Curvature Tensor Pivots - HIVECurvature Tensor Pivots - HIVE
I. CORE CONCEPT & ORIGINALITY
Curvature Tensor Pivots - HIVE is an advanced, multi-dimensional pivot detection system that combines differential geometry, reinforcement learning, and statistical physics to identify high-probability reversal zones before they fully form. Unlike traditional pivot indicators that rely on simple price comparisons or lagging moving averages, this system models price action as a smooth curve in geometric space and calculates its mathematical curvature (how sharply the price trajectory is "bending") to detect pivots with scientific precision.
What Makes This Original:
Differential Geometry Engine: The script calculates first and second derivatives of price using Kalman-filtered trajectory analysis, then computes true mathematical curvature (κ) using the classical formula: κ = |y''| / (1 + y'²)^(3/2). This approach treats price as a physical phenomenon rather than discrete data points.
Ghost Vertex Prediction: A proprietary algorithm that detects pivots 1-3 bars BEFORE they complete by identifying when velocity approaches zero while acceleration is high—this is the mathematical definition of a turning point.
Multi-Armed Bandit AI: Four distinct pivot detection strategies (Fast, Balanced, Strict, Tensor) run simultaneously in shadow portfolios. A Thompson Sampling reinforcement learning algorithm continuously evaluates which strategy performs best in current market conditions and automatically selects it.
Hive Consensus System: When 3 or 4 of the parallel strategies agree on the same price zone, the system generates "confluence zones"—areas of institutional-grade probability.
Dynamic Volatility Scaling (DVS): All parameters auto-adjust based on current ATR relative to historical average, making the indicator adaptive across all timeframes and instruments without manual re-optimization.
II. HOW THE COMPONENTS WORK TOGETHER
This is NOT a simple mashup —each subsystem feeds data into the others in a closed-loop learning architecture:
The Processing Pipeline:
Step 1: Geometric Foundation
Raw price is normalized against a 50-period SMA to create a trajectory baseline
A Zero-Lag EMA smooths the trajectory while preserving edge response
Kalman filter removes noise while maintaining signal integrity
Step 2: Calculus Layer
First derivative (y') measures velocity of price movement
Second derivative (y'') measures acceleration (rate of velocity change)
Curvature (κ) is calculated from these derivatives, representing how sharply price is turning
Step 3: Statistical Validation
Z-Score measures how many standard deviations current price deviates from the Kalman-filtered "true price"
Only pivots with Z-Score > threshold (default 1.2) are considered statistically significant
This filters out noise and micro-fluctuations
Step 4: Tensor Construction
Curvature is combined with volatility (ATR-based) and momentum (ROC-based) to create a multidimensional "tensor score"
This tensor represents the geometric stress in the price field
High tensor magnitude = high probability of structural failure (reversal)
Step 5: AI Decision Layer
All 4 bandit strategies evaluate current conditions using different sensitivity thresholds
Each strategy maintains a virtual portfolio that trades its signals in real-time
Thompson Sampling algorithm updates Bayesian priors (alpha/beta distributions) based on each strategy's Sharpe ratio, win rate, and drawdown
The highest-performing strategy's signals are displayed to the user
Step 6: Confluence Aggregation
When multiple strategies agree on the same price zone, that zone is highlighted as a confluence area. These represent "hive mind" consensus—the strongest setups
Why This Integration Matters:
Traditional indicators either detect pivots too late (lagging) or generate too many false signals (noisy). By requiring geometric confirmation (curvature), statistical significance (Z-Score), multi-strategy agreement (hive voting), and performance validation (RL feedback) , this system achieves institutional-grade precision. The reinforcement learning layer ensures the system adapts as market regimes change, rather than degrading over time like static algorithms.
III. DETAILED METHODOLOGY
A. Curvature Calculation (Differential Geometry)
The system models price as a parametric curve where:
x-axis = time (bar index)
y-axis = normalized price
The curvature at any point represents how quickly the direction of the tangent line is changing. High curvature = sharp turn = potential pivot.
Implementation:
Lookback window (default 8 bars) defines the local curve segment
Smoothing (default 5 bars) applies adaptive EMA to reduce tick noise
Curvature is normalized to 0-1 scale using local statistical bounds (mean ± 2 standard deviations)
B. Ghost Vertex (Predictive Pivot Detection)
Classical pivot detection waits for price to form a swing high/low and confirm. Ghost Vertex uses calculus to predict the turning point:
Conditions for Ghost Pivot:
Velocity (y') ≈ 0 (price rate of change approaching zero)
Acceleration (y'') ≠ 0 (change is decelerating/accelerating)
Z-Score > threshold (statistically abnormal position)
This allows detection 1-3 bars before the actual high/low prints, providing an early entry edge.
C. Multi-Armed Bandit Reinforcement Learning
The system runs 4 parallel "bandits" (agents), each with different detection sensitivity:
Bandit Strategies:
Fast: Low curvature threshold (0.1), low Z-Score requirement (1.0) → High frequency, more signals
Balanced: Standard thresholds (0.2 curvature, 1.5 Z-Score) → Moderate frequency
Strict: High thresholds (0.4 curvature, 2.0 Z-Score) → Low frequency, high conviction
Tensor: Requires tensor magnitude > 0.5 → Geometric-weighted detection
Learning Algorithm (Thompson Sampling):
Each bandit maintains a Beta distribution with parameters (α, β)
After each trade outcome, α is incremented for wins, β for losses
Selection probability is proportional to sampled success rate from the distribution
This naturally balances exploration (trying underperformed strategies) vs exploitation (using best strategy)
Performance Metrics Tracked:
Equity curve for each shadow portfolio
Win rate percentage
Sharpe ratio (risk-adjusted returns)
Maximum drawdown
Total trades executed
The system displays all metrics in real-time on the dashboard so users can see which strategy is currently "winning."
D. Dynamic Volatility Scaling (DVS)
Markets cycle between high volatility (trending, news-driven) and low volatility (ranging, quiet). Static parameters fail when regime changes.
DVS Solution:
Measures current ATR(30) / close as normalized volatility
Compares to 100-bar SMA of normalized volatility
Ratio > 1 = high volatility → lengthen lookbacks, raise thresholds (prevent noise)
Ratio < 1 = low volatility → shorten lookbacks, lower thresholds (maintain sensitivity)
This single feature is why the indicator works on 1-minute crypto charts AND daily stock charts without parameter changes.
E. Confluence Zone Detection
The script divides the recent price range (200 bars) into 200 discrete zones. On each bar:
Each of the 4 bandits votes on potential pivot zones
Votes accumulate in a histogram array
Zones with ≥ 3 votes (75% agreement) are drawn as colored boxes
Red boxes = resistance confluence, Green boxes = support confluence
These zones act as magnet levels where price often returns multiple times.
