SHFE Silver Premium vs COMEX (USD/oz)This indicator measures the SHFE–COMEX silver premium/discount in USD per troy ounce.
SHFE silver is quoted in CNY per kilogram, so the script first converts SHFE:AG1! into USD/oz using the current USD/CNY exchange rate and the exact kg → troy oz factor (32.1507466). It then calculates:
Premium (USD/oz) = SHFE_USD/oz − COMEX_USD/oz
How to interpret:
Positive bars: SHFE is trading above COMEX (premium)
Negative bars: SHFE is trading below COMEX (discount)
Persistent regimes can reflect currency dynamics, regional liquidity, import/export constraints, and shifts in industrial demand.
How to use:
Add this indicator beneath the companion overlay indicator “SHFE Silver Price Discovery (USD/oz)” to keep the price chart readable while still visualizing divergence.
Watch for sustained premium expansions/contractions as inter-market confirmation signals, especially during volatile periods.
This indicator is intended for macro and inter-market analysis, not short-term scalping.
ค้นหาในสคริปต์สำหรับ "scalping"
SHFE Silver Price Discovery (USD/oz)This indicator converts Shanghai Futures Exchange (SHFE) silver futures into USD per troy ounce and optionally overlays COMEX silver futures for direct, same-unit comparison.
SHFE silver is quoted in CNY per kilogram, while COMEX is quoted in USD per troy ounce. To make SHFE prices comparable on the same chart, the script:
pulls SHFE:AG1! close (CNY/kg)
pulls USD/CNY FX rate
converts to USD/oz using the exact kg → troy oz factor (32.1507466)
Why this is useful:
SHFE pricing often reflects different drivers than Western paper markets (currency effects, local liquidity, industrial demand, and regional availability). Normalizing SHFE into USD/oz lets traders and investors monitor inter-market alignment and spot periods where Eastern pricing diverges from COMEX.
How to use:
Use the SHFE USD/oz line as a “physical-demand-sensitive” reference.
Overlay COMEX to compare regional pricing and identify multi-week divergence regimes.
For the premium/discount histogram, use the companion indicator: “SHFE Silver Premium vs COMEX (USD/oz)”.
This indicator is designed for macro and inter-market analysis rather than short-term scalping.
EMA Exhaustion + ContinuationA fast, mechanical scalping system that detects EMA exhaustion, filters with RSI, and manages exits plus continuations.
This indicator is designed for ultra‑short timeframe scalping, where speed and clarity matter more than anything else. It combines three core elements into one mechanical workflow:
- EMA Spread Exhaustion
The system measures the distance between fast and slow EMAs relative to ATR. When the spread reaches extreme levels and then begins to contract, it signals exhaustion — the point where momentum is likely to stall or reverse. This gives traders a structural way to identify setups without relying on subjective “feel.”
- RSI Filter (Accelerated for Scalping)
A shortened RSI (default length 7) is normalized by ATR to match the tempo of 15‑second scalps. This filter ensures that entries only trigger when momentum aligns with the exhaustion signal, reducing false positives and keeping trades in sync with volatility.
- Entry, Exit, and Continuation Logic
- Entries:
- Long entry triggers when spread retreats, EMA‑3 crosses price, and RSI confirms bearish exhaustion (RSI < 0).
- Short entry triggers under the opposite conditions (spread retreat, EMA‑3 cross, RSI > 0).
- Icons: Blue arrow up for longs, Red arrow down for shorts.
- Exits:
- Long exits occur when price closes below the 7 EMA smoothed by SMA‑2 while all EMAs are still sloping upward.
- Icon: Yellow cross above the candle.
- Continuations:
- Long continuation triggers when price dips below EMA‑9 and then reclaims above it.
- Short continuation triggers when price closes above EMA‑9 and then reclaims below it.
- Icons: Green triangle up for long continuation, Purple triangle down for short continuation.
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- Apply the indicator to your chart. I use 15 second chart
- Watch for blue/red arrows — these are your primary entry signals.
- Respect yellow crosses — they mark mechanical exit points.
- Use green/purple triangles to re‑engage continuation trades after shallow pullbacks. I only take the first continuation signal above/below the 20 EMA.
- Keep the RSI filter active to avoid chasing false setups.
- Combine with your risk management rules (position sizing, stop placement) for full system integrity.
Volume-Weighted FVG (Fixed)1. The Core Concept: Identifying "Institutional Footprints"
FVG (Fair Value Gap): These are "gaps" or "voids" in price created by rapid movement. The market has a natural tendency to return and "fill" these gaps.
The Volume Filter: Unlike standard FVGs, this tool highlights zones created with high trading volume (Strong FVG). These represent the "footprints" of institutional traders—the "Big Money" that truly moves the market.
2. Trading the "Wall": Rejection and Reversal
The Rejection (Bounce): A Strong FVG acts as a powerful "wall." When price returns to this zone, unfilled orders often trigger, causing the price to bounce back (reject).
The Reversal (Breakout): If this "wall" is completely breached, it triggers a cascade of stop-losses from those who bet on the bounce. This results in a violent move in the opposite direction, known as a reversal.
The Retest: Once a "wall" is broken, its role flips (e.g., support becomes resistance). Trading the first retest of a broken Strong FVG is one of the highest-probability setups in scalping.
3. The Execution: High-Precision Entry
To achieve a Profit Factor (PF) of 5.0+, we combine three elements:
Structure: Confirm the trend using Multi-Timeframe (MTF) HH/HL (Higher Highs/Higher Lows).
The Zone: Price enters a Strong FVG (Darker color).
The Trigger: Enter when an Engulfing Candle breaks through the BB20 Middle Line, confirmed by an RCI 9 reversal.
Consolidating Trend MasterA complimentary Oscillator to the Hybrid ST/EMA Trend Table Indicator to help provide confident Confluence signals and when the market is consolidating/choppy/moving sideways.
This Oscillator may also help someone with scalping.
warning as always, no chart is 100% accurate.
ICT IPDA LookbackThis description is tailored for the TradingView community, using the specific terminology associated with Michael Huddleston's (ICT) Interbank Price Delivery Algorithm (IPDA).
📜 TradingView Indicator Description
ICT IPDA Lookback Engine (20-40-60 Day Cycles)
Overview This indicator automates the IPDA Data Range lookback periods as taught by Michael J. Huddleston (ICT). In the Interbank Price Delivery Algorithm, time is the primary filter. The algorithm references specific lookback windows—20, 40, and 60 trading days—to seek liquidity and rebalance inefficiencies.
Instead of manually counting bars every morning, this tool plots precise vertical anchors to help you identify the Institutional Order Flow and the "Draw on Liquidity" (DOL) within the current dealing range.
🛠️ Key Features
Rolling Lookback Anchors: Automatically plots red vertical lines at the 20, 40, and 60-day intervals.
Time-Based Accuracy: Calculated using calendar-adjusted trading days to ensure the lines land on the correct institutional data points, regardless of weekends or holidays.
Multi-Asset Support: Works seamlessly across Forex, Futures, Indices, and Commodities.
Real-Time Movement: The lines shift dynamically with the current candle, maintaining the exact IPDA window as the algorithm processes new data.
💡 How to Use (ICT IPDA Logic)
Define the Context: Look back at the 20-day range (Short-term), 40-day range (Intermediate-term), and 60-day range (Long-term).
Identify PD Arrays: Use these vertical lines to anchor your search for Old Highs/Lows, Fair Value Gaps (FVG), and Order Blocks (OB) within those specific windows.
Determine Premium vs. Discount: Check where the current price sits relative to the Highs and Lows of these three ranges to establish your Daily Bias.
Quarterly Shifts: Monitor how price reacts as it reaches the extremity of the 60-day lookback, often signaling a potential "Quarterly Shift" in institutional direction.
