic SMA as a bias rail and trailing reference for partials or re-entries.
Breakout and Continuation
Watch for rapid clustering of new sample markers and a clean flip of the synthetic Supertrend.
The compression of quiet time and expansion in busy bursts often makes breakouts more legible than on uniform time charts.
Mean Reversion
In instruments that oscillate, faded moves against the synthetic Supertrend are easier to time when the bucket cadence slows and Supertrend flattens.
Combine with the synthetic SMA and return statistics in the table for sizing and expectation setting.
Stats table (top right)
Method and Total Samples - Sampling regime and current synthetic history length.
Current Vol or Dollar and Threshold - Live bucket fill versus the trigger.
Bars in Bucket and Avg Bars per Sample - How much time data each synthetic bar tends to compress.
Avg Return and Return StdDev - Simple research metrics over synthetic close-to-close changes.
Why this reduces noise
Time based bars treat a 5 minute print with 1 percent of average participation the same as one with 300 percent. Volume sampling equalizes bar information content. By advancing the bar only when sufficient activity occurs, you skip low quality intervals that add variance but little signal. For banded systems like Supertrend, this often means fewer false flips and cleaner runs.
Notes and tips
Use Dollar Bars on assets where nominal price varies widely over time or across symbols.
Median filter can resist single burst outliers when setting dynamic thresholds.
If you need a stable research baseline, set Use Fixed and keep the threshold constant across tests.
Enable Show Time Bars occasionally to sanity check what the synthetic stream is compressing or stretching.
Link again for reference
Original Volume Based Sampling engine:
Bottom line
When you let participation set the clock, your Supertrend reacts to meaningful flow instead of idle prints. The result is a cleaner state machine, fewer micro whipsaws, and a trend read that respects when the market is actually trading.
CVD Polarity Indicator (With Rolling Smoothed)📊 CVD Polarity Indicator (with Rolling Smoothing)
Purpose
The CVD Polarity Indicator combines Cumulative Volume Delta (CVD) with price bar direction to measure whether buying or selling pressure is in agreement with price action. It then smooths that signal over time, making it easier to see underlying volume-driven market trends.
This indicator is essentially a volume–price agreement oscillator:
- It compares price direction with volume delta (CVD).
- Translates that into per-bar polarity.
- Smooths it into a rolling sum for clarity.
- Adds a short EMA to highlight turning points.
The end result: a tool that helps you see when price action is backed by real volume flows versus when it’s running on weak participation.
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1. Cumulative Volume Delta (CVD)
What it is:
CVD is the cumulative sum of buying vs. selling pressure measured by volume.
- If a bar closes higher than it opens → that bar’s volume is treated as buying pressure (+volume).
- If a bar closes lower than it opens → that bar’s volume is treated as selling pressure (–volume).
Rolling version:
Instead of accumulating indefinitely (which just creates a line that trends forever), this indicator uses a rolling sum over a user-defined number of bars (cumulation_length, default 14).
- This shows the net delta in recent bars, making the CVD more responsive and localized.
2. Bar Direction vs. CVD Change
Each bar has two pieces of directional information:
1. Bar direction: Whether the candle closed above or below its open (close - open).
2. CVD change: Whether cumulative delta increased or decreased from the prior bar (cvd - cvd ).
By comparing these two:
- Agreement (both up or both down):
→ Polarity = +volume (if bullish) or –volume (if bearish).
- Disagreement (bar up but CVD down, or bar down but CVD up):
→ Polarity flips sign, signaling divergence between price and volume.
Thus, raw polarity = a per-bar measure of whether price action and volume delta are in sync.
3. Polarity Smoothing (Rolling Polarity)
- Problem with raw polarity:
It flips bar-to-bar and looks very jagged — not great for seeing trends.
- Solution:
The indicator applies a rolling sum over the past polarity_length bars (default 14).
- This creates a smoother curve, representing the net polarity over time.
- Positive values = net bullish alignment (buyers stronger).
- Negative values = net bearish alignment (sellers stronger).
Think of it like an oscillator showing whether buyers or sellers have had control recently.
4. EMA Smoothing
Finally, a 10-period EMA is applied on top of the rolling polarity line:
- This further reduces noise.
- It helps highlight shifts in the underlying polarity trend.
- Crossovers of the polarity line and its EMA can serve as trade signals (bullish/bearish inflection points).
________________________________________________________________________________
How to Read It
1. Polarity above zero → Recent bars show more bullish agreement between price and volume.
2. Polarity below zero → Recent bars show more bearish agreement.
3. Polarity diverging from price → If price goes up but polarity trends down, it signals weakening buying pressure (potential reversal).
4. EMA crossovers →
- Polarity crossing above its EMA = bullish momentum shift.
- Polarity crossing below its EMA = bearish momentum shift.
Practical Use Cases
- Trend Confirmation
Use polarity to confirm whether a price move is supported by volume. If price rallies but
polarity stays negative, the move is weak.
- Divergence Signals
Watch for divergences between price trend and polarity trend (e.g., higher highs in price but
lower highs in polarity).
- Momentum Shifts
Use EMA crossovers as signals that the underlying balance of buying/selling has flipped.
Helper Lib by tristanlee85Library "helpers"
This library offers various functions and types based on the algorithmic
concepts as authored by ICT.
kv(key, value)
Returns a string of the key/value set, suitable for debug logging
Parameters:
key (string)
value (string)
Returns: A string formatted as "{key}: {value}"
kv(key, value)
Parameters:
key (string)
value (int)
kv(key, value)
Parameters:
key (string)
value (float)
kv(key, value)
Parameters:
key (string)
value (bool)
method enable(this, enable)
Enable/Disable debug logging
Namespace types: Debugger
Parameters:
this (Debugger)
enable (bool) : Set to `true` by default.
method group(this, label)
Creates a group label for nested debug() invocations
Namespace types: Debugger
Parameters:
this (Debugger)
label (string)
method groupEnd(this, label)
Ends the specified debug group
Namespace types: Debugger
Parameters:
this (Debugger)
label (string)
method log(this, s, arg1, arg2, arg3, arg4, arg5)
Logs the param values if debug mode is enabled
Namespace types: Debugger
Parameters:
this (Debugger)
s (string) : Title of the log message
arg1 (string)
arg2 (string)
arg3 (string)
arg4 (string)
arg5 (string)
method logIf(this, expr, s, arg1, arg2, arg3, arg4, arg5)
Same behavior as debug() except will only log if the passed expression is true
Namespace types: Debugger
Parameters:
this (Debugger)
expr (bool) : Boolean expression to determine if debug logs should be logged
s (string) : Title of the log message
arg1 (string)
arg2 (string)
arg3 (string)
arg4 (string)
arg5 (string)
style_getLineStyleFromType(opt)
Returns the corresponding line style constant for the given LineStyleType
Parameters:
opt (series LineStyleType) : The selected line style type
Returns: The Pine Script line style constant
style_getTextSizeFromType(opt)
Returns the corresponding text size constant for the given TextSizeType
Parameters:
opt (series TextSizeType) : The selected text size type
Returns: The Pine Script text size constant
style_getTextHAlignFromType(t)
Returns the corresponding horizontal text align constant for the given HAlignType
Parameters:
t (series HAlignType) : The selected text align type
Returns: The Pine Script text align constant
style_getTextVAlignFromType(t)
Returns the corresponding vertical text align constant for the given VAlignType
Parameters:
t (series VAlignType) : The selected text align type
Returns: The Pine Script text align constant
format_sentimentType(sentiment, pd)
Used to produce a string with the sentiment and PD array type (e.g., "+FVG")
Parameters:
sentiment (series SentimentType) : The sentiment value (e.g., SentimentType.BULLISH)
pd (series PDArrayType) : The price data array (e.g., PDArrayType.FVG)
Returns: A formatted string with the sentiment and PD array (e.g., "+FVG")
format_timeToString(timestamp)
Formats a UNIX timestamp into a date and time string based on predefined formats
Parameters:
timestamp (int) : The UNIX timestamp to format
Returns: A formatted string as "MM-dd (E) - HH:mm"
method init(this)
Initializes the session and validates the configuration. This MUST be called immediately after creating a new instance.
Namespace types: Session
Parameters:
this (Session) : The Session object reference
Returns: The Session object (chainable) or throws a runtime error if invalid
method isActive(this, _time)
Determines if the session is active based on the current bar time
Namespace types: Session
Parameters:
this (Session) : The Session object reference
_time (int)
Returns: `true` if the session is currently active; `false` otherwise
method draw(this)
Draws the line and optional label
Namespace types: LineLabel
Parameters:
this (LineLabel) : The LineLabel object reference
Returns: The LineLabel object (chainable)
method extend(this, x)
Extends the line and label right to the specified bar index
Namespace types: LineLabel
Parameters:
this (LineLabel) : The LineLabel object reference
x (int) : The bar index to extend to
Returns: The LineLabel object (chainable)
method destroy(this)
Removes the line and label from the chart
Namespace types: LineLabel
Parameters:
this (LineLabel) : The LineLabel object reference
isFVG(includeVI, barIdx)
Checks if the previous bars form a Fair Value Gap (FVG)
Parameters:
includeVI (bool) : If true, includes Volume Imbalance in the FVG calculation
barIdx (int) : The index of the bar to check from (default is 0 for the current bar)
Returns: A Gap object if a FVG is detected; otherwise, `na`
isVolumeImbalance(barIdx)
Checks if the previous bars form a Volume Imbalance (VI)
Parameters:
barIdx (int) : The index of the bar to check from (default is 0 for the current bar)
Returns: A Gap object if a VI is detected; otherwise, `na`
isLiquidityVoid(barIdx)
Checks if the previous bars form a Liquidity Void (LV)
Parameters:
barIdx (int) : The index of the bar to check from (default is 0 for the current bar)
Returns: A Gap object if an LV is detected; otherwise, `na`
isSwingPoint(barIdx)
Checks if the previous bars form a swing point
Parameters:
barIdx (int) : The index of the bar to check from (default is 0 for the current bar)
Returns: A SwingPoint object if a swing point is detected; otherwise, `na`
Debugger
A debug logging utility with group support
Fields:
enabled (series bool)
_debugGroupStack (array)
Session
Defines a trading session with a name and time range. When creating a new instance of this type, you MUST call init() immediately.
Fields:
name (series string) : A display-friendly name (e.g., "NY AM")
session (series string) : A string defining the session time range (e.g., "1300-1400")
enabled (series bool) : Optional flag for custom logic; defaults to false
start (series int) : UNIX time representing the session start (set via isActive())
end (series int) : UNIX time representing the session end (set via isActive())
_t (series int)
_start_HH (series float)
_start_mm (series float)
_end_HH (series float)
_end_mm (series float)
Gap
Represents a price inefficiency (gap) with details on sentiment and price levels
Fields:
type (series SentimentType) : The sentiment of the gap (e.g., SentimentType.BULLISH)
name (series string) : A display-friendly name (e.g., "+FVG")
startTime (series int) : UNIX time value for the gap's start
endTime (series int) : UNIX time value for the gap's end
startIndex (series int) : Bar index where the gap starts
endIndex (series int) : Bar index where the gap ends
gapLow (series float) : The lowest price level of the gap
gapHigh (series float) : The highest price level of the gap
ce (series float) : The consequent encroachment level of the gap
SwingPoint
Represents a swing point with details on type and price level
Fields:
type (series SwingPointType) : The type of swing point (e.g., SwingPointType.HIGH)
time (series int) : UNIX time value for the swing point
barIdx (series int) : Bar index where the swing point occurs
price (series float) : The price level of the swing point which is either the high or low of the middle bar
LineLabel
Combines a line and box type to produce a line with a label that is properly aligned
Fields:
x (series int) : The X-axis starting point as a bar index
y (series float) : The Y-axis starting point as the price level
color (series color) : Both the line and text color
width (series int) : Thickness of the line
label (series string) : Text to display
showLabel (series bool) : Boolean to conditionally show/hide the label (default is false)
lineStyle (series LineStyleType) : The style of the line
textSize (series TextSizeType)
_b (series box)
_l (series line)
real_time_candlesIntroduction
The Real-Time Candles Library provides comprehensive tools for creating, manipulating, and visualizing custom timeframe candles in Pine Script. Unlike standard indicators that only update at bar close, this library enables real-time visualization of price action and indicators within the current bar, offering traders unprecedented insight into market dynamics as they unfold.
This library addresses a fundamental limitation in traditional technical analysis: the inability to see how indicators evolve between bar closes. By implementing sophisticated real-time data processing techniques, traders can now observe indicator movements, divergences, and trend changes as they develop, potentially identifying trading opportunities much earlier than with conventional approaches.
Key Features
The library supports two primary candle generation approaches:
Chart-Time Candles: Generate real-time OHLC data for any variable (like RSI, MACD, etc.) while maintaining synchronization with chart bars.
Custom Timeframe (CTF) Candles: Create candles with custom time intervals or tick counts completely independent of the chart's native timeframe.
Both approaches support traditional candlestick and Heikin-Ashi visualization styles, with options for moving average overlays to smooth the data.
Configuration Requirements
For optimal performance with this library:
Set max_bars_back = 5000 in your script settings
When using CTF drawing functions, set max_lines_count = 500, max_boxes_count = 500, and max_labels_count = 500
These settings ensure that you will be able to draw correctly and will avoid any runtime errors.