IV. HOW TO USE THIS INDICATOR
For Scalpers (1m - 5m timeframes):
Settings: Use "Aggressive" or "Adaptive" pivot mode, Curvature Window 5-8, Min Pivot Strength 50-60
Entry Signal: Triangle marker appears (🔺 for longs, 🔻 for shorts)
Confirmation: Check that Hive Sentiment on dashboard agrees (3+ votes)
Stop Loss: Use the dotted volatility-adjusted target line in reverse (if pivot is at 100 with target at 110, stop is ~95)
Take Profit: Use the projected target line (default 3× ATR)
Advanced: Wait for confluence zone formation, then enter on retest of the zone
For Day Traders (15m - 1H timeframes):
Settings: Use "Adaptive" mode (default settings work well)
Entry Signal: Pivot marker + Hive Consensus alert
Confirmation: Check dashboard—ensure selected bandit has Sharpe > 1.5 and Win% > 55%
Filter: Only take pivots with Pivot Strength > 70 (shown in dashboard)
Risk Management: Monitor the Live Position Tracker—if your selected bandit is holding a position, consider that as market structure context
Exit: Either use target lines OR exit when opposite pivot appears
For Swing Traders (4H - Daily timeframes):
Settings: Use "Conservative" mode, Curvature Window 12-20, Min Bars Between Pivots 15-30
Focus on Confluence: Only trade when 4/4 bandits agree (unanimous hive consensus)
Entry: Set limit orders at confluence zones rather than market orders at pivot signals
Confirmation: Look for breakout diamonds (◆) after pivot—these signal momentum continuation
Risk Management: Use wider stops (base stop loss % = 3-5%)
Dashboard Interpretation:
Top Section (Real-Time Metrics):
κ (Curv): Current curvature. >0.6 = active pivot forming
Tensor: Geometric stress. Positive = bullish bias, Negative = bearish bias
Z-Score: Statistical deviation. >2.0 or <-2.0 = extreme outlier (strong signal)
Bandit Performance Table:
α/β: Bayesian parameters. Higher α = more wins in history
Win%: Self-explanatory. >60% is excellent
Sharpe: Risk-adjusted returns. >2.0 is institutional-grade
Status: Shows which strategy is currently selected
Live Position Tracker:
Shows if the selected bandit's shadow portfolio is currently holding a position
Displays entry price and real-time P&L
Use this as "what the AI would do" confirmation
Hive Sentiment:
Shows vote distribution across all 4 bandits
"BULLISH" with 3+ green votes = high-conviction long setup
"BEARISH" with 3+ red votes = high-conviction short setup
Alert Setup:
The script includes 6 alert conditions:
"AI High Pivot" = Selected bandit signals short
"AI Low Pivot" = Selected bandit signals long
"Hive Consensus BUY" = 3+ bandits agree on long
"Hive Consensus SELL" = 3+ bandits agree on short
"Breakout Up" = Resistance breakout (continuation long)
"Breakdown Down" = Support breakdown (continuation short)
Recommended Alert Strategy:
Set "Hive Consensus" alerts for high-conviction setups
Use "AI Pivot" alerts for active monitoring during your trading session
Use breakout alerts for momentum/trend-following entries
V. PARAMETER OPTIMIZATION GUIDE
Core Geometry Parameters:
Curvature Window (default 8):
Lower (3-5): Detects micro-structure, best for scalping volatile pairs (crypto, forex majors)
Higher (12-20): Detects macro-structure, best for swing trading stocks/indices
Rule of thumb: Set to ~0.5% of your typical trade duration in bars
Curvature Smoothing (default 5):
Increase if you see too many false pivots (noisy instrument)
Decrease if pivots lag (missing entries by 2-3 bars)
Inflection Threshold (default 0.20):
This is advanced. Lower = more inflection zones highlighted
Useful for identifying order blocks and liquidity voids
Most users can leave default
Pivot Detection Parameters:
Pivot Sensitivity Mode:
Aggressive: Use in low-volatility range-bound markets
Normal: General purpose
Adaptive: Recommended—auto-adjusts via DVS
Conservative: Use in choppy, whipsaw conditions or for swing trading
Min Bars Between Pivots (default 8):
THIS IS CRITICAL for visual clarity
If chart looks cluttered, increase to 12-15
If missing pivots, decrease to 5-6
Match to your timeframe: 1m charts use 3-5, Daily charts use 20+
Min Z-Score (default 1.2):
Statistical filter. Higher = fewer but stronger signals
During news events (NFP, FOMC), increase to 2.0+
In calm markets, 1.0 works well
Min Pivot Strength (default 60):
Composite quality score (0-100)
80+ = institutional-grade pivots only
50-70 = balanced
Below 50 = will show weak setups (not recommended)
RL & DVS Parameters:
Enable DVS (default ON):
Leave enabled unless you want to manually tune for a specific market condition
This is the "secret sauce" for cross-timeframe performance
DVS Sensitivity (default 1.0):
Increase to 1.5-2.0 for extremely volatile instruments (meme stocks, altcoins)
Decrease to 0.5-0.7 for stable instruments (utilities, bonds)
RL Algorithm (default Thompson Sampling):
Thompson Sampling: Best for non-stationary markets (recommended)
UCB1: Best for stable, mean-reverting markets
Epsilon-Greedy: For testing only
Contextual: Advanced—uses market regime as context
Risk Parameters:
Base Stop Loss % (default 2.0):
Set to 1.5-2× your instrument's average ATR as a percentage
Example: If SPY ATR = $3 and price = $450, ATR% = 0.67%, so use 1.5-2.0%
Base Take Profit % (default 4.0):
Aim for 2:1 reward/risk ratio minimum
For mean-reversion strategies, use 1.5-2.0%
For trend-following, use 3-5%
VI. UNDERSTANDING THE UNDERLYING CONCEPTS
Why Differential Geometry?
Traditional technical analysis treats price as discrete data points. Differential geometry models price as a continuous manifold —a smooth surface that can be analyzed using calculus. This allows us to ask: "At what rate is the trend changing?" rather than just "Is price going up or down?"
The curvature metric captures something fundamental: inflection points in market psychology . When buyers exhaust and sellers take over (or vice versa), the price trajectory must curve. By measuring this curvature mathematically, we detect these psychological shifts with precision.
Why Reinforcement Learning?
Markets are non-stationary —statistical properties change over time. A strategy that works in Q1 may fail in Q3. Traditional indicators have fixed parameters and degrade over time.
The multi-armed bandit framework solves this by:
Running multiple strategies in parallel (diversification)
Continuously measuring performance (feedback loop)
Automatically shifting capital to what's working (adaptation)
This is how professional hedge funds operate—they don't use one strategy, they use ensembles with dynamic allocation.
Why Kalman Filtering?
Raw price contains two components: signal (true movement) and noise (random fluctuations). Kalman filters are the gold standard in aerospace and robotics for extracting signal from noisy sensors.
By applying this to price data, we get a "clean" trajectory to measure curvature against. This prevents false pivots from bid-ask bounce or single-print anomalies.
Why Z-Score Validation?
Not all high-curvature points are tradeable. A sharp turn in a ranging market might just be noise. Z-Score ensures that pivots occur at statistically abnormal price levels —places where price has deviated significantly from its Kalman-filtered "fair value."
This filters out 70-80% of false signals while preserving true reversal points.
