TitanEdge Algo Suite — 4H BTC & ETH (Delta Exchange Ready)TitanEdge Algo Suite — 4H BTC & ETH (Delta Exchange Ready)
TitanEdge Algo Suite is a next-generation trading system that fuses volatility-adaptive logic, order-block structure, SuperTrend direction filtering, and ATR-based exits into a single modular framework.
It’s engineered for 4-hour BTC and ETH swing trading, delivering institutional-grade entries, dynamic risk control, and precise exits.
⚙️ Core Features
1. Volatility Oscillator (0–100)
• Filters trades by volatility intensity.
• Uses ATR, Range, or Bollinger Band Width normalization.
• Trades trigger only when market volatility is high — filtering out sideways or weak trends.
• Ensures trades occur during real momentum expansions.
2. Breakout + Order Block Engine
• Detects pivot highs/lows to confirm authentic breakout levels.
• Identifies “smart money” gaps — institutional imbalance zones often leading to strong reversals or continuations.
• Captures both breakout continuations and order-block reversals.
• Works as a hybrid structure detector combining price action and volatility alignment.
3. SuperTrend Directional Filter
• Optional filter that only allows trades in the direction of the SuperTrend.
• Can automatically close trades when a SuperTrend flip occurs.
• Provides strong trend-following bias and helps avoid countertrend traps.
4. ATR-Based Stop & Trailing System
• Adaptive stop-loss and trailing logic that expands or tightens based on volatility.
• Supports three modes: StopOnly, TrailOnly, and StopAndTrail.
• Works in both ATR-based distance or percentage-based configuration.
• Keeps losing trades small and lets winning trades extend dynamically.
5. Volume-Based Exit Logic
• Detects low-volume exhaustion to identify momentum loss.
• Detects opposite-volume spikes as early reversal signals.
• Optional hybrid “Both” mode combines both detection methods for stronger reliability.
• Ideal for markets where volume surges indicate smart money exits or trap formations.
6. Session Filter & Anti-Churn Control
• Restrict trading hours (optional; not required for crypto).
• Prevents repeated signals and noise-based entries through minimum bars between trades.
• Cooldown logic ensures disciplined trading and avoids strategy overlap.
• Prevents multiple entries in a single bar and filters unconfirmed breakouts.
7. SmartMoney Preset Mode
• Institutional-grade configuration automatically adjusting volatility, ATR, and structural logic.
• Mimics smart money behavior by prioritizing clean structure and high liquidity volatility zones.
• Great for traders who want simplified institutional logic without manual tuning.
Optimized for 4H BTC & ETH
TitanEdge performs best on BTCUSDT and ETHUSDT pairs in the 4-hour timeframe.
The 4H chart captures high-volatility institutional swings, eliminates intraday noise, and provides clear order-block setups.
This timeframe aligns with BTC/ETH volatility cycles, providing consistent signals and cleaner trend confirmation.
Recommended settings for 4H charts:
• Levels Period: 25
• Volatility Filter: 20
• volatility oscillator Auto: disable ( it depend upon your plan test with Disable/enable)
• Volatility Method: BBWidth
• ATR Multiplier: 1.8
• ATR Stop %: 5
• SuperTrend ATR Length: 10
• SuperTrend Factor: 3
• ATR Mode: StopAndTrail
• Hold Bars: 1
• Volume Exit: Disable (Both)
• Session Filter: Off (Crypto runs 24/7)
Entry Logic
• Long Entry: Price breaks above resistance (pivot high), volatility above threshold, and optional SuperTrend confirmation.
• Short Entry: Price breaks below support (pivot low), volatility above threshold, and optional bearish SuperTrend confirmation.
• Additional Entry: Triggered by order-block gaps (smart money imbalances) in volatility expansion phases.
• Trades only when both direction and volatility align to ensure precision entries.
Exit Logic
• ATR Stop and Trail dynamically manage open trades.
• SuperTrend Flip forces exit on trend reversal.
• Volume Exit triggers when volume momentum drops or opposite spike occurs.
• Optional session close exit to flatten trades outside hours.
• Logic prevents premature exits with “Hold Bars” delay after entry.
Why You Need TitanEdge Algo Suite
• Trades only during high-volatility, strong-momentum phases — no false breakouts or choppy trades.
• ATR risk control automatically adjusts to each market’s volatility conditions.
• Identifies institutional order-blocks and clean breakouts for precise entries.
• SuperTrend filter adds directional bias, boosting win-rate consistency.
• Volume exit logic ensures profits are protected when market momentum fades.
• Works 24/7 across all major crypto pairs — fully automated and customizable.
• Built for 4H swing trades — fewer but higher-quality setups.
• Fully compatible with TradingView alerts and bot integration for hands-free execution.
How TitanEdge Makes Profit
• TitanEdge only trades during volatility expansion, when breakout continuation probability is statistically high.
• ATR dynamic stops prevent large losses by scaling protection according to real volatility.
• Trend filtering keeps positions aligned with major market flows.
• Order-block detection ensures entries are based on price structure rather than random signals.
• Volume-based exits secure profits early when momentum weakens.
• SmartMoney Preset provides optimal balance between trade frequency, accuracy, and drawdown control.
• The system compounds edge by maintaining trade discipline — fewer but stronger trades over time.
Delta Exchange Integration (TradingView Bot Ready)
TitanEdge is fully compatible with TradingView alert webhooks and can connect to Delta Exchange or any bot-supported broker.
Alert JSON message format:
{"symbol":"{{ticker}}","side":"{{strategy.order.action}}","qty":1,"trigger_time":"{{timenow}}","strategy_id":"code"}
qty 1 represent 1 lot so if you want to take trade with 5 lots or 0.05eth and write
{"symbol":"{{ticker}}","side":"{{strategy.order.action}}","qty":5,"trigger_time":"{{timenow}}","strategy_id":"code"}
Steps to automate:
Create an alert on TradingView using “Once Per Bar Close”.
Paste your bot or automation webhook URL.
Paste the JSON above as the message.
Configure your bot or API bridge (like PineConnector, AutoView, or WunderTrading) to route signals to Delta Exchange.
On Delta, use BTCUSD or ETHUSD Perpetual pairs with moderate leverage (3x–5x).
Enable Cross Margin for smooth drawdown handling.
Test first on Delta Testnet for safety.
Why 4H BTC & ETH Works Best
• 4H candles capture true volatility swings and filter lower-timeframe noise.
• Aligns with institutional liquidity cycles in BTC and ETH.
• ATR and volume-based stops perform optimally on larger bars.
• Smoother equity curve and less drawdown compared to intraday trading.
• Ideal for traders seeking structured, medium-term trades with high reward-to-risk.
Unique Edge
• Combines breakout, order-block, and volatility principles into one adaptive model.
• Incorporates volatility normalization (ATR/BBWidth) for multi-market adaptability.
• Dynamic ATR stops and trailing protect capital during unstable phases.
• Volume and trend exits create layered protection systems.
• 4H optimization eliminates noise and provides clear institutional alignment.
• SmartMoney preset auto-configures settings to mimic large-player behavior.
• Fully automated via webhooks — no manual execution required.
• Modular design lets you customize each component for different trading styles.
TradingView Bot Integration
TitanEdge is fully plug-and-play with all TradingView-compatible bots.
Each alert sends structured JSON data containing direction, symbol, and quantity, ready for execution on your connected broker.
You can route the data to:
• PineConnector (MT4/MT5 bridge)
• WunderTrading
• AutoView
• Custom Node/REST API handler
This makes TitanEdge a professional-grade strategy suitable for semi-automatic or fully automated crypto trading setups.
Professional Recommendations
• Timeframe: 4H
• Instruments: BTCUSDT, ETHUSDT
• Exchange: Delta Exchange (Perpetual Futures)
• Leverage: 3x–5x
• Session Filter: Off (crypto 24/7)
• Risk per trade: 0.5%–1% of total equity
• Alert Type: Once Per Bar Close
• Volatility Filter: 25–35 depending on market activity
• Always use realistic slippage and fees for backtests.
Summary
TitanEdge Algo Suite is a complete trading framework built to deliver institutional-quality precision with full automation support.
It captures powerful volatility expansions on 4H BTC and ETH charts using clean structure, adaptive stops, and directional trend filters.
Every feature — from entry logic to exits — is designed to protect capital and amplify performance through disciplined, volatility-aware execution.
TitanEdge is not just another script — it’s a professional-grade algorithm that combines volatility intelligence, structural precision, and adaptive risk control.
TitanEdge Algo Suite = Smart Logic × Trend Discipline × Adaptive Risk Control
Optimized for BTC & ETH on 4H charts. Built for traders who demand precision, control, and consistency.
Volum
nOI + Funding + CVD • strategynOI + Funding + CVD Strategy
Overview
This strategy is designed for cryptocurrency trading on platforms like TradingView, focusing on perpetual futures markets. It combines three key indicators—Normalized Open Interest (nOI), Funding Rate, and Cumulative Volume Delta (CVD)—to generate buy and sell signals for long and short positions. The strategy aims to capitalize on market imbalances, such as overextended open interest, funding rate extremes, and volume deltas, which often signal potential reversals or continuations in trending markets.
The script supports pyramiding (up to 10 positions), uses percentage-based position sizing (default 10% of equity per trade), and allows customization of trade directions (longs and shorts can be enabled/disabled independently). It includes multiple signal systems for entries, various exit mechanisms (including stop-loss, take-profit, time-based exits, and conditional closes based on indicators), a Martingale add-on system for averaging positions during drawdowns, and handling of opposite signals (ignore, close, or reverse).
This strategy is not financial advice; backtest thoroughly and use at your own risk. It requires data sources for Open Interest (OI) and Funding Rates, which are fetched via TradingView's security functions (e.g., from Binance for funding premiums).
Key Indicators
1. Normalized Open Interest (nOI)
Group: Open Interest
Purpose: Measures the relative level of open interest over a lookback window to identify overbought (high OI) or oversold (low OI) conditions, which can indicate potential exhaustion in trends.
Calculation:
Fetches OI data (close) from the symbol's standard ticker (e.g., "{symbol}_OI").
Normalizes OI within a user-defined window (default: 500 bars) using min-max scaling: (OI - min_OI) / (max_OI - min_OI) * 100.
Upper threshold (default: 70%): Signals potential short opportunities when crossed from above.
Lower threshold (default: 30%): Signals potential long opportunities when crossed from below.
Visualization: Plotted as a line (teal above upper, red below lower, gray in between). Horizontal lines at upper, mid (50%), lower, and a separator at 102%.
Notes: Handles non-crypto symbols by adjusting timeframe to daily if intraday. Errors if no OI data available.
2. Funding Rate
Group: Funding Rate
Purpose: Tracks the average funding rate (premium index) to detect market sentiment extremes. Positive funding suggests bull bias (longs pay shorts), negative suggests bear bias.
Calculation:
Fetches premium index data from Binance (e.g., "binance:{base}usdt_premium").
Supports lower timeframe aggregation (default: enabled, using 1-min TF) for smoother data.
Averages open and close premiums, clamps values, and scales/shifts for plotting (base: 150, scale: 1000x).
Upper threshold (default: 1.0%): Overheat for shorts.
Lower threshold (default: 1.0%): Overcool for longs.
Ultra level (default: 1.8%): Extreme for additional short signals.
Smoothing: Uses inverse weighted moving average (IWMA) or lower-TF aggregation to reduce noise.
Visualization: Shifted plot (green positive, red negative) with filled areas. Horizontal lines for overheat, overcool, base (0%), and ultra.
Notes: Custom ticker option for non-standard symbols.
3. Cumulative Volume Delta (CVD)
Group: CVD (Cumulative Volume Delta)
Purpose: Measures net buying/selling pressure via volume delta, normalized to identify divergences or confirmations with price.
Calculation:
Delta: +volume if close > open, -volume if close < open.
Cumulative: Rolling cumsum over a window (default: 500 bars), smoothed with EMA (default: 20).
Normalized: Scaled by absolute max in window (-1 to 1 range).
Scaled/shifted for plotting (base: 300 or 0 if anchored, scale: 120x).
Upper threshold (default: 1.0%): Over for shorts.
Lower threshold (default: 1.0%): Under for longs.
Visualization: Shifted plot (aqua positive, purple negative) with filled areas. Horizontal lines for over, under, and separator (default: 252).
Filter Options (for Signal A):
Enable filter (default: false).
Require sign match (Long ≥0, Short ≤0).
Require extreme zones.
Require momentum (rising/falling over N bars, default: 3).
Signal Logics for Entries
Entries are triggered by buy/sell signals from multiple systems (A, B, C, D), filtered by direction toggles and entry conditions.
Signal System A: OI + Funding (with optional CVD filter)
Enabled: Default true.
Sell (Short): nOI > upper threshold, falling over N bars (default: 3), delta ≥ threshold (default: 3%), funding > overheat, and CVD filter OK.
Buy (Long): nOI < lower threshold, rising over N bars (default: 3), delta ≥ threshold (default: 3%), funding < overcool, and CVD filter OK.
Signal System B: Short - Funding Crossunder + Filters
Enabled: Default true.
Sell (Short): Funding crosses under overheat level, optional: CVD > over, nOI < upper.