Usage Examples
Basic Chart-Time Candle Visualization
// Create real-time candles for RSI
float rsi = ta.rsi(close, 14)
Candle rsi_candle = candle_series(rsi, CandleType.candlestick)
// Plot the candles using Pine's built-in function
plotcandle(rsi_candle.Open, rsi_candle.High, rsi_candle.Low, rsi_candle.Close,
"RSI Candles", rsi_candle.candle_color, rsi_candle.candle_color)
Multiple Access Patterns
The library provides three ways to access candle data, accommodating different programming styles:
// 1. Array-based access for collection operations
Candle candles = candle_array(source)
// 2. Object-oriented access for single entity manipulation
Candle candle = candle_series(source)
float value = candle.source(Source.HLC3)
// 3. Tuple-based access for functional programming styles
= candle_tuple(source)
Custom Timeframe Examples
// Create 20-second candles with EMA overlay
plot_ctf_candles(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 20,
timezone = -5,
tied_open = true,
ema_period = 9,
enable_ema = true
)
// Create tick-based candles (new candle every 15 ticks)
plot_ctf_tick_candles(
source = close,
candle_type = CandleType.heikin_ashi,
number_of_ticks = 15,
timezone = -5,
tied_open = true
)
Advanced Usage with Custom Visualization
// Get custom timeframe candles without automatic plotting
CandleCTF my_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 30
)
// Apply custom logic to the candles
float ema_values = my_candles.ctf_ema(14)
// Draw candles and EMA using time-based coordinates
my_candles.draw_ctf_candles_time()
ema_values.draw_ctf_line_time(line_color = #FF6D00)
Library Components
Data Types
Candle: Structure representing chart-time candles with OHLC, polarity, and visualization properties
CandleCTF: Extended candle structure with additional time metadata for custom timeframes
TickData: Structure for individual price updates with time deltas
Enumerations
CandleType: Specifies visualization style (candlestick or Heikin-Ashi)
Source: Defines price components for calculations (Open, High, Low, Close, HL2, etc.)
SampleType: Sets sampling method (Time-based or Tick-based)
Core Functions
get_tick(): Captures current price as a tick data point
candle_array(): Creates an array of candles from price updates
candle_series(): Provides a single candle based on latest data
candle_tuple(): Returns OHLC values as a tuple
ctf_candles_array(): Creates custom timeframe candles without rendering
Visualization Functions
source(): Extracts specific price components from candles
candle_ctf_to_float(): Converts candle data to float arrays
ctf_ema(): Calculates exponential moving averages for candle arrays
draw_ctf_candles_time(): Renders candles using time coordinates
draw_ctf_candles_index(): Renders candles using bar index coordinates
draw_ctf_line_time(): Renders lines using time coordinates
draw_ctf_line_index(): Renders lines using bar index coordinates
Technical Implementation Notes
This library leverages Pine Script's varip variables for state management, creating a sophisticated real-time data processing system. The implementation includes:
Efficient tick capturing: Samples price at every execution, maintaining temporal tracking with time deltas
Smart state management: Uses a hybrid approach with mutable updates at index 0 and historical preservation at index 1+
Temporal synchronization: Manages two time domains (chart time and custom timeframe)
The tooltip implementation provides crucial temporal context for custom timeframe visualizations, allowing users to understand exactly when each candle formed regardless of chart timeframe.
Limitations
Custom timeframe candles cannot be backtested due to Pine Script's limitations with historical tick data
Real-time visualization is only available during live chart updates
Maximum history is constrained by Pine Script's array size limits
Applications
Indicator visualization: See how RSI, MACD, or other indicators evolve in real-time
Volume analysis: Create custom volume profiles independent of chart timeframe
Scalping strategies: Identify short-term patterns with precisely defined time windows
Volatility measurement: Track price movement characteristics within bars
Custom signal generation: Create entry/exit signals based on custom timeframe patterns
Conclusion
The Real-Time Candles Library bridges the gap between traditional technical analysis (based on discrete OHLC bars) and the continuous nature of market movement. By making indicators more responsive to real-time price action, it gives traders a significant edge in timing and decision-making, particularly in fast-moving markets where waiting for bar close could mean missing important opportunities.
Whether you're building custom indicators, researching price patterns, or developing trading strategies, this library provides the foundation for sophisticated real-time analysis in Pine Script.
Implementation Details & Advanced Guide
Core Implementation Concepts
The Real-Time Candles Library implements a sophisticated event-driven architecture within Pine Script's constraints. At its heart, the library creates what's essentially a reactive programming framework handling continuous data streams.
Tick Processing System
The foundation of the library is the get_tick() function, which captures price updates as they occur:
export get_tick(series float source = close, series float na_replace = na)=>
varip float price = na
varip int series_index = -1
varip int old_time = 0
varip int new_time = na
varip float time_delta = 0
// ...
This function:
Samples the current price
Calculates time elapsed since last update
Maintains a sequential index to track updates
The resulting TickData structure serves as the fundamental building block for all candle generation.
State Management Architecture
The library employs a sophisticated state management system using varip variables, which persist across executions within the same bar. This creates a hybrid programming paradigm that's different from standard Pine Script's bar-by-bar model.
For chart-time candles, the core state transition logic is:
// Real-time update of current candle
candle_data := Candle.new(Open, High, Low, Close, polarity, series_index, candle_color)
candles.set(0, candle_data)
// When a new bar starts, preserve the previous candle
if clear_state
candles.insert(1, candle_data)
price.clear()
// Reset state for new candle
Open := Close
price.push(Open)
series_index += 1
This pattern of updating index 0 in real-time while inserting completed candles at index 1 creates an elegant solution for maintaining both current state and historical data.
Custom Timeframe Implementation
The custom timeframe system manages its own time boundaries independent of chart bars:
bool clear_state = switch settings.sample_type
SampleType.Ticks => cumulative_series_idx >= settings.number_of_ticks
SampleType.Time => cumulative_time_delta >= settings.number_of_seconds
This dual-clock system synchronizes two time domains:
Pine's execution clock (bar-by-bar processing)
The custom timeframe clock (tick or time-based)
The library carefully handles temporal discontinuities, ensuring candle formation remains accurate despite irregular tick arrival or market gaps.
Advanced Usage Techniques
1. Creating Custom Indicators with Real-Time Candles
To develop indicators that process real-time data within the current bar:
// Get real-time candles for your data
Candle rsi_candles = candle_array(ta.rsi(close, 14))
// Calculate indicator values based on candle properties
float signal = ta.ema(rsi_candles.first().source(Source.Close), 9)
// Detect patterns that occur within the bar
bool divergence = close > close and rsi_candles.first().Close < rsi_candles.get(1).Close
2. Working with Custom Timeframes and Plotting
For maximum flexibility when visualizing custom timeframe data:
// Create custom timeframe candles
CandleCTF volume_candles = ctf_candles_array(
source = volume,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 60
)
// Convert specific candle properties to float arrays
float volume_closes = volume_candles.candle_ctf_to_float(Source.Close)
// Calculate derived values
float volume_ema = volume_candles.ctf_ema(14)
// Create custom visualization
volume_candles.draw_ctf_candles_time()
volume_ema.draw_ctf_line_time(line_color = color.orange)
3. Creating Hybrid Timeframe Analysis
One powerful application is comparing indicators across multiple timeframes:
// Standard chart timeframe RSI
float chart_rsi = ta.rsi(close, 14)
// Custom 5-second timeframe RSI
CandleCTF ctf_candles = ctf_candles_array(
source = close,
candle_type = CandleType.candlestick,
sample_type = SampleType.Time,
number_of_seconds = 5
)
float fast_rsi_array = ctf_candles.candle_ctf_to_float(Source.Close)
float fast_rsi = fast_rsi_array.first()
// Generate signals based on divergence between timeframes
bool entry_signal = chart_rsi < 30 and fast_rsi > fast_rsi_array.get(1)
Final Notes
This library represents an advanced implementation of real-time data processing within Pine Script's constraints. By creating a reactive programming framework for handling continuous data streams, it enables sophisticated analysis typically only available in dedicated trading platforms.
The design principles employed—including state management, temporal processing, and object-oriented architecture—can serve as patterns for other advanced Pine Script development beyond this specific application.
------------------------
Library "real_time_candles"
A comprehensive library for creating real-time candles with customizable timeframes and sampling methods.
Supports both chart-time and custom-time candles with options for candlestick and Heikin-Ashi visualization.
Allows for tick-based or time-based sampling with moving average overlay capabilities.
get_tick(source, na_replace)
Captures the current price as a tick data point
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
na_replace (float) : Optional - Value to use when source is na
Returns: TickData structure containing price, time since last update, and sequential index
candle_array(source, candle_type, sync_start, bullish_color, bearish_color)
Creates an array of candles based on price updates
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
sync_start (simple bool) : Optional - Whether to synchronize with the start of a new bar
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of Candle objects ordered with most recent at index 0
candle_series(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides a single candle based on the latest price data
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: A single Candle object representing the current state
candle_tuple(source, candle_type, wait_for_sync, bullish_color, bearish_color)
Provides candle data as a tuple of OHLC values
Parameters:
source (float) : Optional - Price source to sample (defaults to close)
candle_type (simple CandleType) : Optional - Type of candle chart to create (candlestick or Heikin-Ashi)
wait_for_sync (simple bool) : Optional - Whether to wait for a new bar before starting
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Tuple representing current candle values
method source(self, source, na_replace)
Extracts a specific price component from a Candle
Namespace types: Candle
Parameters:
self (Candle)
source (series Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
na_replace (float) : Optional - Value to use when source value is na
Returns: The requested price value from the candle
method source(self, source)
Extracts a specific price component from a CandleCTF
Namespace types: CandleCTF
Parameters:
self (CandleCTF)
source (simple Source) : Type of price data to extract (Open, High, Low, Close, or composite values)
Returns: The requested price value from the candle as a varip
method candle_ctf_to_float(self, source)
Converts a specific price component from each CandleCTF to a float array
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
Returns: Array of float values extracted from the candles, ordered with most recent at index 0
method ctf_ema(self, ema_period)
Calculates an Exponential Moving Average for a CandleCTF array
Namespace types: array
Parameters:
self (array)
ema_period (simple float) : Period for the EMA calculation
Returns: Array of float values representing the EMA of the candle data, ordered with most recent at index 0
method draw_ctf_candles_time(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar time coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using time-based x-coordinates
method draw_ctf_candles_index(self, sample_type, number_of_ticks, number_of_seconds, timezone)
Renders custom timeframe candles using bar index coordinates
Namespace types: array
Parameters:
self (array)
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks), used for tooltips
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks), used for tooltips
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time), used for tooltips
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12), used for tooltips
Returns: void - Renders candles on the chart using index-based x-coordinates
method draw_ctf_line_time(self, source, line_size, line_color)
Renders a line representing a price component from the candles using time coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_time(self, line_size, line_color)
Renders a line from a varip float array using time coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using time-based x-coordinates
method draw_ctf_line_index(self, source, line_size, line_color)
Renders a line representing a price component from the candles using index coordinates
Namespace types: array
Parameters:
self (array)
source (simple Source) : Optional - Type of price data to extract (defaults to Close)
line_size (simple int) : Optional - Width of the line
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
method draw_ctf_line_index(self, line_size, line_color)
Renders a line from a varip float array using index coordinates
Namespace types: array
Parameters:
self (array)
line_size (simple int) : Optional - Width of the line, defaults to 2
line_color (simple color) : Optional - Color of the line
Returns: void - Renders a connected line on the chart using index-based x-coordinates
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots tick-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_tick_candles(source, candle_type, number_of_ticks, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots tick-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_ticks (simple int) : Number of ticks per candle
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, line_width, ema_color, use_time_indexing)
Plots time-based candles with moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
ema_period (simple float) : Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with EMA overlay
plot_ctf_time_candles(source, candle_type, number_of_seconds, timezone, tied_open, bullish_color, bearish_color, use_time_indexing)
Plots time-based candles without moving average
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to display
number_of_seconds (simple float) : Time duration per candle in seconds
timezone (simple int) : Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart without moving average
plot_ctf_candles(source, candle_type, sample_type, number_of_ticks, number_of_seconds, timezone, tied_open, ema_period, bullish_color, bearish_color, enable_ema, line_width, ema_color, use_time_indexing)
Unified function for plotting candles with comprehensive options
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Optional - Type of candle chart to display
sample_type (simple SampleType) : Optional - Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
timezone (simple int) : Optional - Timezone offset from UTC (-12 to +12)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
ema_period (simple float) : Optional - Period for the exponential moving average
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
enable_ema (bool) : Optional - Whether to display the EMA overlay
line_width (simple int) : Optional - Width of the moving average line, defaults to 2
ema_color (color) : Optional - Color of the moving average line
use_time_indexing (simple bool) : Optional - When true the function will plot with xloc.time, when false it will plot using xloc.bar_index
Returns: void - Creates visual candle chart with optional EMA overlay
ctf_candles_array(source, candle_type, sample_type, number_of_ticks, number_of_seconds, tied_open, bullish_color, bearish_color)
Creates an array of custom timeframe candles without rendering them
Parameters:
source (float) : Input price source to sample
candle_type (simple CandleType) : Type of candle chart to create (candlestick or Heikin-Ashi)
sample_type (simple SampleType) : Method for sampling data (Time or Ticks)
number_of_ticks (simple int) : Optional - Number of ticks per candle (used when sample_type is Ticks)
number_of_seconds (simple float) : Optional - Time duration per candle in seconds (used when sample_type is Time)
tied_open (simple bool) : Optional - Whether to tie open price to close of previous candle
bullish_color (color) : Optional - Color for bullish candles
bearish_color (color) : Optional - Color for bearish candles
Returns: Array of CandleCTF objects ordered with most recent at index 0
Candle
Structure representing a complete candle with price data and display properties
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
candle_color (series color) : Color to use when rendering the candle
ready (series bool) : Boolean indicating if candle data is valid and ready for use
TickData
Structure for storing individual price updates
Fields:
price (series float) : The price value at this tick
time_delta (series float) : Time elapsed since the previous tick in milliseconds
series_index (series int) : Sequential index identifying this tick
CandleCTF
Structure representing a custom timeframe candle with additional time metadata
Fields:
Open (series float) : Opening price of the candle
High (series float) : Highest price of the candle
Low (series float) : Lowest price of the candle
Close (series float) : Closing price of the candle
polarity (series bool) : Boolean indicating if candle is bullish (true) or bearish (false)
series_index (series int) : Sequential index identifying the candle in the series
open_time (series int) : Timestamp marking when the candle was opened (in Unix time)
time_delta (series float) : Duration of the candle in milliseconds
candle_color (series color) : Color to use when rendering the candle
TrinityBar**TrinityBar Strategy Description**
The TrinityBar strategy is a price‐action based trading model that leverages Bill Williams’ bar thirds concept to generate entry signals and execute market orders automatically. Here’s how it works:
1. **Bar Thirds Calculation:**
The strategy calculates the range of both the current fully formed bar and the previous fully formed bar. It then divides each bar’s range into three equal parts (thirds).
- For the current bar, the lower third and upper third levels are computed.
- The same is done for the previous bar.