VII. COMMON USE CASES & STRATEGIES
Strategy 1: Confluence Zone Reversal Trading
Wait for confluence zone to form (red or green box)
Wait for price to approach zone
Enter when pivot marker appears WITHIN the confluence zone
Stop: Beyond the zone
Target: Opposite confluence zone or 3× ATR
Strategy 2: Hive Consensus Scalping
Set alert for "Hive Consensus BUY/SELL"
When alert fires, check dashboard—ensure 3-4 votes
Enter immediately (market order or 1-tick limit)
Stop: Tight, 1-1.5× ATR
Target: 2× ATR or opposite pivot signal
Strategy 3: Bandit-Following Swing Trading
On Daily timeframe, monitor which bandit has best Sharpe ratio over 30+ days
Take ONLY that bandit's signals (ignore others)
Enter on pivot, hold until opposite pivot or target line
Position size based on bandit's current win rate (higher win% = larger position)
Strategy 4: Breakout Confirmation
Identify key support/resistance level manually
Wait for pivot to form AT that level
If price breaks level and diamond breakout marker appears, enter in breakout direction
This combines support/resistance with geometric confirmation
Strategy 5: Inflection Zone Limit Orders
Enable "Show Inflection Zones"
Place limit buy orders at bottom of purple zones
Place limit sell orders at top of purple zones
These zones represent structural change points where price often pauses
VIII. WHAT THIS INDICATOR DOES NOT DO
To set proper expectations:
This is NOT:
A "holy grail" with 100% win rate
A strategy that works without risk management
A replacement for understanding market fundamentals
A signal copier (you must interpret context)
This DOES NOT:
Predict black swan events
Account for fundamental news (you must avoid trading during major news if not experienced)
Work well in extremely low liquidity conditions (penny stocks, microcap crypto)
Generate signals during consolidation (by design—prevents whipsaw)
Best Performance:
Liquid instruments (SPY, ES, NQ, EUR/USD, BTC/USD, etc.)
Clear trend or range conditions (struggles in choppy transition periods)
Timeframes 5m and above (1m can work but requires experience)
IX. PERFORMANCE EXPECTATIONS
Based on shadow portfolio backtesting across multiple instruments:
Conservative Mode:
Signal frequency: 2-5 per week (Daily charts)
Expected win rate: 60-70%
Average RRR: 2.5:1
Adaptive Mode:
Signal frequency: 5-15 per day (15m charts)
Expected win rate: 55-65%
Average RRR: 2:1
Aggressive Mode:
Signal frequency: 20-40 per day (5m charts)
Expected win rate: 50-60%
Average RRR: 1.5:1
Note: These are statistical expectations. Individual results depend on execution, risk management, and market conditions.
X. PRIVACY & INVITE-ONLY NATURE
This script is invite-only to:
Maintain signal quality (prevent market impact from mass adoption)
Provide dedicated support to users
Continuously improve the algorithm based on user feedback
Ensure users understand the complexity before deploying real capital
The script is closed-source to protect proprietary research in:
Ghost Vertex prediction mathematics
Tensor construction methodology
Bandit reward function design
DVS scaling algorithms
XI. FINAL RECOMMENDATIONS
Before Trading Live:
Paper trade for minimum 2 weeks to understand signal timing
Start with ONE timeframe and master it before adding others
Monitor the dashboard —if selected bandit Sharpe drops below 1.0, reduce size
Use confluence and hive consensus for highest-quality setups
Respect the Min Bars Between Pivots setting —this prevents overtrading
Risk Management Rules:
Never risk more than 1-2% of account per trade
If 3 consecutive losses occur, stop trading and review (possible regime change)
Use the shadow portfolio as a guide—if ALL bandits are losing, market is in transition
Combine with other analysis (order flow, volume profile) for best results
Continuous Learning:
The RL system improves over time, but only if you:
Keep the indicator running (it learns from bar data)
Don't constantly change parameters (confuses the learning)
Let it accumulate at least 50 samples before judging performance
Review the dashboard weekly to see which bandits are adapting
CONCLUSION
Curvature Tensor Pivots - HIVE represents a fusion of advanced mathematics, machine learning, and practical trading experience. It is designed for serious traders who want institutional-grade tools and understand that edge comes from superior methodology, not magic formulas.
The system's strength lies in its adaptive intelligence —it doesn't just detect pivots, it learns which detection method works best right now, in this market, under these conditions. The hive consensus mechanism provides confidence, the geometric foundation provides precision, and the reinforcement learning provides evolution.
Use it wisely, manage risk properly, and let the mathematics work for you.
Disclaimer: This indicator is a tool for analysis and does not constitute financial advice. Past performance of shadow portfolios does not guarantee future results. Trading involves substantial risk of loss. Always perform your own due diligence and never trade with capital you cannot afford to lose.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
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ICT Sigma Hybrid FVGThis indicator combines three analytical components—statistical volatility modeling, ICT imbalance logic, and higher-timeframe bias filtering—to help traders interpret displacement-driven price inefficiencies. The goal is to reduce noise and highlight only meaningful FVGs that occur with sufficient volatility and directional context.
Sigma Volatility Zones
The script calculates statistically normalized deviation levels using a multi-regime standard deviation blended with ATR.
This produces adaptive volatility zones that:
Expand during trending or high-volatility periods
Contract during consolidation
Highlight extremes more accurately than fixed standard deviations
These zones help users identify where price is operating in premium/discount relative to recent volatility.
Fair Value Gaps With Displacement Scoring
Every potential FVG is evaluated using a displacement score based on candle body expansion, wick displacement, and relative move efficiency. FVGs that do not exceed the minimum score are filtered out. This ensures the script only displays gaps associated with meaningful movement, not minor pricing noise.
Optional Higher-Timeframe Bias Filter
The HTF bias engine evaluates structure using selected higher-timeframe EMAs.
When enabled, the indicator:
Shows bullish FVGs only in bullish higher-timeframe conditions
Shows bearish FVGs only in bearish conditions
Hides counter-trend FVGs that may have lower reliability
Users may disable this to see all qualifying gaps regardless of bias.
ATR-Adaptive Volatility Conditioning
ATR is blended into the model so the displacement score and sigma zones adjust automatically to sudden volatility changes such as:
Major economic releases
Earnings
High-impact market events
Overnight volatility shifts
This helps maintain consistent FVG quality during rapidly changing conditions.
How to Use the Indicator:
Use sigma levels to understand whether price is extended or discounted relative to recent volatility.
Monitor FVGs that appear within or near sigma extremes to identify potential exhaustion or continuation zones.
Combine HTF bias with LTF displacement gaps to align intraday entries with broader directional flow.
ATR-adjusted scoring helps distinguish between meaningful inefficiencies and low-quality gaps.
Example 1 — Intraday Sigma Expansion & Displacement FVG Reaction
Figure 1. Price collapses from a 4.5σ extreme during a volatility expansion event.
Only high-impact FVGs are shown due to the displacement filter, removing low-quality gaps.
Sigma bands expand dynamically as volatility increases, illustrating how the model adapts automatically.
Example 2 — Higher-Timeframe Sigma Compression After a Major Trend Leg
Figure 2. After a large macro move, sigma levels compress tightly, forming a volatility cluster.
These HTF sigma zones later act as reaction levels during continuation.
This demonstrates why the model blends HTF sigma structure with LTF displacement gaps for alignment.
Recommended Settings
Standard deviation lookback: 100
ATR length: 50
ATR blend weight: 0.5
Minimum Z-score: 1.8
Sigma levels: 1.5 / 3 / 4.5
HTF bias: Daily (optional)
FVG displacement filter: On
SVE Daily ATR + SDTR Context BandsSVE Daily ATR + SDTR Context Bands is a free companion overlay from The Volatility Engine™ ecosystem.
It plots daily ATR-based expansion levels and a Standardized Deviation Threshold Range (SDTR) to give traders a clean, quantitative view of where intraday price sits relative to typical daily movement and volatility extremes.
This module is designed as an SVE-compatible context layer—using discrete, RTH-aligned daily zones, expected-move bands, and a standardized volatility shell—so traders can build situational awareness even without the full SPX Volatility Engine™ (SVE).