Signal System C: Short - Ultra Funding
Enabled: Default false.
Sell (Short): Funding crosses ultra level (up or down, both default true).
Signal System D: Long - Funding Crossover + Filters
Enabled: Default true.
Buy (Long): Funding crosses over overcool level, optional: CVD < under, nOI > lower.
Combined: Sell if A/B/C active; Buy if A/D active.
Entry Filters
Cooldown: Optional pause between entries (default: false, 3 bars).
Max Entries: Limit pyramiding (default: true, 6 max).
Entries only if both filters pass and direction allowed.
Opposite Signal Handling
Mode: Ignore (default), Reverse (close and enter opposite), or Close (exit only).
Processed before regular entries.
Position Management
Martingale (3 Steps):
Enabled per step (default: all true).
Triggers add-ons at loss levels (defaults: 5%, 8%, 11%) by adding % to position (default: 100% each).
Resets on position close.
Break Even:
Enabled (default: true).
Activates at profit threshold (default: 5%), sets SL better by offset (default: 0.1%).
Exit Systems
Multiple exits checked in sequence.
Exit 1: SL/TP
Enabled: Separate for long/short (default: true).
SL: % from avg price (defaults: 1% long/short).
TP: % from avg price (defaults: 2% long/short).
Exit 2: Funding
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: Funding > upper exit threshold (default: 0.8%).
Short Exit: Funding < lower exit threshold (default: 0.8%).
Exit 3: nOI
Enabled: Separate for long (up) / short (down) (default: true).
Long Exit: nOI > upper exit (default: 85%).
Short Exit: nOI < lower exit (default: 15%).
Exit 4: Global SL
Enabled: Default true.
Exit: If position loss ≥ % (default: 7%).
Exit 5: Break Even (integrated in position block)
Exit 6: Time Limit
Enabled: Separate for long/short (default: true).
Exit: After N bars in trade (defaults: 30 each).
Timer updates on add-ons if enabled (default: true).
Visual Elements
Buy/Sell Labels: Small labels ("BUY"/"SELL") on bars with signals, limited to last 30.
All indicators plotted on a separate pane (overlay=false).
Usage Notes
Backtesting: Adjust parameters based on asset/timeframe. Test on historical data.
Data Requirements: Works best on crypto perps with OI and funding data.
Risk Management: Incorporates SL/TP and global SL; monitor drawdowns with Martingale.
Customization: All thresholds, enables, and scales are inputs for fine-tuning.
Version: Pine Script v6.
For questions or improvements, contact the author. Happy trading!
Volumemetrix Variance StrategyThe “Volumemetrix Variance Strategy” is an advanced Pine Script strategy designed to identify trade entries and exits using a combination of volume profile analysis, candle structure, and volatility filters. It constructs a dynamic volume profile over a specified lookback period to identify critical price levels such as the Point of Control (PoC), Value Area High (VAH), and Value Area Low (VAL). These levels represent zones of high trading activity that often act as support and resistance. The script smooths and adjusts these levels across different timeframes to align short-term market structure with higher-timeframe trends. It incorporates a variety of filters to exclude doji candles, detect continuation or rejection patterns, and confirm alignment with higher timeframe candle direction (e.g., 4-hour bullish or bearish bias).
Trade logic is built around detecting crossovers and breakouts relative to the PoC and value areas. The system can trigger entries based on several configurable behaviors: breakout, retake, bounce, reversal, or rejection near key volume zones. It supports flexible entry conditions for long, short, or both sides of the market, as well as a range of customizable settings for time-based trading restrictions, end-of-day position closures, and alert-based data capture. For execution, the script includes integrated risk management—users can specify take-profit and stop-loss levels, enable moving (trailing) stops, and even apply a “power curve” model to dynamically adjust trailing stops using exponential decay logic that adapts to price progress.
Overall, the Volumemetrix Variance Strategy is a hybrid between a quantitative volume-based strategy and a volatility-adaptive trade manager. It combines fixed range volume profiling with multi-timeframe confirmation, candle pattern validation, and adaptive exit logic. Its architecture allows for detailed trade automation, alert generation for external systems, and real-time control over parameters such as ATR scaling, entry delay, or bar confirmation. The result is a high-granularity framework for both backtesting and live execution that seeks to capture statistically favorable setups around liquidity concentration zones.
MA Break Trend Strategy - Multi Stop MethodsThis is a trend-following trading strategy with multiple stop loss options for both long and short positions.
Entry Signal: Trades are triggered when price crosses above (long) or below (short) a configurable moving average (EMA or SMA, default 200-period)
Volume Confirmation: Optional filter requiring volume to exceed a multiplier (default 1.5x) of the 20-period volume average before entering trades
Five Stop Loss Methods:
- ATR-based: Dynamic stop using Average True Range multiplier below/above entry price
- MA Buffer: Stop set at a percentage offset from a separate moving average (default 50-period EMA)
- Donchian Channel: Uses the lowest low/highest high over a specified lookback period
- Keltner Channel: ATR-based bands around an EMA basis
- Lowest Low/Highest High: Simple swing point stops based on recent price extremes
- Trailing Stops: All stop methods automatically trail in the profitable direction (upward for longs, downward for shorts) to lock in gains while never moving against the position
Visual Indicators:
- Plots the trend-following moving average in blue
- Shows active stop loss levels in red when in a position
- Displays reference lines for all stop types when flat
- Entry signals marked with triangles (green up for long, red down for short)
- Background highlighting for volume-confirmed crossovers
BUY LOW, BUY MORE, SELL HIGH -BUFFET STRATEGY LITE__________________________________________________________________________
Buy Low, Buy More, Sell High With Buffett Meter (LITE – JTMarketAI)
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Category: Quantitative Momentum & Liquidity Flow
Author: JTMarketAI
Architecture: Non-Repainting
This strategy accumulates into validated pullbacks during fear cycles, scales intelligently as price declines into liquidity support, and exits when momentum weakens after meaningful run-ups. It uses synthetic higher-timeframe OHLC data (non-repainting), liquidity imbalance confirmation, adaptive KAMA trend logic, RSI validation, and a live Buffett macro valuation gauge.
This is a patient, conviction-based accumulation engine designed for equities.
It is not a scalp bot.
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Core Features
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Non-repainting (confirmed bars only)
Synthetic HTF OHLC (no lookahead)
Dynamic trailing exit preserves ~80–87% of peak profit
Bull vs Bear liquidity dominance and flow imbalance
Rolling lowest-low tracking (LLL)
NY-session alignment (default)
Buffett Macro Meter integration
Technical Highlights
Flow-confidence derived from volume-order pressure
Adaptive KAMA smoothing for lower-lag confirmation
Daily > Weekly > Monthly synthetic aggregation
LLL progression display for trend exhaustion
Fully profiler-optimized
Supports averaging down when pyramiding enabled
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Why It Does Not Repaint
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All state updates occur only on confirmed bars
Synthetic HTFs built without lookahead
Persistent arrays freeze historical values
Trailing highs updated only after confirmation
No forward-reference to future bars
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Lite Edition Notes
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Manual trading focused
Buffett Meter enabled
Up to 20 trades per session
Visual dashboard included
No alerts, automation, or webhooks (PRO unlocks IBKR + TradersPost)
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Limitations
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Best on intraday equities (1m–4h)
Designed for US stocks only
High-resource if full visuals enabled
Avoid penny stocks and extremely low-volume tickers
Does not guard against after-hours gaps or major news moves
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Warnings
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Contrarian scaling requires discipline and patience
Expect longer-duration trades, not rapid scalps
Use on quality tickers unlikely to permanently collapse
Confirm price behavior outside cash session
Test manually before automating anything
Not suitable for every market environment or asset
Notes on Philosophy
This strategy attempts to accumulate when markets overshoot lower, and distribute after recovery momentum fades. It reflects a patient, value-driven approach built on the principle of buying fear and reducing exposure into strength.
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Disclaimer
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For research and educational use only. Not financial advice. Past performance does not guarantee future results. Test thoroughly and use appropriate risk management.
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Hashtags
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#buffett #quantstrategy #valuemomentum #accumulation #contrarian #nonrepaint #equitystrategy #swingtrading #liquidityanalysis #synthetichtf #tradingviewstrategy
BUY LOW, BUY MORE, SELL HIGH - MARKET FLOW STRATEGY LITE
TV Description - Buffett Meter Lite
body{font-family:Arial,Helvetica,sans-serif;max-width:900px;margin:32px auto;line-height:1.4} h1,h2{margin:16px 0 8px}
Buy Low, Buy More, Sell High With Buffett Meter (Lite v1283 – JTM)
Category: Quantitative Momentum & Liquidity Flow
Author: JTM
Architecture: Non-Repainting
This strategy accumulates into validated pullbacks during fear cycles, scales intelligently as price declines into liquidity support, and exits when momentum weakens after meaningful run-ups. It uses synthetic higher-timeframe OHLC data (non-repainting), liquidity imbalance confirmation, adaptive KAMA trend logic, RSI validation, and a live Buffett macro valuation gauge.
This is a patient, conviction-based accumulation engine designed for equities.
It is not a scalp bot.
Core Features
Non-repainting (confirmed bars only)
Synthetic HTF OHLC (no lookahead)
Dynamic trailing exit preserves ~80–87% of peak profit
Bull vs Bear liquidity dominance and flow imbalance
Rolling lowest-low tracking (LLL)
NY-session alignment (default)
Buffett Macro Meter integration
Technical Highlights
Flow-confidence derived from volume-order pressure
Adaptive KAMA smoothing for lower-lag confirmation
Daily > Weekly > Monthly synthetic aggregation
LLL progression display for trend exhaustion
Fully profiler-optimized
Supports averaging down when pyramiding enabled
Why It Does Not Repaint
All state updates occur only on confirmed bars
Synthetic HTFs built without lookahead
Persistent arrays freeze historical values
Trailing highs updated only after confirmation
No forward-reference to future bars
Lite Edition Notes
Manual trading focused
Buffett Meter enabled
Limit of 20 trades per session
Buffet Meter dashboard included
No alerts, automation, or webhooks (PRO unlocks IBKR + TradersPost)
Limitations
Best on intraday equities (1m–4h)
Designed for US stocks only
High-resource if full visuals enabled
Avoid penny stocks and extremely low-volume tickers
Does not guard against after-hours gaps or major news moves
Warnings
Contrarian scaling requires discipline and patience
Expect longer-duration trades, not rapid scalps
Use on quality tickers unlikely to permanently collapse
Confirm price behavior outside cash session
Test manually before automating anything
Not suitable for every market environment or asset
Notes on Philosophy
This strategy attempts to accumulate when markets overshoot lower, and distribute after recovery momentum fades. It reflects a patient, value-driven approach built on the principle of buying fear and reducing exposure into strength.
This is edge-based, not “trade every wiggle” logic
“Be fearful when others are greedy, and greedy when others are fearful.” — Buffett
“The stock market transfers money from the impatient to the patient.” — Buffett
Disclaimer
For research and educational use only. Not financial advice. Past performance does not guarantee future results. Test thoroughly and use appropriate risk management.
Hashtags
#buffett #quantstrategy #valuemomentum #accumulation #contrarian #nonrepaint #equitystrategy #swingtrading #liquidityanalysis #synthetichtf #tradingviewstrategy
KCB Strategy [Ncentry]This strategy is a strong trend breaking strategy based on the Keltner channel.
Optimized for the bitcoin okx exchange chart.
INDIAN INTRADAY BEASTThe Indian Intraday Beast is a precision-built intraday strategy optimized for the 15-minute timeframe.
It captures high-probability momentum shifts and trend reversals using adaptive price-action logic and proprietary confirmation filters.
Designed for traders who demand clarity, speed, and consistency in India’s fast-paced markets.
Maxtra Range Breakout StrategyRange Breakout Strategy
This strategy identifies periods of price consolidation (range) and enters trades when the price breaks above or below the defined range. A breakout above the range signals a potential uptrend (buy), while a breakout below indicates a potential downtrend (sell). It helps capture strong directional moves following low-volatility phases.
BUY LOW, BUY MORE, SELL HIGH - MARKET FLOW STRATEGY-JTM────────────────────────────────────────────────────────
BUY LOW, BUY MORE, SELL HIGH – MARKET FLOW STRATEGY (v594) – JTM
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Category: Quantitative Momentum & Liquidity Flow Strategy
Author: JTM
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An Adaptive Contrarian live trading strategy that scales into deep pullbacks,
rides liquidity waves, and locks profit automatically, using your TradersPost.io webhook.
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DESCRIPTION
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The "Buy Low, Buy More, Sell High" strategy combines value-based accumulation
with adaptive profit protection. It adds exposure on weakness (new lower lows
and confirmed liquidity support) and closes trades dynamically once a profitable
run-up retraces by a set percentage (default 13%).
It reconstructs multi-timeframe market structure
(Intraday → Daily → Weekly → Monthly → Yearly)
using synthetic OHLCs to avoid repainting, and integrates VWAP anchoring,
adaptive KAMA smoothing, RSI validation, and rolling lower-low tracking.
Contrarian strategies are difficult for the human to be easily comfortable with...
because but the results can be worth the wait. Believe that you truly want to Sell when everyone is buying and buy when everyone is almost done selling. Not vice-versa!