2. **Bar Type Classification:**
Each bar is classified into one of several types based on where its open and close fall relative to its thirds:
- **Bullish Patterns:**
- *1‑3 Bar:* Opens in the lower third and closes in the upper third.
- *2‑3 Bar:* Opens in the middle third and closes in the upper third.
- *3‑3 Bar:* Both open and close are in the upper third.
- **Bearish Patterns:**
- *3‑1 Bar:* Opens in the upper third and closes in the lower third.
- *2‑1 Bar:* Opens in the middle third and closes in the lower third.
- *1‑1 Bar:* Both open and close are in the lower third.
3. **Signal Generation:**
- **Bullish Signal:** A valid buy is generated when the previous bar exhibits any bullish pattern (1‑3, 2‑3, or 3‑3) and the current bar is either a 1‑3 or a 3‑3 bar.
- **Bearish Signal:** A valid sell is generated when the previous bar shows any bearish pattern (1‑1, 2‑1, or 3‑1) and the current bar is either a 1‑1 or a 3‑1 bar.
4. **Visual Alerts:**
When a valid signal is identified, the strategy plots a small triangle below the bar for a buy signal (labeled “B” in green) and a triangle above the bar for a sell signal (labeled “S” in red).
5. **Trade Execution:**
Once a signal is confirmed:
- If a bullish signal is generated, any short positions are closed, and if there is no existing long position, a market long order is entered.
- Conversely, if a bearish signal occurs, any long positions are closed, and a market short order is entered if not already in a short position.
This strategy is designed to capture significant price expansions by relying solely on price action and bar structure, without relying on lagging indicators. It provides a mechanical, systematic approach that removes emotional bias from trading decisions.
NVOL Normalized Volume & VolatilityOVERVIEW
Plots a normalized volume (or volatility) relative to a given bar's typical value across all charted sessions. The concept is similar to Relative Volume (RVOL) and Average True Range (ATR), but rather than using a moving average, this script uses bar data from previous sessions to more accurately separate what's normal from what's anomalous. Compatible on all timeframes and symbols.
Having volume and volatility processed within a single indicator not only allows you to toggle between the two for a consistent data display, it also allows you to measure how correlated they are. These measurements are available in the data table.
DATA & MATH
The core formula used to normalize each bar is:
( Value / Basis ) × Scale
Value
The current bar's volume or volatility (see INPUTS section). When set to volume, it's exactly what you would expect (the volume of the bar). When set to volatility, it's the bar's range (high - low).
Basis
A statistical threshold (Mean, Median, or Q3) plus a Sigma multiple (standard deviations). The default is set to the Mean + Sigma × 3 , which represents 99.7% of data in a normal distribution. The values are derived from the current bar's equivalent in other sessions. For example, if the current bar time is 9:30 AM, all previous 9:30 AM bars would be used to get the Mean and Sigma. Thus Mean + Sigma × 3 would represent the Normal Bar Vol at 9:30 AM.
Scale
Depends on the Normalize setting, where it is 1 when set to Ratio, and 100 when set to Percent. This simply determines the plot's scale (ie. 0 to 1 vs. 0 to 100).
INPUTS
While the default configuration is recommended for a majority of use cases (see BEST PRACTICES), settings should be adjusted so most of the Normalized Plot and Linear Regression are below the Signal Zone. Only the most extreme values should exceed this area.
Normalize
Allows you to specify what should be normalized (Volume or Volatility) and how it should be measured (as a Ratio or Percentage). This sets the value and scale in the core formula.
Basis
Specifies the statistical threshold (Mean, Median, or Q3) and how many standard deviations should be added to it (Sigma). This is the basis in the core formula.
Mean is the sum of values divided by the quantity of values. It's what most people think of when they say "average."
Median is the middle value, where 50% of the data will be lower and 50% will be higher.
Q3 is short for Third Quartile, where 75% of the data will be lower and 25% will be higher (think three quarters).
Sample
Determines the maximum sample size.
All Charted Bars is the default and recommended option, and ignores the adjacent lookback number.
Lookback is not recommended, but it is available for comparisons. It uses the adjacent lookback number and is likely to produce unreliable results outside a very specific context that is not suitable for most traders. Normalization is not a moving average. Unless you have a good reason to limit the sample size, do not use this option and instead use All Charted Bars .
Show Vol. name on plot
Overlays "VOLUME" or "VOLATILITY" on the plot (whichever you've selected).
Lin. Reg.
Polynomial regressions are great for capturing non-linear patterns in data. TradingView offers a "linear regression curve", which this script uses as a substitute. If you're unfamiliar with either term, think of this like a better moving average.
You're able to specify the color, length, and multiple (how much to amplify the value). The linear regression derives its value from the normalized values.
Norm. Val.
This is the color of the normalized value of the current bar (see DATA & MATH section). You're able to specify the default, within signal, and beyond signal colors. As well as the plot style.
Fade in colors between zero and the signal
Programmatically adjust the opacity of the primary plot color based on it's normalized value. When enabled, values equal to 0 will be fully transparent, become more opaque as they move away from 0, and be fully opaque at the signal. Adjusting opacity in this way helps make difference more obvious.
Plot relative to bar direction
If enabled, the normalized value will be multiplied by -1 when a bar's open is greater than the bar's close, mirroring price direction.
Technically volume and volatility are directionless. Meaning there's really no such thing as buy volume, sell volume, positive volatility, or negative volatility. There is just volume (1 buy = 1 sell = 1 volume) and volatility (high - low). Even so, visually reflecting the net effect of pricing pressure can still be useful. That's all this setting does.
Sig. Zone
Signal zones make identifying extremes easier. They do not signal if you should buy or sell, only that the current measurement is beyond what's normal. You are able to adjust the color and bounds of the zone.
Int. Levels
Interim levels can be useful when you want to visually bracket values into high / medium / low. These levels can have a value anywhere between 0 and 1. They will automatically be multiplied by 100 when the scale is set to Percent.
Zero Line
This setting allows you to specify the visibility of the zero line to best suit your trading style.
Volume & Volatility Stats
Displays a table of core values for both volume and volatility. Specifically the actual value, threshold (mean, median, or Q3), sigma (standard deviation), basis, normalized value, and linear regression.
Correlation Stats
Displays a table of correlation statistics for the current bar, as well as the data set average. Specifically the coefficient, R2, and P-Value.
Indices & Sample Size
Displays a table of mixed data. Specifically the current bar's index within the session, the current bar's index within the sample, and the sample size used to normalize the current bar's value.
BEST PRACTICES
NVOL can tell you what's normal for 9:30 AM. RVOL and ATR can only tell you if the current value is higher or lower than a moving average.
In a normal distribution (bell curve) 99.7% of data occurs within 3 standard deviations of the mean. This is why the default basis is set to "Mean, 3"; it includes the typical day-to-day fluctuations, better contextualizing what's actually normal, minimizing false positives.
This means a ratio value greater than 1 only occurs 0.3% of the time. A series of these values warrants your attention. Which is why the default signal zone is between 1 and 2. Ratios beyond 2 would be considered extreme with the default settings.
Inversely, ratio values less than 1 (the normal daily fluctuations) also tell a story. We should expect most values to occur around the middle 3rd, which is why interim levels default to 0.33 and 0.66, visually simplifying a given move's participation. These can be set to whatever you like and only serve as visual aids for your specific trading style.
It's worth noting that the linear regression oscillates when plotted directionally, which can help clarify short term move exhaustion and continuation. Akin to a relative strength index (RSI), it may be used to inform a trading decision, but it should not be the only factor.
MultiLayer Acceleration/Deceleration Strategy [Skyrexio]Overview
MultiLayer Acceleration/Deceleration Strategy leverages the combination of Acceleration/Deceleration Indicator(AC), Williams Alligator, Williams Fractals and Exponential Moving Average (EMA) to obtain the high probability long setups. Moreover, strategy uses multi trades system, adding funds to long position if it considered that current trend has likely became stronger. Acceleration/Deceleration Indicator is used for creating signals, while Alligator and Fractal are used in conjunction as an approximation of short-term trend to filter them. At the same time EMA (default EMA's period = 100) is used as high probability long-term trend filter to open long trades only if it considers current price action as an uptrend. More information in "Methodology" and "Justification of Methodology" paragraphs. The strategy opens only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Multilayer trades opening system: strategy uses only 10% of capital in every trade and open up to 5 trades at the same time if script consider current trend as strong one.
Short and long term trend trade filters: strategy uses EMA as high probability long-term trend filter and Alligator and Fractal combination as a short-term one.
Methodology
The strategy opens long trade when the following price met the conditions:
1. Price closed above EMA (by default, period = 100). Crossover is not obligatory.
2. Combination of Alligator and Williams Fractals shall consider current trend as an upward (all details in "Justification of Methodology" paragraph)
3. Acceleration/Deceleration shall create one of two types of long signals (all details in "Justification of Methodology" paragraph). Buy stop order is placed one tick above the candle's high of last created long signal.
4. If price reaches the order price, long position is opened with 10% of capital.
5. If currently we have opened position and price creates and hit the order price of another one long signal, another one long position will be added to the previous with another one 10% of capital. Strategy allows to open up to 5 long trades simultaneously.
6. If combination of Alligator and Williams Fractals shall consider current trend has been changed from up to downtrend, all long trades will be closed, no matter how many trades has been opened.
Script also has additional visuals. If second long trade has been opened simultaneously the Alligator's teeth line is plotted with the green color. Also for every trade in a row from 2 to 5 the label "Buy More" is also plotted just below the teeth line. With every next simultaneously opened trade the green color of the space between teeth and price became less transparent.
Strategy settings
In the inputs window user can setup strategy setting: EMA Length (by default = 100, period of EMA, used for long-term trend filtering EMA calculation). User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. We'll begin with the simplest: the EMA.
The Exponential Moving Average (EMA) is a type of moving average that assigns greater weight to recent price data, making it more responsive to current market changes compared to the Simple Moving Average (SMA). This tool is widely used in technical analysis to identify trends and generate buy or sell signals. The EMA is calculated as follows:
1.Calculate the Smoothing Multiplier:
Multiplier = 2 / (n + 1), Where n is the number of periods.
2. EMA Calculation
EMA = (Current Price) × Multiplier + (Previous EMA) × (1 − Multiplier)
In this strategy, the EMA acts as a long-term trend filter. For instance, long trades are considered only when the price closes above the EMA (default: 100-period). This increases the likelihood of entering trades aligned with the prevailing trend.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
In this strategy if the most recent up fractal breakout occurs above the Alligator's teeth and follows the last down fractal breakout below the teeth, the algorithm identifies an uptrend. Long trades can be opened during this phase if a signal aligns. If the price breaks a down fractal below the teeth line during an uptrend, the strategy assumes the uptrend has ended and closes all open long trades.
By combining the EMA as a long-term trend filter with the Alligator and fractals as short-term filters, this approach increases the likelihood of opening profitable trades while staying aligned with market dynamics.
Now let's talk about Acceleration/Deceleration signals. AC indicator is calculated using the Awesome Oscillator, so let's first of all briefly explain what is Awesome Oscillator and how it can be calculated. The Awesome Oscillator (AO), developed by Bill Williams, is a momentum indicator designed to measure market momentum by contrasting recent price movements with a longer-term historical perspective. It helps traders detect potential trend reversals and assess the strength of ongoing trends.
The formula for AO is as follows:
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
The Acceleration/Deceleration (AC) Indicator, introduced by Bill Williams, measures the rate of change in market momentum. It highlights shifts in the driving force of price movements and helps traders spot early signs of trend changes. The AC Indicator is particularly useful for identifying whether the current momentum is accelerating or decelerating, which can indicate potential reversals or continuations. For AC calculation we shall use the AO calculated above is the following formula:
AC = AO − SMA5(AO), where SMA5(AO)is the 5-period Simple Moving Average of the Awesome Oscillator
When the AC is above the zero line and rising, it suggests accelerating upward momentum.
When the AC is below the zero line and falling, it indicates accelerating downward momentum.
When the AC is below zero line and rising it suggests the decelerating the downtrend momentum. When AC is above the zero line and falling, it suggests the decelerating the uptrend momentum.
Now we can explain which AC signal types are used in this strategy. The first type of long signal is when AC value is below zero line. In this cases we need to see three rising bars on the histogram in a row after the falling one. The second type of signals occurs above the zero line. There we need only two rising AC bars in a row after the falling one to create the signal. The signal bar is the last green bar in this sequence. The strategy places the buy stop order one tick above the candle's high, which corresponds to the signal bar on AC indicator.
After that we can have the following scenarios:
Price hit the order on the next candle in this case strategy opened long with this price.
Price doesn't hit the order price, the next candle set lower high. If current AC bar is increasing buy stop order changes by the script to the high of this new bar plus one tick. This procedure repeats until price finally hit buy order or current AC bar become decreasing. In the second case buy order cancelled and strategy wait for the next AC signal.
If long trades are initiated, the strategy continues utilizing subsequent signals until the total number of trades reaches a maximum of 5. All open trades are closed when the trend shifts to a downtrend, as determined by the combination of the Alligator and Fractals described earlier.
Why we use AC signals? If currently strategy algorithm considers the high probability of the short-term uptrend with the Alligator and Fractals combination pointed out above and the long-term trend is also suggested by the EMA filter as bullish. Rising AC bars after period of falling AC bars indicates the high probability of local pull back end and there is a high chance to open long trade in the direction of the most likely main uptrend. The numbers of rising bars are different for the different AC values (below or above zero line). This is needed because if AC below zero line the local downtrend is likely to be stronger and needs more rising bars to confirm that it has been changed than if AC is above zero.
Why strategy use only 10% per signal? Sometimes we can see the false signals which appears on sideways. Not risking that much script use only 10% per signal. If the first long trade has been open and price continue going up and our trend approximation by Alligator and Fractals is uptrend, strategy add another one 10% of capital to every next AC signal while number of active trades no more than 5. This capital allocation allows to take part in long trades when current uptrend is likely to be strong and use only 10% of capital when there is a high probability of sideways.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.11.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 10%
Maximum Single Position Loss: -5.15%
Maximum Single Profit: +24.57%
Net Profit: +2108.85 USDT (+21.09%)
Total Trades: 111 (36.94% win rate)
Profit Factor: 2.391
Maximum Accumulated Loss: 367.61 USDT (-2.97%)
Average Profit per Trade: 19.00 USDT (+1.78%)
Average Trade Duration: 75 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 3h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Multi-Timeframe Stochastic Alert [tradeviZion]# Multi-Timeframe Stochastic Alert : Complete User Guide
## 1. Introduction
### What is the Multi-Timeframe Stochastic Alert?
The Multi-Timeframe Stochastic Alert is an advanced technical analysis tool that helps traders identify potential trading opportunities by analyzing momentum across multiple timeframes. It combines the power of the stochastic oscillator with multi-timeframe analysis to provide more reliable trading signals.