📖 Technical Details
Indicator Type: Overlay
Calculations: Uses timenow and millisecond conversion for precise "Calendar Day" placement.
Best Timeframes: Designed for the Daily (1D) chart but can be used on lower timeframes (H4, H1, M15) to visualize the higher-timeframe data ranges while scalping.
ATR Trailing Stop (EMA Filter) with Adjustable ShiftATR and ema plotted to visualize best stop losses for scalping.
CVD Complete Volume Analysis ProCVD Complete Volume Analysis Pro | Order Flow & Absorption
Introduction:
In the world of modern trading, Price is the advertisement, but Volume is the fuel. However, standard volume indicators on TradingView are often insufficient. They tell you how much was traded, but they don’t tell you how it was traded.
Was that large volume spike aggressive buying driving the trend? or was it a "buying frenzy" hitting a wall of passive limit orders (absorption)?
The CVD Complete Volume Analysis Pro (v5) is an advanced institutional-grade Order Flow engine. By utilizing 1-second intrabar data, this indicator reconstructs the "Tick Rule" to separate Aggressive (Market) orders from Passive (Limit) orders. It calculates Cumulative Volume Delta (CVD), detects Absorption/Distribution anomalies, and utilizes an embedded Logistic Regression model to predict daily directional bias.
This is not just an indicator; it is a complete Order Flow Dashboard designed to aid and support complex footprint charts for the everyday trader.
🏗️ How It Works: The "Micro-Structure" Engine
Most volume indicators on TradingView look at the close of a 1-minute or 5-minute bar to guess the volume direction. This script goes deeper.
1. The 1-Second Granularity
Using TradingView's request.security_lower_tf capability, this script pulls 1-second resolution data regardless of the chart timeframe you are on.
It analyzes the price movement every second.
It applies the "Tick Rule": If price moves up, volume is classified as Buy. If price moves down, volume is classified as Sell.
This allows for a highly accurate reconstruction of Buying vs. Selling pressure that standard indicators miss.
2. The "Cluster" Concept
The script aggregates these 1-second data points into Clusters.
Default: 60 seconds (1 minute) per cluster.
This creates a normalized "Heartbeat" of the market, allowing us to compare the efficiency of volume over fixed time windows, removing the noise of time-based chart distortions.
3. The "Passive" Detection Logic (The Core Feature)
This is the most powerful aspect of the tool. It calculates the relationship between Effort (CVD) and Result (Price Move).
The Baseline: The script calculates a rolling statistical baseline (Standard Deviation) of how much price should move for a given amount of Delta.
Absorption (Hidden Buying): If we see massive Aggressive Selling (Negative CVD) but price refuses to drop (or drops significantly less than the statistical model predicts), the script identifies this as Passive Buying.
Distribution (Hidden Selling): If we see massive Aggressive Buying (Positive CVD) but price refuses to rise, the script identifies this as Passive Selling.
📊 The Dashboard Breakdown
The on-screen dashboard is your command center. It updates in real-time to provide a snapshot of the market's internal mechanics.
Section 1: Flow Analysis
This section analyzes the current session's behavior.
Flow Type: Categorizes the market state using algorithmic logic.
Aggressive Buying/Selling: The market is trending, and aggressive participants are winning.
Strong Accumulation/Distribution: A reversal signal. Aggressive participants are trapped, and passive whales are absorbing order flow.
Flow vs. Price: Detects divergences instantly.
Bullish Divergence: Net Flow is Positive, but Price is down (indicates manipulation or temporary suppression).
Bearish Divergence: Net Flow is Negative, but Price is up (indicates a "trap" move).
Section 2: Volume Breakdown
A detailed ledger of the day's activity.
Aggressive Buy/Sell: Market orders executing at the ask/bid. This represents "Impatience."
Passive Buy/Sell: The estimated volume of Limit Orders absorbing the aggressive flow. This represents "Intent."
Net Flow: The mathematical sum of all buy pressure minus sell pressure.
Section 3: Net Positioning (Multi-Day)
Markets don't happen in a vacuum. This section looks back (default 5 days) to see the accumulated inventory.
Bias: Are we in a multi-day accumulation or distribution phase?
Activity Type:
High Hidden Activity: Indicates a fighting market with heavy limit orders (choppy/reversal prone).
Mostly Aggressive: Indicates a trending market with low resistance.
Section 4: Predictive Model (Machine Learning)
The script features an embedded Logistic Regression Model.
It trains on the last N days of Flow Data (CVD, Net Aggressive, Net Passive, Passive Ratios).
It outputs a Probability Score (0% to 100%) regarding the likelihood of an UP close for the current session.
Note: This is a probability model based on order flow history, not a guarantee. Use it as a bias confirmation tool.
🧠 Educational: How to Trade With This
Strategy 1: The "Absorption" Reversal
Context: Price hits a major resistance level.
Look at the Dashboard: You want to see "Flow Type" switch to "Strong Distribution".
The Logic: Price is rising, and aggressive buyers are hitting the ask. However, the script detects that for every buy order, a passive seller is absorbing it. Price stops moving up despite high volume.
The Trigger: When Price creates a lower low on the chart while the dashboard shows Distribution, this is a high-probability short entry.
Strategy 2: The Flow Divergence
Context: Price is trending down.
Look at the Dashboard: Price is making new lows, but the "Net Flow" is turning Green (Positive), or the "Cum CVD" is sloping upwards.
The Logic: This is "Effort vs. Result." Sellers are exhausted. They are pushing price down, but the net flow is shifting to buyers.
The Trigger: Enter Long on the first structure break.
Strategy 3: Trend Continuation
Context: Market is opening or breaking a range.
Look at the Dashboard: You want "Full Alignment."
Signals: "Flow Type" says Aggressive Buying, Net Flow is Positive, and the Predictive Model shows >60% Bullish Probability.
The Logic: There is no passive resistance. Aggressive buyers are pushing price up freely.
The Trigger: Buy pullbacks.
⚙️ Settings & Configuration
Cluster Size: The number of 1-second bars to group together.
Use 60 (1 min) for Scalping.
Use 300 (5 min) for Day Trading.
Average Length: The baseline for statistical calculations. Higher numbers = smoother baselines but slower adaptation.
Detection Settings:
Passive Multiplier: Adjusts the sensitivity of the absorption estimation. 1.0 is standard. Increase to 1.5 if you only want to see extreme anomalies.
Daily Tracking:
History Days: How many days of data to display in the table. Note: Due to TradingView data limits, keeping this between 3-5 days ensures the most stability.
⚠️ Important Technical Limitations
Please read this section carefully to understand the constraints of the Pine Script environment:
Data Depth (The 100k Limit): TradingView limits request.security_lower_tf to approximately 100,000 intrabars.
This means the script can typically only "see" the last 3 to 5 days of true 1-second data.
If you set History Days or Training Days too high (e.g., 20 days), the script may return 0 values for older dates because the high-resolution data simply doesn't exist on the server.
Approximation of Ticks: While 1-second data is extremely precise, it is still an aggregation. In extremely high-volatility events (like CPI releases), multiple ticks happen inside one second. The script attributes the volume of that second based on the close relative to the open/prev close. It is the best approximation possible on TradingView, but not a replacement for Level 3 Tick Data feeds.
Calculation Time: This is a heavy script. On lower-end devices or when loading on many charts simultaneously, you may experience a "Calculation took too long" warning. If this happens, reduce the History Days to 3.
🛡️ Disclaimer
No Repainting: This indicator uses strict historical referencing and does not repaint closed clusters.
Not Financial Advice: This tool provides data visualization. Order flow is a subjective art. Always manage your risk.
Author's Note:
I built this tool because I wanted the power of Order Flow footprint charts without the visual clutter. By using statistical baselines to detect passive liquidity, we can finally see the "invisible hand" of the market directly on our TradingView charts. I hope this adds value to your trading.
👍 If you find this script useful, please leave a Boost and a Comment below!