Forget about trying to time the market at the true top or the true bottom - just ride
the rolling waves and the profits will come ashore.
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CORE FEATURES
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• Non-repainting by design – only confirmed bars update persistent state
• Synthetic HTF OHLC construction avoids lookahead bias
• Adaptive trailing TakeProfit logic aims for (80–87% of peak profit retained)
• AI-like market flow dashboard with Bull/Bear liquidity dominance
• Dynamic rolling "Lowest Low" (LLL) detection and visualization
• Modular time detection and session alignment (New York market default)
• Optional Liquidity Dashboard with intraday/swing dual-mode analytics
1. Non-Repainting Architecture - Long side strategy. Not coded for short selling.
2. Works best on a 1hr/60m intraday chart with a 3hr higher Timeframe (strategy input)
3. Immediately Uncheck Show Trade Signals in the Strategy's Style Settings to eliminate
onscreen clutter
4. Market Liquidity Dashboard can be displayed by setting in the strategy's inputs.
5. You set a price range of stocks you wish to allow to trade when using an alert list.
6. You can set a preview period where gray TV trades alerts to Traderspost are withheld.
7. If you check "Do not LIVE sell any assets today" and update the alert, no Traderspost
8. As well as the Market Flow Dashboard, you can display a table of HLs, and LLs.
Trending stocks will display HLs and Vice Versa.
9. You can switch away from Big Rolling Waves Mode (default) to Intraday Short Moves mode
10. Default Big Wave Rolling Cycle is 120 bars (Recommended) 30,60,90,120 are typical.
(this affects the strategy profitability and choice of entry and exits).
11. Reference to FIFO is about the array size for the stored non-repainting HLs and LLs
12. Option to execute trades on unconfirmed bar is BETA. The strategy Only trades on
confirmed bars always, but I am wanting/hoping to eventually Take Profit on a
BIG ASS institutional candle, morning session bar when they occur.
(a new bar is unconfirmed, building, and tricky to code without
breaking the strategy's reliability). Use at your own risk.
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Technical Highlights
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• AI-inspired “Flow Confidence” through liquidity imbalance between Bull and Bear pressure.
• Adaptive KAMA smoothing for non-lag confirmation.
• Dynamic trailing take-profit computed as 80–87% of the highest profitable run-up.
• Non-repainting multi-timeframe framework (daily–weekly–monthly aggregation).
• LLL Table module for Lowest-Low progression and trend exhaustion.
• Market Flow Dashboard visualizing rolling liquidity dominance and delta pressure.
• Session-aware logic for intraday vs. swing operation.
• All logic has been tuned to peak performance that satisfies the TradingView Profiler.
• Strategy Buys again at a lower price instead of selling and taking a loss. Drawdown Peaks!
but this requires you configure TradingView Strategy Pyramiding orders to 2 or more
and % of equity.
(definitely is more $$ risky, potentially more profitable and might beat Buy and Hold profits)
See the chart above.
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WHY IT DOES NOT REPAINT (even thought the TradingView alert message says it might.)
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1. All trade, table, and OHLC updates occur only on `barstate.isconfirmed`
2. Synthetic HTFs are self-built without `lookahead` or future data
3. All arrays use `var` persistence to freeze past state
4. Trailing TakeProfit peak updates only on confirmed highs
5. No forward-referencing of real-time partial bars
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LIMITATIONS
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1. Heavy computation on long intraday histories (optimize `max_bars_back`)
2. Requires intraday chart resolution (1m–4h)
3. U.S. session defaults (09:30–16:00 ET); adjust for other exchanges
4. Arrays and tables consume memory – disable extra visuals if unneeded
5. Not for use with Crypto, Forex, or Futures.
6. Only to be used with Stocks/Tickers having volume data.
7. Live trading is coded for a TradersPost.io Webhook and a brokerage account. (IBKR)
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WARNINGS
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1. This is an Adaptive and Contrarian Trading strategy that scales into DEEP pullbacks,
rides long liquidity waves, and locks profit automatically.
2. Trades can have a long duration but are minimal. This is not a strategy that will
generate thousands of trades. It will save you on commissions to.
3. It does its best to limit losses and but I cannot guarantee it will work for
all assets, all the time. Market conditions vary. Tickers vary.
4. Use it with assets that you trust not to race to zero dollars.
5. Use this strategy with healthy tickers that have medium to high volatility.
6. To eliminate onscreen clutter, uncheck strategy settings/style/trade signals.
7. I use this strategy exclusively. TradingView alerts run for me 24/7 and ROBO trade.
but you should vet the system with manual trades signals it generates for yourself.
8. It does not prevent you from losing profits in after hours trading and Market News.
9. The BIG ASS new bar of opening candle is Not calculated into the stats until it is confirmed. Especially bothersome for me when its a big 10% down candle. You still need to watch the first 9:30 candle with your eyes. I recommend you watch liquidity at Open using a 1m timeframe.
10. This is a pro-grade coded strategy but is NOT a “Wall Street Quant grade.” strategy.
Institutions rely on:
• slippage models
• depth-of-book impact modeling
• latency simulation
• volume-weighted fills
• partial fills & queue priority
• order slicing (TWAP, VWAP, POV)
Pine Script cannot simulate the above.
11. This Pine Script strategy is market-internal (chart & volume) and for personal-use only. The code remains private to me.
12. To the full-time traders — my respect.
I live in the world of code, not charts, scalps, candles and screens,
so I engineered this 2500-line strategy to trade for me with un-emotional discipline, as you do.
If this strategy resonates with you, I provide it for you to use in the TradingView spirit of community. Backtested results are hypothetical and not indicative of future performance.
Nothing here constitutes investment advice.
Trading involves risk, and users must assume full responsibility for their trading decisions.
Remember, its not about making 'all' the money a stock theoretically could return as if you did a buy and hold many years ago - its about making good money as you navigate the waves of the stormy seas, and not sinking. It about making better trade decisions compared to the persons you are trading against. Have fun all the while making your money - work for you.
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“Be fearful when others are greedy, and be greedy when others are fearful.”
— Warren E. Buffett
“The stock market is a device for transferring money from the impatient to the patient.”
— Warren E. Buffett
True wealth grows through time, not reaction. A person sits in the shade today because
of a tree that somebody planted years ago.
— Warren E. Buffett
Happy Trading!
SigmaKernel - AdaptiveSigmaKernel - Adaptive Self-Optimizing Multi-Factor Trading System
SigmaKernel - Adaptive is a self-learning algorithmic trading strategy that combines four distinct analytical dimensions—momentum, market structure, volume flow, and reversal patterns—within a machine-learning-inspired framework that continuously adjusts its own parameters based on realized trading performance. Unlike traditional fixed-parameter strategies that maintain static weightings regardless of market conditions or results, this system implements a feedback loop that tracks which signal types, directional biases, and market conditions produce profitable outcomes, then mathematically adjusts component weightings, minimum score thresholds, position sizing multipliers, and trade spacing requirements to optimize future performance.
The strategy is designed for futures traders operating on prop firm accounts or live capital, incorporating realistic execution mechanics including configurable entry modes (stop breakout orders, limit pullback entries, or market-on-open), commission structures calibrated to retail futures contracts ($0.62 per contract default), one-tick slippage modeling, and professional risk controls including trailing drawdown guards, daily loss limits, and weekly profit targets. The system features universal futures compatibility—it automatically detects and adapts to any futures contract by reading the instrument's tick size and point value directly from the chart, eliminating the need for manual configuration across different markets.
What Makes This Approach Different
Adaptive Weight Optimization System
The core differentiation is the adaptive learning architecture. The strategy maintains four independent scoring components: momentum analysis (using RSI multi-timeframe, MACD histogram, and DMI/ADX), market structure detection (breakout identification via pivot-based support/resistance and moving average positioning), volume flow analysis (Volume Price Trend indicator with standard deviation confirmation), and reversal pattern recognition (oversold/overbought conditions combined with structural levels).
Each component generates a directional score that is multiplied by its current weight. After every closed trade, the system performs a retrospective analysis on the last N trades (configurable Learning Period, default 15 trades) to calculate win rates for each signal type independently. For example, if momentum-driven trades won 65% of the time while reversal trades won only 35%, the adaptive algorithm increases the momentum weight and decreases the reversal weight proportionally. The adjustment formula is:
New_Weight = Current_Weight + (Component_Win_Rate - Average_Win_Rate) × Adaptation_Speed
This creates a self-correcting mechanism where successful signal generators receive more influence in future composite scores, while underperforming components are de-emphasized. The system separately tracks long versus short win rates and applies directional bias corrections—if shorts consistently outperform longs, the strategy applies a 10% reduction to bullish signals to prevent fighting the prevailing market character.
Dynamic Parameter Adjustment
Beyond component weightings, three critical strategy parameters self-adjust based on performance:
Minimum Signal Score: The threshold required to trigger a trade. If overall win rate falls below 45%, the system increments this threshold by 0.10 per adjustment cycle, making the strategy more selective. If win rate exceeds 60%, the threshold decreases to allow more opportunities. This prevents the strategy from overtrading during unfavorable conditions and capitalizes on high-probability environments.
Risk Multiplier: Controls position sizing aggression. When drawdown exceeds 5%, risk per trade reduces by 10% per cycle. When drawdown falls below 2%, risk increases by 5% per cycle. This implements the professional risk management principle of "bet small when losing, bet bigger when winning" algorithmically.
Bars Between Trades: Spacing filter to prevent overtrading. Base value (default 9 bars) multiplies by drawdown factor and losing streak factor. During drawdown or consecutive losses, spacing expands up to 2x to allow market conditions to change before re-entering.
All adaptation operates during live forward-testing or real trading—there is no in-sample optimization applied to historical data. The system learns solely from its own realized trades.
Universal Futures Compatibility
The strategy implements universal futures instrument detection that automatically adapts to any futures contract without requiring manual configuration. Instead of hardcoding specific contract specifications, the system reads three critical values directly from TradingView's symbol information:
Tick Size Detection: Uses `syminfo.mintick` to obtain the minimum price increment for the current instrument. This value varies widely across markets—ES trades in 0.25 ticks, crude oil (CL) in 0.01 ticks, gold (GC) in 0.10 ticks, and treasury futures (ZB) in increments of 1/32nds. The strategy adapts all entry buffer calculations and stop placement logic to the detected tick size.
Point Value Detection: Uses `syminfo.pointvalue` to determine the dollar value per full point of price movement. For ES, one point equals $50; for crude oil, one point equals $1,000; for gold, one point equals $100. This automatic detection ensures accurate P&L calculations and risk-per-contract measurements across all instruments.
Tick Value Calculation: Combines tick size and point value to compute dollar value per tick: Tick_Value = Tick_Size × Point_Value. This derived value drives all position sizing calculations, ensuring the risk management system correctly accounts for each instrument's economic characteristics.
This universal approach means the strategy functions identically on emini indices (ES, MES, NQ, MNQ), micro indices, energy contracts (CL, NG, RB), metals (GC, SI, HG), agricultural futures (ZC, ZS, ZW), treasury futures (ZB, ZN, ZF), currency futures (6E, 6J, 6B), and any other futures contract available on TradingView. No parameter adjustments or instrument-specific branches exist in the code—the adaptation happens automatically through symbol information queries.
Stop-Out Rate Monitoring System
The strategy includes an intelligent stop-out rate tracking system that monitors the percentage of your last 20 trades (or available trades if fewer than 20) that were stopped out. This metric appears in the dashboard's Performance section with color-coded guidance:
Green (<30% stop-out rate): Very few trades are being stopped out. This suggests either your stops are too loose (giving back profits on reversals) or you're in an exceptional trending market. Consider tightening your Stop Loss ATR multiplier to lock in profits more efficiently.
Orange (30-65% stop-out rate): Healthy range. Your stop placement is appropriately sized for current market conditions and the strategy's risk-reward profile. No adjustment needed.
Red (>65% stop-out rate): Too many trades are being stopped out prematurely. Your stops are likely too tight for the current volatility regime. Consider widening your Stop Loss ATR multiplier to give trades more room to develop.
Critical Design Philosophy: Unlike some systems that automatically adjust stops based on performance statistics, this strategy intentionally keeps stop-loss control in the user's hands. Automatic stop adjustment creates dangerous feedback loops—widening stops increases risk per contract, which forces position size reduction, which distorts performance metrics, leading to incorrect adaptations. Instead, the dashboard provides visibility into stop performance, empowering you to make informed manual adjustments when warranted. This preserves the integrity of the adaptive system while giving you the critical data needed for stop optimization.
Execution Kernel Architecture
The entry system offers three distinct execution modes to match trader preference and market character:
StopBreakout Mode: Places buy-stop orders above the prior bar's high (for longs) or sell-stop orders below the prior bar's low (for shorts), plus a 2-tick buffer. This ensures entries only occur when price confirms directional momentum by breaking recent structure. Ideal for trending and momentum-driven markets.
LimitPullback Mode: Places limit orders at a pullback price calculated as: Entry_Price = Close - (ATR × Pullback_Multiplier) for longs, or Close + (ATR × Pullback_Multiplier) for shorts. Default multiplier is 0.5 ATR. This waits for mean-reversion before entering in the signal direction, capturing better prices in volatile or oscillating markets.