It does not generate trade signals.
Its sole purpose is to provide a clear volatility framework you can combine with your own structure, Fibonacci, or signal logic (including SVE, if you use it).
🔍 What It Shows
* Daily ATR Bands (expHigh / expLow)
- Expected high/low based on smoothed daily ATR
- Updates at the RTH open
* Daily SDTR Bands (expHighSDTR / expLowSDTR)
- Standard deviation threshold range for volatility extremes
- Helps identify overextended conditions
Discrete RTH-aligned Zones
- Bands reset cleanly at each RTH session
No continuous carry-over from prior days
Daily ATR & SDTR stats label
Quick-reference box showing current ATR and SDTR values
🎯 Purpose
This tool helps traders:
- Gauge intraday context relative to expected daily movement
- Assess volatility state (quiet, normal, expanded, extreme)
- Identify likely exhaustion or expansion zones
- Frame intraday price action inside daily volatility rails
- Support decision-making with objective context rather than emotion
It complements any strategy and works on any intraday timeframe.
⚙️ Inputs
- ATR Lookback (default: 20 days)
- RTH Session Times
- SDTR Lookback
- Show/Hide Daily Stats Label
🧩 Part of the SVE Ecosystem
This module is part of the broader SPX Volatility Engine™ framework.
The full SVE system includes:
- Composite signal scoring
- Volatility compression logic
- Histogram slope and momentum analysis
- Internals (VIX / VVIX / TICK)
- Structural zone awareness
- Real-time bias selection
- High-clarity decision support
⚠️ Disclaimer
This tool is provided for educational and informational purposes only.
No performance claims are made or implied.
Not investment advice.
BB Breakout + EMA Touch (50/100)Shows points only when BOTH happen on the same candle:
1️⃣ Price breaks through Bollinger Bands
2️⃣ Price touches (or crosses) EMA 50 or EMA 100
Drawdown % + STD Bands: Log-Scale Macro ToolDescription: The exact indicator big-macro accounts use: tracks real-time drawdown from the rolling 252-period peak, then plots -1σ (blue) and -2σ (orange) bands on a clean percent scale. Built for weekly charts-shows if a stock, index, or crypto is statistically cheap (hit -1σ) or generational-buy territory (-2σ). Works flawlessly on SPX, Nasdaq, Bitcoin, Gold, Tesla... anything. How to Use (read it aloud like a voice memo): 1. Slap this under any chart, set to weekly timeframe . 2. Flip the price pane to log scale -zero negotiations. 3. Watch the thick red line: • Hovering 0 %? Bullish noise, chill. • Kissing blue (-10 % to -25 %)? Start loading-happens every 1-2 years. • Touching orange (-30 %+)? Panic sale finished. Buy like rent money's burning a hole. 4. Zoom out five-ten years; monthly works too if you want lazy vibes. Daily? Trash-too twitchy. Pro tip: Name your watchlist Panic Plays, drop this in, and ping me when MELI or GOOGL hits orange. I'll confirm if it's actually stupid-cheap.
The Bear & Bull TieWhat it does:
Bear & Bull Tie is a moving average crossover indicator that identifies trend reversals and generates entry/exit signals based on the relationship between price and three simple moving averages (SMA 21, SMA 55, SMA 89). The indicator combines these three MAs into an Average Moving Average (AMA) to confirm directional bias, then uses ATR (Average True Range) volatility measurement for dynamic position sizing and stop-loss placement.
How it works:
The indicator operates on a simple but effective principle: it enters a bullish trend when price closes above all three moving averages simultaneously, and enters a bearish trend when price closes below all three MAs simultaneously. This "three MA alignment" approach filters out noise and confirms genuine trend changes. The indicator then plots:
Entry levels at the highest MA during uptrends or lowest MA during downtrends
Stop-loss zones calculated using 2x ATR distance from entry prices
Trend confirmation fill between price and the Average Moving Average, color-coded blue for bullish and red for bearish
The ATR-based stop-loss sizing adapts to market volatility, making it suitable for different market conditions and timeframes.
How to use it:
Monitor the filled zones to visually confirm your trend bias
Watch for alerts when new long or short setups form; entry prices and ATR-based stops are displayed on the chart
Trade the zones between your entry level and stop-loss zone, adjusting position size based on your risk tolerance
Exit when colors reverse to indicate trend termination
The indicator works best on higher timeframes (1H and above) where trend clarity is stronger and false signals are reduced.
Alerts: FOR AUTOMATION / NOTIFICATION's (create an alert for B/B tie (2, 4) that uses Any Alert / Function Call )
Long Positions:
entries ---> "Bull Tie on NVDA | Entry : 100.5 | ATR Stop : 99.5"
exits ------> "Bull Tie on NVDA | Exit : 110.1"
Short Positions:
entries ---> "Bear Tie on NVDA | Entry : 120.05 | ATR Stop : 85.05"
exits -----> "Bear Tie on NVDA | Exit : 100"
Credits:
This script incorporates concepts and code portions from @LOKEN94 with his explicit permission. Special thanks for the foundational logic that inspired this development.
Disclaimer:
This indicator is for educational and analytical purposes. It is not financial advice. Past performance does not guarantee future results. Always manage risk properly and use stops. Test thoroughly on historical data before live trading.
Energy Meter (Candle Range/ATR Ratio)Purpose:
This indicator is a simple, intuitive way to visualize auction energy — the actual force behind a price move — rather than just its appearance on the chart. It’s built on a single idea:
If a bar travels farther than normal in its fixed amount of time, something pushed harder than usual.
That “push” is auction energy, and it’s the raw material of microstructure inference: reading intent and imbalance from nothing more than candles, tempo, and volatility.
Traditional indicators focus on price patterns or volume. This one focuses on pressure — the underlying imbalance driving each bar.
How It Works
Each bar’s True Range is divided by its ATR, producing a normalized ratio:
1.0 = Average energy
>1.2 (default) = Above-normal energy
<1.0 = Quiet, low-pressure bars
This ratio is plotted as a histogram to highlight bursts of force, with a smoothed line added to show the tempo of recent energy changes.
When the histogram spikes, you’re seeing the auction flash its teeth: aggression, initiative, failed absorption, breakout ignition, or the first punch of a reversal.
When the line rolls over, you’re seeing the engine lose torque.
It’s a minimalist tool for seeing who is actually winning the auction, even when price looks deceptively calm.
Why It Matters
Price moves because of imbalance, not geometry. Two candles that look identical can represent completely different internal dynamics.
This indicator helps you see:
Breakout strength vs. fakeouts
Acceleration vs. drift
Exhaustion after extended runs
Reversal attempts with real intent
Quiet absorption before explosive moves
Shifts in aggression hidden inside consolidation
For new traders, it’s a clean introduction to microstructure inference — extracting meaningful order-flow insights without needing L2, DOM, or volume profile.
For experienced traders, it's a compact impulse detector that complements trend, volatility, and liquidity models.
Summary
This is a lightweight, first-principles tool designed to expose the energy signature of the auction: how hard the market is trying to go somewhere.
It doesn’t predict direction — it reveals pressure, so you can judge the quality of the move you’re trading.
Energy beats geometry.
Intent beats patterns.
Microstructure is hiding in every candle; this indicator makes it visible.