### Key Features and Benefits
- Simultaneous analysis of 6 different timeframes
- Advanced alert system with customizable conditions
- Real-time visual feedback with color-coded signals
- Comprehensive data table with instant market insights
- Motivational trading messages for psychological support
- Flexible theme support for comfortable viewing
### How it Can Help Your Trading
- Identify stronger trends by confirming momentum across multiple timeframes
- Reduce false signals through multi-timeframe confirmation
- Stay informed of market changes with customizable alerts
- Make more informed decisions with comprehensive market data
- Maintain trading discipline with clear visual signals
## 2. Understanding the Display
### The Stochastic Chart
The main chart displays three key components:
1. ** K-Line (Fast) **: The primary stochastic line (default color: green)
2. ** D-Line (Slow) **: The signal line (default color: red)
3. ** Reference Lines **:
- Overbought Level (80): Upper dashed line
- Middle Line (50): Center dashed line
- Oversold Level (20): Lower dashed line
### The Information Table
The table provides a comprehensive view of stochastic readings across all timeframes. Here's what each column means:
#### Column Explanations:
1. ** Timeframe **
- Shows the time period for each row
- Example: "5" = 5 minutes, "15" = 15 minutes, etc.
2. ** K Value **
- The fast stochastic line value (0-100)
- Higher values indicate stronger upward momentum
- Lower values indicate stronger downward momentum
3. ** D Value **
- The slow stochastic line value (0-100)
- Helps confirm momentum direction
- Crossovers with K-line can signal potential trades
4. ** Status **
- Shows current momentum with symbols:
- ▲ = Increasing (bullish)
- ▼ = Decreasing (bearish)
- Color matches the trend direction
5. ** Trend **
- Shows the current market condition:
- "Overbought" (above 80)
- "Bullish" (above 50)
- "Bearish" (below 50)
- "Oversold" (below 20)
#### Row Explanations:
1. ** Title Row **
- Shows "🎯 Multi-Timeframe Stochastic"
- Indicates the indicator is active
2. ** Header Row **
- Contains column titles
- Dark blue background for easy reading
3. ** Timeframe Rows **
- Six rows showing different timeframe analyses
- Each row updates independently
- Color-coded for easy trend identification
4. **Message Row**
- Shows rotating motivational messages
- Updates every 5 bars
- Helps maintain trading discipline
### Visual Indicators and Colors
- ** Green Background **: Indicates bullish conditions
- ** Red Background **: Indicates bearish conditions
- ** Color Intensity **: Shows strength of the signal
- ** Background Highlights **: Appear when alert conditions are met
## 3. Core Settings Groups
### Stochastic Settings
These settings control the core calculation of the stochastic oscillator.
1. ** Length (Default: 14) **
- What it does: Determines the lookback period for calculations
- Higher values (e.g., 21): More stable, fewer signals
- Lower values (e.g., 8): More sensitive, more signals
- Recommended:
* Day Trading: 8-14
* Swing Trading: 14-21
* Position Trading: 21-30
2. ** Smooth K (Default: 3) **
- What it does: Smooths the main stochastic line
- Higher values: Smoother line, fewer false signals
- Lower values: More responsive, but more noise
- Recommended:
* Day Trading: 2-3
* Swing Trading: 3-5
* Position Trading: 5-7
3. ** Smooth D (Default: 3) **
- What it does: Smooths the signal line
- Works in conjunction with Smooth K
- Usually kept equal to or slightly higher than Smooth K
- Recommended: Keep same as Smooth K for consistency
4. ** Source (Default: Close) **
- What it does: Determines price data for calculations
- Options: Close, Open, High, Low, HL2, HLC3, OHLC4
- Recommended: Stick with Close for most reliable signals
### Timeframe Settings
Controls the multiple timeframes analyzed by the indicator.
1. ** Main Timeframes (TF1-TF6) **
- TF1 (Default: 10): Shortest timeframe for quick signals
- TF2 (Default: 15): Short-term trend confirmation
- TF3 (Default: 30): Medium-term trend analysis
- TF4 (Default: 30): Additional medium-term confirmation
- TF5 (Default: 60): Longer-term trend analysis
- TF6 (Default: 240): Major trend confirmation
Recommended Combinations:
* Scalping: 1, 3, 5, 15, 30, 60
* Day Trading: 5, 15, 30, 60, 240, D
* Swing Trading: 15, 60, 240, D, W, M
2. ** Wait for Bar Close (Default: true) **
- What it does: Controls when calculations update
- True: More reliable but slightly delayed signals
- False: Faster signals but may change before bar closes
- Recommended: Keep True for more reliable signals
### Alert Settings
#### Main Alert Settings
1. ** Enable Alerts (Default: true) **
- Master switch for all alert notifications
- Toggle this off when you don't want any alerts
- Useful during testing or when you want to focus on visual signals only
2. ** Alert Condition (Options) **
- "Above Middle": Bullish momentum alerts only
- "Below Middle": Bearish momentum alerts only
- "Both": Alerts for both directions
- Recommended:
* Trending Markets: Choose direction matching the trend
* Ranging Markets: Use "Both" to catch reversals
* New Traders: Start with "Both" until you develop a specific strategy
3. ** Alert Frequency **
- "Once Per Bar": Immediate alerts during the bar
- "Once Per Bar Close": Alerts only after bar closes
- Recommended:
* Day Trading: "Once Per Bar" for quick reactions
* Swing Trading: "Once Per Bar Close" for confirmed signals
* Beginners: "Once Per Bar Close" to reduce false signals
#### Timeframe Check Settings
1. ** First Check (TF1) **
- Purpose: Confirms basic trend direction
- Alert Triggers When:
* For Bullish: Stochastic is above middle line (50)
* For Bearish: Stochastic is below middle line (50)
* For Both: Triggers in either direction based on position relative to middle line
- Settings:
* Enable/Disable: Turn first check on/off
* Timeframe: Default 5 minutes
- Best Used For:
* Quick trend confirmation
* Entry timing
* Scalping setups
2. ** Second Check (TF2) **
- Purpose: Confirms both position and momentum
- Alert Triggers When:
* For Bullish: Stochastic is above middle line AND both K&D lines are increasing
* For Bearish: Stochastic is below middle line AND both K&D lines are decreasing
* For Both: Triggers based on position and direction matching current condition
- Settings:
* Enable/Disable: Turn second check on/off
* Timeframe: Default 15 minutes
- Best Used For:
* Trend strength confirmation
* Avoiding false breakouts
* Day trading setups
3. ** Third Check (TF3) **
- Purpose: Confirms overall momentum direction
- Alert Triggers When:
* For Bullish: Both K&D lines are increasing (momentum confirmation)
* For Bearish: Both K&D lines are decreasing (momentum confirmation)
* For Both: Triggers based on matching momentum direction
- Settings:
* Enable/Disable: Turn third check on/off
* Timeframe: Default 30 minutes
- Best Used For:
* Major trend confirmation
* Swing trading setups
* Avoiding trades against the main trend
Note: All three conditions must be met simultaneously for the alert to trigger. This multi-timeframe confirmation helps reduce false signals and provides stronger trade setups.
#### Alert Combinations Examples
1. ** Conservative Setup **
- Enable all three checks
- Use "Once Per Bar Close"
- Timeframe Selection Example:
* First Check: 15 minutes
* Second Check: 1 hour (60 minutes)
* Third Check: 4 hours (240 minutes)
- Wider gaps between timeframes reduce noise and false signals
- Best for: Swing trading, beginners
2. ** Aggressive Setup **
- Enable first two checks only
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
- Closer timeframes for quicker signals
- Best for: Day trading, experienced traders
3. ** Balanced Setup **
- Enable all checks
- Use "Once Per Bar"
- Timeframe Selection Example:
* First Check: 5 minutes
* Second Check: 15 minutes
* Third Check: 1 hour (60 minutes)
- Balanced spacing between timeframes
- Best for: All-around trading
### Visual Settings
#### Alert Visual Settings
1. ** Show Background Color (Default: true) **
- What it does: Highlights chart background when alerts trigger
- Benefits:
* Makes signals more visible
* Helps spot opportunities quickly
* Provides visual confirmation of alerts
- When to disable:
* If using multiple indicators
* When preferring a cleaner chart
* During manual backtesting
2. ** Background Transparency (Default: 90) **
- Range: 0 (solid) to 100 (invisible)
- Recommended Settings:
* Clean Charts: 90-95
* Multiple Indicators: 85-90
* Single Indicator: 80-85
- Tip: Adjust based on your chart's overall visibility
3. ** Background Colors **
- Bullish Background:
* Default: Green
* Indicates upward momentum
* Customizable to match your theme
- Bearish Background:
* Default: Red
* Indicates downward momentum
* Customizable to match your theme
#### Level Settings
1. ** Oversold Level (Default: 20) **
- Traditional Setting: 20
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 10): More conservative
* Higher values (e.g., 30): More aggressive
- Trading Applications:
* Potential bullish reversal zone
* Support level in uptrends
* Entry point for long positions
2. ** Overbought Level (Default: 80) **
- Traditional Setting: 80
- Adjustable Range: 0-100
- Usage:
* Lower values (e.g., 70): More aggressive
* Higher values (e.g., 90): More conservative
- Trading Applications:
* Potential bearish reversal zone
* Resistance level in downtrends
* Exit point for long positions
3. ** Middle Line (Default: 50) **
- Purpose: Trend direction separator
- Applications:
* Above 50: Bullish territory
* Below 50: Bearish territory
* Crossing 50: Potential trend change
- Trading Uses:
* Trend confirmation
* Entry/exit trigger
* Risk management level
#### Color Settings
1. ** Bullish Color (Default: Green) **
- Used for:
* K-Line (Main stochastic line)
* Status symbols when trending up
* Trend labels for bullish conditions
- Customization:
* Choose colors that stand out
* Match your trading platform theme
* Consider color blindness accessibility
2. ** Bearish Color (Default: Red) **
- Used for:
* D-Line (Signal line)
* Status symbols when trending down
* Trend labels for bearish conditions
- Customization:
* Choose contrasting colors
* Ensure visibility on your chart
* Consider monitor settings
3. ** Neutral Color (Default: Gray) **
- Used for:
* Middle line (50 level)
- Customization:
* Should be less prominent
* Easy on the eyes
* Good background contrast
### Theme Settings
1. **Color Theme Options**
- Dark Theme (Default):
* Dark background with white text
* Optimized for dark chart backgrounds
* Reduces eye strain in low light
- Light Theme:
* Light background with black text
* Better visibility in bright conditions
- Custom Theme:
* Use your own color preferences
2. ** Available Theme Colors **
- Table Background
- Table Text
- Table Headers
Note: The theme affects only the table display colors. The stochastic lines and alert backgrounds use their own color settings.
### Table Settings
#### Position and Size
1. ** Table Position **
- Options:
* Top Right (Default)
* Middle Right
* Bottom Right
* Top Left
* Middle Left
* Bottom Left
- Considerations:
* Chart space utilization
* Personal preference
* Multiple monitor setups
2. ** Text Sizes **
- Title Size Options:
* Tiny: Minimal space usage
* Small: Compact but readable
* Normal (Default): Standard visibility
* Large: Enhanced readability
* Huge: Maximum visibility
- Data Size Options:
* Recommended: One size smaller than title
* Adjust based on screen resolution
* Consider viewing distance
3. ** Empowering Messages **
- Purpose:
* Maintain trading discipline
* Provide psychological support
* Remind of best practices
- Rotation:
* Changes every 5 bars
* Categories include:
- Market Wisdom
- Strategy & Discipline
- Mindset & Growth
- Technical Mastery
- Market Philosophy
## 4. Setting Up for Different Trading Styles
### Day Trading Setup
1. **Timeframes**
- Primary: 5, 15, 30 minutes
- Secondary: 1H, 4H
- Alert Settings: "Once Per Bar"
2. ** Stochastic Settings **
- Length: 8-14
- Smooth K/D: 2-3
- Alert Condition: Match market trend
3. ** Visual Settings **
- Background: Enabled
- Transparency: 85-90
- Theme: Based on trading hours
### Swing Trading Setup
1. ** Timeframes **
- Primary: 1H, 4H, Daily
- Secondary: Weekly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 14-21
- Smooth K/D: 3-5
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Optional
- Transparency: 90-95
- Theme: Personal preference
### Position Trading Setup
1. ** Timeframes **
- Primary: Daily, Weekly
- Secondary: Monthly
- Alert Settings: "Once Per Bar Close"
2. ** Stochastic Settings **
- Length: 21-30
- Smooth K/D: 5-7
- Alert Condition: "Both"
3. ** Visual Settings **
- Background: Disabled
- Focus on table data
- Theme: High contrast
## 5. Troubleshooting Guide
### Common Issues and Solutions
1. ** Too Many Alerts **
- Cause: Settings too sensitive
- Solutions:
* Increase timeframe intervals
* Use "Once Per Bar Close"
* Enable fewer timeframe checks
* Adjust stochastic length higher
2. ** Missed Signals **
- Cause: Settings too conservative
- Solutions:
* Decrease timeframe intervals
* Use "Once Per Bar"
* Enable more timeframe checks
* Adjust stochastic length lower
3. ** False Signals **
- Cause: Insufficient confirmation
- Solutions:
* Enable all three timeframe checks
* Use larger timeframe gaps
* Wait for bar close
* Confirm with price action
4. ** Visual Clarity Issues **
- Cause: Poor contrast or overlap
- Solutions:
* Adjust transparency
* Change theme settings
* Reposition table
* Modify color scheme
### Best Practices
1. ** Getting Started **
- Start with default settings
- Use "Both" alert condition
- Enable all timeframe checks
- Wait for bar close
- Monitor for a few days
2. ** Fine-Tuning **
- Adjust one setting at a time
- Document changes and results
- Test in different market conditions
- Find your optimal timeframe combination
- Balance sensitivity with reliability
3. ** Risk Management **
- Don't trade against major trends
- Confirm signals with price action
- Use appropriate position sizing
- Set clear stop losses
- Follow your trading plan
4. ** Regular Maintenance **
- Review settings weekly
- Adjust for market conditions
- Update color scheme for visibility
- Clean up chart regularly
- Maintain trading journal
## 6. Tips for Success
1. ** Entry Strategies **
- Wait for all timeframes to align
- Confirm with price action
- Use proper position sizing
- Consider market conditions
2. ** Exit Strategies **
- Trail stops using indicator levels
- Take partial profits at targets
- Honor your stop losses
- Don't fight the trend
3. ** Psychology **
- Stay disciplined with settings
- Don't override system signals
- Keep emotions in check
- Learn from each trade
4. ** Continuous Improvement **
- Record your trades
- Review performance regularly
- Adjust settings gradually
- Stay educated on markets
WaveTrend With Divs & RSI(STOCH) Divs by WeloTradesWaveTrend with Divergences & RSI(STOCH) Divergences by WeloTrades
Overview
The "WaveTrend With Divergences & RSI(STOCH) Divergences" is an advanced Pine Script™ indicator designed for TradingView, offering a multi-dimensional analysis of market conditions. This script integrates several technical indicators—WaveTrend, Money Flow Index (MFI), RSI, and Stochastic RSI—into a cohesive tool that identifies both regular and hidden divergences across these indicators. These divergences can indicate potential market reversals and provide critical trading opportunities.