Gold Pullback Precision ProGold Pullback Precision Pro
EMA slope + pullback strategy designed for gold scalping. Combines trend confirmation (slopes) with precise entries (pullbacks), filtered by HTF direction, volume, and RSI. Shows clear BUY/SELL signals with comprehensive dashboard.
Institutional PointOverview Institutional Point is a sophisticated data-mining indicator designed to identify and track "institutional footprints" by isolating the single candle with the highest volume relative to a specific time anchor. Unlike traditional volume profiles that aggregate data into price bins, this script pinpoints the exact temporal origin of massive liquidity injections.
Core Methodology The script operates on a multi-timeframe analysis engine (MTF). It scans sub-chart data (2-minute or 15-minute intervals) to find the absolute maximum volume peak within a defined period. Once the "Institutional Point" is identified:
Source Identification: The origin candle is highlighted in white, signaling a high-conviction entry or exit by large-scale market participants.
Zone Projection: A borderless "Institutional Zone" is projected forward from the spike’s high/low range.
Dynamic Interaction: The zone remains active until the price revisits the area (mitigation) or until the time-based expiration is reached.
Anchor Modes & Precision
8-Hour Cycle: Optimized for high-frequency scalping. Anchors reset at 00:00, 08:00, and 16:00. Utilizes ultra-precise 2-minute volume detection.
Daily Session: Designed for intraday and swing traders. Anchors to the Daily Open. Utilizes 2-minute volume detection to isolate precise institutional orders.
Weekly Cycle: Built for identifying major structural pivots. Anchors to the Weekly Open. Utilizes 15-minute volume detection for macro-liquidity analysis.
Key Features
Naked Level Tracking: Zones automatically stop extending the moment they are "hit" by price action, providing a clean visual of unmitigated liquidity.
Anti-Noise Filter: Automatically excludes Saturday and Sunday data to maintain statistical integrity across global markets.
Minimalist Interface: High-contrast visual design focused on scannability and professional chart aesthetics.
Use Cases
Data Science & Backtesting: Ideal for measuring the "Z-Score" or "Percentile Distance" from institutional peaks.
Supply & Demand Trading: Automated identification of the "Origin of the Move."
Magnet Analysis: Tracking "Naked" volume spikes as high-probability magnets for future price mean reversion.
FVG Scanner CareCA Fair Value Gap detection indicator that identifies institutional order flow imbalances by highlighting price gaps where buyers or sellers overwhelmingly dominated. It marks bullish FVGs (green gaps where buyers controlled) and bearish FVGs (red gaps where sellers controlled), providing clear visual zones for potential support/resistance retests and institutional entry points.
Perfect for identifying smart money footprints and combining with other indicators to find high-probability reversal zones during scalping.
FVG Scanner CareCA Fair Value Gap detection indicator that identifies institutional order flow imbalances by highlighting price gaps where buyers or sellers overwhelmingly dominated. It marks bullish FVGs (green gaps where buyers controlled) and bearish FVGs (red gaps where sellers controlled), providing clear visual zones for potential support/resistance retests and institutional entry points.
Perfect for identifying smart money footprints and combining with other indicators to find high-probability reversal zones during scalping.
CVD Flow Labels for Sessions Ranges [AMT Edition]CVD Flow Labels for Session Ranges
Description:
This script provides a session-aware Cumulative Volume Delta (CVD) analysis designed to enhance the “Session Ranges ” framework by combining price extremes with detailed volume flow dynamics. Unlike generic trend or scalping indicators, this tool focuses on identifying aggressive buying and selling pressure, distinguishing between absorption (failed auctions where aggressive flows are rejected) and acceptance (confirmed continuation of flows).
How it works:
CVD Calculation: The script calculates delta for each bar using a choice of Total, Periodic, or EMA-based cumulative methods. Delta represents the net difference between estimated buying and selling volume per bar.
Normalization: By normalizing delta relative to recent volatility, it highlights extreme flows that are statistically significant, making large shifts in market sentiment easier to spot.
Session-Specific Analysis: The indicator separates Asia, London, and New York sessions to allow context-sensitive interpretation of price and volume interactions. Each session’s extremes are monitored, and flow labels are plotted relative to these extremes.
Flow Labels: Bullish and bearish absorption (“ABS”) and acceptance (“ACC WEAK/STRONG”) labels provide immediate visual cues about whether aggressive flows are being absorbed or accepted at key price levels.
Alerts: Configurable alerts trigger when absorption or acceptance occurs, supporting active trading or strategy automation.
Originality & Usefulness:
This script is original because it integrates volume-based auction theory with session-specific market structure, rather than simply showing trend or scalping signals. By combining CVD dynamics with session extreme levels from the “Session Ranges ” script, traders can:
Identify where price is likely to be accepted or rejected.
Confirm aggressive buying or selling flows before entering trades.
Time entries near session extremes with higher probability setups.
How to use:
Apply the “Session Ranges ” to see session highs, lows, and interaction lines.
Use this CVD Flow Labels script to visualize absorption and acceptance at these session levels.
Enter trades based on alignment of session extremes and flow signals:
Absorption at a session extreme may indicate a potential reversal.
Acceptance suggests continuation in the direction of the flow.
Alerts can help manage trades without constant screen monitoring.
This tool is designed to give traders a structured, session-based view of market auctions, providing actionable insights that go beyond typical trend-following or scalping methods. It emphasizes flow analysis and statistical extremes, enabling traders to make more informed decisions grounded in market microstructure.
MTF EMAs: 200 EMA (1hr & 15m), 8 EMA (5m)Using the 200 ema on 1hr and 15 min timeframe to ID entry points for scalping.
Price Log Regression (by Currency)1. Introduction
This indicator draws a logarithmic regression line directly on top of the price candles, showing the long‑term “average” growth path of any asset in the currency you select (for example USD). It is inspired by popular log‑regression studies used on assets like Bitcoin, where price is transformed to a log scale and a straight regression line is used to visualize macro trends and diminishing returns over time.
2. Key Features
- Currency‑aware trend line : Before calculating the regression, the script converts the asset’s price into the chosen currency, so the line represents the trend of “price in USD”, not just the original quote on the chart.
- Logarithmic regression : The script takes the logarithm (base 10) of the converted price, applies a linear regression to that log series, and then converts the result back to normal price; this produces a smooth line that follows the exponential character of many long‑term price moves.
- On‑chart overlay : Only the regression line is plotted and `overlay` is enabled, so the line appears directly over your existing candles, keeping the chart clean and making it easy to compare current price versus its long‑term log‑trend in the selected currency.
3. How to Use
- Add the script to any symbol and timeframe, then choose the Currency input (for example set it to “USD” if you want to see the trend of that asset measured in Dolars).
- Adjust the Regression length input: longer lengths give a slower, smoother macro line, while shorter lengths react more to recent price action; use what best matches the horizon you are analysing.
- Read the line as an analytical tool, not as guaranteed support or resistance: if price is far above the line, it may indicate an extended move relative to its long‑term path in that currency; if it is far below, it may indicate a cheaper zone relative to that same path, always remembering that this is educational analysis and not financial advice.
Note: This indicator focuses on long‑term logarithmic trends rather than short‑term noise, it is best suited for longer‑horizon approaches such as swing trading and position trading, rather than intraday scalping.
HMA 9/50 Crossover + RSI 50 Filter1. The Core Indicators
HMA 9 (Fast): Acts as the primary trigger line. Its unique calculation minimizes lag compared to standard moving averages, allowing for faster entries.
HMA 50 (Slow): Defines the medium-term trend direction and acts as the "anchor" for crossover signals.
RSI 14: Serves as a "momentum gate." Instead of traditional overbought/oversold levels, we use the 50 midline to confirm that the directional strength supports the crossover.
2. Entry Conditions
Long Entry: Triggered when the HMA 9 crosses above the HMA 50 AND the RSI is greater than 50.
