Twin Range Filter StrategyThis is the strategy version of the popular Twin Range Filter by colinmck.
Recommended use with Renko Candlesticks.
Source:
Strategy!
AltCoin Index Correlation🧠 AltCoin Index Correlation — Strategy Overview
AltCoin Index Correlation is a dynamic EMA-based trading strategy designed primarily for altcoins, but also adaptable to stocks and indices, thanks to its flexible reference index system.
🧭 Strategy Philosophy
The core idea behind this strategy is simple yet powerful:
Price action becomes more meaningful when it aligns with broader market context.
This script analyzes the correlation between the asset’s trend and a reference index trend, using dual EMA (Exponential Moving Average) crossovers for both.
When both the altcoin and the reference index (e.g. Altcoin Dominance, BTC Dominance, Total Market Cap, or even indices like the NASDAQ 100 or S&P 500) are aligned in trend direction, the script considers it a high-confidence setup.
It also includes:
Optional inverse correlation logic (for contrarian setups)
Custom leverage settings (e.g., 1x, 1.8x, etc.)
A dynamic scale-out mechanism during weakening trends
Date filtering for controlled backtests
A live performance dashboard with equity, PnL, win rate, drawdown, APR, and more
⚙️ Default Settings & Backtest Results
Timeframe tested: 1H
Test date: May 20, 2025
Sample: 100 high-cap altcoins
Reference index: CRYPTOCAP:OTHERS.D (Altcoin Dominance)
Leverage: 1.8x (180% of capital used)
📊 With default settings:
Win rate: ~80%
Higher profits, due to increased exposure
Best suited for confident trend followers with higher risk tolerance
📉 With fixed capital or 1x leverage:
Win rate improves to ~90%
Lower returns, but greater capital preservation
Ideal for conservative or risk-managed trading styles
🔄 Versatility
While tailored for altcoins, this strategy supports traditional markets as well:
Easily switch the reference index to OANDA:NAS100USD or S&P 500 for stock correlation trading
Adjust EMA lengths and leverage to match the asset class and volatility profile
🧩 Suggested Use
Best used on trending markets (not sideways)
Ideal for 1H timeframes, but adjustable
Suitable for traders who want a rules-based, macro-aware entry/exit system
Try it out, customize it to your style, try different settings and share your results with the community!
Feedback is welcome — and improvements are always in progress.
🚀 ### Check my profile for other juicy hints and original strategies. ### 🚀
Volume FIltered RSI Buy/Sell StrategyVolume Filtered RSI Buy/Sell Strategy
Introduction
This publication introduces the "Volume Filtered RSI Buy/Sell Strategy," a systematic trading approach designed specifically for cryptocurrency markets. This strategy combines RSI momentum signals with volume confirmation and precise candle pattern recognition to identify high-probability entry points while filtering out weak signals.
Overview
The strategy implements a multi-layered filtering system that requires several conditions to align before entering a trade. By requiring RSI momentum shifts, significant volume, and strong candle patterns, the system aims to capture only the most reliable trade setups. Built-in risk management features provide automatic stop-loss and take-profit placement based on either ATR volatility or fixed percentage risk.
Strategy Core Components:
RSI Momentum Detection : Identifies transitions from oversold to bullish (for longs) and overbought to bearish (for shorts)
Volume Confirmation : Ensures entries occur with above-average volume, filtering out low-liquidity signals
Candle Pattern Analysis : Requires strong bullish/bearish candles where the body comprises at least 50% of the candle range
Optional Supertrend Filter : Provides trend alignment confirmation across multiple timeframes
Dynamic ATR Stop-Loss System : Adapts protection levels based on current market volatility
Default Settings:
RSI Parameters : 14-period length with 70/30 overbought/oversold levels
Risk Management : 1.5 risk-reward ratio with option for ATR-based or fixed 0.5% stop-loss
Commission : 0.055% per trade (realistic for major exchanges)
Initial Capital : 100 USDT (realistic for average trader)
Order Size : Recommended 20 USDT per trade (20% risk per trade)
Entry Logic:
The strategy creates a powerful filtering system by requiring all of the following conditions to align:
Long Entry : RSI crosses above 30 from below + Strong bullish candle (body > 50% of range) + Volume > 14-period SMA
Short Entry : RSI crosses below 70 from above + Strong bearish candle (body > 50% of range) + Volume > 14-period SMA
Optional Trend Alignment : When enabled, entries must align with Supertrend direction
Exit Methods:
The strategy offers two comprehensive exit approaches:
ATR-Based : Dynamically calculates stop-loss and take-profit levels based on current volatility (3.5x ATR multiplier)
Fixed Percentage : Uses a consistent 0.5% stop-loss with take-profit set at 1.5x the risk distance
Visualization : All entry points, stop-loss levels and take-profit targets are clearly displayed on the chart
Why This Combination Works:
The power of this strategy comes from its multi-confirmation approach:
RSI identifies potential momentum shifts but can produce false signals in ranging markets
Volume confirmation ensures trades are only taken when sufficient market interest exists
Candle pattern requirements filter out weak reversals by demanding strong price action
When combined, these three filters significantly reduce false signals while capturing strong momentum shifts
Backtesting Results:
When tested on BTCUSDT 5-minute chart with the default settings:
Total trades: 53 (provides sufficient sample size)
Profitable trades: 58.49%
Profit factor: 1.472
Max drawdown: 3.01%
Net profit: +6.52%
Recommended Usage:
Optimal Timeframe : 5-minute chart for BTCUSDT
Trade Direction : Can be configured for Long-only, Short-only or Both directions
Risk Management : The default settings risk approximately 1% per trade with the recommended 20 USDT order size on 100 USDT capital
Indicator Mode : For those who prefer manual trade management, right-click on chart and disable "Trades On Chart"
Customization Options:
The strategy provides multiple parameters that can be adjusted to match different trading styles:
RSI length and overbought/oversold levels
ATR period for stop-loss calculation
Risk-reward ratio
Fixed stop-loss percentage
Optional Supertrend filter with adjustable factor and period
Disclaimer
This strategy is shared for educational purposes only. The default parameters have been tested to provide a balance between win rate and profitability, but past performance does not guarantee future results. The commission setting (0.055%) reflects realistic exchange fees, and the recommended position sizing (20% of capital) is higher than traditional 1-2% but represents common practice in cryptocurrency trading. Users should thoroughly test any changes to parameters before trading real capital.
Cyber Strategy V1Сyber Strategy V1 – Indicator Testing & Strategy Execution Framework
✅ Overview
Cyber Strategy V1 is a closed-source strategy framework engineered to turn any of yours external indicator into a systematic, rule-based trading system. Designed for rigorous testing and live deployment, it combines multi-signal inputs, confirmations and automated execution paths to help traders and developers validate signal quality and manage risk with precision.
✅ Core Functionality
Multi-Source Independent Signal Inputs
Reversal Logic
Take Profit: up to 5 staggered TP levels, specified as percentage
Stop Loss: configurable via fixed percentage or dynamic SL that trails a reverse signals.
✅ Statistical Drawdown Analysis
For all profitable trades, tracks the maximum intratrade drawdown.
Computes percentile levels of profitable trades that hits minimum drawdowns to inform:
Entry buffer zones (e.g. avoid entering during transient noise)
Partial entry scaling prices.
✅ Signal Confirmation
Optional confirmation delays: hold entry until other signal section send a confirmation from another indicator.
✅ Automated Execution Integrations
Cornix Text Alerts: Generates pre-formatted alerts compatible with Cornix for semi-automated or bot trading.
Webhook Support: Emits JSON payloads on order-fill events to any endpoint, enabling full automation through third-party services or custom order-routing systems.
Important Notes
⚠️ THIS STRATEGY DOES NOT INCLUDE INDICATORS. Examples shown on screenshots use third-party tools. NO PROPRIETARY INDICATORS INCLUDED: Cyber Strategy V1 relies entirely on external signal inputs.
⚠️ All backtesting parameters are customizable; thorough backtesting under realistic slippage, fees and spread assumptions is essential before live deployment.
ICT 2022 Mentorship Model StrategyICT 2022 Mentorship Model Strategy
Introduction
This publication introduces the "ICT 2022 Mentorship Model Strategy," a systematic trading approach based on the Inner Circle Trader concepts. Designed for traders looking to identify institutional footprints in the market, this strategy captures high-probability setups by recognizing specific price action sequences.