This indicator is not just a simple combination of popular tools; it offers extensive customization options, organized data presentation, and valuable trading signals that are easy to interpret. Whether you're a day trader or a long-term investor, this script enhances your ability to make informed decisions.
Originality and Usefulness
The originality of this script lies in its integration and the synergy it creates among the indicators used. Rather than merely combining multiple indicators, this script allows them to work together, enhancing each other's strengths. For example, by identifying divergences across WaveTrend, RSI, and Stochastic RSI simultaneously, the script provides multiple layers of confirmation, which reduces the likelihood of false signals and increases the reliability of trading signals.
The usefulness of this script is apparent in its ability to offer a consolidated view of market dynamics. It not only simplifies the analytical process by combining different indicators but also provides deeper insights through its divergence detection features. This comprehensive approach is designed to help traders identify potential market reversals, confirm trends, and ultimately make more informed trading decisions.
How the Components Work Together
1. Cross-Validation of Signals
WaveTrend: This indicator is primarily used to identify overbought and oversold conditions, as well as potential buy and sell signals. WaveTrend's ability to smooth price data and reduce noise makes it a reliable tool for identifying trend reversals.
RSI & Stochastic RSI: These momentum oscillators are used to measure the speed and change of price movements. While RSI identifies general overbought and oversold conditions, Stochastic RSI offers a more granular view by tracking the RSI’s level relative to its high-low range over a period of time. When these indicators align with WaveTrend signals, it adds a layer of confirmation that enhances the reliability of the signals.
Money Flow Index (MFI): This volume-weighted indicator assesses the inflow and outflow of money in an asset, giving insights into buying and selling pressure. By analyzing the MFI alongside WaveTrend and RSI indicators, the script can cross-validate signals, ensuring that buy or sell signals are supported by actual market volume.
Example Bullish scenario:
When a bullish divergence is detected on the RSI and confirmed by a corresponding bullish signal on the WaveTrend, along with an increasing Money Flow Index, the probability of a successful trade setup increases. This cross-validation minimizes the risk of acting on false signals, which might occur when relying on a single indicator.
Example Bearish scenario:
When a bearish divergence is detected on the RSI and confirmed by a corresponding bearish signal on the WaveTrend, along with an decreasing Money Flow Index, the probability of a successful trade setup increases. This cross-validation minimizes the risk of acting on false signals, which might occur when relying on a single indicator.
2. Divergence Detection and Market Reversals
Regular Divergences: Occur when the price action and an indicator (like RSI or WaveTrend) move in opposite directions. Regular bullish divergence signals a potential upward reversal when the price makes a lower low while the indicator makes a higher low. Conversely, regular bearish divergence suggests a downward reversal when the price makes a higher high, but the indicator makes a lower high.
Hidden Divergences: These occur when the price action and indicator move in the same direction, but with different momentum. Hidden bullish divergence suggests the continuation of an uptrend, while hidden bearish divergence suggests the continuation of a downtrend. By detecting these divergences across multiple indicators, the script identifies potential trend reversals or continuations with greater accuracy.
Example: The script might detect a regular bullish divergence on the WaveTrend while simultaneously identifying a hidden bullish divergence on the RSI. This combination suggests that while a trend reversal is possible, the overall market sentiment remains bullish, providing a nuanced view of the market.
A Regular Bullish Divergence Example:
A Hidden Bullish Divergence Example:
A Regular Bearish Divergence Example:
A Hidden Bearish Divergence Example:
3. Trend Strength and Sentiment Analysis
WaveTrend: Measures the strength and direction of the trend. By identifying the extremes of market sentiment (overbought and oversold levels), WaveTrend provides early signals for potential reversals.
Money Flow Index (MFI): Assesses the underlying sentiment by analyzing the flow of money. A rising MFI during an uptrend confirms strong buying pressure, while a falling MFI during a downtrend confirms selling pressure. This helps traders assess whether a trend is likely to continue or reverse.
RSI & Stochastic RSI: Offer a momentum-based perspective on the trend’s strength. High RSI or Stochastic RSI values indicate that the asset may be overbought, suggesting a potential reversal. Conversely, low values indicate oversold conditions, signaling a possible upward reversal.
Example:
During a strong uptrend, the WaveTrend & RSI's might signal overbought conditions, suggesting caution. If the MFI also shows decreasing buying pressure and the RSI reaches extreme levels, these indicators together suggest that the trend might be weakening, and a reversal could be imminent.
Example:
During a strong downtrend, the WaveTrend & RSI's might signal oversold conditions, suggesting caution. If the MFI also shows increasing buying pressure and the RSI reaches extreme levels, these indicators together suggest that the trend might be weakening, and a reversal could be imminent.
Conclusion
The "WaveTrend With Divergences & RSI(STOCH) Divergences" script offers a powerful, integrated approach to technical analysis by combining trend, momentum, and sentiment indicators into a single tool. Its unique value lies in the cross-validation of signals, the ability to detect divergences, and the comprehensive view it provides of market conditions. By offering traders multiple layers of analysis and customization options, this script is designed to enhance trading decisions, reduce false signals, and provide clearer insights into market dynamics.
WAVETREND
Display of WaveTrend:
Display of WaveTrend Setting:
WaveTrend Indicator Explanation
The WaveTrend indicator helps identify overbought and oversold conditions, as well as potential buy and sell signals. Its flexibility allows traders to adapt it to various strategies, making it a versatile tool in technical analysis.
WaveTrend Input Settings:
WT MA Source: Default: HLC3
What it is: The data source used for calculating the WaveTrend Moving Average.
What it does: Determines the input data to smooth price action and filter noise.
Example: Using HLC3 (average of High, Low, Close) provides a smoother data representation compared to using just the closing price.
Length (WT MA Length): Default: 3
What it is: The period used to calculate the Moving Average.
What it does: Adjusts the sensitivity of the WaveTrend indicator, where shorter lengths respond more quickly to price changes.
Example: A length of 3 is ideal for short-term analysis, providing quick reactions to price movements.
WT Channel Length & Average: Default: WT Channel Length = 9, Average = 12
What it is: Lengths used to calculate the WaveTrend channel and its average.
What it does: Smooths out the WaveTrend further, reducing false signals by averaging over a set period.
Example: Higher values reduce noise and help in identifying more reliable trends.
Channel: Style, Width, and Color:
What it is: Customization options for the WaveTrend channel's appearance.
What it does: Adjusts how the channel is displayed, including line style, width, and color.
Example: Choosing an area style with a distinct color can make the WaveTrend indicator clearly visible on the chart.
WT Buy & Sell Signals:
What it is: Settings to enable and customize buy and sell signals based on WaveTrend.
What it does: Allows for the display of buy/sell signals and customization of their shapes and colors.
When it gives a Buy Signal: Generated when the WaveTrend line crosses below an oversold level and then rises back, indicating a potential upward price movement.
When it gives a Sell Signal: Triggered when the WaveTrend line crosses above an overbought level and then declines, suggesting a possible downward trend.
Example: The script identifies these signals based on mean reversion principles, where prices tend to revert to the mean after reaching extremes. Traders can use these signals to time their entries and exits effectively.
WAVETREND OVERBOUGTH AND OVERSOLD LEVELS
Display of WaveTrend with Overbought & Oversold Levels:
Display of WaveTrend Overbought & Oversold Levels Settings:
WaveTrend Overbought & Oversold Levels Explanation
WT OB & OS Levels: Default: OB Level 1 = 53, OB Level 2 = 60, OS Level 1 = -53, OS Level 2 = -60
What it is: The default overbought and oversold levels used by the WaveTrend indicator to signal potential market reversals.
What it does: When the WaveTrend crosses above the OB levels, it indicates an overbought condition, potentially signaling a reversal or selling opportunity. Conversely, when it crosses below the OS levels, it indicates an oversold condition, potentially signaling a reversal or buying opportunity.
Example: A trader might use these levels to time entry or exit points, such as selling when the WaveTrend crosses into the overbought zone or buying when it crosses into the oversold zone.
Show OB/OS Levels: Default: True
What it is: Toggle options to show or hide the overbought and oversold levels on your chart.
What it does: When enabled, these levels will be visually represented on your chart, helping you to easily identify when the market reaches these critical thresholds.
Example: Displaying these levels can help you quickly see when the WaveTrend is approaching or has crossed into overbought or oversold territory, allowing for more informed trading decisions.
Line Style, Width, and Color for OB/OS Levels:
What it is: Options to customize the appearance of the OB and OS levels on your chart, including line style (solid, dotted, dashed), line width, and color.
What it does: These settings allow you to adjust how prominently these levels are displayed on your chart, which can help you better visualize and respond to overbought or oversold conditions.
Example: Setting a thicker, dashed line in a contrasting color can make these levels stand out more clearly, aiding in quick visual identification.
Example of Use:
Scenario: A trader wants to identify potential selling points when the market is overbought. They set the OB levels at 53 and 60, choosing a solid, red line style to make these levels clear on their chart. As the WaveTrend crosses above 53, they monitor for further price action, and upon crossing 60, they consider initiating a sell order.
WAVETREND DIVERGENCES
Display of WaveTrend Divergence:
Display of WaveTrend Divergence Setting:
WaveTrend Divergence Indicator Explanation
The WaveTrend Divergence feature helps identify potential reversal points in the market by highlighting divergences between the price and the WaveTrend indicator. Divergences can signal a shift in market momentum, indicating a possible trend reversal. This component allows traders to visualize and customize divergence detection on their charts.
WaveTrend Divergence Input Settings:
Potential Reversal Range: Default: 28
What it is: The number of bars to look back when detecting potential tops and bottoms.
What it does: Sets the range for identifying possible reversal points based on historical data.
Example: A setting of 28 looks back across the last 28 bars to find reversal points, offering a balance between responsiveness and reliability.
Reversal Minimum LVL OB & OS: Default: OB = 35, OS = -35
What it is: The minimum overbought and oversold levels required for detecting potential reversals.
What it does: Adjusts the thresholds that trigger a reversal signal based on the WaveTrend indicator.
Example: A higher OB level reduces the sensitivity to overbought conditions, potentially filtering out false reversal signals.
Lookback Bar Left & Right: Default: Left = 10, Right = 1
What it is: The number of bars to the left and right used to confirm a top or bottom.
What it does: Helps determine the position of peaks and troughs in the price action.
Example: A larger left lookback captures more extended price action before the peak, while a smaller right lookback focuses on the immediate past.
Lookback Range Min & Max: Default: Min = 5, Max = 60
What it is: The minimum and maximum range for the lookback period when identifying divergences.
What it does: Fine-tunes the detection of divergences by controlling the range over which the indicator looks back.
Example: A wider range increases the chances of detecting divergences across different market conditions.
R.Div Minimum LVL OB & OS: Default: OB = 53, OS = -53
What it is: The threshold levels for detecting regular divergences.
What it does: Adjusts the sensitivity of the regular divergence detection.
Example: Higher thresholds make the detection more conservative, identifying only stronger divergence signals.
H.Div Minimum LVL OB & OS: Default: OB = 20, OS = -20
What it is: The threshold levels for detecting hidden divergences.
What it does: Similar to regular divergence settings but for hidden divergences, which can indicate potential reversals that are less obvious.
Example: Lower thresholds make the hidden divergence detection more sensitive, capturing subtler market shifts.
Divergence Label Options:
What it is: Options to display and customize labels for regular and hidden divergences.
What it does: Allows users to visually differentiate between regular and hidden divergences using customizable labels and colors.
Example: Using different colors and symbols for regular (R) and hidden (H) divergences makes it easier to interpret signals on the chart.
Text Size and Color:
What it is: Customization options for the size and color of divergence labels.
What it does: Adjusts the readability and visibility of divergence labels on the chart.
Example: Larger text size may be preferred for charts with a lot of data, ensuring divergence labels stand out clearly.
FAST & SLOW MONEY FLOW INDEX
Display of Fast & Slow Money Flow:
Display of Fast & Slow Money Flow Setting:
Fast Money Flow Indicator Explanation
The Fast Money Flow indicator helps traders identify the flow of money into and out of an asset over a shorter time frame. By tracking the volume-weighted average of price movements, it provides insights into buying and selling pressure in the market, which can be crucial for making timely trading decisions.
Fast Money Flow Input Settings:
Fast Money Flow: Length: Default: 9
What it is: The period used for calculating the Fast Money Flow.
What it does: Determines the sensitivity of the Money Flow calculation. A shorter length makes the indicator more responsive to recent price changes, while a longer length provides a smoother signal.
Example: A length of 9 is suitable for traders looking to capture quick shifts in market sentiment over a short period.