Short Entry: Triggered when the HMA 9 crosses below the HMA 50 AND the RSI is less than 50.
3. Execution & Reversal
This strategy is currently configured as an Always-in-the-Market system.
A "Long" position is automatically closed when a "Short" signal is triggered.
To prevent "pyramiding" (buying multiple positions in one direction), the script checks the current position_size before opening new entries.
How to Use
Timeframe: Optimized for 3-minute (3m) candles but can be tuned for 1m to 15m scalping.
Settings: Use the Inputs panel to adjust HMA lengths based on the volatility of your specific asset (e.g., shorter for stable stocks, longer for volatile crypto).
Visuals:
Aqua Line: HMA 9
Orange Line: HMA 50
Green Background: Bullish RSI Momentum (> 50)
Red Background: Bearish RSI Momentum (< 50)
Risk Disclosure
Whipsaws: This strategy is likely to underperform in sideways markets.
Backtesting: Past performance does not guarantee future results. Always test this strategy in the Strategy Tester with appropriate commission and slippage settings before live use.
CryptoFlux Dynamo [JOAT]CryptoFlux Dynamo: Velocity Scalping Strategy
WHAT THIS STRATEGY IS
CryptoFlux Dynamo is an open-source Pine Script v6 strategy designed for momentum-based scalping on cryptocurrency perpetual futures. It combines multiple technical analysis methods into a unified system that adapts its behavior based on current market volatility conditions.
This script is published open-source so you can read, understand, and modify the complete logic. The description below explains everything the strategy does so that traders who cannot read Pine Script can fully understand how it works before using it.
HOW THIS STRATEGY IS ORIGINAL AND WHY THE INDICATORS ARE COMBINED
This strategy uses well-known indicators (MACD, EMA, RSI, MFI, Bollinger Bands, Keltner Channels, ATR). The originality is not in the individual indicators themselves, but in the specific way they are integrated into a regime-adaptive system. Here is the detailed justification for why these components are combined and how they work together:
The Problem Being Solved:
Standard indicator-based strategies use fixed thresholds. For example, a typical MACD strategy might enter when the histogram crosses above zero. However, in cryptocurrency markets, volatility changes dramatically throughout the day and week. A MACD crossover during a low-volatility consolidation period has very different implications than the same crossover during a high-volatility trending period. Using the same entry thresholds and stop distances in both conditions leads to either:
Too many false signals during consolidation (if thresholds are loose)
Missing valid opportunities during expansion (if thresholds are tight)
Stops that are too tight during volatility spikes (causing premature exits)
Stops that are too wide during compression (giving back profits)
The Solution Approach:
This strategy first classifies the current volatility regime using normalized ATR (ATR as a percentage of price), then dynamically adjusts ALL other parameters based on that classification. This creates a context-aware system rather than a static threshold comparison.
How Each Component Contributes to the System:
ATR-Based Regime Classification (The Foundation)
The strategy calculates ATR over 21 periods, smooths it with a 13-period EMA to reduce noise from wicks, then divides by price to get a normalized percentage. This ATR% is classified into three regimes:
- Compression (ATR% < 0.8%): Market is consolidating, breakouts are more likely but false signals are common
- Expansion (ATR% 0.8% - 1.6%): Normal trending conditions
- Velocity (ATR% > 1.6%): High volatility, larger moves but also larger adverse excursions
This regime classification then controls stop distances, profit targets, trailing stop offsets, and signal strength requirements. The regime acts as a "meta-parameter" that tunes the entire system.
EMA Ribbon (8/21/34) - Trend Structure Detection
The three EMAs establish trend direction and structure. When EMA 8 > EMA 21 > EMA 34, the trend structure is bullish. The slope of the middle EMA (21) is calculated over 8 bars and converted to degrees using arctangent. This slope measurement quantifies trend strength, not just direction.
Why these specific periods? The 8/21/34 sequence follows Fibonacci-like spacing and provides good separation on 5-minute cryptocurrency charts. The fast EMA (8) responds to immediate price action, the mid EMA (21) represents the short-term trend, and the slow EMA (34) acts as a trend filter.
The EMA ribbon works with the regime classification: during compression regimes, the strategy requires stronger ribbon alignment before entry because false breakouts are more common.
MACD (8/21/5) - Momentum Measurement
The MACD uses faster parameters (8/21/5) than the standard (12/26/9) because cryptocurrency markets move faster than traditional markets. The histogram is smoothed with a 5-period EMA to reduce noise.
The key innovation is the adaptive histogram baseline. Instead of using a fixed threshold, the strategy calculates a rolling baseline from the smoothed absolute histogram value, then multiplies by a sensitivity factor (1.15). This means the threshold for "significant momentum" automatically adjusts based on recent momentum levels.
The MACD works with the regime classification: during velocity regimes, the histogram baseline is effectively higher because recent momentum has been stronger, preventing entries on relatively weak momentum.
RSI (21 period) and MFI (21 period) - Independent Momentum Confirmation
RSI measures momentum using price changes only. MFI (Money Flow Index) measures momentum using price AND volume. By requiring both to confirm, the strategy filters out price moves that lack volume support.
The 21-period length is longer than typical (14) to reduce noise on 5-minute charts. The trigger threshold (55 for longs, 45 for shorts) is slightly offset from 50 to require momentum in the trade direction, not just neutral readings.
These indicators work together: a signal requires RSI > 55 AND MFI > 55 for longs. This dual confirmation reduces false signals from price manipulation or low-volume moves.
Bollinger Bands (1.5 mult) and Keltner Channels (1.8 mult) - Squeeze Detection
When Bollinger Bands contract inside Keltner Channels, volatility is compressing and a breakout is likely. This is the "squeeze" condition. When the bands expand back outside the channels, the squeeze "releases."
The strategy uses a 1.5 multiplier for Bollinger Bands (tighter than standard 2.0) and 1.8 for Keltner Channels. These values were chosen to identify meaningful squeezes on 5-minute cryptocurrency charts without triggering too frequently.
The squeeze detection works with the regime classification: squeeze releases during compression regimes receive additional signal strength points because breakouts from consolidation are more significant.
Volume Impulse Detection - Institutional Participation Filter
The strategy calculates a volume baseline (34-period SMA) and standard deviation. A "volume impulse" is detected when current volume exceeds the baseline by 1.15x OR when the volume z-score exceeds 0.5.
This filter ensures entries occur when there is meaningful market participation, not during low-volume periods where price moves are less reliable.
Volume impulse is required for all entries and adds points to the composite signal strength score.
Cycle Oscillator - Trend Alignment Filter
The strategy calculates a 55-period EMA as a cycle basis, then measures price deviation from this basis as a percentage. When price is more than 0.15% above the cycle basis, the cycle is bullish. When more than 0.15% below, the cycle is bearish.
This filter prevents counter-trend entries. Long signals require bullish cycle alignment; short signals require bearish cycle alignment.
BTC Dominance Filter (Optional) - Market Regime Filter
The strategy can optionally use BTC.D (Bitcoin Dominance) as a market regime filter. When BTC dominance is rising (slope > 0.12), the market is in "risk-off" mode and long entries on altcoins are filtered. When dominance is falling (slope < -0.12), short entries are filtered.
This filter is optional because the BTC.D data feed may lag during low-liquidity periods.
How The Components Work Together (The Mashup Justification):
The strategy uses a composite scoring system where each signal pathway contributes points:
Trend Break pathway (30 points): Requires EMA ribbon alignment + positive slope + price breaks above recent structure high
Momentum Surge pathway (30 points): Requires MACD histogram > adaptive baseline + MACD line > signal + RSI > 55 + MFI > 55 + volume impulse
Squeeze Release pathway (25 points): Requires BB inside KC (squeeze) then release + momentum bias + histogram confirmation
Micro Pullback pathway (15 points): Requires shallow retracement to fast EMA within established trend + histogram confirmation + volume impulse
Additional modifiers:
+5 points if volume impulse is present, -5 if absent
+5 points in velocity regime, -2 in compression regime
+5 points if cycle is aligned, -5 if counter-trend
A trade only executes when the composite score reaches the minimum threshold (default 55) AND all filters agree (session, cycle bias, BTC dominance if enabled).