Overview
The strategy implements the core principles from the ICT 2022 Mentorship model, focusing on a three-step sequence: Liquidity Sweep (LS), Market Structure Shift (MSS) with Displacement, and Entry via Fair Value Gaps (FVG). It's optimized for cryptocurrency markets on the 5-minute timeframe, with optional higher timeframe bias filtering.
Indicators & Libraries:
OrderBlockRefiner : Leverages TFlab's OrderBlockRefiner library for precise setup identification
OrderBlockDrawing : Utilizes TFlab's visualization system for clear market analysis
FVGDetectorLibrary : Employs TFlab's FVG detection algorithm to identify Fair Value Gaps
Strategy Core Components:
Liquidity Sweeps (LS) : Detects when price moves above a swing high or below a swing low, triggering stop orders before reversing
Market Structure Shifts (MSS) : Identifies clear breaks of near-term swing points in the opposite direction to the liquidity sweep
Fair Value Gaps (FVG) : Recognizes three-candle patterns indicating price imbalances, often left behind by strong directional moves
Strategy Settings:
Swing Period : Default at 50, determines the lookback for swing high/low points
FVG Length : Default at 120, sets how long Fair Value Gaps remain active for trading
MSS Length : Default at 80, determines the window for detecting market structure shifts
FVG Filtering : Optional width filter with selectable aggressiveness (Very Aggressive to Very Defensive)
Entry Level : Configurable to Proximal, 50% OB, or Distal positions within the FVG
Entry Methods:
The strategy offers multiple entry approaches to accommodate different trading styles:
Proximal Touch Market : Enters immediately when price touches the FVG boundary
FVG Level Limit Order : Places a limit order at the specified FVG level
Candle Close Inside FVG : Enters only when a candle closes inside the FVG area
Exit Conditions:
Stop Loss Placement : Multiple methods including MSS Swing Point, FVG Distal, Liquidity Sweep Extreme, and more
Take Profit : Risk-to-reward based targets with a default 1.5R setting
Buffer Settings : Configurable stop-loss buffer as a percentage of the risk distance
Risk Management Features:
Time Filtering : Optional trading during specific "Kill Zones" (Asian, London, New York sessions)
HTF Bias Filtering : Option to align trades with higher timeframe trends
Volume Filtering : Ensures FVG creation occurs on significant volume
Consecutive Loss Protection : Automatically pauses trading after 3 consecutive losses for 4 hours
Statistics Dashboard : Real-time performance metrics including win rate, profit factor, and drawdown
The strategy is optimized for BYBIT:BTCUSDT.P and other major cryptocurrency pairs, particularly effective on 5-minute charts for intraday trading. But ofcourse this is also applicable for any markets like stocks, forex, commodities and indicies.
Visual Features:
This implementation includes comprehensive visualization of FVGs, market structure shifts, and liquidity levels. Active trade management displays show entry points, stop-loss levels, and take-profit targets, with color-coded bars during active trades.
I've spent significant time creating this complete implementation of the ICT 2022 Mentorship concepts. The strategy includes robust risk management, flexible entry methods, and advanced filtering options. Feel free to adjust the settings to suit your trading style - detailed tooltips are provided for each parameter.
Acknowledgements:
Special thanks to TFlab for the excellent libraries and the basis of the indicator that power this strategy's core functionality:
- OrderBlockRefiner_TradingFinder
- OrderBlockDrawing_TradingFinder
- FVGDetectorLibrary
Special Thanks to the PH community that is helping me learn, practice, and apply these into my daily trading for free - THE ASCENT!
PS.
Note you can always turn the visuals on or off from the style tab/section of the indicator
For a clean chart, I recommend turning the Background Color of HTF Bias, as well as bar colors to OFF, but for refrence you can always turn it back on.
Also, feel free to customize the colors, lines, background, to your preference.
Disclaimer
This strategy is shared for educational purposes only and must be thoroughly tested under diverse market conditions. Past performance does not guarantee future results. Trading cryptocurrencies involves substantial risk of loss and is not suitable for every investor. The effectiveness of this strategy can change with market conditions - what works in one period may not work in another. Always use proper risk management.
MACD Green column buy Red column sell Histogram StrategyBuy Condition:
When the MACD Histogram turns from negative to positive (from red bars to green bars), it triggers strategy.entry('MACD_Buy', strategy.long), executing a buy operation.
Sell Condition:
When the MACD Histogram turns from positive to negative (from green bars to red bars), it triggers strategy.close('MACD_Buy'), executing a sell operation.
Plotting remains unchanged:
Green and red bars are displayed correctly, and both the MACD and signal lines are plotted as usual.
Disclaimer:
This strategy is for educational and reference purposes only.
You should not use this strategy for real trading, and I am not responsible for any losses incurred from using this strategy under any circumstances.
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逻辑解释：
1.买入条件：
当 MACD 的 Histogram 从负转正（由红柱变为绿柱）时，触发 strategy.entry('MACD_Buy', strategy.long)，执行买入操作。
2.卖出条件：
当 MACD 的 Histogram 从正转负（由绿柱变为红柱）时，触发 strategy.close('MACD_Buy')，执行卖出操作。
3.绘图保持不变：
绿柱和红柱都正常显示，MACD 和信号线也正常绘制。
本策略仅供学习与参考，不构成投资建议
您不应该使用此策略进行真实交易，任何情况下使用此策略造成的损失本人概不负责
Smart Fib StrategySmart Fibonacci Strategy
This advanced trading strategy combines the power of adaptive SMA entries with Fibonacci-based exit levels to create a comprehensive trend-following system that self-optimizes based on historical market conditions. Credit goes to Julien_Eche who created the "Best SMA Finder" which received an Editors Pick award.
Strategy Overview
The Smart Fibonacci Strategy employs a two-pronged approach to trading:
1. Intelligent Entries: Uses a self-optimizing SMA (Simple Moving Average) to identify optimal entry points. The system automatically tests multiple SMA lengths against historical data to determine which period provides the most robust trading signals.
2. Fibonacci-Based Exits: Implements ATR-adjusted Fibonacci bands to establish precise exit targets, with risk-management options ranging from conservative to aggressive.
This dual methodology creates a balanced system that adapts to changing market conditions while providing clear visual reference points for trade management.
Key Features
- **Self-Optimizing Entries**: Automatically calculates the most profitable SMA length based on historical performance
- **Adjustable Risk Parameters**: Choose between low-risk and high-risk exit targets
- **Directional Flexibility**: Trade long-only, short-only, or both directions
- **Visualization Tools**: Customizable display of entry lines and exit bands
- **Performance Statistics**: Comprehensive stats table showing key metrics
- **Smoothing Option**: Reduces noise in the Fibonacci bands for cleaner signals
Trading Rules
Entry Signals
- **Long Entry**: When price crosses above the blue center line (optimal SMA)
- **Short Entry**: When price crosses below the blue center line (optimal SMA)
### Exit Levels
- **Low Risk Option**: Exit at the first Fibonacci band (1.618 * ATR)
- **High Risk Option**: Exit at the second Fibonacci band (2.618 * ATR)
Strategy Parameters
Display Settings
- Toggle visibility of the stats table and indicator components
Strategy Settings
- Select trading direction (long, short, or both)
- Choose exit method (low risk or high risk)
- Set minimum trades threshold for SMA optimization
SMA Settings
- Option to use auto-optimized or fixed-length SMA
- Customize SMA length when using fixed option
Fibonacci Settings
- Adjust ATR period and SMA basis for Fibonacci bands
- Enable/disable smoothing function
- Customize Fibonacci ratio multipliers
Appearance Settings
- Modify colors, line widths, and transparency
Optimization Methodology
The strategy employs a sophisticated optimization algorithm that:
1. Tests multiple SMA lengths against historical data
2. Evaluates performance based on trade count, profit factor, and win rate
3. Calculates a "robustness score" that balances profitability with statistical significance
4. Selects the SMA length with the highest robustness score
This ensures that the strategy's entry signals are continuously adapting to the most effective parameters for current market conditions.