Fast MFI Area Multiplier: Default: 5
What it is: A multiplier applied to the Money Flow area calculation.
What it does: Adjusts the size of the Money Flow area on the chart, effectively amplifying or reducing the visual impact of the indicator.
Example: A higher multiplier can make the Money Flow more prominent on the chart, aiding in the quick identification of significant money flow changes.
Y Position (Y Pos): Default: 0
What it is: The vertical position adjustment for the Fast Money Flow plot on the chart.
What it does: Allows you to move the Money Flow plot up or down on the chart to avoid overlap with other indicators.
Example: Adjusting the Y Position can be useful if you have multiple indicators on the chart and need to maintain clarity.
Fast MFI Style, Width, and Color:
What it is: Customization options for how the Fast Money Flow is displayed on the chart.
What it does: Enables you to choose between different plot styles (line or area), set the line width, and select colors for positive and negative money flow.
Example: Using different colors for positive (green) and negative (red) money flow helps to visually distinguish between periods of buying and selling pressure.
Slow Money Flow Indicator Explanation
The Slow Money Flow indicator tracks the flow of money into and out of an asset over a longer time frame. It provides a broader perspective on market sentiment, smoothing out short-term fluctuations and highlighting longer-term trends.
Slow Money Flow Input Settings:
Slow Money Flow: Length: Default: 12
What it is: The period used for calculating the Slow Money Flow.
What it does: A longer period smooths out short-term fluctuations, providing a clearer view of the overall money flow trend.
Example: A length of 12 is often used by traders looking to identify sustained trends rather than short-term volatility.
Slow MFI Area Multiplier: Default: 5
What it is: A multiplier applied to the Slow Money Flow area calculation.
What it does: Adjusts the size of the Money Flow area on the chart, helping to emphasize the indicator’s significance.
Example: Increasing the multiplier can help highlight the Money Flow in markets with less volatile price action.
Y Position (Y Pos): Default: 0
What it is: The vertical position adjustment for the Slow Money Flow plot on the chart.
What it does: Allows for vertical repositioning of the Money Flow plot to maintain chart clarity when used with other indicators.
Example: Adjusting the Y Position ensures that the Slow Money Flow indicator does not overlap with other key indicators on the chart.
Slow MFI Style, Width, and Color:
What it is: Customization options for the visual display of the Slow Money Flow on the chart.
What it does: Allows you to choose the plot style (line or area), set the line width, and select colors to differentiate positive and negative money flow.
Example: Customizing the colors for the Slow Money Flow allows traders to quickly distinguish between buying and selling trends in the market.
RSI
Display of RSI:
Display of RSI Setting:
RSI Indicator Explanation
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It is typically used to identify overbought or oversold conditions in the market, providing traders with potential signals for buying or selling.
RSI Input Settings:
RSI Source: Default: Close
What it is: The data source used for calculating the RSI.
What it does: Determines which price data (e.g., close, open) is used in the RSI calculation, affecting how the indicator reflects market conditions.
Example: Using the closing price is standard practice, as it reflects the final agreed-upon price for a given time period.
MA Type (Moving Average Type): Default: SMA
What it is: The type of moving average applied to the RSI for smoothing purposes.
What it does: Changes the smoothing technique of the RSI, impacting how quickly the indicator responds to price movements.
Example: Using an Exponential Moving Average (EMA) will make the RSI more sensitive to recent price changes compared to a Simple Moving Average (SMA).
RSI Length: Default: 14
What it is: The period over which the RSI is calculated.
What it does: Adjusts the sensitivity of the RSI. A shorter length (e.g., 7) makes the RSI more responsive to recent price changes, while a longer length (e.g., 21) smooths out the indicator, reducing the number of signals.
Example: A 14-period RSI is commonly used for identifying overbought and oversold conditions, providing a balance between sensitivity and reliability.
RSI Plot Style, Width, and Color:
What it is: Options to customize the appearance of the RSI line on the chart.
What it does: Allows you to adjust the visual representation of the RSI, including the line width and color.
Example: Setting a thicker line width and a bright color like yellow can make the RSI more visible on the chart, aiding in quick analysis.
Display of RSI with RSI Moving Average:
RSI Moving Average Explanation
The RSI Moving Average adds a smoothing layer to the RSI, helping to filter out noise and provide clearer signals. It is particularly useful for confirming trend strength and identifying potential reversals.
RSI Moving Average Input Settings:
MA Length: Default: 14
What it is: The period over which the Moving Average is calculated on the RSI.
What it does: Adjusts the smoothing of the RSI, helping to reduce false signals and provide a clearer trend indication.
Example: A 14-period moving average on the RSI can smooth out short-term fluctuations, making it easier to spot genuine overbought or oversold conditions.
MA Plot Style, Width, and Color:
What it is: Customization options for how the RSI Moving Average is displayed on the chart.
What it does: Allows you to adjust the line width and color, helping to differentiate the Moving Average from the main RSI line.
Example: Using a contrasting color for the RSI Moving Average (e.g., magenta) can help it stand out against the main RSI line, making it easier to interpret the indicator.
STOCHASTIC RSI
Display of Stochastic RSI:
Display of Stochastic RSI Setting:
Stochastic RSI Indicator Explanation
The Stochastic RSI (Stoch RSI) is a momentum oscillator that measures the level of the RSI relative to its high-low range over a set period of time. It is used to identify overbought and oversold conditions, providing potential buy and sell signals based on momentum shifts.
Stochastic RSI Input Settings:
Stochastic RSI Length: Default: 14
What it is: The period over which the Stochastic RSI is calculated.
What it does: Adjusts the sensitivity of the Stochastic RSI. A shorter length makes the indicator more responsive to recent price changes, while a longer length smooths out the fluctuations, reducing noise.
Example: A length of 14 is commonly used to identify momentum shifts over a medium-term period, providing a balanced view of potential overbought or oversold conditions.
Display of Stochastic RSI %K Line:
Stochastic RSI %K Line Explanation
The %K line in the Stochastic RSI is the main line that tracks the momentum of the RSI over the chosen period. It is the faster-moving component of the Stochastic RSI, often used to identify entry and exit points.
Stochastic RSI %K Input Settings:
%K Length: Default: 3
What it is: The period used for smoothing the %K line of the Stochastic RSI.
What it does: Smoothing the %K line helps reduce noise and provides a clearer signal for potential market reversals.
Example: A smoothing length of 3 is common, offering a balance between responsiveness and noise reduction, making it easier to spot significant momentum shifts.
%K Plot Style, Width, and Color:
What it is: Customization options for the visual representation of the %K line.
What it does: Allows you to adjust the appearance of the %K line on the chart, including line width and color, to fit your visual preferences.
Example: Setting a blue color and a medium width for the %K line makes it stand out clearly on the chart, helping to identify key points of momentum change.
%K Fill Color (Above):
What it is: The fill color that appears above the %K line on the chart.
What it does: Adds visual clarity by shading the area above the %K line, making it easier to interpret the direction and strength of momentum.
Example: Using a light blue fill color above the %K line can help emphasize bullish momentum, making it visually prominent.
Display of Stochastic RSI %D Line:
Stochastic RSI %D Line Explanation
The %D line in the Stochastic RSI is a moving average of the %K line and acts as a signal line. It is slower-moving compared to the %K line and is often used to confirm signals or identify potential reversals when it crosses the %K line.
Stochastic RSI %D Input Settings:
%D Length: Default: 3
What it is: The period used for smoothing the %D line of the Stochastic RSI.
What it does: Smooths out the %D line, making it less sensitive to short-term fluctuations and more reliable for identifying significant market signals.
Example: A length of 3 is often used to provide a smoothed signal line that can help confirm trends or reversals indicated by the %K line.
%D Plot Style, Width, and Color:
What it is: Customization options for the visual representation of the %D line.
What it does: Allows you to adjust the appearance of the %D line on the chart, including line width and color, to match your preferences.
Example: Setting an orange color and a thicker line width for the %D line can help differentiate it from the %K line, making crossover points easier to spot.
%D Fill Color (Below):
What it is: The fill color that appears below the %D line on the chart.
What it does: Adds visual clarity by shading the area below the %D line, making it easier to interpret bearish momentum.
Example: Using a light orange fill color below the %D line can highlight bearish conditions, making it visually easier to identify.
RSI & STOCHASTIC RSI OVERBOUGHT AND OVERSOLD LEVELS
Display of RSI & Stochastic with Overbought & Oversold Levels:
Display of RSI & Stochastic Overbought & Oversold Settings:
RSI & Stochastic Overbought & Oversold Levels Explanation
The Overbought (OB) and Oversold (OS) levels for RSI and Stochastic RSI indicators are key thresholds that help traders identify potential reversal points in the market. These levels are used to determine when an asset is likely overbought or oversold, which can signal a potential trend reversal.
RSI & Stochastic Overbought & Oversold Input Settings:
RSI & Stochastic Level 1 Overbought (OB) & Oversold (OS): Default: OB Level = 170, OS Level = 130
What it is: The first set of thresholds for determining overbought and oversold conditions for both RSI and Stochastic RSI indicators.
What it does: When the RSI or Stochastic RSI crosses above the overbought level, it suggests that the asset might be overbought, potentially signaling a sell opportunity. Conversely, when these indicators drop below the oversold level, it suggests the asset might be oversold, potentially signaling a buy opportunity.
Example: If the RSI crosses above 170, traders might look for signs of a potential trend reversal to the downside, while a cross below 130 might indicate a reversal to the upside.
RSI & Stochastic Level 2 Overbought (OB) & Oversold (OS): Default: OB Level = 180, OS Level = 120
What it is: The second set of thresholds for determining overbought and oversold conditions for both RSI and Stochastic RSI indicators.
What it does: These levels provide an additional set of reference points, allowing traders to differentiate between varying degrees of overbought and oversold conditions, potentially leading to more refined trading decisions.
Example: When the RSI crosses above 180, it might indicate an extreme overbought condition, which could be a stronger signal for a sell, while a cross below 120 might indicate an extreme oversold condition, which could be a stronger signal for a buy.
RSI & Stochastic Overbought (OB) Band Customization:
OB Level 1: Width, Style, and Color:
What it is: Customization options for the visual appearance of the first overbought band on the chart.
What it does: Allows you to set the line width, style (solid, dotted, dashed), and color for the first overbought band, enhancing its visibility on the chart.
Example: A dashed red line with medium width can clearly indicate the first overbought level, helping traders quickly identify when this threshold is crossed.
OB Level 2: Width, Style, and Color:
What it is: Customization options for the visual appearance of the second overbought band on the chart.
What it does: Allows you to set the line width, style, and color for the second overbought band, providing a clear distinction from the first band.
Example: A dashed red line with a slightly thicker width can represent a more significant overbought level, making it easier to differentiate from the first level.
RSI & Stochastic Oversold (OS) Band Customization:
OS Level 1: Width, Style, and Color:
What it is: Customization options for the visual appearance of the first oversold band on the chart.
What it does: Allows you to set the line width, style (solid, dotted, dashed), and color for the first oversold band, making it visually prominent.
Example: A dashed green line with medium width can highlight the first oversold level, helping traders identify potential buying opportunities.
OS Level 2: Width, Style, and Color:
What it is: Customization options for the visual appearance of the second oversold band on the chart.
What it does: Allows you to set the line width, style, and color for the second oversold band, providing an additional visual cue for extreme oversold conditions.
Example: A dashed green line with a thicker width can represent a more significant oversold level, offering a stronger visual cue for potential buying opportunities.
RSI DIVERGENCES
Display of RSI Divergence Labels:
Display of RSI Divergence Settings:
RSI Divergence Lookback Explanation
The RSI Divergence settings allow traders to customize the parameters for detecting divergences between the RSI (Relative Strength Index) and price action. Divergences occur when the price moves in the opposite direction to the RSI, potentially signaling a trend reversal. These settings help refine the accuracy of divergence detection by adjusting the lookback period and range. ( NOTE: This setting only imply to the RSI. This doesn't effect the STOCHASTIC RSI. )
RSI Divergence Lookback Input Settings:
Lookback Left: Default: 10
What it is: The number of bars to look back from the current bar to detect a potential divergence.
What it does: Defines the left-side lookback period for identifying pivot points in the RSI, which are used to spot divergences. A longer lookback period may capture more significant trends but could also miss shorter-term divergences.
Example: A setting of 10 bars means the script will consider pivot points up to 10 bars before the current bar to check for divergence patterns.
Lookback Right: Default: 1
What it is: The number of bars to look forward from the current bar to complete the divergence pattern.
What it does: Defines the right-side lookback period for confirming a potential divergence. This setting helps ensure that the identified divergence is valid by allowing the script to check subsequent bars for confirmation.
Example: A setting of 1 bar means the script will look at the next bar to confirm the divergence pattern, ensuring that the signal is reliable.
Lookback Range Min: Default: 5
What it is: The minimum range of bars required to detect a valid divergence.
What it does: Sets a lower bound on the range of bars considered for divergence detection. A lower minimum range might capture more frequent but possibly less significant divergences.
Example: Setting the minimum range to 5 ensures that only divergences spanning at least 5 bars are considered, filtering out very short-term patterns.
Lookback Range Max: Default: 60
What it is: The maximum range of bars within which a divergence can be detected.
What it does: Sets an upper bound on the range of bars considered for divergence detection. A larger maximum range might capture more significant divergences but could also include less relevant long-term patterns.
Example: Setting the maximum range to 60 bars allows the script to detect divergences over a longer timeframe, capturing more extended divergence patterns that could indicate major trend reversals.
RSI Divergence Explanation
RSI divergences occur when the RSI indicator and price action move in opposite directions, signaling potential trend reversals. This section of the settings allows traders to customize the appearance and detection of both regular and hidden bullish and bearish divergences.
RSI Divergence Input Settings:
R. Bullish Div Label: Default: True
What it is: An option to display labels for regular bullish divergences.
What it does: Enables or disables the visibility of labels that mark regular bullish divergences, where the price makes a lower low while the RSI makes a higher low, indicating a potential upward reversal.
Example: A trader might use this to spot buying opportunities in a downtrend when a bullish divergence suggests the trend may be reversing.
Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bullish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Selecting a green label color and a distinct line width makes bullish divergences easily recognizable on your chart.
R. Bearish Div Label: Default: True
What it is: An option to display labels for regular bearish divergences.