MarketNextOpen Mode: Executes at market on the bar immediately following signal generation. This provides fastest execution but sacrifices the filtering effect of requiring price confirmation.
All pending entry orders include a configurable Time-To-Live (TTL, default 6 bars). If an order is not filled within the TTL period, it cancels automatically to prevent stale signals from executing in changed market conditions.
Professional Exit Management
The exit system implements a three-stage progression: initial stop loss, breakeven adjustment, and dynamic trailing stop.
Initial Stop Loss: Calculated as entry price ± (ATR × User_Stop_Multiplier × Volatility_Adjustment). Users have direct control via the Stop Loss ATR multiplier (default 1.25). The system then applies volatility regime adjustments: ×1.2 in high-volatility environments (stops automatically widen), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. This ensures stops adapt to market character while maintaining user control over baseline risk tolerance.
Breakeven Trigger: When profit reaches a configurable multiple of initial risk (default 1.0R), the stop loss automatically moves to breakeven (entry price). This locks in zero-loss status once the trade demonstrates favorable movement.
Trailing Stop Activation: When profit reaches the Trail_Trigger_R multiple (default 1.2R), the system cancels the fixed stop and activates a dynamic trailing stop. The trail uses Step and Offset parameters defined in R-multiples. For example, with Trail_Offset_R = 1.0 and Trail_Step_R = 1.5, the stop trails 1.0R behind price and moves in 1.5R increments. This captures extended moves while protecting accumulated profit.
Additional failsafes include maximum time-in-trade (exits after N bars if specified) and end-of-session flatten (automatically closes all positions X minutes before session end to avoid overnight exposure).
Core Calculation Methodology
Signal Component Scoring
Momentum Component:
- Calculates 14-period DMI (Directional Movement Index) with ADX strength filter (trending when ADX > 25)
- Computes three RSI timeframes: fast (7-period), medium (14-period), slow (21-period)
- Analyzes MACD (12/26/9) histogram for directional acceleration
- Bullish momentum: uptrend (DI+ > DI- with ADX > 25) + MACD histogram rising above zero + RSI fast between 50-80 = +1.6 score
- Bearish momentum: downtrend (DI- > DI+ with ADX > 25) + MACD histogram falling below zero + RSI fast between 20-50 = -1.6 score
- Score multiplies by volatility adjustment factor: ×0.8 in high volatility (momentum less reliable), ×1.2 in low volatility (momentum more persistent)
Structure Component:
- Identifies swing highs and lows using 10-bar pivot lookback on both sides
- Maintains most recent swing high as dynamic resistance, most recent swing low as dynamic support
- Detects breakouts: bullish when close crosses above resistance with prior bar below; bearish when close crosses below support with prior bar above
- Breakout score: ±1.0 for confirmed break
- Moving average alignment: +0.5 when price > SMA20 > SMA50 (bullish structure); -0.5 when price < SMA20 < SMA50 (bearish structure)
- Total structure range: -1.5 to +1.5
Volume Component:
- Calculates Volume Price Trend: VPT = Σ [(Close - Close ) / Close × Volume]
- Compares VPT to its 10-period EMA as signal line (similar to MACD logic)
- Computes 20-period volume moving average and standard deviation
- High volume event: current volume > (volume_average + 1× std_dev)
- Bullish volume: VPT > VPT_signal AND high_volume = +1.0
- Bearish volume: VPT < VPT_signal AND high_volume = -1.0
- No score if volume is not elevated (filters out low-conviction moves)
Reversal Component:
- Identifies extreme RSI conditions: RSI slow < 30 (oversold) or > 70 (overbought)
- Requires structural confluence: price at or below support level for bullish reversal; at or above resistance for bearish reversal
- Requires momentum shift: RSI fast must be rising (for bull) or falling (for bear) to confirm reversal in progress
- Bullish reversal: RSI < 30 AND price ≤ support AND RSI rising = +1.0
- Bearish reversal: RSI > 70 AND price ≥ resistance AND RSI falling = -1.0
Composite Score Calculation
Final_Score = (Momentum × Weight_M) + (Structure × Weight_S) + (Volume × Weight_V) + (Reversal × Weight_R)
Initial weights: Momentum = 1.0, Structure = 1.2, Volume = 0.8, Reversal = 0.6
These weights adapt after each trade based on component-specific performance as described above.
The system also applies directional bias adjustment: if recent long trades have significantly lower win rate than shorts, bullish scores multiply by 0.9 to reduce aggressive long entries. Vice versa for underperforming shorts.
Position Sizing Algorithm
The position sizing calculation incorporates multiple confidence factors and automatically scales to any futures contract:
1. Base risk amount = Account_Size × Base_Risk_Percent × Adaptive_Risk_Multiplier
2. Stop distance in price units = ATR × User_Stop_Multiplier × Volatility_Regime_Multiplier × Entry_Buffer
3. Risk per contract = Stop_Distance × Dollar_Per_Point (automatically detected from instrument)
4. Raw position size = Risk_Amount / Risk_Per_Contract
Then applies confidence scaling:
- Signal confidence = min(|Weighted_Score| / Min_Score_Threshold, 2.0) — higher scores receive larger size, capped at 2×
- Direction confidence = Long_Win_Rate (for bulls) or Short_Win_Rate (for bears)
- Type confidence = Win_Rate of dominant signal type (momentum/structure/volume/reversal)
- Total confidence = (Signal_Confidence + Direction_Confidence + Type_Confidence) / 3
Adjusted size = Raw_Size × Total_Confidence × Losing_Streak_Reduction
Losing streak reduction = 0.5 if losing_streak ≥ 5, otherwise 1.0
Universal Maximum Position Calculation: Instead of hardcoded limits per instrument, the system calculates maximum position size as: Max_Contracts = Account_Size / 25000, clamped between 1 and 10 contracts. This means a $50,000 account allows up to 2 contracts, a $100,000 account allows up to 4 contracts, regardless of which futures contract is being traded. This universal approach maintains consistent risk exposure across different instruments while preventing overleveraging.
Final size is rounded to integer and bounded by the calculated maximum.
Session and Risk Management System
Timezone-Aware Session Control
The strategy implements timezone-correct session filtering. Users specify session start hour, end hour, and timezone from 12 supported zones (New York, Chicago, Los Angeles, London, Frankfurt, Moscow, Tokyo, Hong Kong, Shanghai, Singapore, Sydney, UTC). The system converts bar timestamps to the selected timezone before applying session logic.
For split sessions (e.g., Asian session 18:00-02:00), the logic correctly handles time wraparound. Weekend trading can be optionally disabled (default: disabled) to avoid low-liquidity weekend price action.
Multi-Layer Risk Controls
Daily Loss Limit: Strategy ceases all new entries when daily P&L reaches negative threshold (default $2,000). This prevents catastrophic drawdown days. Resets at timezone-corrected day boundary.
Weekly Profit Target: Strategy ceases trading when weekly profit reaches target (default $10,000). This implements the professional principle of "take the win and stop pushing luck." Resets on timezone-corrected Monday.
Maximum Daily Trades: Hard cap on entries per day (default 20) to prevent overtrading during volatile conditions when many signals may generate.
Trailing Drawdown Guard: Optional prop-firm-style trailing stop on account equity. When enabled, if equity drops below (Peak_Equity - Trailing_DD_Amount), all trading halts. This simulates the common prop firm rule where exceeding trailing drawdown results in account termination.
All limits display status in the real-time dashboard, showing "MAX LOSS HIT", "WEEKLY TARGET MET", or "ACTIVE" depending on current state.
How To Use This Strategy
Initial Setup
1. Apply the strategy to your desired futures chart (tested on 5-minute through daily timeframes)
2. The strategy will automatically detect your instrument's specifications—no manual configuration needed for different contracts
3. Configure your account size and risk parameters in the Core Settings section
4. Set your trading session hours and timezone to match your availability
5. Adjust the Stop Loss ATR multiplier based on your risk tolerance (0.8-1.2 for tighter stops, 1.5-2.5 for wider stops)
6. Select your preferred entry execution mode (recommend StopBreakout for beginners)
7. Enable adaptation (recommended) or disable for fixed-parameter operation
8. Review the strategy's Properties in the Strategy Tester settings and verify commission/slippage match your broker's actual costs
The universal futures detection means you can switch between ES, NQ, CL, GC, ZB, or any other futures contract without changing any strategy parameters—the system will automatically adapt its calculations to each instrument's unique specifications.
Dashboard Interpretation
The strategy displays a comprehensive real-time dashboard in the top-right corner showing:
Market State Section:
- Trend: Shows UPTREND/DOWNTREND/CONSOLIDATING/NEUTRAL based on ADX and DMI analysis
- ADX Value: Current trend strength (>25 = strong trend, <20 = consolidating)
- Momentum: BULL/BEAR/NEUTRAL classification with current momentum score
- Volatility: HIGH/LOW/NORMAL regime with ATR percentage of price
Volume Profile Section (Large dashboard only):
- VPT Flow: Directional bias from volume analysis
- Volume Status: HIGH/LOW/NORMAL with relative volume multiplier
Performance Section:
- Daily P&L: Current day's profit/loss with color coding
- Daily Trades: Number of completed trades today
- Weekly P&L: Current week's profit/loss
- Target %: Progress toward weekly profit target
- Stop-Out Rate: Percentage of last 20 trades (or available trades if <20) that were stopped out. Includes all stop types: initial stops, breakeven stops, trailing stops, timeout exits, and EOD flattens. Color coded with actionable guidance:
- Green (<30%): Shows "TIGHTEN" guidance. Very few stop-outs suggests stops may be too loose or exceptional market conditions. Consider reducing Stop Loss ATR multiplier.
- Orange (30-65%): Shows "OK" guidance. Healthy stop-out rate indicating appropriate stop placement for current conditions.
- Red (>65%): Shows "WIDEN" guidance. Too many premature stop-outs. Consider increasing Stop Loss ATR multiplier to give trades more room.
- Status: Overall trading status (ACTIVE/MAX LOSS HIT/WEEKLY TARGET MET/FILTERS ACTIVE)
Adaptive Engine Section:
- Min Score: Current minimum threshold for trade entry (higher = more selective)
- Risk Mult: Current position sizing multiplier (adjusts with performance)
- Bars BTW: Current minimum bars required between trades
- Drawdown: Current drawdown percentage from equity peak
- Weights: M/S/V/R showing current component weightings
Win Rates Section:
- Type: Win rates for Momentum, Structure, Volume, Reversal signal types
- Direction: Win rates for Long vs Short trades
Color coding shows green for >50% win rate, red for <50%
Session Info Section:
- Session Hours: Active trading window with timezone
- Weekend Trading: ENABLED/DISABLED status
- Session Status: ACTIVE/INACTIVE based on current time
Signal Generation and Entry
The strategy generates entries when the weighted composite score exceeds the adaptive minimum threshold (initial value configurable, typically 1.5 to 2.5). Entries display as layered triangle markers on the chart:
- Long Signal: Three green upward triangles below the entry bar
- Short Signal: Three red downward triangles above the entry bar
Triangle tooltip shows the signal score and dominant signal type (MOMENTUM/STRUCTURE/VOLUME/REVERSAL).
Position Management and Stop Optimization
Once entered, the strategy automatically manages the position through its three-stage exit system. Monitor the Stop-Out Rate metric in the dashboard to optimize your stop placement:
If Stop-Out Rate is Green (<30%): You're rarely being stopped out. This could mean:
- Your stops are too loose, allowing trades to give back too much profit on reversals
- You're in an exceptional trending market where tight stops would work better
- Action: Consider reducing your Stop Loss ATR multiplier by 0.1-0.2 to tighten stops and lock in profits more efficiently
If Stop-Out Rate is Orange (30-65%): Optimal range. Your stops are appropriately sized for the strategy's risk-reward profile and current market volatility. No adjustment needed.
If Stop-Out Rate is Red (>65%): You're being stopped out too frequently. This means:
- Your stops are too tight for current market volatility
- Trades need more room to develop before reaching profit targets
- Action: Increase your Stop Loss ATR multiplier by 0.1-0.3 to give trades more breathing room
Remember: The stop-out rate calculation includes all exit types (initial stops, breakeven stops, trailing stops, timeouts, EOD flattens). A trade that reaches breakeven and gets stopped out at entry price counts as a stop-out, even though it didn't lose money. This is intentional—it indicates the stop placement didn't allow the trade to develop into profit.
Optimization Workflow
For traders wanting to customize the strategy for their specific instrument and timeframe:
Week 1-2: Run with defaults, adaptation enabled
Allow the system to execute at least 30-50 trades (the Learning Period plus additional buffer). Monitor which session periods, signal types, and market conditions produce the best results. Observe your stop-out rate—if it's consistently red or green, plan to adjust Stop Loss ATR multiplier after the learning period. Do not adjust parameters yet—let the adaptive system establish baseline performance data.