Risk Management
Position sizing is fixed at $2,000 per trade, allowing for consistent exposure across all trading setups. The Fibonacci-based exit system provides two distinct risk management approaches:
- **Conservative Approach**: Using the first Fibonacci band for exits produces more frequent but smaller wins
- **Aggressive Approach**: Using the second Fibonacci band allows for larger potential gains at the cost of increased volatility
Ideal Usage
This strategy is best suited for:
- Trending markets with clear directional moves
- Timeframes from 4H to Daily for most balanced results
- Instruments with moderate volatility (stocks, forex, commodities)
Traders can further enhance performance by combining this strategy with broader market analysis to confirm the prevailing trend direction.
RCI Strategy [PineIndicators]RCI Strategy
This strategy leverages the Rank Correlation Index (RCI) — a statistical oscillator that measures the relationship between time and price rank — combined with a configurable moving average filter. It offers clean, rule-based entries and exits, and visually enhanced trade tracking via labeled markers and boxes on the chart.
The RCI Strategy is well-suited for momentum traders looking to capture directional shifts with confirmation through RCI smoothing.
Core Logic
1. Rank Correlation Index (RCI)
Measures how closely price changes correlate with time rankings.
Values range between -100 and +100.
Thresholds at ±80 help identify potential reversals or extremes.
2. RCI Smoothing via Moving Average
A moving average (MA) is applied to the RCI to smooth out fluctuations.
Supported MA types:
SMA
EMA
SMMA (RMA)
WMA
VWMA
Users can disable the smoothing by selecting "None".
Trade Entry Logic
Long Entry: RCI crosses above the selected moving average.
Short Entry: RCI crosses below the moving average.
Entries are restricted by trade direction settings:
Long Only
Short Only
Long & Short
Visual Features
RCI Panel Display
Plots RCI line and its moving average in a separate pane.
Horizontal guide lines at 0, +80, and -80 help visualize signal zones.
Trade Labels on Chart
Buy Label: Plotted when a long entry is executed.
Close Label: Plotted when any position is closed.
Triangle markers for visual emphasis on direction change.
Trade Visualization Boxes
A colored box is drawn between entry and exit prices.
Green = profitable trade; Red = losing trade.
Two horizontal lines connect entry and exit prices for reference.
Customization Parameters
RCI Source: Select input price for the RCI (default: close).
RCI Length: Set sensitivity of the oscillator.
MA Type and Length: Choose and configure the smoothing filter.
Trade Direction Mode: Define whether to allow Long, Short, or both.
Use Cases
Swing traders who want to trade directional reversals with statistical backing.
Traders seeking a clean and visual strategy based on rank momentum.
Environments where both trend and range dynamics occur.
Conclusion
The RCI Strategy is a non-repainting, rule-based trading model that combines rank correlation momentum with smoothed trend logic. Its clean visual markers, labeled trades, and flexible MA filters make it a valuable tool for discretionary and systematic traders alike.
Parabolic RSI Strategy [ChartPrime × PineIndicators]This strategy combines the strengths of the Relative Strength Index (RSI) with a Parabolic SAR logic applied directly to RSI values.
Full credit to ChartPrime for the original concept and indicator, licensed under the MPL 2.0.
It provides clear momentum-based trade signals using an innovative method that tracks RSI trend reversals via a customized Parabolic SAR, enhancing traditional oscillator strategies with dynamic trend confirmation.
How It Works
The system overlays a Parabolic SAR on the RSI, detecting trend shifts in RSI itself rather than on price, offering early reversal insight with visual and algorithmic clarity.
Core Components
1. RSI-Based Trend Detection
Calculates RSI using a customizable length (default: 14).
Uses upper and lower thresholds (default: 70/30) for overbought/oversold zones.
2. Parabolic SAR Applied to RSI
A custom Parabolic SAR function tracks momentum within the RSI, not price.
This allows the system to capture RSI trend reversals more responsively.
Configurable SAR parameters: Start, Increment, and Maximum acceleration.
3. Signal Generation
Long Entry: Triggered when the SAR flips below the RSI line.
Short Entry: Triggered when the SAR flips above the RSI line.
Optional RSI filter ensures that:
Long entries only occur above a minimum RSI (e.g. 50).
Short entries only occur below a maximum RSI.
Built-in logic prevents new positions from being opened against trend without prior exit.
Trade Modes & Controls
Choose from:
Long Only
Short Only
Long & Short
Optional setting to reverse positions on opposite signal (instead of waiting for a flat close).
Visual Features
1. RSI Plotting with Thresholds
RSI is displayed in a dedicated pane with overbought/oversold fill zones.
Custom horizontal lines mark threshold boundaries.
2. Parabolic SAR Overlay on RSI
SAR dots color-coded for trend direction.
Visible only when enabled by user input.
3. Entry & Exit Markers
Diamonds: Mark entry points (above for shorts, below for longs).
Crosses: Mark exit points.
Strategy Strengths
Provides early momentum reversal entries without relying on price candles.
Combines oscillator and trend logic without repainting.
Works well in both trending and mean-reverting markets.
Easy to configure with fine-tuned filter options.
Recommended Use Cases
Intraday or swing traders who want to catch RSI-based reversals early.
Traders seeking smoother signals than price-based Parabolic SAR entries.
Users of RSI looking to reduce false positives via trend tracking.
Customization Options
RSI Length and Thresholds.
SAR Start, Increment, and Maximum values.
Trade Direction Mode (Long, Short, Both).
Optional RSI filter and reverse-on-signal settings.
SAR dot color customization.
Conclusion
The Parabolic RSI Strategy is an innovative, non-repainting momentum strategy that enhances RSI-based systems with trend-confirming logic using Parabolic SAR. By applying SAR logic to RSI values, this strategy offers early, visualized, and filtered entries and exits that adapt to market dynamics.
Credit to ChartPrime for the original methodology, published under MPL-2.0.
Praetor Sentinel V11.2 NOLOOSE BETA📈 Praetor Sentinel V11.2 – "NOLOOSE BETA"
Algorithmic Trading Strategy for Trend Markets with Adaptive Risk Management
Praetor Sentinel V11.2 is an advanced algorithmic trading strategy for TradingView, specifically designed to operate in strong trend conditions. It combines multiple technical systems—including dynamic trend filters, multi-layer EMA structures, ADX-based volatility control, and adaptive trailing stops—into a powerful and automated trading framework.
🔧 Core Features
Multi-EMA Trend Detection: Two EMA pairs (short/long) to identify and confirm directional trends.
XO-EMA Breakout Logic: Fast EMA crossover to detect breakout opportunities.
ADX Trend Filter: Trades only during strong market trends (above custom ADX threshold).
HTF Filter: Optional higher timeframe trend confirmation (e.g. Daily 50 EMA).
VWAP Validation: Ensures entries aren't taken against the volumetric average.
RSI Filter: Adds a momentum filter (e.g. RSI > 50 for long trades).
🎯 Entry Signals
The strategy uses two entry types:
Breakout Entries: Based on XO-EMA cross and multi-EMA trend alignment.
Pullback Entries: Configurable via various methods such as EMA21 reentry, RSI reversal, engulfing candles, or VWAP reclaim.
All entries can be delayed via confirmation candle logic, requiring a bullish or bearish follow-up bar.
🛡️ Risk Management & Exit Logic
Dynamic ATR Trailing Stop: Adjusts stop distance according to market volatility with optional swing high/low protection.
Break-Even Logic: Locks in trades at breakeven once a defined profit is reached.
Hard Stop-Loss: Caps potential loss per trade with a fixed % (e.g. 1%).
Safe Mode ("NOLOOSE"): Exits early if price moves too far against the position — ideal for automated bots that must avoid drawdowns.
🤖 Automation & Alerts
This strategy is fully automatable with services like 3Commas using built-in alert messages for entries and exits.
All parameters are fully configurable to adapt to different assets, timeframes, and trading styles.
⚙️ Additional Features
Configurable leverage & position sizing
Time-based trading window
Built-in Anchored VWAP
Modular design for easy extension
📌 Summary
Praetor Sentinel V11.2 is a professional-grade tool for trend traders who want rule-based entry/exit logic, adaptive stop systems, and robust protection features. When paired with automation tools, it offers a reliable, low-maintenance setup that emphasizes safety, structure, and scalability.
🛠 How to Use Praetor Sentinel V11.2 – NOLOOSE BETA
🔍 1. Basic Configuration (Required)
Setting Description
Enable Long Trades Enables long (buy) positions.