What it does: Enables or disables the visibility of labels that mark regular bearish divergences, where the price makes a higher high while the RSI makes a lower high, indicating a potential downward reversal.
Example: A trader might use this to spot selling opportunities in an uptrend when a bearish divergence suggests the trend may be reversing.
Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bearish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Choosing a red label color and a specific line width makes bearish divergences clearly stand out on your chart.
H. Bullish Div Label: Default: False
What it is: An option to display labels for hidden bullish divergences.
What it does: Enables or disables the visibility of labels that mark hidden bullish divergences, where the price makes a higher low while the RSI makes a lower low, indicating potential continuation of an uptrend.
Example: A trader might use this to confirm an existing uptrend when a hidden bullish divergence signals continued buying strength.
Hidden Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bullish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A softer green color with a thinner line width might be chosen to subtly indicate hidden bullish divergences, keeping the chart clean while providing useful information.
H. Bearish Div Label: Default: False
What it is: An option to display labels for hidden bearish divergences.
What it does: Enables or disables the visibility of labels that mark hidden bearish divergences, where the price makes a lower high while the RSI makes a higher high, indicating potential continuation of a downtrend.
Example: A trader might use this to confirm an existing downtrend when a hidden bearish divergence signals continued selling pressure.
Hidden Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bearish divergence labels.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A muted red color with a thinner line width might be selected to indicate hidden bearish divergences without overwhelming the chart.
Divergence Text Size and Color: Default: S (Small)
What it is: Settings to adjust the size and color of text labels for RSI divergences.
What it does: Allows you to customize the size and color of text labels that display the divergence information on the chart.
Example: Choosing a small text size with a bright white color can make divergence labels easily readable without taking up too much space on the chart.
STOCHASTIC DIVERGENCES
Display of Stochastic RSI Divergence Labels:
Display of Stochastic RSI Divergence Settings:
Stochastic RSI Divergence Explanation
Stochastic RSI divergences occur when the Stochastic RSI indicator and price action move in opposite directions, signaling potential trend reversals. These settings allow traders to customize the detection and visual representation of both regular and hidden bullish and bearish divergences in the Stochastic RSI.
Stochastic RSI Divergence Input Settings:
R. Bullish Div Label: Default: True
What it is: An option to display labels for regular bullish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark regular bullish divergences, where the price makes a lower low while the Stochastic RSI makes a higher low, indicating a potential upward reversal.
Example: A trader might use this to spot buying opportunities in a downtrend when a bullish divergence in the Stochastic RSI suggests the trend may be reversing.
Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bullish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Selecting a blue label color and a distinct line width makes bullish divergences in the Stochastic RSI easily recognizable on your chart.
R. Bearish Div Label: Default: True
What it is: An option to display labels for regular bearish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark regular bearish divergences, where the price makes a higher high while the Stochastic RSI makes a lower high, indicating a potential downward reversal.
Example: A trader might use this to spot selling opportunities in an uptrend when a bearish divergence in the Stochastic RSI suggests the trend may be reversing.
Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of regular bearish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: Choosing an orange label color and a specific line width makes bearish divergences in the Stochastic RSI clearly stand out on your chart.
H. Bullish Div Label: Default: False
What it is: An option to display labels for hidden bullish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark hidden bullish divergences, where the price makes a higher low while the Stochastic RSI makes a lower low, indicating potential continuation of an uptrend.
Example: A trader might use this to confirm an existing uptrend when a hidden bullish divergence in the Stochastic RSI signals continued buying strength.
Hidden Bullish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bullish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A softer blue color with a thinner line width might be chosen to subtly indicate hidden bullish divergences, keeping the chart clean while providing useful information.
H. Bearish Div Label: Default: False
What it is: An option to display labels for hidden bearish divergences in the Stochastic RSI.
What it does: Enables or disables the visibility of labels that mark hidden bearish divergences, where the price makes a lower high while the Stochastic RSI makes a higher high, indicating potential continuation of a downtrend.
Example: A trader might use this to confirm an existing downtrend when a hidden bearish divergence in the Stochastic RSI signals continued selling pressure.
Hidden Bearish Label Color, Line Width, and Line Color:
What it is: Settings to customize the appearance of hidden bearish divergence labels in the Stochastic RSI.
What it does: Allows you to choose the color of the labels, adjust the width of the divergence lines, and select the color for these lines.
Example: A muted orange color with a thinner line width might be selected to indicate hidden bearish divergences without overwhelming the chart.
Divergence Text Size and Color: Default: S (Small)
What it is: Settings to adjust the size and color of text labels for Stochastic RSI divergences.
What it does: Allows you to customize the size and color of text labels that display the divergence information on the chart.
Example: Choosing a small text size with a bright white color can make divergence labels easily readable without taking up too much space on the chart.
Alert System:
Custom Alerts for Divergences and Reversals:
What it is: The script includes customizable alert conditions to notify you of detected divergences or potential reversals based on WaveTrend, RSI, and Stochastic RSI.
What it does: Helps you stay informed of key market movements without constantly monitoring the charts, enabling timely decisions.
Example: Setting an alert for regular bearish divergence on the WaveTrend could notify you of a potential sell opportunity as soon as it is detected.
How to Use Alerts:
Set up custom alerts in TradingView based on these conditions to be notified of potential trading opportunities. Alerts are triggered when the indicator detects conditions that match the selected criteria, such as divergences or potential reversals.
By following the detailed guidelines and examples above, you can effectively use and customize this powerful indicator to suit your trading strategy.
For further understanding and customization, refer to the input settings within the script and adjust them to match your trading style and preferences.
How Components Work Together
Synergy and Cross-Validation: The indicator combines multiple layers of analysis to validate trading signals. For example, a WaveTrend buy signal that coincides with a bullish divergence in RSI and positive fast money flow is likely to be more reliable than any single indicator’s signal. This cross-validation reduces the likelihood of false signals and enhances decision-making.
Comprehensive Market Analysis: Each component plays a role in analyzing different aspects of the market. WaveTrend focuses on trend strength, Money Flow indicators assess market sentiment, while RSI and Stochastic RSI offer detailed views of price momentum and potential reversals.
Ideal For
Traders who require a reliable, multifaceted tool for detecting market trends and reversals.
Investors seeking a deeper understanding of market dynamics across different timeframes and conditions, whether in forex, equities, or cryptocurrency markets.
This script is designed to provide a comprehensive tool for technical analysis, combining multiple indicators and divergence detection into one versatile and customizable script. It is especially useful for traders who want to monitor various indicators simultaneously and look for convergence or divergence signals across different technical tools.
Acknowledgements
Special thanks to these amazing creators for inspiration and their creations:
I want to thank these amazing creators for creating there amazing indicators , that inspired me and also gave me a head start by making this indicator! Without their amazing indicators it wouldn't be possible!
vumanchu: VuManChu Cipher B Divergences.
MisterMoTa: RSI + Divergences + Alerts .
DevLucem: Plain Stochastic Divergence.
Note
This indicator is designed to be a powerful tool in your trading arsenal. However , it is essential to backtest and adjust the settings according to your trading strategy before applying it to live trading . If you have any questions or need further assistance, feel free to reach out.
CandleStick [TradingFinder] - All Reversal & Trend Patterns🔵 Introduction
"Candlesticks" patterns are used to predict price movements. We have included 5 of the best candlestick patterns that are common and very useful in "technical analysis" in this script to identify them automatically. The most important advantage of this indicator for users is saving time and high precision in identifying patterns.
These patterns are "Pin Bar," "Dark Cloud," "Piercing Line," "3 Inside Bar," and "Engulfing." By using these patterns, you can predict price movements more accurately and therefore make better decisions in your trades.
🔵 How to Use
Pin Bar : This pattern consists of a Candle where "Open Price," "Close Price," "High Price," and "Low Price" form the "Candle Body," and it also has "Long Shadow" and "Short Shadow." In the visual appearance of the Pin Bar pattern, we have a candle body and a pin bar shadow, where the candle body is smaller relative to the shadow.
Just as the candle body plays an important role in analysis, the pin bar shadow can also be influential. The larger the pin bar shadow, the stronger the expectation of a trend reversal.
When a "bearish pin bar" occurs at resistance or the chart ceiling, it can be predicted that the price trend will be downward. Similarly, at support points and the chart floor, a "bullish pin bar" can indicate an upward price movement.
Additionally, patterns like "Hammer," "Shooting Star," "Hanging Man," and "Inverted Hammer" are types of pin bars. Pin bars are formed in two ways: bullish pin bars have a long lower shadow, and bearish pin bars have a long upper shadow. Important: Displaying "Bullish Pin Bar" is labeled "BuPB," and "Bearish Pin Bar" is labeled "BePB."
Dark Cloud : The Dark Cloud pattern is one type of two-candle patterns that occurs at the end of an uptrend. The 2-candle pattern indicates the shape of this pattern, which actually consists of 2 candles, one bullish and one bearish. This pattern indicates a trend reversal and is quite powerful.
The Dark Cloud pattern is seen when, after a bullish candle at the end of an uptrend, a bearish candle opens at a higher level (weakly, equal, or higher) than the closing point of the bullish candle and finally closes at a point approximately in the middle of the previous candle. In this indicator, the Dark Cloud pattern is identified as "Wick" and "Strong" .
The difference between these two lies in the strictness of their conditions. Important: Strong Dark Cloud is labeled "SDC," and Weak Dark Cloud is labeled "WDC."
Piercing Line : The Piercing candlestick pattern consists of 2 candles, the first being bearish and consistent with the previous trend, and the second being bullish. The conditions of the pattern are such that the first candle is bearish and a price gap is created between the two candles upon the opening of the next candle because its opening price is below (weakly equal to or less than) the closing price of the previous candle.
Additionally, its closing price must be at least 50% above the red candle.
This means that the second candle must penetrate at least 50% into the first candle. Important: Strong Piercing Line is labeled "SPL," and Weak Piercing Line is labeled "WPL."
3 Inside Bar (3 Bar Reversal) : The 3 Inside Bar pattern is a reversal pattern. This pattern consists of 3 consecutive candles and can be either bullish or bearish. In the bullish pattern (Inside Up) formed at the end of a downtrend, the last candle must be bullish, and the third candle from the end must be bearish.
Additionally, the close price must be more than 50% of the third candle from the end. In the bearish pattern (Inside Down) formed at the end of an uptrend, the last candle must be bearish, and the third candle from the end must be bullish. Additionally, the close price must be less than 50% of the third candle from the end. Important: Bullish 3 Inside Bar is labeled "Bu3IB," and Bearish 3 Inside Bar is labeled "Be3IB."
Engulfing : The Engulfing candlestick pattern is a reversal pattern and consists of at least two candles, where one of them completely engulfs the body of the previous or following candle due to high volatility.
For this reason, the term "engulfing" is used for this pattern. This pattern occurs when the price body of a candle encompasses one or more candles before it. Engulfing candles can be bullish or bearish. Bullish Engulfing forms as a reversal candle at the end of a downtrend.
Bullish Engulfing indicates strong buying power and signals the beginning of an uptrend. This pattern is a bullish candle with a long upward body that completely covers the downward body before it. Bearish Engulfing, as a reversal pattern, is a long bearish candle that engulfs the upward candle before it.
Bearish Engulfing forms at the end of an uptrend and indicates the pressure of new sellers and their strong power. Additionally, forming this pattern at resistance levels and the absence of a lower shadow increases its credibility. Important: Bullish Engulfing is labeled "BuE," and Bearish Engulfing is labeled "BeE."
🔵 Settings
This section, you can use the buttons "Show Pin Bar," "Show Dark Cloud," "Show Piercing Line," "Show 3 Inside Bar," and "Show Engulfing" to enable or disable the display of each of these candlestick patterns.
Volume Delta Trailing Stop [LuxAlgo]The ' Volume Delta Trailing Stop ' indicator uses Lower Time Frame (LTF) volume delta data which can provide potential entries together with a Volume-Delta based Trailing Stop-line .
🔶 USAGE
Our 'Volume Delta Trailing Stop' script can show potential entries/Stop Loss lines
A trigger line needs to be broken before a position is taken, after which a Volume Delta-controlled Trailing Stop-line is created:
🔶 DETAILS
🔹 Volume rises when bought or sold
🔹 When the opening price appears on the chart, a buy/sell order has been executed.
If that order is less than the available supply of that particular price, volume will rise, without moving the price.
🔹 When the opening price is the same as the closing price, the volume of that bar can be seen as "neutral volume" (nV); nor "up", nor "down" volume.
Example
A buy order doesn't fill the first available supply in the order book. This price will be the opening price with a certain volume.
When at closing time, price still hasn't moved (the first available supply in the order book isn't filled, or no movement downwards),
the closing price will be equal to the opening price, but with volume. This can be seen as "neutral volume (nV)".
🔹 Delta Volume (ΔV): this is "up volume" minus "down volume"
🔹 Standard volume is colored red when closing price is lower than opening price ( = "down volume").
🔹 Standard volume is colored green when closing price is higher OR equal (nV) than opening price ( = "up volume").
🔹 Neutral Volume
The "Neutral-Volume" is considered "Up-Volume" - setting will dictate whether nV is considered as green 'buy' volume or not.
🔶 EXAMPLE
29 July 10:00 -> 10:05, chart timeframe 5 minutes, open 29311.28, close 29313.89
close > open, so the volume (39.55) is colored green ("up volume").
(The Volume script used in the following examples is the open-source publication Volume Columns w. Alerts (V) from LucF )
Let's zoom to the 1-minute TF:
The same period is now divided into more bars, volume direction (color) is dependable on the difference between open and close.
Counting up and down volume gives a more detailed result, it remains in an upward direction though):
(ΔV = +15.51)
Let's further zoom in to the 1-second TF:
The same period is now divided into even more bars (more possibility for changing direction on each bar)
Here we see several bars that haven't moved in price, but they have volume ("neutral" volume).
(neutral volume is coloured light green here, while up volume is coloured darker green)
When we count all green and red volume bars, the result is quite different:
(ΔV = -0.35)
In total more volume is found when price went downwards, yet price went up in these 5 minutes.
-> This is the heart of our publication, when this divergence occurs, you can see a barcolor changement:
• orange: when price went up, but LTF Volume was mainly in a downward direction.