Week 3-4: Analyze adaptation behavior and optimize stops
Review the dashboard's adaptive weights and win rates. If certain signal types consistently show <40% win rate, consider slightly reducing their base weight. If a particular entry mode produces better fill quality and win rate, switch to that mode. If you notice the minimum score threshold has climbed very high (>3.0), market conditions may not suit the strategy's logic—consider switching instruments or timeframes.
Based on your Stop-Out Rate observations:
- Consistently <30%: Reduce Stop Loss ATR multiplier by 0.2-0.3
- Consistently >65%: Increase Stop Loss ATR multiplier by 0.2-0.4
- Oscillating between zones: Leave stops at default and let volatility regime adjustments handle it
Ongoing: Fine-tune risk and execution
Adjust the following based on your risk tolerance and account type:
- Base Risk Per Trade: 0.5% for conservative, 0.75% for moderate, 1.0% for aggressive
- Stop Loss ATR Multiplier: 0.8-1.2 for tight stops (scalping), 1.5-2.5 for wide stops (swing trading)
- Bars Between Trades: Lower (5-7) for more opportunities, higher (12-20) for more selective
- Entry Mode: Experiment between modes to find best fit for current market character
- Session Hours: Narrow to specific high-performance session windows if certain hours consistently underperform
Never adjust: Do not manually modify the adaptive weights, minimum score, or risk multiplier after the system has begun learning. These parameters are self-optimizing and manual interference defeats the adaptive mechanism.
Parameter Descriptions and Optimization Guidelines
Adaptive Intelligence Group
Enable Self-Optimization (default: true): Master switch for the adaptive learning system. When enabled, component weights, minimum score, risk multiplier, and trade spacing adjust based on realized performance. Disable to run the strategy with fixed parameters (useful for comparing adaptive vs non-adaptive performance).
Learning Period (default: 15 trades): Number of most recent trades to analyze for performance calculations. Shorter values (10-12) adapt more quickly to recent conditions but may overreact to variance. Longer values (20-30) produce more stable adaptations but respond slower to regime changes. For volatile markets, use shorter periods. For stable trends, use longer periods.
Adaptation Speed (default: 0.25): Controls the magnitude of parameter adjustments per learning cycle. Lower values (0.05-0.15) make gradual, conservative changes. Higher values (0.35-0.50) make aggressive adjustments. Faster adaptation helps in rapidly changing markets but increases parameter instability. Start with default and increase only if you observe the system failing to adapt quickly enough to obvious performance patterns.
Performance Memory (default: 100 trades): Maximum number of historical trades stored for analysis. This array size does not affect learning (which uses only Learning Period trades) but provides data for future analytics features including stop-out rate tracking. Higher values consume more memory but provide richer historical dataset. Typical users should not need to modify this.
Core Settings Group
Account Size (default: $50,000): Starting capital for position sizing calculations. This should match your actual account size for accurate risk per trade. The strategy uses this value to calculate dollar risk amounts and determine maximum position size (1 contract per $25,000).
Weekly Profit Target (default: $10,000): When weekly P&L reaches this value, the strategy stops taking new trades for the remainder of the week. This implements a "quit while ahead" rule common in professional trading. Set to a realistic weekly goal—20% of account size per week ($10K on $50K) is very aggressive; 5-10% is more sustainable.
Max Daily Loss (default: $2,000): When daily P&L reaches this negative threshold, strategy stops all new entries for the day. This is your maximum acceptable daily loss. Professional traders typically set this at 2-4% of account size. A $2,000 loss on a $50,000 account = 4%.
Base Risk Per Trade % (default: 0.5%): Initial percentage of account to risk on each trade before adaptive multiplier and confidence scaling. 0.5% is conservative, 0.75% is moderate, 1.0-1.5% is aggressive. Remember that actual risk per trade = Base Risk × Adaptive Risk Multiplier × Confidence Factors, so the realized risk will vary.
Trade Filters Group
Base Minimum Signal Score (default: 1.5): Initial threshold that composite weighted score must exceed to generate a signal. Lower values (1.0-1.5) produce more trades with lower average quality. Higher values (2.0-3.0) produce fewer, higher-quality setups. This value adapts automatically when adaptive mode is enabled, but the base sets the starting point. For trending markets, lower values work well. For choppy markets, use higher values.
Base Bars Between Trades (default: 9): Minimum bars that must elapse after an entry before another signal can trigger. This prevents overtrading and allows previous trades time to develop. Lower values (3-6) suit scalping on lower timeframes. Higher values (15-30) suit swing trading on higher timeframes. This value also adapts based on drawdown and losing streaks.
Max Daily Trades (default: 20): Hard limit on total trades per day regardless of signal quality. This prevents runaway trading during extremely volatile days when many signals may generate. For 5-minute charts, 20 trades/day is reasonable. For 1-hour charts, 5-10 trades/day is more typical.
Session Group
Session Start Hour (default: 5): Hour (0-23 format) when trading is allowed to begin, in the timezone specified. For US futures trading in Chicago time, session typically starts at 5:00 or 6:00 PM (17:00 or 18:00) Sunday evening.
Session End Hour (default: 17): Hour when trading stops and no new entries are allowed. For US equity index futures, regular session ends at 4:00 PM (16:00) Central Time.
Allow Weekend Trading (default: false): Whether strategy can trade on Saturday/Sunday. Most futures have low volume on weekends; keeping this disabled is recommended unless you specifically trade Sunday evening open.
Session Timezone (default: America/Chicago): Timezone for session hour interpretation. Select your local timezone or the timezone of your instrument's primary exchange. This ensures session logic aligns with your intended trading hours.
Prop Guards Group
Trailing Drawdown Guard (default: false): Enables prop-firm-style trailing maximum drawdown. When enabled, if equity drops below (Peak Equity - Trailing DD Amount), all trading halts for the remainder of the backtest/live session. This simulates rules used by funded trader programs where exceeding trailing drawdown terminates the account.
Trailing DD Amount (default: $2,500): Dollar amount of drawdown allowed from equity peak. If your equity reaches $55,000, the trailing stop sets at $52,500. If equity then drops to $52,499, the guard triggers and trading ceases.
Execution Kernel Group
Entry Mode (default: StopBreakout):
- StopBreakout: Places stop orders above/below signal bar requiring price confirmation
- LimitPullback: Places limit orders at pullback prices seeking better fills
- MarketNextOpen: Executes immediately at market on next bar
Limit Offset (default: 0.5x ATR): For LimitPullback mode, how far below/above current price to place the limit order. Smaller values (0.3-0.5) seek minor pullbacks. Larger values (0.8-1.2) wait for deeper retracements but may miss trades.
Entry TTL (default: 6 bars, 0=off): Bars an entry order remains pending before cancelling. Shorter values (3-4) keep signals fresh. Longer values (8-12) allow more time for fills but risk executing stale signals. Set to 0 to disable TTL (orders remain active indefinitely until filled or opposite signal).
Exits Group
Stop Loss (default: 1.25x ATR): Base stop distance as a multiple of the 14-period ATR. This is your primary risk control parameter and directly impacts your stop-out rate. Lower values (0.8-1.0) create tighter stops that reduce risk per trade but may get stopped out prematurely in volatile conditions—expect stop-out rates above 65% (red zone). Higher values (1.5-2.5) give trades more room to breathe but increase risk per contract—expect stop-out rates below 30% (green zone). The system applies additional volatility regime adjustments on top of this base: ×1.2 in high volatility environments (stops widen automatically), ×0.8 in low volatility (stops tighten), ×1.0 in normal conditions. For scalping on lower timeframes, use 0.8-1.2. For swing trading on higher timeframes, use 1.5-2.5. Monitor the Stop-Out Rate metric in the dashboard and adjust this parameter to keep it in the healthy 30-65% orange zone.
Move to Breakeven at (default: 1.0R): When profit reaches this multiple of initial risk, stop moves to breakeven. 1.0R means after price moves in your favor by the distance you risked, you're protected at entry price. Lower values (0.5-0.8R) lock in breakeven faster. Higher values (1.5-2.0R) allow more room before protection.
Start Trailing at (default: 1.2R): When profit reaches this multiple, the fixed stop transitions to a dynamic trailing stop. This should be greater than the BE trigger. Values typically range 1.0-2.0R depending on how much profit you want secured before trailing activates.
Trail Offset (default: 1.0R): How far behind price the trailing stop follows. Tighter offsets (0.5-0.8R) protect profit more aggressively but may exit prematurely. Wider offsets (1.5-2.5R) allow more room for profit to run but risk giving back more on reversals.
Trail Step (default: 1.5R): How far price must move in profitable direction before the stop advances. Smaller steps (0.5-1.0R) move the stop more frequently, tightening protection continuously. Larger steps (2.0-3.0R) move the stop less often, giving trades more breathing room.
Max Bars In Trade (default: 0=off): Maximum bars allowed in a position before forced exit. This prevents trades from "going stale" during periods of no meaningful price action. For 5-minute charts, 50-100 bars (4-8 hours) is reasonable. For daily charts, 5-10 bars (1-2 weeks) is typical. Set to 0 to disable.
Flatten near Session End (default: true): Whether to automatically close all positions as session end approaches. Recommended to avoid carrying positions into off-hours with low liquidity.
Minutes before end (default: 5): How many minutes before session end to flatten. 5-15 minutes provides buffer for order execution before the session boundary.
Visual Effects Configuration Group
Dashboard Size (default: Normal): Controls information density in the dashboard. Small shows only critical metrics (excludes stop-out rate). Normal shows comprehensive data including stop-out rate. Large shows all available metrics including weights, session info, and volume analysis. Larger sizes consume more screen space but provide complete visibility.
Show Quantum Field (default: true): Displays animated grid pattern on the chart indicating market state. Disable if you prefer cleaner charts or experience performance issues on lower-end hardware.
Show Wick Pressure Lines (default: true): Draws dynamic lines from bars with extreme wicks, indicating potential support/resistance or liquidity absorption zones. Disable for simpler visualization.
Show Morphism Energy Beams (default: true): Displays directional beams showing momentum energy flow. Beams intensify during strong trends. Disable if you find this visually distracting.
Show Order Flow Clouds (default: true): Draws translucent boxes representing volume flow bullish/bearish bias. Disable for cleaner price action visibility.
Show Fractal Grid (default: true): Displays multi-timeframe support/resistance levels based on fractal price structure at 10/20/30/40/50 bar periods. Disable if you only want to see primary pivot levels.
Glow Intensity (default: 4): Controls the brightness and thickness of visual effects. Lower values (1-2) for subtle visualization. Higher values (7-10) for maximum visibility but potentially cluttered charts.
Color Theme (default: Cyber): Visual color scheme. Cyber uses cyan/magenta futuristic colors. Quantum uses aqua/purple. Matrix uses green/red terminal style. Aurora uses pastel pink/purple gradient. Choose based on personal preference and monitor calibration.
Show Watermark (default: true): Displays animated watermark at bottom of chart with creator credit and current P&L. Disable if you want completely clean charts or need screen space.
Performance Characteristics and Best Use Cases
Optimal Conditions
This strategy performs best in markets exhibiting:
Trending phases with periodic pullbacks: The combination of momentum and structure components excels when price establishes directional bias but provides retracement opportunities for entries. Markets with 60-70% trending bars and 30-40% consolidation produce the highest win rates.
Medium to high volatility: The ATR-based stop sizing and dynamic risk adjustment require sufficient price movement to generate meaningful profit relative to risk. Instruments with 2-4% daily ATR relative to price work well. Extremely low volatility (<1% daily ATR) generates too many scratch trades.
Clear volume patterns: The VPT volume component adds significant edge when volume expansions align with directional moves. Instruments and timeframes where volume data reflects actual transaction flow (versus tick volume proxies) perform better.
Regular session structure: Futures markets with defined opening and closing hours, consistent liquidity throughout the session, and clear overnight/day session separation allow the session controls and time-based failsafes to function optimally.
Sufficient liquidity for stop execution: The stop breakout entry mode requires that stop orders can fill without significant slippage. Highly liquid contracts work better than illiquid instruments where stop orders may face adverse fills.
Suboptimal Conditions
The strategy may struggle with:
Extreme chop with no directional persistence: When ADX remains below 15 for extended periods and price oscillates rapidly without establishing trends, the momentum component generates conflicting signals. Win rate typically drops below 40% in these conditions, triggering the adaptive system to increase minimum score thresholds until conditions improve. Stop-out rates may also spike into the red zone.
Gap-heavy instruments: Markets with frequent overnight gaps disrupt the continuous price assumptions underlying ATR stops and EMA-based structure analysis. Gaps can also cause stop orders to fill at prices far from intended levels, distorting stop-out rate metrics.
Very low timeframes with excessive noise: On 1-minute or tick charts, the signal components react to micro-structure noise rather than meaningful price swings. The strategy works best on 5-minute through daily timeframes where price movements reflect actual order flow shifts.
Extended low-volatility compression: During historically low volatility periods, profit targets become difficult to reach before mean-reversion occurs. The trail offset, even when set to minimum, may be too wide for the compressed price environment. Stop-out rates may drop to green zone indicating stops should be tightened.
Parabolic moves or climactic exhaustion: Vertical price advances or selloffs where price moves multiple ATRs in single bars can trigger momentum signals at exhaustion points. The structure and reversal components attempt to filter these, but extreme moves may override normal logic.