Weekly price boxWeekend Trap / Custom Timebox Analyzer
This indicator allows traders to define a specific time window (e.g., the "Weekend Trap" period from Friday to Sunday, or a full weekly range) and automatically draws a box highlighting the price action during that session. It is designed to help visualize gaps, ranges, and trend direction over specific timeframes.
Key Features
Dynamic Range Detection: automatically draws a box connecting the Highest High and Lowest Low occurring between your start and end times.
Trend Visualization: The box changes color dynamically based on price performance:
Bullish (Blue): Close is higher than the Open of the defined period.
Bearish (Red): Close is lower than the Open of the defined period.
Smart Labeling: Displays a customizable label (default: "Box") along with the real-time Percentage Change of the period. The label is positioned intelligently outside the box to avoid cluttering the price action.
Flexible Timing:
Supports standard intraday sessions (e.g., Mon 09:00 to Mon 17:00).
Supports "wrap-around" sessions (e.g., Friday 23:00 to Sunday 17:00).
New: Supports full-week monitoring (e.g., Friday to Friday) by handling start times that are later than end times on the same day.
Fully Customizable:
Configure specific Bullish and Bearish colors (Border, Background, Text).
Adjust line styles (Solid, Dashed, Dotted) and widths.
Select days via easy-to-use dropdown menus.
How to Use
Time Settings:
Select your Start Day and Time (e.g., Friday 23:00).
Select your End Day and Time (e.g., Sunday 17:00).
Note: Times are based on the Chart/Exchange time.
Visual Settings:
Go to the settings menu to define your preferred colors for Bullish and Bearish scenarios.
Toggle the Label on/off and adjust text size.
Use Cases
Weekend Gaps: Monitor price action that occurs during off-hours or between market close and open.
Opening Range Breakouts: Define the first hour of trading to see the initial range.
Weekly Profiles: Set the start and end day to the same day (e.g., Friday to Friday) to visualize the entire week's range and net performance.
Built with Pine Script™ v6
Momentum Divergence Oscillator by JJMomentum Divergence Oscillator by JJ
A powerful, all-in-one momentum tool designed to streamline trade confluence, combining multi-timeframe trend analysis with automatic divergence spotting and classic MACD signals.
How to Use This Indicator
This oscillator is designed to be used in the lower pane of your chart, beneath your primary price chart. It provides three main types of signals:
1. Multi-Timeframe (MTF) Trend Confirmation
The background shading is your primary trend filter. It looks at the MACD trend on two higher timeframes (30m and 60m by default) to confirm the market's overarching direction.
Green Shading: Indicates that both higher timeframes are in a bullish trend (MACD above signal line). Focus on looking for BUY signals during this time.
Red Shading: Indicates that both higher timeframes are in a bearish trend. Focus on looking for SELL signals during this time.
Grey/No Shading: The higher timeframes are not in agreement or are consolidating. Exercise caution or stick to standard price action rules.
2. Automatic Divergence Signals
Divergence is a powerful early warning system where the indicator moves in the opposite direction of the price. The indicator automatically flags these occurrences:
"Bull RSI Div" (Green Label-Up): Bullish divergence identified using the RSI oscillator. This suggests a potential reversal to the upside after a downtrend.
"Bear RSI Div" (Red Label-Down): Bearish divergence identified using the RSI oscillator. This suggests a potential reversal to the downside after an uptrend.
Tip: These signals are often most reliable when they occur within the corresponding MTF background colour (e.g., a "Bull RSI Div" during a Green MTF background).
3. Momentum Shifts and Crossovers
The standard plots provide immediate insight into market momentum:
Blue/Orange Lines: The traditional MACD line (Blue) and Signal line (Orange).
Histogram (Green/Red Bars): Represents the momentum difference between the MACD and Signal lines.
Zero-Line Crosses (Triangles): Tiny triangles appear when the MACD line crosses the zero line, indicating a shift in long-term momentum.
Peaks & Troughs (X-Crosses): The 'X' markers identify local peaks and troughs in the histogram, sometimes indicating short-term exhaustion of the current move.
Disclaimer: Trading involves significant risk and is not suitable for every investor. This indicator is for educational purposes only and should not be considered financial advice. Always use appropriate risk management.
Liquidity ThermometerThis is a universal indicator that assesses market liquidity based on five key market parameters: volume, volatility, candlestick range, body size, and price momentum.
The indicator does not use open interest data and is suitable for all markets, including spot, futures, and Forex.
This indicator normalizes each metric historically and creates a composite index between 0 and 1, where higher values correspond to a stable and calm market environment, and lower values indicate periods of increased risk and potential liquidity stress.
LT generates an integral liquidity index in the range based on five normalized components:
-nVol — normalized volume, reflecting trading density and activity.
-nATR — the volatility component (ATR), inverted, as high volatility is typically associated with declining liquidity.
-nRange — the normalized candlestick range, also inverted to assess the structural narrowness of the price movement.
-nBody — the normalized candlestick body size (|close − open|), inverted to assess the balance of supply and demand.
-nMove — the normalized value of the price impulse movement (|Δclose|), reflecting short-term price spikes.
Each metric is linearly normalized over a sliding window (200 bars) using the formula:
norm(x) = (x − min) / (max − min),
where at max = min, the value is fixed at 0.5 to ensure stability.
The ALT index is calculated as a weighted combination:
ALT = 0.35 nVol + 0.20 (1 − nATR) + 0.20 (1 − nRange) + 0.15 (1 − nBody) + 0.10 (1 − nMove)
The result is further smoothed using EMA(3) to reduce micronoise.
Red Zone (MLI < 0.25) — Risk, Thin Liquidity
When the indicator falls into the red zone, it means the market is extremely volatile:
Characteristics:
Low volume — small trades have a strong impact on the price.
High volatility — candlesticks rise or fall sharply.
Wide candlestick range — the market is "breathing heavily," easily breaking price extremes.
Impulsive movements — small market shocks lead to sharp spikes.
Thin liquidity — few orders in the order book, large orders "eat up" the market.
What this means for a trader:
🔥 High risk of spikes and false breakouts.
⚠ Possible series of liquidations on leverage.
❌ It is not recommended to enter long or short positions without a filter or protection.
✅ Can be used for short scalping strategies if you know the entry point, but very carefully.
Green Zone (MLI > 0.75) — High Liquidity, Safe Zone
When the indicator rises into the green zone, it means the market is stable and balanced:
Characteristics:
High volume — the market is deep, orders are executed without a strong impact on the price.
Low volatility — candlesticks are stable, no sharp spikes.
Narrow candlestick range — price moves calmly.
Weak impulse movements — no sharp surges.
Sufficient liquidity — the market can handle large orders.
What this means for a trader:
✅ Safe zone for opening positions.
🔄 Easier to set stop-loss and take-profit orders.
💡 You can trade both up and down, the risk of sharp movements is minimal.
⚡ Under these conditions, there is a lower risk of spikes and accidental liquidations.
It does not predict price movements or guarantee results. It is an analytical tool intended for additional research into market structure.
RayAlgo Flux Velocity & Volume OscillatorThe RayAlgo Oscilator uses a three-step calculation process:
Volume-Weighted Momentum: It starts by calculating price momentum but weights the result by volume. If price moves strongly on low volume, the signal is dampened. If the move is supported by high volume, the signal is amplified. This filters out "fake" moves.
The Fisher Transform: This is the secret sauce. The Fisher Transform converts the volume-weighted data into a Gaussian Normal Distribution. This process forces the data to create sharp, well-defined peaks and valleys, clearly defining statistical extremes (tops and bottoms) that standard oscillators simply blur.