This scoring system is the core innovation: instead of requiring ALL conditions to be true (which would generate very few signals) or ANY condition to be true (which would generate too many false signals), the strategy requires ENOUGH conditions to be true, with different conditions contributing different weights based on their reliability.
HOW THE STRATEGY CALCULATES ENTRIES AND EXITS
Entry Logic:
1. Calculate current volatility regime from ATR%
2. Calculate all indicator values (MACD, EMA, RSI, MFI, squeeze, volume)
3. Evaluate each signal pathway and sum points
4. Check all filters (session, cycle, dominance, kill switch)
5. If composite score >= 55 AND all filters pass, generate entry signal
6. Calculate position size based on risk per trade and regime-adjusted stop distance
7. Execute entry with regime name as comment
Position Sizing Formula:
RiskCapital = Equity * (0.65 / 100)
StopDistance = ATR * StopMultiplier(regime)
RawQuantity = RiskCapital / StopDistance
MaxQuantity = Equity * (12 / 100) / Price
Quantity = min(RawQuantity, MaxQuantity)
Quantity = round(Quantity / 0.001) * 0.001
This ensures each trade risks approximately 0.65% of equity regardless of volatility, while capping total exposure at 12% of equity.
Stop Loss Calculation:
Stop distance is ATR multiplied by a regime-specific multiplier:
Compression regime: 1.05x ATR (tighter stops because moves are smaller)
Expansion regime: 1.55x ATR (standard stops)
Velocity regime: 2.1x ATR (wider stops to avoid premature exits during volatility)
Take Profit Calculation:
Target distance is ATR multiplied by regime-specific multiplier and base risk/reward:
Compression regime: 1.6x ATR * 1.8 base R:R * 0.9 regime bonus = approximately 2.6x ATR
Expansion regime: 2.05x ATR * 1.8 base R:R * 1.0 regime bonus = approximately 3.7x ATR
Velocity regime: 2.8x ATR * 1.8 base R:R * 1.15 regime bonus = approximately 5.8x ATR
Trailing Stop Logic:
When adaptive trailing is enabled, the strategy calculates a trailing offset based on ATR and regime:
Compression regime: 1.1x base offset (looser trailing to avoid noise)
Expansion regime: 1.0x base offset (standard)
Velocity regime: 0.8x base offset (tighter trailing to lock in profits during fast moves)
The trailing stop only activates when it would be tighter than the initial stop.
Momentum Fail-Safe Exits:
The strategy closes positions early if momentum reverses:
Long positions close if MACD histogram turns negative OR EMA ribbon structure breaks (fast EMA crosses below mid EMA)
Short positions close if MACD histogram turns positive OR EMA ribbon structure breaks
This prevents holding through momentum reversals even if stop loss hasn't been hit.
Kill Switch:
If maximum drawdown exceeds 6.5%, the strategy disables new entries until manually reset. This prevents continued trading during adverse conditions.
HOW TO USE THIS STRATEGY
Step 1: Apply to Chart
Use a 5-minute chart of a high-liquidity cryptocurrency perpetual (BTC/USDT, ETH/USDT recommended)
Ensure at least 200 bars of history are loaded for indicator stabilization
Use standard candlestick charts only (not Heikin Ashi, Renko, or other non-standard types)
Step 2: Understand the Visual Elements
EMA Ribbon: Three lines (8/21/34 periods) showing trend structure. Bullish when stacked upward, bearish when stacked downward.
Background Color: Shows current volatility regime
- Indigo/dark blue = Compression (low volatility)
- Purple = Expansion (normal volatility)
- Magenta/pink = Velocity (high volatility)
Bar Colors: Reflect signal strength divergence. Brighter colors indicate stronger directional bias.
Triangle Markers: Entry signals. Up triangles below bars = long entry. Down triangles above bars = short entry.
Dashboard (top-right): Real-time display of regime, ATR%, signal strengths, position status, stops, targets, and risk metrics.
Step 3: Interpret the Dashboard
Regime: Current volatility classification (Compression/Expansion/Velocity)
ATR%: Normalized volatility as percentage of price
Long/Short Strength: Current composite signal scores (0-100)
Cycle Osc: Price deviation from 55-period EMA as percentage
Dominance: BTC.D slope and filter status
Position: Current position direction or "Flat"
Stop/Target: Current stop loss and take profit levels
Kill Switch: Status of drawdown protection
Volume Z: Current volume z-score
Impulse: Whether volume impulse condition is met
Step 4: Adjust Parameters for Your Needs
For more conservative trading: Increase "Minimum Composite Signal Strength" to 65 or higher
For more aggressive trading: Decrease to 50 (but expect more false signals)
For higher timeframes (15m+): Increase "Structure Break Window" to 12-15, increase "RSI Momentum Trigger" to 58
For lower liquidity pairs: Increase "Volume Impulse Multiplier" to 1.3, increase slippage in strategy properties
To disable short selling: Uncheck "Enable Short Structure"
To disable BTC dominance filter: Uncheck "BTC Dominance Confirmation"
STRATEGY PROPERTIES (BACKTEST SETTINGS)
These are the exact settings used in the strategy's Properties dialog box. You must use these same settings when evaluating the backtest results shown in the publication:
Initial Capital: $100,000
Justification: This amount is higher than typical retail accounts. I chose this value to demonstrate percentage-based returns that scale proportionally. The strategy uses percentage-based position sizing (0.65% risk per trade), so a $10,000 account would see the same percentage returns with 10x smaller position sizes. The absolute dollar amounts in the backtest should be interpreted as percentages of capital.
Commission: 0.04% (commission_value = 0.04)
Justification: This reflects typical perpetual futures exchange fees. Major exchanges charge between 0.02% (maker) and 0.075% (taker). The 0.04% value is a reasonable middle estimate. If your exchange charges different fees, adjust this value accordingly. Higher fees will reduce net profitability.
Slippage: 1 tick
Justification: This is conservative for liquid pairs like BTC/USDT on major exchanges during normal conditions. For less liquid altcoins or during high volatility, actual slippage may be higher. If you trade less liquid pairs, increase this value to 2-3 ticks for more realistic results.
Pyramiding: 1
Justification: No position stacking. The strategy holds only one position at a time. This simplifies risk management and prevents overexposure.
calc_on_every_tick: true
Justification: The strategy evaluates on every price update, not just bar close. This is necessary for scalping timeframes where waiting for bar close would miss opportunities. Note that this setting means backtest results may differ slightly from bar-close-only evaluation.
calc_on_order_fills: true
Justification: The strategy recalculates immediately after order fills for faster response to position changes.
RISK PER TRADE JUSTIFICATION
The default risk per trade is 0.65% of equity. This is well within the TradingView guideline that "risking more than 5-10% on a trade is not typically considered viable."
With the 12% maximum exposure cap, even if the strategy takes multiple consecutive losses, the total risk remains manageable. The kill switch at 6.5% drawdown provides additional protection by halting new entries during adverse conditions.
The position sizing formula ensures that stop distance (which varies by regime) is accounted for, so actual risk per trade remains approximately 0.65% regardless of volatility conditions.
SAMPLE SIZE CONSIDERATIONS
For statistically meaningful backtest results, you should select a dataset that generates at least 100 trades. On 5-minute BTC/USDT charts, this typically requires:
2-3 months of data during normal market conditions
1-2 months during high-volatility periods
3-4 months during low-volatility consolidation periods
The strategy's selectivity (requiring 55+ composite score plus all filters) means it generates fewer signals than less filtered approaches. If your backtest shows fewer than 100 trades, extend the date range or reduce the minimum signal strength threshold.