Enable Short Trades Enables short (sell) positions.
Leverage Used for position sizing calculations.
Position Size % Defines % of capital to be used per trade.
⏰ 2. Time Filter (Optional)
Restricts trading to a defined time range.
Setting Description
Start Date Start date for strategy to be active.
End Date End date for strategy to stop.
Time Zone Time zone for above settings.
📊 3. Trend Setup (Essential for Entry Signals)
Setting Description
MA Type Type of moving average: EMA or SMA.
EMA1/2 Short & Long Two EMA-based systems to determine trend.
Fast/Slow EMA (XO) Used for crossover breakout detection.
HTF Filter Uses higher timeframe trend for additional confirmation.
RSI Filter Confirms entries only if momentum (RSI) supports it.
ADX Threshold Ensures trades only occur during strong trends.
🎯 4. Entry Logic
Setting Description
Pullback Entry Type Enables optional entry setups:
"Off"
"EMA21"
"RSI"
"Engulfing"
"VWAP"
| Use Confirmation Candle | Entry is delayed until a confirmation bar appears. |
| VWAP Confirmation | Trade only if price is above/below the VWAP (based on direction). |
Note: You can combine breakout + pullback signals. Only one has to trigger.
🧯 5. Risk Control & Exit Settings
Setting Description
Trailing Stop Mode
"Standard": Classic trailing stop
"Dynamic ATR": Adjusts to current volatility
"Dynamic ATR + Swing": Adds swing high/low buffer
| Enable Break-Even | Moves SL to breakeven once a target % gain is reached. |
| Enable Hard Stop-Loss | Fixed stop-loss (e.g. 1%) to cap trade risk. |
| Enable Safe Mode | Exits trade early if price moves against it beyond defined % (e.g. 0.3%). |
🔔 6. Alerts & Bot Automation
Setting Description
Entry Long/Short Msg Text message sent via alert when a position opens.
Exit Long/Short Msg Alert message for stop-loss/exit logic.
How to automate with 3Commas:
Load the strategy on your chart.
Manually create alerts using "Create Alert" in TradingView.
Use the built-in alert_message values for bot integration.
✅ Recommended Settings (Example for BTC/ETH on 1H)
Long & Short: ✅ Enabled
Leverage: 2.0
Timeframe: 1H
Pullback Entry: "EMA21"
MA Type: EMA
HTF Filter: Enabled (Daily EMA50)
RSI Filter: Enabled
VWAP Filter: Enabled
Break-Even: On at 0.5%
Hard SL: 1.0%
Safe Mode: On at -0.3%
Trailing Stop: "Dynamic ATR + Swing"
📘 Pro Tips for Testing & Customization
Use the Strategy Tester in TradingView to analyze performance over different assets.
Experiment with timeframes and entry modes.
Ideal for trending assets like BTC, ETH, SOL, etc.
You can expand it with take-profit logic, fixed TPs, indicator exits, etc.
Dual-Phase Trend Regime Strategy [Zeiierman X PineIndicators]This strategy is based on the Dual-Phase Trend Regime Indicator by Zeiierman.
Full credit for the original concept and logic goes to Zeiierman.
This non-repainting strategy dynamically switches between fast and slow oscillators based on market volatility, providing adaptive entries and exits with high clarity and reliability.
Core Concepts
1. Adaptive Dual Oscillator Logic
The system uses two oscillators:
Fast Oscillator: Activated in high-volatility phases for quick reaction.
Slow Oscillator: Used during low-volatility phases to reduce noise.
The system automatically selects the appropriate oscillator depending on the market's volatility regime.
2. Volatility Regime Detection
Volatility is calculated using the standard deviation of returns. A median-split algorithm clusters volatility into:
Low Volatility Cluster
High Volatility Cluster
The current volatility is then compared to these clusters to determine whether the regime is low or high volatility.
3. Trend Regime Identification
Based on the active oscillator:
Bullish Trend: Oscillator > 0.5
Bearish Trend: Oscillator < 0.5
Neutral Trend: Oscillator = 0.5
The strategy reacts to changes in this trend regime.
4. Signal Source Options
You can choose between:
Regime Shift (Arrows): Trade based on oscillator value changes (from bullish to bearish and vice versa).
Oscillator Cross: Trade based on crossovers between the fast and slow oscillators.
Trade Logic
Trade Direction Options
Long Only
Short Only
Long & Short
Entry Conditions
Long Entry: Triggered on bullish regime shift or fast crossing above slow.
Short Entry: Triggered on bearish regime shift or fast crossing below slow.
Exit Conditions
Long Exit: Triggered on bearish shift or fast crossing below slow.
Short Exit: Triggered on bullish shift or fast crossing above slow.
The strategy closes opposing positions before opening new ones.
Visual Features
Oscillator Bands: Plots fast and slow oscillators, colored by trend.
Background Highlight: Indicates current trend regime.
Signal Markers: Triangle shapes show bullish/bearish shifts.
Dashboard Table: Displays live trend status ("Bullish", "Bearish", "Neutral") in the chart’s corner.
Inputs & Customization
Oscillator Periods – Fast and slow lengths.
Refit Interval – How often volatility clusters update.
Volatility Lookback & Smoothing
Color Settings – Choose your own bullish/bearish colors.
Signal Mode – Regime shift or oscillator crossover.
Trade Direction Mode
Use Cases
Swing Trading: Take entries based on adaptive regime shifts.
Trend Following: Follow the active trend using filtered oscillator logic.
Volatility-Responsive Systems: Adjust your trade behavior depending on market volatility.
Clean Exit Management: Automatically closes positions on opposite signal.
Conclusion
The Dual-Phase Trend Regime Strategy is a smart, adaptive, non-repainting system that:
Automatically switches between fast and slow trend logic.
Responds dynamically to changes in volatility.
Provides clean and visual entry/exit signals.
Supports both momentum and reversal trading logic.
This strategy is ideal for traders seeking a volatility-aware, trend-sensitive tool across any market or timeframe.
Full credit to Zeiierman.
Reversal Strength Meter – Adib NooraniThe Reversal Strength Meter is an oscillator designed to identify potential reversal zones based on supply and demand dynamics. It uses smoothed stochastic logic to reduce noise and highlight areas where momentum may be weakening, signaling possible market turning points.
🔹 Smooth, noise-reduced stochastic oscillator
🔹 Custom zones to highlight potential supply and demand imbalances
🔹 Non-repainting, compatible across all timeframes and assets
🔹 Visual-only tool — intended to support discretionary trading decisions
This oscillator assists scalpers and intraday traders in tracking subtle shifts in momentum, helping them identify when a market may be preparing to reverse — always keeping in mind that trading is based on probabilities, not certainties.
📘 How to Use the Indicator Efficiently
For Reversal Trading:
Buy Setup
– When the blue line dips below the 20 level, wait for it to re-enter above 20.
– Look for reversal candlestick patterns (e.g., bullish engulfing, hammer, or morning star).
– Enter above the pattern’s high, with a stop loss below its low.
Sell Setup
– When the blue line rises above the 80 level, wait for it to re-enter below 80.
– Look for bearish candlestick patterns (e.g., bearish engulfing, inverted hammer, or evening star).
– Enter below the pattern’s low, with a stop loss above its high.
🛡 Risk Management Guidelines
Risk only 0.5% of your capital per trade
Book 50% profits at a 1:1 risk-reward ratio
Trail the remaining 50% using price action or other supporting indicators
Reversal Scalping Ribbon - Adib NooraniThe Reversal Scalping Ribbon is a trend-following overlay tool designed to visually identify potential reversal zones based on price extremes and dynamic volatility bands. It calculates adaptive upper and lower bands using price action and custom ATR logic, helping traders quickly assess market direction and possible turning points
🔹 Volatility-adjusted bands based on price highs/lows
🔹 Color-coded ribbons to indicate trend bias and potential reversal shifts
🔹 No repainting, works on all timeframes and assets
🔹 Visual-only display, no trade signals — supports discretion-based entries
This ribbon is designed for scalpers and intraday traders to spot reversal setups with clarity. It enhances your trading by showing real-time market bias without unnecessary distractions. By focusing on probabilities, it helps to improve decision-making in fast-paced environments
How to use the indicator efficiently
For Reversal Trading:
Buy: When price closes below the green ribbon with a red candle, then re-enters with a green candle. Enter above the high of the green candle with a stop loss below the lowest low of the recent green/red candles
Sell: When price closes above the red ribbon with a green candle, then re-enters with a red candle. Enter below the low of the red candle with a stop loss above the highest high of the recent red/green candles
Risk Management:
Limit risk to 0.5% of your capital per trade
Take 50% profit at a 1:1 risk-reward ratio
For the remaining 50%, trail using the lower edge of the green band for buys and the upper edge of the red band for sells
Gabriel's Price Action Strategy🧠 Gabriel's Price Action Strategy — Smart Signal Sequence with Dynamic Risk Control
Created by: OneWallStreetQuant
Strategy Type: Momentum-based Sequence Logic + Smart Volume & RSI Filters
Ideal For: Intraday scalping, swing trading, and momentum trend entries on stocks, forex, crypto, indices.