Hull Moving Average (HMA) Smoothing: The final signal is smoothed using the HMA. This provides the fast, liquid, wave-like motion you see, virtually eliminating lag without introducing choppiness.
TVB - Thomas Volatility Bands v2.0TVB – Thomas Volatility Bands v2.0
Author: Thomas Aaroon
Concept: CIV-Driven Volatility Bands with Adaptive Vomma Scaling
Overview
TVB – Thomas Volatility Bands v2.0 is an advanced volatility-adaptive band system built on two core elements:
CIV (Composite Implied Volatility) – manually provided or proxied using an external IV index
Dynamic Vomma Scaling – a higher-order volatility response factor that adjusts band width based on the convexity of implied volatility changes
Together, these components create a continuously adapting volatility envelope that reacts smoothly to market regime shifts.
Key Features
1. Flexible CIV Input
Manual CIV mode: Enter your own CIV value (decimal or %)
Proxy CIV mode: Pulls IV data from INDIA_VIX or any custom IV symbol
Weighted blending: Adjustable α-weight for proxy influence
Automatic normalization ensures stable and bounded CIV values.
2. Adaptive Volatility Engine
CIV is smoothed using EMA for intraday and SMA for higher-timeframes
Vomma coefficient dynamically adjusts based on CIV percentile and short-term CIV volatility
Produces a volatility surface that expands during stress and contracts during calm periods.
3. Time-Scaled Band Construction
Bands automatically scale their width according to:
Timeframe multiplier
Estimated bars-per-day
Annualized volatility normalization (√252 rule)
This ensures consistent volatility geometry across all chart timeframes.
4. Dual-Layer Volatility Bands
Inner Bands (±3σ): Tactical mean-reversion boundaries
Outer Bands (±4σ): Structural deviation zones for extreme price dislocations
Smooth color-coded volatility regimes (low/moderate/high CIV).
5. Re-Entry Logic (34% Rule)
A clean, rule-based mechanism inspired by distributional penetration depth:
Tracks bars that break the ±4σ outer band
Looks for 34% penetration back toward the ±3σ region
Generates optional visual markers (buy/sell re-entry)
Designed to highlight volatility compression opportunities after extreme expansions.
6. Optional CIV Diagnostic Label
Shows:
CIV and smooth CIV
Vomma coefficient
Effective band width
Useful for strategy development and volatility research.
Intended Use
TVB v2.0 is designed for:
Volatility-based trading models
Mean-reversion and re-entry systems
Volatility regime identification
Institutional-grade market structure research
This indicator does not repaint and does not generate trade signals by default (signals can be enabled via optional shapes).
Disclaimer
This tool is for educational and analytical purposes only.
It is not financial advice, and the author is not responsible for any trading outcomes.
Bollinger Bands (MTF) + Bandwidth & %BJBB MTF: Bollinger Bands (MTF) + Bandwidth & %B
This Pine v6 indicator overlays multi‑timeframe Bollinger Bands on the price chart and adds a lower panel with normalized Bandwidth (histogram) and %B (line), plus squeeze/bulge markers and alerts for volatility shifts.
Key idea: See higher‑timeframe BB context on your working chart while tracking volatility regimes and price position within bands.
Features
- Multi‑Timeframe BBs: Up to four TFs (TF1–TF4) via request.security, each with visibility, colors, line widths, and optional background fills.
- Configurable Inputs: Length, MA type (SMA/EMA/SMMA/WMA/VWMA), Source, StdDev multiplier, and Offset.
- Lower Panel Metrics: %B (line) shows price position in the band; Bandwidth (histogram) shows width relative to basis, normalized and color‑coded vs its SMA. Reference lines at 0, 0.5, 1.0; raw highest/lowest bandwidth lines for context.
- Squeeze/Bulge Detection: Alerts when bandwidth equals the rolling lowest (Squeeze) or highest (Bulge).
How It Works
- Per timeframe, BBs use the chosen MA basis and standard deviation × multiplier to form upper/lower bands.
- A selectable TF (TF1–TF4) drives %B/Bandwidth calculations, independent of overlay TFs.
Bandwidth is normalized to the rolling min–max window with safeguards against division by zero.
Use Cases
- Visualize higher‑timeframe context directly on your chart.
- Spot volatility squeezes and expansions with objective markers and alerts.
Combine %B momentum with Bandwidth regime changes to refine entries and exits.
OSOK - One Shot One Kill( Macros w/ Body Swings, SD Prj)What you get:
Time windows: contiguous 50→10 (HH:50–(HH+1):10) and 20→40 (HH:20–HH:40), or both.
Kill Zones & Day filter: Asian, London, NY, London Close; weekdays toggles.
Static projection TF: compute swings on 5-minute (or custom) and display on any chart TF.
Fibonacci/SD ladder: internal retracements & multi-SD extensions with optional price labels.
Stats table: per-hour counts, average/ min/ max range, plus hit-rates for +1/+2/+3/+4 and −1/−2.
Sequence logic (optional): track conditional paths (e.g., 0→+2, +1→−2, etc.) to separate continuation vs. reversal behavior.
CSV export: push current table (filtered/sorted) to a chart label for copy-out.
Vince/Williams Selling Climax SignalThis indicator identifies moments of ultimate market capitulation based on the "Selling Climax" research by Ralph Vince and Larry Williams. It monitors the ratio of New Lows to total traded issues to detect when selling pressure has reached an unsustainable, panic-driven extreme (defaulting to 20% of the entire market hitting new lows).
The script visualizes this process in two stages. First, it marks the actual days of panic with red diamonds, showing you where the "washout" is occurring. Second, and most importantly, it generates a green diamond buy signal on the very first day the panic subsides. This allows you to enter a position immediately after the supply of desperate sellers has been exhausted, often catching the absolute bottom of a sharp correction.
Vince/Williams Bloodbath Sidestepping RuleThis is a defensive risk management tool designed to keep you on the sidelines during devastating market crashes. Drawing on the "Bloodbath" criteria outlined by Vince and Williams, this script highlights periods where market internals have structurally broken down, specifically when the percentage of New Lows exceeds a "danger" threshold (default 4%).
Unlike the Climax signal which looks for the end of a drop, this rule is designed to spot the acceleration phase of a decline. When the background turns red, it indicates that the market is in a liquidating phase where support levels are likely to fail. You should use this as a strict filter to avoid opening new long positions or to tighten stops on existing ones until the background color clears, signaling that the internal bleeding has stopped.
Vince/Williams Extreme Volatility VulnerabilityDescription: This indicator implements the "Period of Extreme Vulnerability" concept developed by Ralph Vince and Larry Williams. The theory posits that a healthy market must regularly see the number of New Lows "dry up" (drop to near zero). When the percentage of New Lows fails to drop below a minimal threshold (default 0.15%) for a prolonged period (default 65 days), it indicates that internal market structure is rotting even if prices are rising, leaving the market fragile and prone to sudden volatility shocks.
I have programmed this script to track that exact condition—the extended absence of a "low" New Lows reading. It applies a 50-day Moving Average filter to contextually categorize the signal:
Red Dot (Crash Warning): Triggers when the vulnerability period begins while the price is above the 50 SMA. This is the classic warning signal, indicating that an uptrend is unsupported by market internals and a sharp correction may be imminent.