Fewer than 100 trades produces statistically unreliable results. Win rate, profit factor, and other metrics can vary significantly with small sample sizes.
STRATEGY DESIGN COMPROMISES AND LIMITATIONS
Every strategy involves trade-offs. Here are the compromises made in this design and the limitations you should understand:
Selectivity vs. Opportunity Trade-off
The 55-point minimum threshold filters many potential trades. This reduces false signals but also misses valid setups that don't meet all criteria. Lowering the threshold increases trade frequency but decreases win rate. There is no "correct" threshold; it depends on your preference for fewer higher-quality signals vs. more signals with lower individual quality.
Regime Classification Lag
The ATR-based regime detection uses historical data (21 periods + 13-period smoothing). It cannot predict sudden volatility spikes. During flash crashes or black swan events, the strategy may be classified in the wrong regime for several bars before the classification updates. This is an inherent limitation of any lagging indicator.
Indicator Parameter Sensitivity
The default parameters (MACD 8/21/5, EMA 8/21/34, RSI 21, etc.) are tuned for BTC/ETH perpetuals on 5-minute charts during 2024 market conditions. Different assets, timeframes, or market regimes may require different parameters. There is no guarantee that parameters optimized on historical data will perform similarly in the future.
BTC Dominance Filter Limitations
The CRYPTOCAP:BTC.D data feed may lag during low-liquidity periods or weekends. The dominance slope calculation uses a 5-bar SMA, adding additional delay. If you notice the filter behaving unexpectedly, consider disabling it.
Backtest vs. Live Execution Differences
TradingView backtesting does not replicate actual broker execution. Key differences:
Backtests assume perfect fills at calculated prices; real execution involves order book depth, latency, and partial fills
The calc_on_every_tick setting improves backtest realism but still cannot capture sub-bar price action or order book dynamics
Commission and slippage settings are estimates; actual costs vary by exchange, time of day, and market conditions
Funding rates on perpetual futures are not modeled in backtests and can significantly impact profitability over time
Exchange-specific limitations (position limits, liquidation mechanics, order types) are not modeled
Market Condition Dependencies
This strategy is designed for trending and breakout conditions. During extended sideways consolidation with no clear direction, the strategy may generate few signals or experience whipsaws. No strategy performs well in all market conditions.
Cryptocurrency-Specific Risks
Cryptocurrency markets operate 24/7 without session boundaries. This means:
No natural "overnight" risk reduction
Volatility can spike at any time
Liquidity varies significantly by time of day
Exchange outages or issues can occur at any time
WHAT THIS STRATEGY DOES NOT DO
To be straightforward about limitations:
This strategy does not guarantee profits. Past backtest performance does not indicate future results.
This strategy does not predict the future. It reacts to current conditions based on historical patterns.
This strategy does not account for funding rates, which can significantly impact perpetual futures profitability.
This strategy does not model exchange-specific execution issues (partial fills, requotes, outages).
This strategy does not adapt to fundamental news events or black swan scenarios.
This strategy is not optimized for all market conditions. It may underperform during extended consolidation.
IMPORTANT RISK WARNINGS
Past performance does not guarantee future results. The backtest results shown reflect specific historical market conditions and parameter settings. Markets change constantly, and strategies that performed well historically may underperform or lose money in the future. A single backtest run does not constitute proof of future profitability.
Trading involves substantial risk of loss. Cryptocurrency derivatives are highly volatile instruments. You can lose your entire investment. Only trade with capital you can afford to lose completely.
This is not financial advice. This strategy is provided for educational and informational purposes only. It does not constitute investment advice, trading recommendations, or any form of financial guidance. The author is not a licensed financial advisor.
You are responsible for your own decisions. Before using this strategy with real capital:
Thoroughly understand the code and logic by reading the open-source implementation
Forward test with paper trading or very small positions for an extended period
Verify that commission, slippage, and execution assumptions match your actual trading environment
Understand that live results will differ from backtest results
Consider consulting with a qualified financial advisor
No guarantees or warranties. This strategy is provided "as is" without any guarantees of profitability, accuracy, or suitability for any purpose. The author is not responsible for any losses incurred from using this strategy.
OPEN-SOURCE CODE STRUCTURE
The strategy code is organized into these sections for readability:
Configuration Architecture: Input parameters organized into logical groups (Core Controls, Optimization Constants, Regime Intelligence, Signal Pathways, Risk Architecture, Visualization)
Helper Functions: calcQty() for position sizing, clamp01() and normalize() for value normalization, calcMFI() for Money Flow Index calculation
Core Indicator Engine: EMA ribbon, ATR and regime classification, MACD with adaptive baseline, RSI, MFI, volume analytics, cycle oscillator, BTC dominance filter, squeeze detection
Signal Pathway Logic: Trend break, momentum surge, squeeze release, micro pullback pathways with composite scoring
Entry/Exit Orchestration: Signal filtering, position sizing, entry execution, stop/target calculation, trailing stop logic, momentum fail-safe exits
Visualization Layer: EMA plots, regime background, bar coloring, signal labels, dashboard table
You can read and modify any part of the code. Understanding the logic before deployment is strongly recommended.
- Made with passion by officialjackofalltrades
Order Blocks & Breaker BlocksOrder Blocks & Breaker Blocks
Enhance your trading with this advanced indicator that highlights Bullish and Bearish Order Blocks (OBs) and Breaker Blocks on any chart. It is designed to help traders quickly identify key supply and demand zones and potential reversal points with clear visual cues.
Key Features
Automatically highlights Bullish and Bearish OBs.
Detects Breaker Blocks when OB levels are violated, signaling potential trend shifts.
Fully customizable visuals:
Box and Breaker Box transparency
Line transparency, width, and style (Solid, Dashed, Dotted)
Option to calculate OBs using candle body or high/low.
Adjustable number of recent OBs displayed.
Recommended Settings by Timeframe
Timeframe Swing Lookback Show OBs Notes
5 min 10 3 For fast intraday trading and scalping.
15 min 12 3 For intraday trend analysis
1H 15 3 Ideal for intraday support/resistance and breakout detection.
4H 22 3 Captures stronger OBs for swing trades.
Daily 22 3 Highlights major supply and demand zones for trend trading.
Weekly 30 2 Focuses on long-term OBs for strategic analysis.
These values provide a good balance of accuracy and chart clarity across all timeframes.
Why Use This Indicator
Quickly visualize key supply and demand zones.
Identify potential reversals and breakout points.
Improve trade timing and risk management with enhanced visual clarity.
Works across all major timeframes, making it suitable for intraday, swing, and long-term traders.
Box Theory [Interactive Zones] PyraTimeThis script combines Nicholas Darvas’s "Box Theory" with modern Supply and Demand (Premium/Discount) concepts. It automatically identifies the most recent Swing High and Swing Low to delineate the current trading range.
The purpose of this tool is to visualize market structure and help traders identify when price is relatively expensive (Premium) or cheap (Discount) within a defined range.
Visual Guide: What You Are Seeing
The Box: Represents the active trading range defined by the most recent significant Swing High and Swing Low.
Red Zone (Premium): The top 25% of the range. Mathematically, prices here are considered "expensive" relative to the current structure.
Green Zone (Discount): The bottom 25% of the range. Prices here are considered "cheap" relative to the current structure.
Grey Zone (Equilibrium): The middle 50% of the range. This is the area of fair value where price often consolidates.
Dashed Line (EQ): The exact 50% midpoint of the range.
Tutorial: How to Trade Using This Indicator
Method 1: Mean Reversion (Range Trading) This method applies when the market is moving sideways.
Identify Structure: Wait for a box to form.