🚀 Overview
Gabriel's Price Action Strategy is a multi-layered, logic-driven trading system that combines:
✅ Candle Sequence Detection: Detects persistent bullish/bearish momentum using a smart configurable sequence of green/red candles.
✅ Structure Break Filtering: Prevents entries if recent price invalidates the momentum setup (e.g., a red candle breaks a bullish low).
✅ Custom Volume Engine: Integrates a hybrid tick-volume model using Negative/Positive Volume Index (NVI-PVI) to identify smart money flows.
✅ Advanced RSI Logic: Uses Jurik RSX for accurate oversold/overbought filtering.
✅ Optional MTF Trend Filter: Validates trend direction using a slope-based Jurik MA on higher timeframes.
✅ MPT-Based DMI Filter: Adds pyramid entries only during strong trend phases, based on Gain/Pain ratios and Ulcer-index smoothed ADX.
✅ Risk Management: ATR-based SL/TP and fully customizable trailing logic for both profit and stop-loss.
📈 Entry Logic
Trades are triggered only when:
A minimum number of recent candles are bullish/bearish (Min Green/Red Candles)
Structure has not been broken by opposite price action (optional)
Relative volume exceeds average (optional)
RSI is below overbought or above oversold (optional)
MTF slope is aligned with trend direction (optional)
💡 Key Features
Custom Candle Logic: Detects momentum shifts using a tunable lookback window (up to 50 bars).
Smart Volume Filtering: Volume is intelligently estimated using tick-based ranges and NVI-PVI deltas.
Risk Management Built-in: Set your ATR length, SL/TP multipliers, and dynamic trailing offsets with full control.
Scorecard System: A built-in scoring engine evaluates Win Rate, Drawdown, Sharpe Ratio, Recovery Factor, and Profit Factor — visualized on chart as a label.
Backtest-Friendly: Includes date range toggles, bar-magnifier support, and optimized execution on every tick.
📊 Strategy Scorecard (Label)
Automatically calculates:
✅ Total Trades
✅ Win Rate (%)
✅ Net Profit
✅ Profit Factor
✅ Expected Payoff
✅ Max & Avg Drawdown
✅ Recovery Factor
✅ Sharpe Ratio
✅ VaR (95%)
Plus, assigns a normalized score from 0 to 100 for evaluating overall robustness.
⚙️ Customization
Every module — from entry filters to pyramiding and trailing logic — is fully configurable:
Volume Filters ✅
RSI Filters ✅
Structure Break Checks ✅
HTF Jurik MA & Slope Threshold ✅
Multi-Timeframe Mode ✅
Backtest Score Visualization ✅
⚠️ Notes
Enable bar magnifier and calc on every tick for best accuracy.
On early bars, signal logic may delay until enough candles are available.
Best paired with assets showing directional volatility (SPY, BTC, ETH, Gold, etc.).
Ideally paired on trending timeframes such as M1, M5, M15, M30, 1HR, 4 Hourly, Daily, Weekly, Monthly, etc.
Moving Average Shift WaveTrend StrategyMoving Average Shift WaveTrend Strategy
🧭 Overview
The Moving Average Shift WaveTrend Strategy is a trend-following and momentum-based trading system designed to be overlayed on TradingView charts. It executes trades based on the confluence of multiple technical conditions—volatility, session timing, trend direction, and oscillator momentum—to deliver logical and systematic trade entries and exits.
🎯 Strategy Objectives
Enter trades aligned with the prevailing long-term trend
Exit trades on confirmed momentum reversals
Avoid false signals using session timing and volatility filters
Apply structured risk management with automatic TP, SL, and trailing stops
⚙️ Key Features
Selectable MA types: SMA, EMA, SMMA (RMA), WMA, VWMA
Dual-filter logic using a custom oscillator and moving averages
Session and volatility filters to eliminate low-quality setups
Trailing stop, configurable Take Profit / Stop Loss logic
“In-wave flag” prevents overtrading within the same trend wave
Visual clarity with color-shifting candles and entry/exit markers
📈 Trading Rules
✅ Long Entry Conditions:
Price is above the selected MA
Oscillator is positive and rising
200-period EMA indicates an uptrend
ATR exceeds its median value (sufficient volatility)
Entry occurs between 09:00–17:00 (exchange time)
Not currently in an active wave
🔻 Short Entry Conditions:
Price is below the selected MA
Oscillator is negative and falling
200-period EMA indicates a downtrend
All other long-entry conditions are inverted
❌ Exit Conditions:
Take Profit or Stop Loss is hit
Opposing signals from oscillator and MA
Trailing stop is triggered
🛡️ Risk Management Parameters
Pair: ETH/USD
Timeframe: 4H
Starting Capital: $3,000
Commission: 0.02%
Slippage: 2 pips
Risk per Trade: 2% of account equity (adjustable)
Total Trades: 224
Backtest Period: May 24, 2016 — April 7, 2025
Note: Risk parameters are fully customizable to suit your trading style and broker conditions.
🔧 Trading Parameters & Filters
Time Filter: Trades allowed only between 09:00–17:00 (exchange time)
Volatility Filter: ATR must be above its median value
Trend Filter: Long-term 200-period EMA
📊 Technical Settings
Moving Average
Type: SMA
Length: 40
Source: hl2
Oscillator
Length: 15
Threshold: 0.5
Risk Management
Take Profit: 1.5%
Stop Loss: 1.0%
Trailing Stop: 1.0%
👁️ Visual Support
MA and oscillator color changes indicate directional bias
Clear chart markers show entry and exit points
Trailing stops and risk controls are transparently managed
🚀 Strategy Improvements & Uniqueness
In-wave flag avoids repeated entries within the same trend phase
Filtering based on time, volatility, and trend ensures higher-quality trades
Dynamic high/low tracking allows precise trailing stop placement
Fully rule-based execution reduces emotional decision-making
💡 Inspirations & Attribution
This strategy is inspired by the excellent concept from:
ChartPrime – “Moving Average Shift”
It expands on the original idea with advanced trade filters and trailing logic.
Source reference:
📌 Summary
The Moving Average Shift WaveTrend Strategy offers a rule-based, reliable approach to trend trading. By combining trend and momentum filters with robust risk controls, it provides a consistent framework suitable for various market conditions and trading styles.
⚠️ Disclaimer
This script is for educational purposes only. Trading involves risk. Always use proper backtesting and risk evaluation before applying in live markets.
RSI Full [Titans_Invest]RSI Full
One of the most complete RSI indicators on the market.
While maintaining the classic RSI foundation, our indicator integrates multiple entry conditions to generate more accurate buy and sell signals.
All conditions are fully configurable, allowing complete customization to fit your trading strategy.
⯁ WHAT IS THE RSI❓
The Relative Strength Index (RSI) is a technical analysis indicator developed by J. Welles Wilder. It measures the magnitude of recent price movements to evaluate overbought or oversold conditions in a market. The RSI is an oscillator that ranges from 0 to 100 and is commonly used to identify potential reversal points, as well as the strength of a trend.
⯁ HOW TO USE THE RSI❓
The RSI is calculated based on average gains and losses over a specified period (usually 14 periods). It is plotted on a scale from 0 to 100 and includes three main zones:
Overbought: When the RSI is above 70, indicating that the asset may be overbought.
Oversold: When the RSI is below 30, indicating that the asset may be oversold.
Neutral Zone: Between 30 and 70, where there is no clear signal of overbought or oversold conditions.