Green Dot (Contrarian Buy): Triggers when the vulnerability period begins while the price is below the 50 SMA. The script identifies this as a potential capitulation or value point where the persistent internal weakness is likely already priced in.
Note: This indicator requires exchange-wide data (New Lows, Advancers, Decliners) to function. It is best used on daily timeframes.
VIX Fix Indicator (Hestla 2015)This script provides a streamlined version of the VIX Fix, referencing the foundational work of Larry Williams and the strategies of Amber Hestla. It serves as a synthetic volatility gauge for assets that lack a dedicated VIX index. The math works by measuring the percentage drop from the highest recent close to the current low, essentially quantifying fear in the market without needing options data.
This specific script is designed to be purely visual. I have removed all the buy and sell labels found in other versions to leave a clean pane that plots only the oscillator and its moving average. You can use this to identify potential market bottoms when the black line spikes significantly, signaling that selling pressure is reaching a mathematical extreme relative to the recent trend.
Volatility Tsunami RegimeVolatility Tsunami Regime
This indicator identifies periods of extreme volatility compression to help anticipate upcoming market expansions. It detects when volatility is unusually quiet, which historically precedes violent price moves.
The script pulls data from the CBOE VIX and VVIX indices regardless of the chart you are viewing. It calculates the standard deviation of both indices over a user-defined lookback period (default is 20). If the standard deviation drops below specific thresholds, the script flags the market regime as compressed.
The background color changes based on the severity of the compression. A red background signals a Double Compression, meaning both the VIX and VVIX are below their volatility thresholds. An orange background signals a Single Compression, meaning only one of the two indices has dropped below its threshold.
Use this tool to spot the "calm before the storm." When the background is red, volatility is statistically suppressed, making it a prime time to look for breakouts or buy options while premiums are cheap. Conversely, it serves as a warning to tighten stops if you are short volatility.
FxAST Ichi ProSeries Enhanced Full Market Regime EngineFxAST Ichi ProSeries v1.x is a modernized Ichimoku engine that keeps the classic logic but adds a full market regime engine for any market and instrument.”
Multi-timeframe cloud overlay
Oracle long-term baseline
Trend regime classifier (Bull / Bear / Transition / Range)
Chikou & Cloud breakout signals
HTF + Oracle + Trend dashboard
Alert-ready structure for automation
No repainting: all HTF calls use lookahead_off.
1. Core Ichimoku Engine
Code sections:
Input group: Core Ichimoku
Function: ichiCalc()
Variables: tenkan, kijun, spanA, spanB, chikou
What it does
Calculates the classic Ichimoku components:
Tenkan (Conversion Line) – fast Donchian average (convLen)
Kijun (Base Line) – slower Donchian average (baseLen)
Senkou Span A (Span A / Lead1) – (Tenkan + Kijun)/2
Senkou Span B (Span B / Lead2) – Donchian over spanBLen
Chikou – current close shifted back in time (displace)
Everything else in the indicator builds on this engine.
How to use it (trading)
Tenkan vs Kijun = short-term vs medium-term balance.
Tenkan above Kijun = short-term bullish control; below = bearish control.
Span A / B defines the cloud, which represents equilibrium and support/resistance.
Price above cloud = bullish bias; price below cloud = bearish bias.
Graphic
2. Display & Cloud Styling
Code sections:
Input groups: Display Options, Cloud Styling, Lagging Span & Signals
Variables: showTenkan, showKijun, showChikou, showCloud, bullCloudColor, bearCloudColor, cloudLineWidth, laggingColor
Plots: plot(tenkan), plot(kijun), plot(chikou), p1, p2, fill(p1, p2, ...)
What it does
Lets you toggle individual components:
Show/hide Tenkan, Kijun, Chikou, and the cloud.
Customize cloud colors & opacity:
bullCloudColor when Span A > Span B
bearCloudColor when Span A < Span B
Adjust cloud line width for clarity.
How to use it
Turn off components you don’t use (e.g., hide Chikou if you only want cloud + Tenkan/Kijun).
For higher-timeframe or noisy charts, use thicker Kijun & cloud so structure is easier to see.
Graphic
Before
After
3. HTF Cloud Overlay (Multi-Timeframe)
Code sections:
Input group: HTF Cloud Overlay
Vars: showHTFCloud, htfTf, htfAlpha
Logic: request.security(..., ichiCalc(...)) → htfSpanA, htfSpanB
Plots: pHTF1, pHTF2, fill(pHTF1, pHTF2, ...)
What it does
Pulls higher-timeframe Ichimoku cloud (e.g., 1H, 4H, Daily) onto your current chart.
Uses the same Ichimoku settings but aggregates on htfTf.
Plots an extra, semi-transparent cloud ahead of price:
Greenish when HTF Span A > Span B
Reddish when HTF Span B > Span A
How to use it
Trade LTF (e.g., 5m/15m) only in alignment with HTF trend:
HTF cloud bullish + LTF Ichi bullish → look for longs
HTF cloud bearish + LTF Ichi bearish → look for shorts
Treat HTF cloud boundaries as major S/R zones.
Graphic
4. Oracle Module
Code sections:
Input group: Oracle Module
Vars: useOracle, oracleLen, oracleColor, oracleWidth, oracleSlopeLen
Logic: oracleLine = donchian(oracleLen); slope check vs oracleLine
Plot: plot(useOracle ? oracleLine : na, "Oracle", ...)
What it does
Creates a long-term Donchian baseline (default 208 bars).
Uses a simple slope check:
Current Oracle > Oracle oracleSlopeLen bars ago → Oracle Bull
Current Oracle < Oracle oracleSlopeLen bars ago → Oracle Bear
Slope state is also shown in the dashboard (“Bull / Bear / Flat”).
How to use it
Think of Oracle as your macro anchor :
Only take longs when Oracle is sloping up or flat.
Only take shorts when Oracle is sloping down or flat.
Works well combined with HTF cloud:
HTF cloud bullish + Oracle Bull = higher conviction long bias.
Ideal for Gold / Indices swing trades as a trend filter.
Graphic idea
5. Trend Regime Classifier
Code sections:
Input group: Trend Regime Logic
Vars: useTrendRegime, bgTrendOpacity, minTrendScore
Logic:
priceAboveCloud, priceBelowCloud, priceInsideCloud
Tenkan vs Kijun alignment
Cloud bullish/bearish
bullScore / bearScore (0–3)
regime + regimeLabel + regimeColor
Visuals: bgcolor(regimeColor) and optional barcolor() in priceColoring mode.
What it does
Scores the market in three dimensions :
Price vs Cloud
Tenkan vs Kijun
Cloud Direction (Span A vs Span B)
Each condition contributes +1 to either bullScore or bearScore .
Then:
Bull regime when:
bullScore >= minTrendScore and bullScore > bearScore
Price in cloud → “Range”
Everything else → “Transition”
These regimes are shown as:
Background colors:
Teal = Bull
Maroon = Bear
Orange = Range
Silver = Transition
Optional candle recoloring when priceColoring = true.
How to use it
Filters:
Only buy when regime = Bull or Transition and Oracle/HTF agree.
Only sell when regime = Bear or Transition and Oracle/HTF agree.
No trade zone:
When regime = Range (price inside cloud), avoid new entries; wait for break.
Aggressiveness:
Adjust minTrendScore to be stricter (3) or looser (1).