The adaptive learning system naturally reduces signal frequency and position sizing during unfavorable conditions. If you observe multiple consecutive days with zero trades and "FILTERS ACTIVE" status, this indicates the strategy has self-adjusted to avoid poor conditions rather than forcing trades.
Instrument Recommendations
Emini Index Futures (ES, MES, NQ, MNQ, YM, RTY): Excellent fit. High liquidity, clear volatility patterns, strong volume signals, defined session structure. These instruments have been extensively tested and the universal detection handles all contract specifications automatically.
Micro Index Futures (MES, MNQ, M2K, MYM): Excellent fit for smaller accounts. Same market characteristics as the standard eminis but with reduced contract sizes allowing proper risk management on accounts below $50,000.
Energy Futures (CL, NG, RB, HO): Good to mixed fit. Crude oil (CL) works well due to strong trends and reasonable volatility. Natural gas (NG) can be extremely volatile—consider reducing Base Risk to 0.3-0.4% and increasing Stop Loss ATR multiplier to 1.8-2.2 for NG. The strategy automatically detects the $10/tick value for CL and adjusts position sizing accordingly.
Metal Futures (GC, SI, HG, PL): Good fit. Gold (GC) and silver (SI) exhibit clear trending behavior and work well with the momentum/structure components. The strategy automatically handles the different point values ($100/point for gold, $5,000/point for silver).
Agricultural Futures (ZC, ZS, ZW, ZL): Good fit. Grain futures often trend strongly during seasonal periods. The strategy handles the unique tick sizes (1/4 cent increments) and point values ($50/point for corn/wheat, $60/point for soybeans) automatically.
Treasury Futures (ZB, ZN, ZF, ZT): Good fit for trending rates environments. The strategy automatically handles the fractional tick sizing (32nds for ZB/ZN, halves of 32nds for ZF/ZT) through the universal detection system.
Currency Futures (6E, 6J, 6B, 6A, 6C): Good fit. Major currency pairs exhibit smooth trending behavior. The strategy automatically detects point values which vary significantly ($12.50/tick for 6E, $12.50/tick for 6J, $6.25/tick for 6B).
Cryptocurrency Futures (BTC, ETH, MBT, MET): Mixed fit. These markets have extreme volatility requiring parameter adjustment. Increase Base Risk to 0.8-1.2% and Stop Loss ATR multiplier to 2.0-3.0 to account for wider stop distances. Enable 24-hour trading and weekend trading as these markets have no traditional sessions.
The universal futures compatibility means you can apply this strategy to any of these markets without code modification—simply open the chart of your desired contract and the strategy will automatically configure itself to that instrument's specifications.
Important Disclaimers and Realistic Expectations
This is a sophisticated trading strategy that combines multiple analytical methods within an adaptive framework designed for active traders who will monitor performance and market conditions. It is not a "set and forget" fully automated system, nor should it be treated as a guaranteed profit generator.
Backtesting Realism and Limitations
The strategy includes realistic trading costs and execution assumptions:
- Commission: $0.62 per contract per side (accurate for many retail futures brokers)
- Slippage: 1 tick per entry and exit (conservative estimate for liquid futures)
- Position sizing: Realistic risk percentages and maximum contract limits based on account size
- No repainting: All calculations use confirmed bar data only—signals do not change retroactively
However, backtesting cannot fully capture live trading reality:
- Order fill delays: In live trading, stop and limit orders may not fill instantly at the exact tick shown in backtest
- Volatile periods: During high volatility or low liquidity (news events, rollover days, pre-holidays), slippage may exceed the 1-tick assumption significantly
- Gap risk: The backtest assumes stops fill at stop price, but gaps can cause fills far beyond intended exit levels
- Psychological factors: Seeing actual capital at risk creates emotional pressures not present in backtesting, potentially leading to premature manual intervention
The strategy's backtest results should be viewed as best-case scenarios. Real trading will typically produce 10-30% lower returns than backtest due to the above factors.
Risk Warnings
All trading involves substantial risk of loss. The adaptive learning system can improve parameter selection over time, but it cannot predict future price movements or guarantee profitable performance. Past wins do not ensure future wins.
Losing streaks are inevitable. Even with a 60% win rate, you will encounter sequences of 5, 6, or more consecutive losses due to normal probability distributions. The strategy includes losing streak detection and automatic risk reduction, but you must have sufficient capital to survive these drawdowns.
Market regime changes can invalidate learned patterns. If the strategy learns from 50 trades during a trending regime, then the market shifts to a ranging regime, the adapted parameters may initially be misaligned with the new environment. The system will re-adapt, but this transition period may produce suboptimal results.
Prop firm traders: understand your specific rules. Every prop firm has different rules regarding maximum drawdown, daily loss limits, consistency requirements, and prohibited trading behaviors. While this strategy includes common prop guardrails, you must verify it complies with your specific firm's rules and adjust parameters accordingly.
Never risk capital you cannot afford to lose. This strategy can produce substantial drawdowns, especially during learning periods or market regime shifts. Only trade with speculative capital that, if lost, would not impact your financial stability.
Recommended Usage
Paper trade first: Run the strategy on a simulated account for at least 50 trades or 1 month before committing real capital. Observe how the adaptive system behaves, identify any patterns in losing trades, monitor your stop-out rate trends, and verify your understanding of the entry/exit mechanics.
Start with minimum position sizing: When transitioning to live trading, reduce the Base Risk parameter to 0.3-0.4% initially (vs 0.5-1.0% in testing) to reduce early impact while the system learns your live broker's execution characteristics.
Monitor daily, but do not micromanage: Check the dashboard daily to ensure the strategy is operating normally and risk controls have not triggered unexpectedly. Pay special attention to the Stop-Out Rate metric—if it remains in the red or green zones for multiple days, adjust your Stop Loss ATR multiplier accordingly. However, resist the urge to manually adjust adaptive weights or disable trades based on short-term performance. Allow the adaptive system at least 30 trades to establish patterns before making manual changes.
Combine with other analysis: While this strategy can operate standalone, professional traders typically use systematic strategies as one component of a broader approach. Consider using the strategy for trade execution while applying your own higher-timeframe analysis or fundamental view for trade filtering or sizing adjustments.
Keep a trading journal: Document each week's results, note market conditions (trending vs ranging, high vs low volatility), record stop-out rates and any Stop Loss ATR adjustments you made, and document any manual interventions. Over time, this journal will help you identify conditions where the strategy excels versus struggles, allowing you to selectively enable or disable trading during certain environments.
Technical Implementation Notes
All calculations execute on closed bars only (`calc_on_every_tick=false`) ensuring that signals and values do not repaint. Once a bar closes and a signal generates, that signal is permanent in the history.
The strategy uses fixed-quantity position sizing (`default_qty_type=strategy.fixed, default_qty_value=1`) with the actual contract quantity determined by the position sizing function and passed to the entry commands. This approach provides maximum control over risk allocation.
Order management uses Pine Script's native `strategy.entry()` and `strategy.exit()` functions with appropriate parameters for stops, limits, and trailing stops. All orders include explicit from_entry references to ensure they apply to the correct position.
The adaptive learning arrays (trade_returns, trade_directions, trade_types, trade_hours, trade_was_stopped) are maintained as circular buffers capped at PERFORMANCE_MEMORY size (default 100 trades). When a new trade closes, its data is added to the beginning of the array using `array.unshift()`, and the oldest trade is removed using `array.pop()` if capacity is exceeded. The stop-out tracking system analyzes the trade_was_stopped array to calculate the rolling percentage displayed in the dashboard.
Dashboard rendering occurs only on the confirmed bar (`barstate.isconfirmed`) to minimize computational overhead. The table is pre-created with sufficient rows for the selected dashboard size and cells are populated with current values each update.
Visual effects (fractal grid, wick pressure, morphism beams, order flow clouds, quantum field) recalculate on each bar for real-time chart updates. These are computationally intensive—if you experience chart lag, disable these visual components. The core strategy logic continues to function identically regardless of visual settings.
Timezone conversions use Pine Script's built-in timezone parameter on the `hour()`, `minute()`, and `dayofweek()` functions. This ensures session logic and daily/weekly resets occur at correct boundaries regardless of the chart's default timezone or the server's timezone.
The universal futures detection queries `syminfo.mintick` and `syminfo.pointvalue` on each strategy initialization to obtain the current instrument's specifications. These values remain constant throughout the strategy's execution on a given chart but automatically update when the strategy is applied to a different instrument.
The strategy has been tested on TradingView across timeframes from 5-minute through daily and across multiple futures instrument types including equity indices, energy, metals, agriculture, treasuries, and currencies. It functions identically on all instruments due to the percentage-based risk model and ATR-relative calculations which adapt automatically to price scale and volatility, combined with the universal futures detection system that handles contract-specific specifications.
FluxVector Liquidity Universal Trendline FluxVector Liquidity Trendline FFTL
Summary in one paragraph
FFTL is a single adaptive trendline for stocks ETFs FX crypto and indices on one minute to daily. It fires only when price action pressure and volatility curvature align. It is original because it fuses a directional liquidity pulse from candle geometry and normalized volume with realized volatility curvature and an impact efficiency term to modulate a Kalman like state without ATR VWAP or moving averages. Add it to a clean chart and use the colored line plus alerts. Shapes can move while a bar is open and settle on close. For conservative alerts select on bar close.
Scope and intent
• Markets. Major FX pairs index futures large cap equities liquid crypto top ETFs
• Timeframes. One minute to daily
• Default demo used in the publication. SPY on 30min
• Purpose. Reduce false flips and chop by gating the line reaction to noise and by using a one bar projection
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique fusion. Directional Liquidity Pulse plus Volatility Curvature plus Impact Efficiency drives an adaptive gain for a one dimensional state
• Failure mode addressed. One or two shock candles that break ordinary trendlines and saw chop in flat regimes
• Testability. All windows and gains are inputs
• Portable yardstick. Returns use natural log units and range is bar high minus low
• Protected scripts. Not used. Method disclosed plainly here
Method overview in plain language
Base measures
• Return basis. Natural log of close over prior close. Average absolute return over a window is a unit of motion
Components
• Directional Liquidity Pulse DLP. Measures signed participation from body and wick imbalance scaled by normalized volume and variance stabilized
• Volatility Curvature. Second difference of realized volatility from returns highlights expansion or compression
• Impact Efficiency. Price change per unit range and volume boosts gain during efficient moves
• Energy score. Z scores of the above form a single energy that controls the state gain
• One bar projection. Current slope extended by one bar for anticipatory checks
Fusion rule
Weighted sum inside the energy score then logistic mapping to a gain between k min and k max. The state updates toward price plus a small flow push.
Signal rule
• Long suggestion and order when close is below trend and the one bar projection is above the trend
• Short suggestion and flip when close is above trend and the one bar projection is below the trend
• WAIT is implicit when neither condition holds
• In position states end on the opposite condition
What you will see on the chart
• Colored trendline teal for rising red for falling gray for flat
• Optional projection line one bar ahead
• Optional background can be enabled in code
• Alerts on price cross and on slope flips
Inputs with guidance
Setup
• Price source. Close by default
Logic
• Flow window. Typical range 20 to 80. Higher smooths the pulse and reduces flips
• Vol window. Typical range 30 to 120. Higher calms curvature
• Energy window. Typical range 20 to 80. Higher slows regime changes
• Min gain and Max gain. Raise max to react faster. Raise min to keep momentum in chop
UI
• Show 1 bar projection. Colors for up down flat
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• Commission percent 0.03
• Slippage 5
• Default order size method percent of equity value 3%
• Pyramiding 0
• Process orders on close off
• Calc on every tick off
• Recalculate after order is filled off
Realism and responsible publication
• No performance claims
• Intrabar reminder. Shapes can move while a bar forms and settle on close
• Strategy uses standard candles only
Honest limitations and failure modes
• Sudden gaps and thin liquidity can still produce fast flips
• Very quiet regimes reduce contrast. Use larger windows and lower max gain
• Session time uses the exchange time of the chart if you enable any windows later
• Past results never guarantee future outcomes
Open source reuse and credits
• None
BankNifty Etharia Aggresive Buyer / SellerOverview
Professional intraday trading strategy for BankNifty Futures that identifies high-probability setups by combining multiple technical indicators. Works in BOTH directions - LONG and SHORT.
Best Timeframe: 5-Minute Chart
Key Features:
✅ Multi-Confluence Entry System - All indicators must align for signal
✅ Bidirectional Trading - Captures both uptrends and downtrends
✅ Advanced Risk Management - Daily loss limits, consecutive loss protection
✅ Smart Exit System - Partial profit taking + trailing stops
✅ Session-Based Trading - Avoids opening and closing volatility
Entry Logic:
LONG Signals:
Price above Kernel Regression (trend confirmation)
Price above VWAP with positive slope (momentum)
Cumulative Volume Delta bullish (buying pressure)
Volume spike or increasing volume (strength confirmation)
Strong bullish candle with 60%+ body ratio
RSI filter to avoid overbought entries
SHORT Signals:
Price below Kernel Regression (downtrend confirmation)
Price below VWAP with negative slope (bearish momentum)
CVD bearish (selling pressure dominates)
High volume confirmation
Strong bearish candle pattern
RSI filter to avoid oversold entries
Exit Management:
🎯 Target 1: 1.5 R:R (50% position exit)
🎯 Target 2: 2.5 R:R (full exit)
🛡️ Stop Loss Options: ATR-based, Swing-based, or Fixed
🟡 Trailing Stop: Activates after 1.2 R:R, trails at 0.8 R:R
⏰ Time-Based Exit: Closes all positions 5 mins before session end
Risk Controls:
Maximum trades per day (default: 5)
Consecutive loss limit (default: 2)
Daily loss limit: 2.5% of capital
Daily profit target: 5% (stops trading when reached)
Position sizing based on account risk percentage
Recommended Settings:
Asset: BankNifty Futures (NSE:BANKNIFTY1!)