⯁ ENTRY CONDITIONS
The conditions below are fully flexible and allow for complete customization of the signal.
______________________________________________________
🔹 CONDITIONS TO BUY 📈
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND/OR .
📈 RSI Conditions:
🔹 RSI > Upper
🔹 RSI < Upper
🔹 RSI > Lower
🔹 RSI < Lower
🔹 RSI > Middle
🔹 RSI < Middle
🔹 RSI > MA
🔹 RSI < MA
📈 MA Conditions:
🔹 MA > Upper
🔹 MA < Upper
🔹 MA > Lower
🔹 MA < Lower
📈 Crossovers:
🔹 RSI (Crossover) Upper
🔹 RSI (Crossunder) Upper
🔹 RSI (Crossover) Lower
🔹 RSI (Crossunder) Lower
🔹 RSI (Crossover) Middle
🔹 RSI (Crossunder) Middle
🔹 RSI (Crossover) MA
🔹 RSI (Crossunder) MA
🔹 MA (Crossover) Upper
🔹 MA (Crossunder) Upper
🔹 MA (Crossover) Lower
🔹 MA (Crossunder) Lower
📈 RSI Divergences:
🔹 RSI Divergence Bull
🔹 RSI Divergence Bear
______________________________________________________
______________________________________________________
🔸 CONDITIONS TO SELL 📉
______________________________________________________
• Signal Validity: The signal will remain valid for X bars .
• Signal Sequence: Configurable as AND/OR .
📉 RSI Conditions:
🔸 RSI > Upper
🔸 RSI < Upper
🔸 RSI > Lower
🔸 RSI < Lower
🔸 RSI > Middle
🔸 RSI < Middle
🔸 RSI > MA
🔸 RSI < MA
📉 MA Conditions:
🔸 MA > Upper
🔸 MA < Upper
🔸 MA > Lower
🔸 MA < Lower
📉 Crossovers:
🔸 RSI (Crossover) Upper
🔸 RSI (Crossunder) Upper
🔸 RSI (Crossover) Lower
🔸 RSI (Crossunder) Lower
🔸 RSI (Crossover) Middle
🔸 RSI (Crossunder) Middle
🔸 RSI (Crossover) MA
🔸 RSI (Crossunder) MA
🔸 MA (Crossover) Upper
🔸 MA (Crossunder) Upper
🔸 MA (Crossover) Lower
🔸 MA (Crossunder) Lower
📉 RSI Divergences:
🔸 RSI Divergence Bull
🔸 RSI Divergence Bear
______________________________________________________
______________________________________________________
🤖 AUTOMATION 🤖
• You can automate the BUY and SELL signals of this indicator.
______________________________________________________
______________________________________________________
⯁ UNIQUE FEATURES
______________________________________________________
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
Signal Validity: The signal will remain valid for X bars
Signal Sequence: Configurable as AND/OR
Condition Table: BUY/SELL
Condition Labels: BUY/SELL
Plot Labels in the Graph Above: BUY/SELL
Automate and Monitor Signals/Alerts: BUY/SELL
______________________________________________________
📜 SCRIPT : RSI Full
🎴 Art by : @Titans_Invest & @DiFlip
👨💻 Dev by : @Titans_Invest & @DiFlip
🎑 Titans Invest — The Wizards Without Gloves 🧤
✨ Enjoy the Spell!
______________________________________________________
o Mission 🗺
• Inspire Traders to manifest Magic in the Market.
o Vision 𐓏
• To elevate collective Energy 𐓷𐓏
ZVOL — Z-Score Volume Heatmapⓩ ZVOL transforms raw volume into a statistically calibrated heatmap using Z-score thresholds. Unlike classic volume indicators that rely on fixed MA comparisons, ZVOL calculates how many standard deviations each volume bar deviates from its mean. This makes the reading adaptive across timeframes and assets, in order to distinguish meaningful crowd behavior from random volatility.
📊 The core display is a five-zone histogram, each encoded by color and statistical depth. Optional background shading mirrors these zones across the entire pane, revealing subtle compression or structural rhythm shifts across time. By grounding the volume reading in volatility-adjusted context, ZVOL inhibits impulsive trading tactics by compelling the structure, not the sentiment, to dictate the signal.
🥵 Heatmap Coloration:
🌚 Suppressed volume — congestion, coiling phases
🩱 Stable flow — early trend or resting volume
🏀 High activity — emerging pressure
💔 Extreme — possible climax or institutional print
🎗️ A dynamic Fibonacci-based 21:34-period EMA ribbon overlays the histogram. The fill area inverts color on crossover, providing a real-time read on tempo, expansion, or divergence between price structure and crowd effort.
💡 LTF Usage Suggestions:
• Confirm breakout legs when orange or red zones align with range exits
• Fade overextended moves when red bars appear into resistance
• Watch for rising EMAs and orange volume to front-run impulsive moves
• Combine with volatility suppression (e.g. ATR) to catch compression → expansion transitions
🥂 Ideal Pairings:
• OBVX Conviction Bias — to confirm directional intent behind volume shifts
• SUPeR TReND 2.718 — for directional filters
• ATR Turbulence Ribbon — to detect compression phases
👥 The OBVX Conviction Bias adds a second dimension to ZVOL by revealing whether crowd effort is aligning with price direction or diverging beneath the surface. While ZVOL identifies statistical anomalies in raw volume, OBVX tracks directional commitment using cumulative volume and moving average cross logic. Use them together to spot fake-outs, anticipate structure-confirmed breakouts, or time pullbacks with volume-based conviction.
🔬 ZVOL isn’t just a volume filter — it’s a structural lens. It reveals when crowd effort is meaningful, when it's fading, and when something is about to shift. Designed for structure-aware traders who care about context, not noise.
7-Channel Trend Meter v3🔥 7-Channel Trend Meter – Ultimate Trend Confirmation Tool 💹
Purpose: Supplementary indicator used as confirmation
The 7-Channel Trend Meter offers an all-in-one confirmation system that combines 7 high-accuracy indicators into one easy-to-read visual tool. Say goodbye to guesswork and unnecessary tab-switching—just clear, actionable signals for smarter trades. Whether you're trading stocks, crypto, or forex, this indicator streamlines your decision-making process and enhances your strategy’s performance.
⚙️ What’s Inside The Box?
Here is each tool that the Trend Meter uses, and why/how they're used:
Average Directional Index: Confirms market strength ✅
Directional Movement Index: Confirms trend direction ✅
EMA Cross: Confirms reversals in trend through average price ✅
Relative Strength Index: Confirms trend through divergences ✅
Stochastic Oscillator: Confirms shifts in momentum ✅
Supertrend: Confirms trend-following using ATR calculations ✅
Volume Delta: Confirms buying/selling pressure weight by finding differences ✅
🧾 How To Read It:
🟨 Bar 1 – Market Strength Meter:
Light Gold 🟡: Strong market with trending conditions.
Dark Gold 🟤: Weakening market or consolidation—proceed with caution.
📊 Bars 2 to 7 – Trend Direction Confirmations:
🟩 Green: Bullish signal, uptrend likely.
🟥 Red: Bearish signal, downtrend likely.
💯 Why it's helpful to traders:
✅ 7 Confirmations in 1 View: No need to flip between multiple charts.
✅ Visual Clarity: Spot trends instantly with a quick glance.
✅ Perfect for Entry Confirmation: Confirm trade signals before pulling the trigger.
✅ Boosts Your Win Rate: Make data-backed decisions, not guesses.
✅ Works Across Multiple Markets: Stocks, crypto, forex—you name it 🌍.
🤔 "What's with the indicator mashup/How do these components work together? 🤔
The 7-Channel Trend Meter is designed as an original and useful tool that integrates multiple indicators to enhance trading decisions, rather than merely combining existing tools without logical coherence. This strategic mashup creates a comprehensive analysis framework that offers deeper insights into market conditions by capitalizing on each component's unique strengths. The careful integration of seven indicators creates a unified system that eliminates conflicting signals and enhances the decision-making process. Rather than simply merging indicators for the sake of it, the 7-Channel Trend Meter is designed to streamline trading strategies, making it a practical tool for traders across various markets. By leveraging the combined strengths of these indicators, traders can act with greater confidence, backed by comprehensive data rather than fragmented insights. Here’s how they synergistically work together:
Average Directional Index (ADX) and Directional Movement Index (DMI): The reason for this mashup is because ADX indicates the strength of the prevailing trend, while the DMI pinpoints its direction. Together, they equip traders with a dual framework that not only identifies whether to engage with a trend but also quantifies its strength, allowing for more decisive trading strategies.