Wait for Extremes: Do not trade when price is in the middle (Grey/White area). Wait for price to enter the Red or Green zones.
Entry Trigger:
Shorts: When price enters the Red Zone, look for a rejection (wicks leaving the zone) or a lower timeframe breakdown. Target the EQ (Midline) as your first take profit.
Longs: When price enters the Green Zone, look for support formation. Target the EQ (Midline) as your first take profit.
Method 2: Trend Continuation (Breakouts) This method applies when the market is trending strongly.
Breakout: Monitor the alerts. A close outside the box indicates a potential shift in market structure.
Retest: After a breakout up, the old "Red Zone" (Resistance) often flips to become new Support. Wait for price to pull back to the top of the old box before entering.
Configuration Guide (Settings)
Pivot Left/Right Bars (Sensitivity):
Default (20/20): Best for Swing Trading. It filters out market noise and only draws boxes based on major structural points.
Lower (5/5): Best for Scalping. It will create smaller, more frequent boxes but increases the risk of false signals.
Zone Percentage:
Default (25%): Standard deviation for Supply/Demand zones.
Alternative (15%): Use this for "sniping" entries at the absolute extremes of the range.
Multi-Timeframe (MTF):
Enable "Use Higher Timeframe" to see Daily or Weekly ranges while trading on lower timeframes (like the 15m or 1H). This helps keep your intraday trades aligned with the major trend.
Technical Note on "Lag" This indicator uses Pivots to draw the box. A pivot is only confirmed after a certain number of bars have passed (the "Pivot Right Bars" setting).
Example: If "Pivot Right Bars" is set to 20, the box will update 20 bars after the actual high or low occurred. This is necessary to confirm that the point was indeed a Swing High/Low. Do not treat the box lines as predictive; they are reactive to confirmed structure.
Multi-Fractal Trading Plan [Gemini] v22Multi-Fractal Trading Plan
The Multi-Fractal Trading Plan is a quantitative market structure engine designed to filter noise and generate actionable daily strategies. Unlike standard auto-trendline indicators that clutter charts with irrelevant data, this system utilizes Fractal Geometry to categorize market liquidity into three institutional layers: Minor (Intraday), Medium (Swing), and Major (Institutional).
This tool functions as a Strategic Advisor, not just a drawing tool. It calculates the delta between price and structural pivots in real-time, alerting you when price enters high-probability "Hot Zones" and generating a live trading plan on your dashboard.
Core Features
1. Three-Tier Fractal Engine The algorithm tracks 15 distinct fractal lengths simultaneously, aggregating them into a clean hierarchy:
Minor Structure (Thin Lines): Captures high-frequency volatility for scalping.
Medium Structure (Medium Lines): Identifies significant swing points and intermediate targets.
Major Structure (Thick Lines): Maps the "Institutional" defense lines where trend reversals and major breakouts occur.
2. The Strategic Dashboard A dynamic data panel in the bottom-right eliminates analysis paralysis:
Floor & Ceiling Targets: Displays the precise price levels of the nearest Support and Resistance.
AI Logic Output: The script analyzes market conditions to generate a specific command, such as "WATCH FOR BREAKOUT", "Near Lows (Look Long?)", or "WAIT (No Setup)".
3. "Hot Zone" Detection Never miss a critical test of structure.
Dynamic Alerting: When price trades within 1% (adjustable) of a Major Trend Line, the indicator’s labels turn Bright Yellow and flash a warning (e.g., "⚠️ WATCH: MAJOR RES").
Focus: This visual cue highlights the exact moment execution is required, reducing screen fatigue.
4. The Quant Web & Markers
Pivot Validation: Deep blue fractal markers (▲/▼) identify the exact candles responsible for the structure.
Inter-Timeframe Web: Faint dotted lines connect Minor pivots directly to Major pivots, visualizing the "hidden" elasticity between short-term noise and long-term trend anchors.
5. Enterprise Stability Engine Engineered to solve the "Vertical Line" and "1970 Epoch" glitches common in Pine Script trend indicators. This engine is optimized for Futures (NQ/ES), Forex, and Crypto, ensuring stability across all timeframes (including gaps on ETH/RTH charts).
Operational Guide
Consult the Dashboard: Before executing, check the "Strategy" output. If it says "WAIT", the market is in chop. If it says "WATCH FOR BOUNCE", prepare your entry criteria.
Monitor Hot Zones: A Yellow Label indicates price is testing a major liquidity level. This is your signal to watch for a rejection wick or a high-volume breakout.
Utilize the Web: Use the faint web lines to find "confluence" where a short-term pullback aligns with a long-term trend line.
Configuration
Show History: Toggles "Ghost Lines" (Blue) to display historical structure and broken trends.
Fractal Points: Toggles the geometric pivot markers.
Hot Zone %: Adjusts the sensitivity of the Yellow Warning system (Default: 1%).
Max Line Length: A noise filter that removes stale or "spiderweb" lines that are no longer statistically relevant.
BALANCED Strategy: Intraday Pro + Smart DashboardWelcome to the BALANCED Strategy: Intraday Pro.
This all-in-one indicator is designed for Intraday traders looking to capture trend movements while effectively filtering out sideways market noise. It combines the power of Supertrend for direction, EMA 100 for the baseline trend, and rigorous validation via RSI and ADX.
The script also integrates a complete Risk Management system with targets based on the Golden Ratio (Fibonacci) and a real-time Dashboard.
⏳ Recommended Timeframes
This algorithm is optimized for Intraday volatility:
M5 (5 Minutes) ⭐️: Ideal for quick Scalping. The ADX filter is crucial here to avoid false signals.
M15 (15 Minutes) 🏆: The "Sweet Spot." It offers the best balance between signal frequency and trend reliability.
M30 / H1: For a "Swing Intraday" approach—calmer, fewer signals, but higher precision.
Not recommended for M1 (1 Minute) with default settings (too much noise).
🚀 How It Works
The algorithm follows a strict 3-step logic to generate high-quality signals:
1. Trend Identification (The Engine)
Supertrend: Determines the immediate direction.
EMA 100: Acts as a background trend filter. We only buy above and sell below the EMA.
2. Noise Filtering (Safety)
ADX (Average Directional Index): The signal is only validated if there is sufficient volatility (Configurable threshold, default 12) to avoid "chop markets" (flat markets).
RSI (Relative Strength Index): Strict momentum filter. Buy only if RSI > 50, Sell if RSI < 50.
3. Entry Confirmation (The Trigger)
The script doesn't just rely on a crossover. It waits for "Price Action" confirmation: the candle must close higher than the previous one (for Long) or lower (for Short) to validate the entry.
🛡️ Risk Management (Money Management)
This is the core strength of this tool. Upon signal validation, the script automatically calculates and plots:
Stop Loss (SL): Based on volatility (ATR). It places the stop at the recent Low/High with a safety padding.
Take Profit (TP): Two modes available:
Fibonacci Mode (Default): Targets the 1.618 extension (Golden Ratio) of the risk taken.
Fixed Ratio Mode: Targets a manual Risk/Reward ratio (e.g., 2.0).
📊 The Dashboard
Located at the bottom right, the smart dashboard provides vital info at a glance:
Signal Time: To check if the alert is fresh.
Type (LONG/SHORT): Color-coded (Green/Pink).
Tech Data: RSI and ADX values at the moment of the signal.
Exact Prices: Entry Level, Target (TP), and Stop Loss (SL).
⚙️ Configurable Settings
Sensitivity: Adjust the Supertrend factor (Default 2.0).
Filters: Toggle the RSI filter ON/OFF or adjust the ADX threshold.
Execution: Choose between Fibonacci Target (1.618) or a Manual Ratio.
⚠️ Disclaimer: This tool is a technical decision aid and does not constitute financial investment advice. Always use prudent risk management and backtest the indicator on your preferred assets before live use.