• blue: when price went down, but LTF Volume was mainly in an upwards direction.
When we split the green "up volume" into "up" and "neutral", the difference is even higher
(here "neutral volume" is colored grey):
(ΔV = -12.76; "up" - "down")
🔶 CONCEPTS
bullishBear = current bar is red but LTF volume is in upward direction -> blue bar
bearishBull = current bar is green but LTF volume is in downward direction -> orange bar
🔹 Potential positioning - forming of Trigger-line
When not in position, the script will wait for a divergence between price and volume direction. When found, a Trigger-line will appear:
• at high when a blue bar appears ( bullishBear ).
• at low when an orange bar appears ( bearishBull ).
Next step is when the Trigger-line is broken by close or high/low (settings: Trigger )
Here, the closing price went under the grey Trigger-line -> bearish position:
🔹 Trailing Stop-line
When the Trigger-line is broken, the Trailing Stop-line (TS-line) will start:
• low when bullish position
• high when bearish position
You can choose (settings -> Trigger -> Close or H/L ) whether close price or high/low should break the Trigger-line
When alerts are enabled ("Any alert() function call"), you'll get the following message:
• ' signal up ' when bullish position
• ' signal down' when bearish position
After that, the TS-line will be adjusted when:
• a blue bullishBear bar appears when in bullish position -> lowest of {low , previous blue bar's high or orange bar's low}
• an orange bearishBull bar appears when in bearish position -> highest of {high, previous blue bar's high or orange bar's low}
When alerts are enabled ("Any alert() function call"), and the TS-line is broken, you'll get the following message:
• ' TS-line broken down ' when out bullish position
• ' TS-line broken up ' when out bearish position
🔹 Reference Point
Default the direction of price will be evaluated by comparing closing price with opening price.
When open and close are the same, you'll get "neutral volume".
You can use "previous close" instead (as in built-in volume indicator) to include gaps.
If close equals open , but close is lower than previous close , it will be regarded as " down volume ",
similar, when close is higher than previous close , it will be regarded as " up volume "
Note, the setting applies for the current timeframe AND Lower timeframe:
Based on: " open " (close - open)
Based on: " previous close " (close - previous close)
🔹 Adjustment
When the TS-line changes, this can be adjusted with a percentage of price , or a multiple of " True Range "
Default (Δ line -> Adjustment - 0)
Δ line -> Adjustment 0.03% (of price)
Δ line -> Mult of TR (10)
🔶 SETTINGS
🔹 LTF: choose your Lower TimeFrame: 1S (seconds), 5S, 10S, 15S, 30S, 1 minute)
🔹 Trigger: Choose the trigger for breaking the Trigger-line ; close or H/L (high when bullish position, low when bearish position)
🔹 Δ line ( Trailing Stop-line ): add/subtract an adjustment when the TS-line changes ( default: Adjustment ):
• Adjustment ( default: 0 ): add/subtract an extra % of price
• Mult of TR : add/subtract a multiple of True Range
🔹 Based on: compare closing price against:
• open
• previous close
🔹 "Neutral-Volume" is considered "Up-Volume" : this setting will dictate whether nV is considered as green 'buy' volume or not.
🔶 CONSIDERATIONS
🔹 The lowest LTF (1S) will give you more detail and will get data close to tick data.
However, a maximum of 100,000 intrabars can be used in calculations .
This means on the daily chart you won't see anything since 1 day ~ 86400 seconds. (just over 1 bar)
-> choose a lower chart timeframe, or choose a higher LTF (5S, 10S, ... 1 minute)
🔹 Always choose a LTF lower than the current chart timeframe.
🔹 Pine Script™ code using this request.security_lower_tf() may calculate differently on historical and real-time bars, leading to repainting .
Volume Profile (Maps) [LuxAlgo]The Pine Script® developers have unleashed "maps"!
Volume Profile (Maps) displays volume, associated with price, above and below the latest price, by using maps
The largest and second-largest volume is highlighted.
🔶 USAGE
The proposed script can highlight more frequent closing prices/prices with the highest volume, potentially highlighting more liquid areas. The prices with the highest associated volume (in red and orange in the indicator) can eventually be used as support/resistance levels.
Voids within the volume profile can highlight large price displacements (volatile variations).
🔶 CONCEPTS
🔹 Maps
A map object is a collection that consists of key - value pairs
Each key is unique and can only appear once. When adding a new value with a key that the map already contains, that value replaces the old value associated with the key .
You can change the value of a particular key though, for example adding volume (value) at the same price (key), the latter technique is used in this script.
Volume is added to the map, associated with a particular price (default close, can be set at high, low, open,...)
When the map already contains the same price (key), the value (volume) is added to the existing volume at the associated price.
A map can contain maximum 50K values, which is more than enough to hold 20K bars (Basic 5K - Premium plan 20K), so the whole history can be put into a map.
🔹 Visible line/box limit
We can only display maximum 500 line.new() though.
The code locates the current (last) close, and displays volume values around this price, using lines, for example 250 lines above and 250 lines below current price.
If one side contains fewer values, the other side can show more lines, taking the maximum out of the 500 visible line limitation.
Example (max. 500 lines visible)
• 100 values below close
• 2000 values above close
-> 100 values will be displayed below close
-> 400 remaining -> 400 values will be displayed above close
Pushing the limits even further, when ' Amount of bars ' is set higher than 500, boxes - box.new() - will be used as well.
These have a limit of 500 as well, bringing the total limit to 1000.
Note that there are visual differences when boxes overlap against lines.
If this is confusing, please keep ' Amount of bars ' at max. 500 (then only lines will be used).
🔹 Rounding function
This publication contains 2 round functions, which can be used to widen the Volume Profile
Round
• "Round" set at zero -> nothing changes to the source number
• "Round" set below zero -> x digit(s) after the decimal point, starting from the right side, and rounded.
• "Round" set above zero -> x digit(s) before the decimal point, starting from the right side, and rounded.
Example: 123456.789
0->123456.789
1->123456.79
2->123456.8
3->123457
-1->123460
-2->123500
Step
Another option is custom steps.
After setting "Round" to "Step", choose the desired steps in price,
Examples
• 2 -> 1234.00, 1236.00, 1238.00, 1240.00
• 5 -> 1230.00, 1235.00, 1240.00, 1245.00
• 100 -> 1200.00, 1300.00, 1400.00, 1500.00
• 0.05 -> 1234.00, 1234.05, 1234.10, 1234.15
•••
🔶 FEATURES
🔹 Adjust position & width
🔹 Table
The table shows the details:
• Size originalMap : amount of elements in original map
• # higher: amount of elements, higher than last "close" (source)
• index "close" : index of last "close" (source), or # element, lower than source
• Size newMap : amount of elements in new map (used for display lines)
• # higher : amount of elements in newMap, higher than last "close" (source)
• # lower : amount of elements in newMap, lower than last "close" (source)
🔹 Volume * currency
Let's take as example BTCUSD, relative to USD, 10 volume at a price of 100 BTCUSD will be very different than 10 volume at a price of 30000 (1K vs. 300K)
If you want volume to be associated with USD, enable Volume * currency . Volume will then be multiplied by the price:
• 10 volume, 1 BTC = 100 -> 1000
• 10 volume, 1 BTC = 30K -> 300K
Disabled
Enabled
🔶 DETAILS
🔹 Put
When the map doesn't contain a price, it will be added, using map.put(id, key, value)
In our code:
map.put(originalMap, price, volume)
or
originalMap.put(price, volume)
A key (price) is now associated with a value (volume) -> key : value
Since all keys are unique, we don't have to know its position to extract the value, we just need to know the key -> map.get(id, key)
We use map.get() when a certain key already exists in the map, and we want to add volume with that value.
if originalMap.contains(price)
originalMap.put(price, originalMap.get(price) + volume)
-> At the last bar, all prices (source) are now associated with volume.
🔹 Copy & sort
Next, every key of the map is copied and sorted (array of keys), after which the index (idx) is retrieved of last (current) price.
copyK = originalMap.keys().copy()
copyK.sort()
idx = copyK.binary_search_leftmost(src)
Then left and right side of idx is investigated to show a maximum amount of lines at both sides of last price.
🔹 New map & display
The keys (from sorted array of copied keys) that will be displayed are put in a new map, with the associated volume values from the original map.
newMap = map.new()
🔹 Re-cap
• put in original amp (price key, volume value)
• copy & sort
• find index of last price
• fetch relevant keys left/right from that index
• put keys in new map and fetch volume associated with these keys (from original map)
Simple example (only show 5 lines)
bar 0, price = 2, volume = 23
bar 1, price = 4, volume = 3
bar 2, price = 8, volume = 21
bar 3, price = 6, volume = 7
bar 4, price = 9, volume = 13
bar 5, price = 5, volume = 85
bar 6, price = 3, volume = 13
bar 7, price = 1, volume = 4
bar 8, price = 7, volume = 9
Original map:
Copied keys array:
Sorted:
-> 5 keys around last price (7) are fetched (5, 6, 7, 8, 9)
-> keys are placed into new map + volume values from original map
Lastly, these values are displayed.
🔶 SETTINGS
Source : Set source of choice; default close , can be set as high , low , open , ...
Volume & currency : Enable to multiply volume with price (see Features )
Amount of bars : Set amount of bars which you want to include in the Volume Profile
Max lines : maximum 1000 (if you want to use only lines, and no boxes -> max. 500, see Concepts )
🔹 Round -> ' Round/Step '
Round -> see Concepts
Step -> see Concepts
🔹 Display Volume Profile
Offset: shifts the Volume Profile (max. 500 bars to the right of last bar, see Features )
Max width Volume Profile: largest volume will be x bars wide, the rest is displayed as a ratio against largest volume (see Features )
Show table : Show details (see Features )
🔶 LIMITATIONS
• Lines won't go further than first bar (coded).
• The Volume Profile can be placed maximum 500 bar to the right of last price.
• Maximum 500 lines/boxes can be displayed
Developing Market Profile / TPO [Honestcowboy]The Developing Market Profile Indicator aims to broaden the horizon of Market Profile / TPO research and trading. While standard Market Profiles aim is to show where PRICE is in relation to TIME on a previous session (usually a day). Developing Market Profile will change bar by bar and display PRICE in relation to TIME for a user specified number of past bars.
What is a market profile?
"Market Profile is an intra-day charting technique (price vertical, time/activity horizontal) devised by J. Peter Steidlmayer. Steidlmayer was seeking a way to determine and to evaluate market value as it developed in the day time frame. The concept was to display price on a vertical axis against time on the horizontal, and the ensuing graphic generally is a bell shape--fatter at the middle prices, with activity trailing off and volume diminished at the extreme higher and lower prices."
For education on market profiles I recommend you search the net and study some profitable traders who use it.
Key Differences
Does not have a value area but distinguishes each column in relation to the biggest column in percentage terms.
Updates bar by bar
Does not take sessions into account
Shows historical values for each bar
While there is an entire education system build around Market Profiles they usually focus on a daily profile and in some cases how the value area develops during the day (there are indicators showing the developing value area).
The idea of trading based on a developing value area is what inspired me to build the Developing Market Profile.
🟦 CALCULATION
Think of this Developing Market Profile the same way as you would think of a moving average. On each bar it will lookback 200 bars (or as user specified) and calculate a Market Profile from those bars (range).
🔹Market Profile gets calculated using these steps:
Get the highest high and lowest low of the price range.
Separate that range into user specified amount of price zones (all spaced evenly)
Loop through the ranges bars and on each bar check in which price zones price was, then add +1 to the zones price was in (we do this using the OccurenceArray)
After it looped through all bars in the range it will draw columns for each price zone (using boxes) and make them as wide as the OccurenceArray dictates in number of bars
🔹Coloring each column:
The script will find the biggest column in the Profile and use that as a reference for all other columns. It will then decide for each column individually how big it is in % compared to the biggest column. It will use that percentage to decide which color to give it, top 20% will be red, top 40% purple, top 60% blue, top 80% green and all the rest yellow. The user is able to adjust these numbers for further customisation.
The historical display of the profiles uses plotchar() and will not only use the color of the column at that time but the % rating will also decide transparancy for further detail when analysing how the profiles developed over time. Each of those historical profiles is calculated using its own 200 past bars. This makes the script very heavy and that is why it includes optimisation settings, more info below.
🟦 USAGE
My general idea of the markets is that they are ever changing and that in studying that changing behaviour a good trader is able to distinguish new behaviour from old behaviour and adapt his approach before losing traders "weak hands" do.
A Market Profile can visually show a trader what kind of market environment we currently are in. In training this visual feedback helps traders remember past market environments and how the market behaved during these times.
Use the history shown using plotchars in colors to get an idea of how the Market Profile looked at each bar of the chart.
This history will help in studying how price moves at different stages of the Market Profile development.
I'm in no way an expert in trading Market Profiles so take this information with a grain of salt. Below an idea of how I would trade using this indicator:
🟦 SETTINGS
🔹MARKET PROFILING
Lookback: The amount of bars the Market Profile will look in the past to calculate where price has been the most in that range
Resolution: This is the amount of columns the Market Profile will have. These columns are calculated using the highest and lowest point price has been for the lookback period
Resolution is limited to a maximum of 32 because of pinescript plotting limits (64). Each plotchar() because of using variable colors takes up 2 of these slots
🔹VISUAL SETTINGS
Profile Distance From Chart: The amount of bars the market profile will be offset from the current bar
Border width (MP): The line thickness of the Market Profile column borders
Character: This is the character the history will use to show past profiles, default is a square.
Color theme: You can pick 5 colors from biggest column of the Profile to smallest column of the profile.
Numbers: these are for % to decide column color. So on default top 20% will be red, top 40% purple... Always use these in descending order
Show Market Profile: This setting will enable/disable the current Market Profile (columns on right side of current bar)
Show Profile History: This setting will enable/disable the Profile History which are the colored characters you see on each bar
🔹OPTIMISATION AND DEBUGGING
Calculate from here: The Market Profile will only start to calculate bar by bar from this point. Setting is needed to optimise loading time and quite frankly without it the script would probably exceed tradingview loading time limits.
Min Size: This setting is there to avoid visual bugs in the script. Scaling the chart there can be issues where the Market Profile extends all the way to 0. To avoid this use a minimum size bigger than the bugged bottom box