EMA Cross: The reason for this addition to the mashup is because this tool signals potential trend reversals by identifying moving average crossovers. When combined with the ADX and DMI, traders can better differentiate between genuine trend shifts and market noise, leading to more accurate entries.
Relative Strength Index (RSI) and Stochastic Oscillator: The reason for this mashup is because by using both momentum indicators, traders gain a multifaceted view of market dynamics. The RSI assesses overbought or oversold conditions, while the Stochastic Oscillator confirms momentum shifts. When both agree with the trend signals from the DMI, it enhances the reliability of reversal or continuation strategies.
Supertrend: The reason for this addition to the mashup is because as a trailing stop based on market volatility, the Supertrend indicator works hand-in-hand with the ADX’s strength assessment, allowing traders to ride strong trends while managing risk. This cohesion prevents premature exits during minor pullbacks.
Volume Delta: The reason for this addition to the mashup is because integrating volume analysis helps validate signals from the price action indicators. Significant volume behind a price movement reinforces the likelihood of its continuation, ensuring that traders can act on well-supported signals.
🔍 How it does what it says it does 🔍
While the exact calculations remain proprietary, the following outlines how the components synergistically work to aid traders in making informed decisions:
Market Strength Assessment: Average Directional Index (ADX)
This component is used as confirmation by measuring the strength of the market trend on a scale from 0 to 100. A reading above 20 generally indicates a strong trend, while readings below 20 suggest sideways movement. The Trend Meter flags strong trends, effectively helping traders identify optimal conditions for entering positions.
Trend Direction Confirmation: Directional Movement Index (DMI)
This component is used as confirmation by distinguishing between bullish and bearish trends by evaluating price movements. This combination allows traders to confirm not only if a trend exists but also its direction, informing whether to buy or sell.
Trend Reversal Detection: Exponential Moving Average (EMA) Cross
This component is used as confirmation by calculating two EMAs (one shorter and one longer) to identify potential reversal points. When the shorter EMA crosses above the longer EMA, it signals a bullish reversal, and vice versa for bearish reversals. This helps traders pinpoint optimal entry or exit points.
Momentum Analysis: Relative Strength Index (RSI) and Stochastic Oscillator
These components are used as confirmation by providing insights into momentum. The RSI assesses the speed and change of price movements, indicating overbought or oversold conditions. The Stochastic Oscillator compares a particular closing price to a range of prices over a specified period. This helps identify whether momentum is slowing or speeding up, offering a clear view of potential reversal points. When both the RSI and Stochastic Oscillator converge on signals, it increases the reliability of those signals in trading decisions.
Volatility-Based Trend Following: Supertrend
This component is used as confirmation by utilizing Average True Range (ATR) calculations to help traders stay in momentum-driven trades by providing dynamic support and resistance levels that adapt to volatility. This enables better risk management while allowing traders to capture stronger trends.
Volume Confirmation: Volume Delta
This component is used as confirmation by analyzing buying and selling pressure by measuring the difference between buy and sell volumes, offering critical insights into market sentiment. Significant volume behind a price movement increases confidence in the sustainability of that move.
🧠 Pro Tip:
When all 7 bars line up in green or red, it’s time to take action: load up for a confirmed move or sit back and wait for market confirmation. Let the Trend Meter guide your strategy with precision.
Conclusion:
Integrate the 7-Channel Trend Meter as useful confirmation for your TradingView strategy and stop trading like the average retail trader. This tool eliminates the noise and helps you stay focused on high-confidence trades.
Adaptive Fibonacci Pullback System -FibonacciFluxAdaptive Fibonacci Pullback System (AFPS) - FibonacciFlux
This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0). Original concepts by FibonacciFlux.
Abstract
The Adaptive Fibonacci Pullback System (AFPS) presents a sophisticated, institutional-grade algorithmic strategy engineered for high-probability trend pullback entries. Developed by FibonacciFlux, AFPS uniquely integrates a proprietary Multi-Fibonacci Supertrend engine (0.618, 1.618, 2.618 ratios) for harmonic volatility assessment, an Adaptive Moving Average (AMA) Channel providing dynamic market context, and a synergistic Multi-Timeframe (MTF) filter suite (RSI, MACD, Volume). This strategy transcends simple indicator combinations through its strict, multi-stage confluence validation logic. Historical simulations suggest that specific MTF filter configurations can yield exceptional performance metrics, potentially achieving Profit Factors exceeding 2.6 , indicative of institutional-level potential, while maintaining controlled risk under realistic trading parameters (managed equity risk, commission, slippage).
4 hourly MTF filtering
1. Introduction: Elevating Pullback Trading with Adaptive Confluence
Traditional pullback strategies often struggle with noise, false signals, and adapting to changing market dynamics. AFPS addresses these challenges by introducing a novel framework grounded in Fibonacci principles and adaptive logic. Instead of relying on static levels or single confirmations, AFPS seeks high-probability pullback entries within established trends by validating signals through a rigorous confluence of:
Harmonic Volatility Context: Understanding the trend's stability and potential turning points using the unique Multi-Fibonacci Supertrend.
Adaptive Market Structure: Assessing the prevailing trend regime via the AMA Channel.
Multi-Dimensional Confirmation: Filtering signals with lower-timeframe Momentum (RSI), Trend Alignment (MACD), and Market Conviction (Volume) using the MTF suite.
The objective is to achieve superior signal quality and adaptability, moving beyond conventional pullback methodologies.
2. Core Methodology: Synergistic Integration
AFPS's effectiveness stems from the engineered synergy between its core components:
2.1. Multi-Fibonacci Supertrend Engine: Utilizes specific Fibonacci ratios (0.618, 1.618, 2.618) applied to ATR, creating a multi-layered volatility envelope potentially resonant with market harmonics. The averaged and EMA-smoothed result (`smoothed_supertrend`) provides a robust, dynamic trend baseline and context filter.
// Key Components: Multi-Fibonacci Supertrend & Smoothing
average_supertrend = (supertrend1 + supertrend2 + supertrend3) / 3
smoothed_supertrend = ta.ema(average_supertrend, st_smooth_length)
2.2. Adaptive Moving Average (AMA) Channel: Provides dynamic market context. The `ama_midline` serves as a key filter in the entry logic, confirming the broader trend bias relative to adaptive price action. Extended Fibonacci levels derived from the channel width offer potential dynamic S/R zones.
// Key Component: AMA Midline
ama_midline = (ama_high_band + ama_low_band) / 2
2.3. Multi-Timeframe (MTF) Filter Suite: An optional but powerful validation layer (RSI, MACD, Volume) assessed on a lower timeframe. Acts as a **validation cascade** – signals must pass all enabled filters simultaneously.
2.4. High-Confluence Entry Logic: The core innovation. A pullback entry requires a specific sequence and validation:
Price interaction with `average_supertrend` and recovery above/below `smoothed_supertrend`.
Price confirmation relative to the `ama_midline`.
Simultaneous validation by all enabled MTF filters.
// Simplified Long Entry Logic Example (incorporates key elements)
long_entry_condition = enable_long_positions and
(low < average_supertrend and close > smoothed_supertrend) and // Pullback & Recovery
(close > ama_midline and close > ama_midline) and // AMA Confirmation
(rsi_filter_long_ok and macd_filter_long_ok and volume_filter_ok) // MTF Validation
This strict, multi-stage confluence significantly elevates signal quality compared to simpler pullback approaches.
1hourly filtering
3. Realistic Implementation and Performance Potential
AFPS is designed for practical application, incorporating realistic defaults and highlighting performance potential with crucial context:
3.1. Realistic Default Strategy Settings:
The script includes responsible default parameters:
strategy('Adaptive Fibonacci Pullback System - FibonacciFlux', shorttitle = "AFPS", ...,
initial_capital = 10000, // Accessible capital
default_qty_type = strategy.percent_of_equity, // Equity-based risk
default_qty_value = 4, // Default 4% equity risk per initial trade
commission_type = strategy.commission.percent,
commission_value = 0.03, // Realistic commission
slippage = 2, // Realistic slippage
pyramiding = 2 // Limited pyramiding allowed
)
Note: The default 4% risk (`default_qty_value = 4`) requires careful user assessment and adjustment based on individual risk tolerance.