Timeframe: 5-minute
Initial Capital: ₹1,00,000
Risk per trade: 1%
Commission: 0.05%
Slippage: 5 points
Performance Expectations:
Win Rate: 55-65%
Profit Factor: 1.5-2.0
Average Trades/Day: 3-8
Risk:Reward: 1:1.8 average
Customizable Parameters:
Trading direction (Long Only / Short Only / Both)
Indicator lengths and thresholds
Stop loss type and targets
Risk management limits
Trading session hours
Best For:
Intraday traders seeking systematic, rule-based entries with strong confluence, proper risk management, and the ability to profit from both bullish and bearish market conditions.
DayFlow VWAP Relay Forex Majors StrategySummary in one paragraph
DayFlow VWAP Relay is a day-trading strategy for major FX pairs on intraday timeframes, demonstrated on EURUSD 15 minutes. It waits for alignment between a daily anchored VWAP regime check, residual percentiles, and lower-timeframe micro flow before suggesting trades. The originality is the fusion of daily VWAP residual percentiles with a live micro-flow score from 1 minute data to switch between fade and breakout behavior inside the same session. Add it to a clean chart and use the markers and alerts.
Scope and intent
• Markets: Major FX pairs such as EURUSD, GBPUSD, USDJPY, AUDUSD, USDCHF, USDCAD
• Timeframes: One minute to one hour
• Default demo in this publication: EURUSD on 15 minutes
• Purpose: Reduce false starts by acting only when context, location and micro flow agree
• Limits: This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Core novelty: Residual percentiles to daily anchored VWAP decide “balanced versus expanding day”. A separate 1 minute micro-flow score confirms direction, so the same model fades extremes in balance and rides range breaks in expansion
• Failure modes addressed: Chop fakeouts and unconfirmed breakouts are filtered by the expansion gate and micro-flow threshold
• Testability: Every input is exposed. Bands, background regime color, and markers show why a suggestion appears
• Portable yardstick: Stops and targets are ATR multiples converted to ticks, which transfer across symbols
• Open source status: No reused third-party code that requires attribution
Method overview in plain language
The day is anchored with a VWAP that updates from the daily session start. Price minus VWAP is the residual. Percentiles of that residual measured over a rolling window define location extremes for the current day. A regime score compares residual volatility to price volatility. When expansion is low, the day is treated as balanced and the model fades residual extremes if 1 minute micro flow points back to VWAP. When expansion is high, the model trades breakouts outside the VWAP bands if slope and micro flow agree with the move.
Base measures
• Range basis: True Range smoothed by ATR for stops and targets, length 14
• Return basis: Not required for signals; residuals are absolute price distance to VWAP
Components
• Daily Anchor VWAP Bands. VWAP with standard-deviation bands. Slope sign is used for trend confirmation on breakouts
• Residual Percentiles. Rolling percentiles of close minus VWAP over Signal length. Identify location extremes inside the day
• Expansion Ratio. Standard deviation of residuals divided by standard deviation of price over Signal length. Classifies balanced versus expanding day
• Micro Flow. Net up minus down closes from 1 minute data across a short span, normalized to −1..+1. Confirms direction and avoids fades against pressure
• Session Window optional. Restricts trading to your configured hours to avoid thin periods
• Cooldown optional. Bars to wait after a position closes to prevent immediate re-entry
Fusion rule
Gating rather than weighting. First choose regime by Expansion Ratio versus the Expansion gate. Inside each regime all listed conditions must be true: location test plus micro-flow threshold plus session window plus cooldown. Breakouts also require VWAP slope alignment.
Signal rule
• Long suggestion on balanced day: residual at or below the lower percentile and micro flow positive above the gate while inside session and cooldown is satisfied
• Short suggestion on balanced day: residual at or above the upper percentile and micro flow negative below the gate while inside session and cooldown is satisfied
• Long suggestion on expanding day: close above the upper VWAP band, VWAP slope positive, micro flow positive, session and cooldown satisfied
• Short suggestion on expanding day: close below the lower VWAP band, VWAP slope negative, micro flow negative, session and cooldown satisfied
• Positions flip on opposite suggestions or exit by brackets
What you will see on the chart
• Markers on suggestion bars: L for long, S for short
• Exit occurs on reverse signal or when a bracket order is filled
• Reference lines: daily anchored VWAP with upper and lower bands
• Optional background: teal for balanced day, orange for expanding day
Inputs with guidance
Setup
• Signal length. Residual and regime window. Typical 40 to 100. Higher smooths, lower reacts faster
Micro Flow
• Micro TF. Lower timeframe used for micro flow, default 1 minute
• Micro span bars. Count of lower-TF bars. Typical 5 to 20
• Micro flow gate 0..1. Minimum absolute flow. Raising it demands stronger confirmation and reduces trade count
VWAP Bands
• VWAP stdev multiplier. Band width. Typical 0.8 to 1.6. Wider bands reduce breakout frequency and increase fade distance
• Expansion gate 0..3. Threshold to switch from fades to breakouts. Raising it favors fades, lowering it favors breakouts
Sessions
• Use session filter. Enable to trade only inside your window
• Trade window UTC. Default 07:00 to 17:00
Risk
• ATR length. Stop and target basis. Typical 10 to 21
• Stop ATR x. Initial stop distance in ATR multiples
• Target ATR x. Profit target distance in ATR multiples
• Cooldown bars after close. Wait bars before a new entry
• Side. Both, long only, or short only
View
• Show VWAP and bands
• Color bars by residual regime
Properties visible in this publication
• Initial capital 10000
• Base currency Default
• request.security uses lookahead off everywhere
• Strategy: Percent of equity with value 3. Pyramiding 0. Commission cash per order 0.0001 USD. Slippage 3 ticks. Process orders on close ON. Bar magnifier ON. Recalculate after order is filled OFF. Calc on every tick OFF. Using standard OHLC fills ON.
Realism and responsible publication
No performance claims. Past results never guarantee future outcomes. Fills and slippage vary by venue. Shapes can move while a bar forms and settle on close. Strategies must run on standard candles for signals and orders.
Honest limitations and failure modes
High impact news, session opens, and thin liquidity can invalidate assumptions. Very quiet days can reduce contrast between residuals and price volatility. Session windows use the chart exchange time. If both stop and target are touched within a single bar, TradingView’s standard OHLC price-movement model decides the outcome.
Expect different behavior on illiquid pairs or during holidays. The model is sensitive to session definitions and feed time. Past results never guarantee future outcomes.
Legal
Education and research only. Not investment advice. You are responsible for your decisions. Test on historical data and in simulation before any live use. Use realistic costs.
VWAP Retest + EMA9 Cross + Candle Pattern V2📈 VWAP Retest + EMA9 Cross + Candle Pattern Strategy_V2
Setup: This intraday momentum strategy combines 3 core elements:
• VWAP Retest: Price retests VWAP within a small buffer zone
• EMA9 Crossover: EMA9 crosses above VWAP within the last 3 bars
• Bullish Candle Pattern: At least one bullish signal — Hammer, Engulfing, or Momentum candle
A trade is triggered only during the US morning session (9:30–12:30 EST) and only if price is above yesterday’s high, suggesting strong momentum.
⚙️ Strategy Settings
• Initial Capital: $100,000
• Position Sizing: 10% of equity per trade
• Commission: 0.03% per trade
• Slippage: 1 tick
• Take Profit: +3% from entry
• Stop Loss: 0.5% below VWAP at entry
• Forced Exit: 1:00 PM EST
📊 Strategy Logic
• VWAP Retest Filter ensures entry is near a value zone.
• EMA9 Cross Confirmation aligns short-term momentum with volume-weighted price.
• Bullish Candle Patterns provide price action confirmation:
○ ✅ Hammer
○ ✅ Bullish Engulfing
○ ✅ Large momentum body
• Above Yesterday’s High (YH) acts as a bullish bias filter.
🧪 Backtest Results (Jan 2023 – Oct 2025)
• Total Trades: 120
• Win Rate: 52.5%
• Profit Factor: 1.18
• Max Drawdown: 1.22%
• Net P&L: +$1,064 (+1.06%)
Due to chart data limits, only part of the period may be visible on publication charts.
🔍 Chart Visuals
This strategy plots:
• VWAP (white) and EMA9 (orange)
• Candle pattern markers:
○ “H” = Hammer
○ “BE” = Bullish Engulfing
○ “M” = Momentum Candle
• “SETUP” label when all conditions are met
• YH/YL labels for context — previous day’s high/low
💡 Use Case
This setup is designed for intraday momentum scalping, ideal for traders who:
• Trade morning breakouts
• Use VWAP as a dynamic support/resistance
• Want clear, rule-based entries based on both trend and price action
Educational and research use - not financial advice.
多指标量化交易DIY- The indicator includes a very large menu of leading tools, each with its own logic to determine uptrend or downtrend impulses. Highlights include:
- Range Filter: Uses a dynamic centerline and bands computed via conditional EMA/SMA and range sizing to define directional movement. It can operate in a default mode or an alternative “DW” mode.
- Rational Quadratic Kernel (RQK): Applies a kernel smoothing model (Nadaraya Watson) to detect uptrends and downtrends with a focus on noise reduction.
- Supertrend, Half Trend, SSL Channel: Classic trend-following tools that derive direction from ATR-based bands or moving average channels.
- Ichimoku Cloud and SuperIchi: Multi-component systems validating trend via cloud position, conversion/base line relationships, projected cloud, and lagging span.
- TSI (True Strength Index), DPO (Detrended Price Oscillator), AO (Awesome Oscillator), MACD, STC (Schaff Trend Cycle), QQE Mod: Momentum and cycle tools that parse direction from crossovers, zero-line behavior, and momentum shifts.
- Donchian Trend Ribbon, Chandelier Exit: Trend and exit tools that can validate breakouts or sustained trend strength.
- ADX/DMI: Measures trend strength and directional movement via +DI/-DI relationships and minimum ADX thresholds.
- RSI and Stochastic: Use crossovers, level exits, or threshold filters to gate entries based on overbought/oversold dynamics or relative strength trends.
- Vortex, Chaikin Money Flow, VWAP, Bull Bear Power, ROC, Wolfpack Id, Hull Suite: A diverse set of directional, momentum, and volume-based indicators to suit different markets and styles.
- Trendline Breakout and Range Detector: Price-behavior filters that confirm signals during breakouts or within defined ranges.
Confirmation Filters
- Each filter is optional. When enabled, it must validate the leading condition for a signal to pass. Examples:
- EMA Filter: Requires price to be above a specified EMA for longs and below for shorts, filtering signals that contradict broader trend or baseline levels.
- 2 EMA Cross and 3 EMA Cross: Enforce moving average cross conditions (fast above slow for long, the reverse for short) or a three-line stacking logic for more stringent trend alignment.
- RQK, Supertrend, Half Trend, Donchian, QQE, Hull, MACD (crossover vs. zero-line), AO (zero line or AC momentum variants), SSL: Each adds its characteristic validation pattern.
- RSI family (MA cross, exits OB/OS zones, threshold levels) plus RSI MA direction and RSI/RSI MA limits: Multiple ways to constrain signals via relative strength behavior and trajectories.
- Choppiness Index and Damiani Volatility: Prevent entries during ranging conditions or insufficient volatility; choppiness thresholds and volatility states gate the trade.
- VWAP, Volume modes (above MA, simple up/down, delta), Chaikin Money Flow: Volume and flow conditions that ensure signals happen in supportive liquidity or accumulation/distribution contexts.
- ADX/DMI thresholds: Demand a minimum trend strength and directional DI alignment to reduce whipsaw trades.
- Trendline Breakout and Range Detector: Confirm that the price is breaking structure or remains within active range consistent with the leading setup.
- By combining several filters you can create strict, conservative entries or looser setups depending on your goals.
Range Filter Engine
- A core building block, the Range Filter uses conditional EMA and SMA functions to compute adaptive bands around a dynamic centerline. It supports two types:
- Type 1: The centerline updates when price exceeds the band thresholds; bands define acceptable drift ranges.
- Type 2: Uses quantized steps (via floor operations) relative to the previous centerline to handle larger moves in discrete increments.
- The engine offers smoothing for range values using a secondary EMA and can switch between raw and averaged outputs. Its hi/lo bands and centerline compose a corridor that defines directional movement and potential breakout confirmation.
Signal Construction
- The script computes:
- leadinglongcond and leadingshortcond : The primary directional signals from the chosen leading indicator.