Hyper Insight MA Strategy [Universal]Hyper Insight MA Strategy ** is a comprehensive trend-following engine designed for traders who require precision and flexibility. Unlike standard indicators that lock you into a single calculation method, this strategy serves as a "Universal Adapter," allowing you to **Mix & Match 13 different Moving Average types** for both the Fast and Slow trend lines independently.
Whether you need the smoothness of T3, the responsiveness of HMA, or the classic reliability of SMA, this script enables you to backtest thousands of combinations to find the perfect edge for your specific asset class.
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🔬 Deep Dive: Calculation Logic of Included MAs
This strategy includes 13 distinct calculation methods. Understanding the math behind them will help you choose the right tool for your specific market conditions.
#### 1. Standard Averages
* **SMA (Simple Moving Average):** The unweighted mean of the previous $n$ data points.
* *Logic:* Treats every price point in the period with equal importance. Good for identifying long-term macro trends but reacts slowly to recent volatility.
* **WMA (Weighted Moving Average):** A linear weighted average.
* *Logic:* Assigns heavier weight to current data linearly (e.g., $1, 2, 3... n$). It reacts faster than SMA but is still relatively smooth.
* **SWMA (Symmetrically Weighted Moving Average):**
* *Logic:* Uses a fixed-length window (usually 4 bars) with symmetrical weights $ $. It prioritizes the center of the recent data window.
#### 2. Exponential & Lag-Reducing Averages
* **EMA (Exponential Moving Average):**
* *Logic:* Applies an exponential decay weighting factor. Recent prices have significantly more impact on the average than older prices, reducing lag compared to SMA.
* **RMA (Running Moving Average):** Also known as Wilder's Smoothing (used in RSI).
* *Logic:* It is essentially an EMA but with a slower alpha weight of $1/length$. It provides a very smooth, stable line that filters out noise effectively.
* **DEMA (Double Exponential Moving Average):**
* *Logic:* Calculated as $2 \times EMA - EMA(EMA)$. By subtracting the "lag" (the smoothed EMA) from the original EMA, DEMA provides a much faster reaction to price changes with less noise than a standard EMA.
* **TEMA (Triple Exponential Moving Average):**
* *Logic:* Calculated as $3 \times EMA - 3 \times EMA(EMA) + EMA(EMA(EMA))$. This effectively eliminates the lag inherent in single and double EMAs, making it an extremely fast-tracking indicator for scalping.
#### 3. Advanced & Adaptive Averages
* **HMA (Hull Moving Average):**
* *Logic:* A composite formula involving Weighted Moving Averages: ASX:WMA (2 \times Integer(n/2)) - WMA(n)$. The result is then smoothed by a $\sqrt{n}$ WMA.
* *Effect:* It eliminates lag almost entirely while managing to improve curve smoothness, solving the traditional trade-off between speed and noise.
* **ZLEMA (Zero Lag Exponential Moving Average):**
* *Logic:* This calculation attempts to remove lag by modifying the data source before smoothing. It calculates a "lag" value $(length-1)/2$ and applies an EMA to the data: $Source + (Source - Source )$. This creates a projection effect that tracks price tightly.
* **T3 (Tillson T3 Moving Average):**
* *Logic:* A complex smoothing technique that runs an EMA through a filter multiple times using a "Volume Factor" (set to 0.7 in this script).
* *Effect:* It produces a curve that is incredibly smooth and free of "overshoot," making it excellent for filtering out market chop.
* **ALMA (Arnaud Legoux Moving Average):**
* *Logic:* Uses a Gaussian distribution (bell curve) to assign weights. It allows the user to offset the moving average (moving the peak of the weight) to align it perfectly with the price, balancing smoothness and responsiveness.
* **LSMA (Least Squares Moving Average):**
* *Logic:* Calculates the endpoint of a Linear Regression line for the lookback period. It essentially guesses where the price "should" be based on the best-fit line of the recent trend.
* **VWMA (Volume Weighted Moving Average):**
* *Logic:* Weights the closing price by the volume of that bar.
* *Effect:* Prices on high volume days pull the MA harder than prices on low volume days. This is excellent for validating true trend strength (i.e., a breakout on high volume will move the VWMA significantly).
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### 🛠 Features & Settings
* **Universal Switching:** Change the `Fast MA` and `Slow MA` types instantly via the settings menu.
* **Trend Cloud:** A dynamic background fill (Green/Red) highlights the crossover zone for immediate visual trend identification.
* **Strategy Mode:** Built-in Backtesting logic triggers `LONG` entries when Fast MA crosses over Slow MA, and `EXIT` when Fast MA crosses under.
### ⚠️ Disclaimer
This script is intended for educational and research purposes. The wide variety of MA combinations can produce vastly different results. Past performance is not indicative of future results. Please use proper risk management.
Bayesian Liquidity Pain & Gain [Instit. Vol Weighted]Bayesian Liquidity Pain & Gain Indicator
Stop guessing where support and resistance are.
The Bayesian Liquidity Pain & Gain indicator moves beyond arbitrary lines and raw price action. It quantifies Institutional Intent by calculating the exact price levels where large volume has been accumulated and visualizes the "Pain" (stress) those participants feel when the market moves against them.
The Logic: Quantified Institutional Stress
Institutions don't trade single candles; they accumulate positions over time. This indicator tracks their Volume-Weighted Average Cost Basis to answer two critical questions:
Where did they enter? (The Cost Basis Lines)
Are they underwater? (The Pain Clouds)
By normalizing price distance using volatility (ATR) and statistical deviation (Z-Score), we filter out noise and only highlight zones where "Smart Money" is statistically forced to defend their positions or capitulate.
How to Read the Chart
1. The Cost Basis Lines (Anchors)
• 🟢 Green Line (Buyer Cost Basis): The average price where institutions accumulated long positions. This acts as dynamic Support.
• 🔴 Red Line (Seller Cost Basis): The average price where institutions accumulated short positions. This acts as dynamic Resistance.
2. The Pain Clouds (Signals)
When price moves significantly away from the cost basis (Z-Score > 2.0), "Clouds" appear to visualize the PnL status of the participants:
• 🔴 Red Cloud (Buyer Pain): Price is below the buyer's entry. Buyers are losing money (in the red). This creates a "Discount" zone where they may defend support.
• 🟢 Green Cloud (Seller Pain): Price is above the seller's entry. Sellers are losing money (shorts are squeezed). This indicates strong bullish momentum.
3. The Multi-Timeframe Dashboard
A real-time HUD showing the Z-Score status across 4 timeframes (1m, 5m, 15m, 1h):
• 🟢 Green: Profitable/Neutral (Trend Continuation)
• 🟠 Orange: Warning (Pressure Building)
• 🔴 Red: Critical Pain (High Probability Reversal)
Trading Strategies
Setup 1: The Defensive Bounce (Long)
• Context: Price drops into a 🔴 Red Cloud (Buyer Pain).
• Trigger: Price touches the 🟢 Green Line (Buyer Cost Basis) and shows a rejection wick.
• Logic: Institutional buyers defend their cost basis to avoid realizing losses.
Setup 2: The Short Squeeze (Momentum)
• Context: Price rallies into a 🟢 Green Cloud (Seller Pain).
• Trigger: Price holds above the 🔴 Red Line (Seller Cost Basis).
• Logic: Short sellers are trapped and forced to buy back (cover), fueling the rally.
Fractal Alignment:
For high-conviction trades, wait for the Dashboard to show "Pain" signals on both the 1h (Anchor) and 5m (Trigger) timeframes simultaneously.
Settings
• Memory Length (Default 144): The lookback period for the institutional cost basis. Increase for swing trading, decrease for scalping.
• Sigma Threshold (Default 2.0): The statistical confidence level for "Pain". Higher values = fewer, stronger signals.
• Volume Amp: When enabled, high volume amplifies the pain signal, giving more weight to institutional footprints.