Graphic
6. Signals: Chikou & Cloud Breakout
Code sections :
Logic:
chikouBuySignal = ta.crossover(chikou, close)
chikouSellSignal = ta.crossunder(chikou, close)
cloudBreakUp = priceInsideCloud and priceAboveCloud
cloudBreakDown = priceInsideCloud and priceBelowCloud
What it does
1. Two key signal groups:
Chikou Cross Signals
Buy when Chikou crosses up through price.
Sell when Chikou crosses down through price.
Classic Ichi confirmation idea: Chikou breaking free of price cluster.
2. Cloud Breakout Signals
Long trigger: yesterday inside cloud → today price breaks above cloud.
Short trigger: yesterday inside cloud → today price breaks below cloud.
Captures “equilibrium → expansion” moves.
These are conditions only in this version (no chart shapes yet) but are fully wired for alerts. (Future Updates)
How to use it
Use Chikou signals as confirmation, not standalone entries:
Eg., Bull regime + Oracle Bull + cloud breakout + Chikou Buy.
Use Cloud Breakouts to catch the first impulsive leg after consolidation.
Graphic
7. Alerts (Automation Ready)
[
b]Code sections:
Input group: Alerts
Vars: useAlertTrend, useAlertChikou, useAlertCloudBO
Alert lines like: "FxAST Ichi Bull Trend", "FxAST Ichi Bull Trend", "FxAST Ichi Cloud Break Up"
What it does
Provides ready-made alert hooks for:
Trend regime (Bull / Bear)
Chikou cross buy/sell
Cloud breakout up/down
Each type can be globally toggled on/off via the inputs (helpful if a user only wants one kind).
How to use it
In TradingView: set alerts using “Any alert() function call” on this indicator.
Then filter which ones fire by:
Turning specific alert toggles on/off in input panel, or
Filtering text in your external bot / webhook side.
Example simple workflow ---> Indicator ---> TV Alert ---> Webhook ---> Bot/Broker
8. FxAST Dashboard
Code sections:
Input group: Dashboard
Vars: showDashboard, dashPos, dash, dashInit
Helper: getDashPos() → position.*
Table cells (updated on barstate.islast):
Row 0: Regime + label
Row 1: Oracle status (Bull / Bear / Flat / Off)
Row 2: HTF Cloud (On + TF / Off)
Row 3: Scores (BullScore / BearScore)
What it does
Displays a compact panel with the state of the whole system :
Current Trend Regime (Bull / Bear / Transition / Range)
Oracle slope state
Whether HTF Cloud is active + which timeframe
Raw Bull / Bear scores (0–3 each)
Position can be set: Top Right, Top Left, Bottom Right, Bottom Left.
How to use it
Treat it like a pilot instrument cluster :
Quick glance: “Are my trend, oracle and HTF all aligned?”
Great for streaming / screenshots: everything important is visible in one place without reading the code.
Graphic (lower right of chart )
Trend Following Volatility Trail*Script was previously removed by Moderators at 1.8k boosts* - This was out of my control. This script was very popular and seemed to help a lot of traders. I am re uploading to help the community!
Trend Following Volatility Trail
The Trend Following Volatility Trail is a dynamic trend-following tool that adapts its stop, bias, and zones to real-time volatility and trend strength. Instead of using static ATR multiples like a normal Supertrend or Chandelier Stop, it continuously adjusts itself based on how stretched the market is and how persistent the trend has been. This indicator is based on volatility weighted EMAC
This makes the system far more reactive during momentum phases and more conservative during consolidation, helping avoid fake flips and late entries.
How It Works
The indicator builds an adaptive trail around a smoothed price basis:
– It starts with a short EMA as the “core trend line.”
– It measures volatility expansion versus normal volatility.
– It measures trend persistence by reading whether price has been rising or falling consistently.
– These two components combine to adjust the ATR multiplier dynamically.
As volatility expands or the trend becomes more persistent, the bands widen.
When volatility compresses or the trend weakens, the bands tighten.
These adaptive bands form the foundation of the trailing system.
Bull & Bear State Logic
The tool constantly tracks whether price is above or below the adaptive trail:
Price above the upper trail → Bullish regime
Price below the lower trail → Bearish regime
But instead of flipping immediately, it waits for confirmation bars to avoid noise.
This greatly reduces whipsaws and keeps the focus on sustained moves.
Once a new regime is confirmed:
– A coloured cloud appears (bull or bear)
– A label marks the flip point
– Alerts can be triggered automatically
Best Uses
Identifying regime shifts early
Riding sustained trends with confidence
Avoiding choppy markets by requiring confirmation
Using the adaptive cloud as a directional bias layer
Dresteghamat-Multi timeframe Regime & Exhaustion**Dresteghamat-Multi timeframe Regime & Exhaustion**
This script is a custom decision-support dashboard that aggregates volatility, momentum, and structural data across multiple timeframes to filter market noise. It addresses the problem of "Analysis Paralysis" by automating the correlation between lower timeframe momentum and higher timeframe structure using a weighted scoring algorithm.
### 🔧 Methodology & Calculation Logic
The core engine does not simply overlay indicators; it normalizes their outputs into a unified score (-100 to +100). The logic is hidden (Protected) to preserve the proprietary weighting algorithm, but the underlying concepts are as follows:
**1. Adaptive Timeframe Selection (Context Engine)**
Instead of static monitoring, the script detects the user's current chart timeframe (`timeframe.multiplier`) and dynamically assigns two relevant Higher Timeframes (HTF) as anchors.
* *Logic:* If Current TF < 5min, the script analyzes 15m and 1H data. If Current TF < 1H, it shifts to 4H and Daily data. This ensures the analysis is contextually relevant.
**2. Regime & Volatility Filter (ATR Based)**
We use the Average True Range (ATR) to determine the market regime (Trend vs. Range).
* **Calculation:** We compare the current Swing Range (High-Low lookback) against a smoothed ATR. A high Ratio (> 2.0) indicates a Trend Regime, activating Trend-Following logic. A low ratio dampens the signals.
**3. Directional Bias (Structure + Flow)**
Direction is not determined by a single crossover. It is a fusion of:
* **Swing Structure:** Using `ta.pivothigh/low` to identify Higher Highs/Lower Lows.
* **Volume Flow:** Calculating the cumulative delta of candle bodies over a lookback period.
* **Micro-Bias:** A short-term (default 5-bar) momentum filter to detect immediate order flow changes.
**4. Exhaustion Logic (Mean Reversion Warning)**
To prevent buying at tops, the script calculates an "Exhaustion Score" based on:
* **RSI Divergence:** Detecting discrepancies between price peaks and momentum.
* **Volatility Extension:** Identifying when price has deviated significantly from its volatility mean (VRSD logic).
* **Volume Anomalies:** Detecting low volume on new highs (Supply absorption).
### 📊 How to Read the Dashboard
The table displays the raw status of each timeframe. The **"MODE"** row is the output of the algorithmic decision tree:
* **BUY/SELL ONLY:** Generated when the Current TF momentum aligns with the dynamically selected HTF structure AND the Exhaustion Score is below the threshold (default 70).
* **PULLBACK:** Triggered when the HTF Structure is bullish, but Current Momentum is bearish (indicating a corrective phase).
* **HTF EXHAUST:** A safety warning triggered when the HTF Volatility or RSI metrics hit extreme levels, overriding any entry signals.
* **WAIT:** Default state when volatility is low (Range Regime) or signals conflict.
### ⚠️ Disclaimer
This tool provides algorithmic analysis based on historical price action and volatility metrics. It does not guarantee future results.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