- longCond and shortCond : Final signals formed by combining the leading conditions with all enabled confirmations. Each confirmation contributes a boolean gate. If a filter is disabled, it contributes a neutral pass-through, keeping the logic intact without enforcing that condition.
- Expiry Logic: The code counts consecutive bars where the leading condition remains true. If confirmations do not line up within the user-defined “Signal Expiry Candle Count,” the setup is abandoned and the signal does not trigger.
- Alternation: An optional state ensures that long and short signals alternate. This can reduce repeated entries in the same direction without a clear reset.
- Finally, longCondition and shortCondition represent the actionable signals after expiry and alternation logic. These drive the label plotting and alert conditions.
Visualization
- Buy and Sell Labels: When longCondition or shortCondition confirm, the script plots annotated labels directly on the chart, making entries easy to see at a glance. The labels use color coding and clear text tags (“long” vs. “short”).
- Dashboard: A table summarizes the status of the leading indicator and all confirmations. Each row shows the indicator label and whether it passed (✔️) or failed (❌) on the current bar. This intensely practical UI helps you diagnose why a signal did or did not trigger, empowering faster strategy iteration and parameter tuning.
- Failed Confirmation Markers: If a setup expires (count exceeds the limit) and confirmations failed to align, the script can mark the chart with a small label and provide a tooltip listing which confirmations did not pass. It’s a helpful audit trail to understand missed trades or prevent “chasing” invalid signals.
- Data Window Values: The script outputs signal states to the data window, which can be useful for debugging or building composite conditions in multi-indicator templates.
Inputs and Parameters
- You control the indicator from a comprehensive input panel:
- Setup: Signal expiry count, whether to enforce alternating signals, and whether to display labels and the dashboard (including position and size).
- Leading Indicator: Choose the primary signal generator from the large list.
- Per-Filter Toggles: For each confirmation, a respect... toggle enables or disables it. Many include sub-options (like MACD type, Stochastic mode, RSI mode, ADX variants, thresholds for choppiness/volatility, etc.) to fine-tune behavior.
- Range Filter Settings: Choose type and behavior; select default vs. DW mode and smoothing. The underlying functions adjust band sizes using ATR, average change, standard deviation, or user-defined scales.
- Because everything is customizable, you can adapt the indicator to different assets, volatility regimes, and timeframes.
Alerts and Automation
- The script defines alert conditions tied to longCondition and shortCondition . You can set these alerts in your chart to trigger notifications or webhook calls for automated execution in external bots. The alert text is simple, and you can configure your own message template when creating alerts in the chart, including JSON payloads for algorithmic integration.
Typical Workflow
- Select a Leading Indicator aligned with your style. For trend following, Supertrend or SSL may be appropriate; for momentum, MACD or TSI; for range/trend-change detection, Range Filter, RQK, or Donchian.
- Add a few key Confirmation Filters that complement the leading signal. For example:
- Pair Supertrend with EMA Filter and RSI MA Direction to ensure trend alignment and positive momentum.
- Combine MACD Crossover with ADX/DMI and Volume Above MA to avoid signals in low-trend or low-liquidity conditions.
- Use RQK with Choppiness Index and Damiani Volatility to only act when the market is trending and volatile enough.
- Set a sensible Signal Expiry Candle Count. Shorter expiry keeps entries timely and reduces lag; longer expiry captures setups that mature slowly.
- Observe the Dashboard during live markets to see which filters pass or fail, then iterate. Tighten or loosen thresholds and filter combinations as needed.
- For automation, turn on alerts for the final conditions and use webhook payloads to notify your trading robot.
Strengths and Practical Notes
- Flexibility: The indicator is a toolkit rather than a single rigid model. It lets you test different combinations rapidly and visualize outcomes immediately.
- Clarity: Labels, dashboard, and failed-confirmation markers make it easy to audit behavior and refine settings without digging into code.
- Robustness: The expiry and alternation options add discipline, avoiding the temptation to enter late or repeatedly in one direction without a reset.
- Modular Design: The logical gates (“respect…”) make the behavior transparent: if a filter is on, it must pass; if it’s off, the signal ignores it. This keeps reasoning clean.
- Avoiding Overfitting: Because you can stack many filters, it’s tempting to over-constrain signals. Start simple (one leading indicator and one or two confirmations). Add complexity only if it demonstrably improves your edge across varied market regimes.
Limitations and Recommendations
- No single configuration is universally optimal. Markets change; tune filters for the instrument and timeframe you trade and revisit settings periodically.
- Trend filters can underperform in choppy markets; likewise, momentum filters can false-trigger in quiet periods. Consider using Choppiness Index or Damiani to gate signals by regime.
- Use expiry wisely. Too short may miss good setups that need a few bars to confirm; too long may cause late entries. Balance responsiveness and accuracy.
- Always consider risk management externally (position sizing, stops, profit targets). The indicator focuses on signal quality; combining it with robust trade management methods will improve results.
Example Configurations
- Trend-Following Setup:
- Leading: Supertrend uptrend for longs and downtrend for shorts.
- Confirmations: EMA Filter (price above 200 EMA for long, below for short), ADX/DMI (trend strength above threshold with +DI/-DI alignment), Volume Above MA.
- Expiry: 3–4 bars to keep entries timely.
- Result: Strong bias toward sustained moves while avoiding weak trends and thin liquidity.
- Mean-Reversion to Momentum Crossover:
- Leading: RSI exits from OB/OS zones (e.g., RSI leaves oversold for long and leaves overbought for short).
- Confirmations: 2 EMA Cross (fast crossing slow in the same direction), MACD zero-line behavior for added momentum validation.
- Expiry: 2–3 bars for responsive re-entry.
- Result: Captures momentum transitions after short-term extremes, with extra confirmation to reduce head-fakes.
- Range Breakout Focus:
- Leading: Range Filter Type 2 or Donchian Trend Ribbon to detect breakouts.
- Confirmations: Damiani Volatility (avoid low-volatility false breaks), Choppiness Index (prefer trend-ready states), ROC positive/negative threshold.
- Expiry: 1–3 bars to act on breakout windows.
- Result: Better alignment to breakout dynamics, gating trades by volatility and regime.
Conclusion
- This indicator is a comprehensive, configurable framework that merges a chosen leading signal with an array of corroborating filters, disciplined expiry handling, and intuitive visualization. It’s designed to help you build high-quality entry signals tailored to your approach, whether that’s trend-following, breakout trading, momentum capturing, or a hybrid. By surfacing pass/fail states in a dashboard and allowing alert-based automation, it bridges the gap between discretionary analysis and systematic execution. With sensible parameter tuning and thoughtful filter selection, it can serve as a robust backbone for signal generation across diverse instruments and timeframes.
5min ORB with FVG God Modethis is 15 min Order Block strategy who works verry well on 3 min chart just must to close some
trading hours
USDJPY Fair Value Gap + Session Strategy🎯 Overview
This strategy combines Fair Value Gaps (FVGs) with session-based order flow analysis, specifically optimized for USDJPY. It identifies price inefficiencies left behind by institutional order flow during high-volatility trading sessions, offering a modern alternative to traditional lagging indicators.
🔬 What Are Fair Value Gaps?
Fair Value Gaps represent areas where aggressive institutional buying or selling created "gaps" in the market structure:
Bullish FVG: Price moves up so aggressively that it leaves unfilled buy orders behind
Bearish FVG: Price moves down so quickly that it leaves unfilled sell orders behind
Research shows approximately 80% of FVGs get "filled" (price returns to the gap) within 20-60 bars, making them highly predictable trading zones.
(see the generated image above)
(see the generated image above)
FVG Detection Logic:
text
// Bullish FVG: Gap between high and current low
bullishFVG = low > high and high > high
// Bearish FVG: Gap between low and current high
bearishFVG = high < low and low < low
🌏 Session-Based Trading
Why Sessions Matter for USDJPY
(see the generated image above)
Tokyo Session (00:00-09:00 UTC)
Highest volatility during first hour (00:00-01:00 UTC)
Average movement: 51-60 pips
Best for breakout strategies
London/NY Overlap (13:00-16:00 UTC)
Maximum liquidity and institutional participation
Tightest spreads and most reliable FVG formations
Optimal for continuation trades
Monday Premium Effect
USDJPY moves 120+ pips on Mondays due to weekend positioning
Enhanced FVG formation during session opens
📊 Strategy Components
(see the generated image above)
1. Fair Value Gap Detection
Identifies bullish and bearish FVGs automatically
Age limit: FVGs expire after 20 bars to avoid stale setups
Size filter: Minimum gap size to filter out noise
2. Session Filtering
Tokyo Open focus: Trades during first hour of Asian session
London/NY Overlap: Captures high-liquidity institutional flows
Weekend gap strategy: Enhanced signals on Monday opens
3. Volume Confirmation
Requires 1.5x average volume spike
Confirms institutional participation
Reduces false signals
4. Trend Alignment
50 EMA filter ensures trades align with higher timeframe trend
Long trades above EMA, short trades below
Prevents costly counter-trend trades
5. Risk Management
2:1 Risk/Reward minimum ensures profitability with 40%+ win rate
Percentage-based stops adapt to USDJPY volatility (0.3% default)
Configurable position sizing
🎯 Entry Conditions
(see the generated image above)
Long Entry (BUY)
✅ Bullish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price above 50 EMA (trend confirmation)
✅ Bullish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
Short Entry (SELL)
✅ Bearish FVG detected in previous bars
✅ Price returns to FVG zone during active trading session
✅ Volume spike above 1.5x average
✅ Price below 50 EMA (trend confirmation)
✅ Bearish candle closes within FVG zone
✅ Trading during Tokyo open OR London/NY overlap
📈 Expected Performance
Backtesting Results (Based on Similar Strategies):
Win Rate: 44-59% (profitable due to high R:R ratio)
Average Winner: 60-90 pips during London/NY sessions
Average Loser: 30-40 pips (tight stops at FVG boundaries)
Risk/Reward: 2:1 minimum, often 3:1 during strong trends
Best Performance: Monday Tokyo opens and Wednesday London/NY overlaps
Why This Works for USDJPY:
90% correlation with US-Japan bond yield spreads
High volatility provides sufficient pip movement
Heavy institutional/central bank participation creates clear FVGs
Consistent volatility patterns across trading sessions
⚙️ Configurable Parameters
Session Settings:
Trade Tokyo Session (Enable/Disable)
Trade London/NY Overlap (Enable/Disable)
FVG Settings:
FVG Minimum Size (Filter small gaps)
Maximum FVG Age (20 bars default)
Show FVG Markers (Visual display)
Volume Settings:
Use Volume Filter (Enable/Disable)
Volume Multiplier (1.5x default)
Volume Average Period (20 bars)
Trend Settings:
Use Trend Filter (Enable/Disable)
Trend EMA Period (50 default)
Risk Management:
Risk/Reward Ratio (2.0 default)
Stop Loss Percentage (0.3% default)
🎨 Visual Indicators
🟡 Yellow Line: 50 EMA trend filter
🟢 Green Triangles: Long entry signals
🔴 Red Triangles: Short entry signals
🟢 Green Dots: Bullish FVG zones
🔴 Red Dots: Bearish FVG zones
🟦 Blue Background: Tokyo open session
🟧 Orange Background: London/NY overlap
📊 Recommended Settings
Optimal Timeframes:
Primary: 5-minute charts (scalping)
Secondary: 15-minute charts (swing trading)
Parameter Optimization:
Conservative: Stop Loss 0.2%, R:R 2:1, Volume 2.0x
Balanced: Stop Loss 0.3%, R:R 2:1, Volume 1.5x (default)
Aggressive: Stop Loss 0.4%, R:R 1.5:1, Volume 1.2x
Risk Management:
Maximum 1-2% of account per trade
Daily loss limit: Stop after 3-5 consecutive losses
Use fixed percentage position sizing
⚠️ Important Considerations
Avoid Trading During:
Major news events (BOJ interventions, NFP, FOMC)
Holiday periods with reduced liquidity
Low volatility Asian afternoon sessions
When US-Japan yield differential narrows sharply
Best Practices:
Limit to 2-3 trades per session maximum
Always respect the 50 EMA trend filter
Never risk more than planned per trade
Paper trade for 2-4 weeks before live implementation
Track performance by session and day of week
🚀 How to Use
Add the script to your USDJPY chart
Set timeframe to 5-minute or 15-minute
Adjust parameters based on your risk tolerance
Enable strategy alerts for automated notifications
Wait for visual signals (triangles) to appear
Enter trades according to your risk management rules
📚 Strategy Foundation
This strategy is based on:
Smart Money Concepts (SMC): Institutional order flow tracking
Market Microstructure: Understanding how FVGs form in electronic trading
Quantified Risk Management: Statistical edge through proper R:R ratios
Session Liquidity Patterns: Exploiting predictable volatility cycles
Short Only Bot (3Commas Webhook Uyumlu)Short işlem açmaya ce 3commans ile uyumlu hacim odaklı indikatör. halka açık herkes kullanabilir.
High Volume Candle Breakouts [Engr. Havery]this plots high volume candles on your chart then when a breakout happens, it gives you an alert then place your limits on the active range. goodluck and have fun