3.2. Historical Performance Insights & Institutional Potential:
Backtesting provides insights into historical behavior under specific conditions (always specify Asset/Timeframe/Dates when sharing results):
Default Performance Example: With defaults, historical tests might show characteristics like Overall PF ~1.38, Max DD ~1.16%, with potential Long/Short performance variance (e.g., Long PF 1.6+, Short PF < 1).
Optimized MTF Filter Performance: Crucially, historical simulations demonstrate that meticulous configuration of the MTF filters (particularly RSI and potentially others depending on market) can significantly enhance performance. Under specific, optimized MTF filter settings combined with appropriate risk management (e.g., 7.5% risk), historical tests have indicated the potential to achieve **Profit Factors exceeding 2.6**, alongside controlled drawdowns (e.g., ~1.32%). This level of performance, if consistently achievable (which requires ongoing adaptation), aligns with metrics often sought in institutional trading environments.
Disclaimer Reminder: These results are strictly historical simulations. Past performance does not guarantee future results. Achieving high performance requires careful parameter tuning, adaptation to changing markets, and robust risk management.
3.3. Emphasizing Risk Management:
Effective use of AFPS mandates active risk management. Utilize the built-in Stop Loss, Take Profit, and Trailing Stop features. The `pyramiding = 2` setting requires particularly diligent oversight. Do not rely solely on default settings.
4. Conclusion: Advancing Trend Pullback Strategies
The Adaptive Fibonacci Pullback System (AFPS) offers a sophisticated, theoretically grounded, and highly adaptable framework for identifying and executing high-probability trend pullback trades. Its unique blend of Fibonacci resonance, adaptive context, and multi-dimensional MTF filtering represents a significant advancement over conventional methods. While requiring thoughtful implementation and risk management, AFPS provides discerning traders with a powerful tool potentially capable of achieving institutional-level performance characteristics under optimized conditions.
Acknowledgments
Developed by FibonacciFlux. Inspired by principles of Fibonacci analysis, adaptive averaging, and multi-timeframe confirmation techniques explored within the trading community.
Disclaimer
Trading involves substantial risk. AFPS is an analytical tool, not a guarantee of profit. Past performance is not indicative of future results. Market conditions change. Users are solely responsible for their decisions and risk management. Thorough testing is essential. Deploy at your own considered risk.
Uptrick X PineIndicators: Z-Score Flow StrategyThis strategy is based on the Z-Score Flow Indicator developed by Uptrick. Full credit for the original concept and logic goes to Uptrick.
The Z-Score Flow Strategy combines statistical mean-reversion logic with trend filtering, RSI confirmation, and multi-mode trade execution, offering a flexible and structured approach to trading both reversals and trend continuations.
Core Concepts Behind Z-Score Flow
1. Z-Score Mean Reversion Logic
The Z-score measures how far current price deviates from its statistical mean, in standard deviations.
A high positive Z-score (e.g. > 2) suggests price is overbought and may revert downward.
A low negative Z-score (e.g. < -2) suggests price is oversold and may revert upward.
The strategy uses Z-score thresholds to trigger signals when price deviates far enough from its mean.
2. Trend Filtering with EMA
To prevent counter-trend entries, the strategy includes a trend filter based on a 50-period EMA:
Only allows long entries if price is below EMA (mean-reversion in downtrends).
Only allows short entries if price is above EMA (mean-reversion in uptrends).
3. RSI Confirmation and Lockout System
An RSI smoothing mechanism helps confirm signals and avoid whipsaws:
RSI must be below 30 and rising to allow buys.
RSI must be above 70 and falling to allow sells.
Once a signal occurs, it is "locked out" until RSI re-enters the neutral zone (30–70).
This avoids multiple signals in overextended zones and reduces overtrading.
Entry Signal Logic
A buy or sell is triggered when:
Z-score crosses below (buy) or above (sell) the threshold.
RSI smoothed condition is met (oversold and rising / overbought and falling).
The trend condition (EMA filter) aligns.
A cooldown period has passed since the last opposite trade.
This layered approach helps ensure signal quality and timing precision.
Trade Modes
The strategy includes three distinct trade modes to adapt to various market behaviors:
1. Standard Mode
Trades are opened using the Z-score + RSI + trend filter logic.
Each signal must pass all layered conditions.
2. Zero Cross Mode
Trades are based on the Z-score crossing zero.
This mode is useful in trend continuation setups, rather than mean reversion.
3. Trend Reversal Mode
Trades occur when the mean slope direction changes, i.e., basis line changes color.
Helps capture early trend shifts with less lag.
Each mode can be customized for long-only, short-only, or long & short execution.
Visual Components
1. Z-Score Mean Line
The basis (mean) line is colored based on slope direction.
Green = bullish slope, Purple = bearish slope, Gray = flat.
A wide shadow band underneath reflects current trend momentum.
2. Gradient Fill to Price
A gradient zone between price and the mean reflects:
Price above mean = bearish zone with purple overlay.
Price below mean = bullish zone with teal overlay.
This visual aid quickly reveals market positioning relative to equilibrium.
3. Signal Markers
"𝓤𝓹" labels appear for buy signals.
"𝓓𝓸𝔀𝓷" labels appear for sell signals.
These are colored and positioned according to trend context.
Customization Options
Z-Score Period & Thresholds: Define sensitivity to price deviations.
EMA Trend Filter Length: Filter entries with long-term bias.
RSI & Smoothing Periods: Fine-tune RSI confirmation conditions.
Cooldown Period: Prevent signal spam and enforce timing gaps.
Slope Index: Adjust how far back to compare mean slope.
Visual Settings: Toggle mean lines, gradients, and more.
Use Cases & Strategy Strengths
1. Mean-Reversion Trading
Ideal for catching pullbacks in trending markets or fading overextended price moves.
2. Trend Continuation or Reversal
With multiple trade modes, traders can choose between fading price extremes or trading slope momentum.
3. Signal Clarity and Risk Control
The combination of Z-score, RSI, EMA trend, and cooldown logic provides high-confidence signals with built-in filters.
Conclusion
The Z-Score Flow Strategy by Uptrick X PineIndicators is a versatile and structured trading system that:
Fuses statistical deviation (Z-score) with technical filters.
Provides both mean-reversion and trend-based entry logic.
Uses visual overlays and signal labels for clarity.
Prevents noise-driven trades via cooldown and lockout systems.
This strategy is well-suited for traders seeking a data-driven, multi-condition entry framework that can adapt to various market types.
Full credit for the original concept and indicator goes to Uptrick.
VIDYA Auto-Trading(Reversal Logic)Overview
This script is a dynamic trend-following strategy based on the Variable Index Dynamic Average (VIDYA). It adapts in real time to market volatility, aiming to enhance entry precision and optimize risk management.
⚠️ This strategy is intended for educational and research purposes. Past performance does not guarantee future results. All results are based on historical simulations using fixed parameters.
Strategy Objectives
The objective of this strategy is to respond swiftly to sudden price movements and trend reversals, providing consistent and reliable trade signals under historical testing conditions. It is designed to be intuitive and efficient for traders of all levels.
Key Features
Momentum Sensitivity via VIDYA: Reacts quickly to momentum shifts, allowing for accurate trend-following entries.
Volatility-Based ATR Bands: Automatically adjusts stop levels and entry conditions based on current market volatility.
Intuitive Trend Visualization: Uptrends are marked with green zones, and downtrends with red zones, giving traders clear visual guidance.
Trading Rules
Long Entry: Triggered when price crosses above the upper band. Any existing short position is closed.
Short Entry: Triggered when price crosses below the lower band. Any existing long position is closed.
Exit Conditions: Positions are reversed based on signal changes, using a position reversal strategy.
Risk Management Parameters
Market: ETHUSD(5M)
Account Size: $3,000 (reasonable approximation for individual traders)
Commission: 0.02%
Slippage: 2 pip
Risk per Trade: 5% of account equity (adjusted to comply with TradingView guidelines for realistic risk levels)
Number of Trades: 251 (based on backtest over the selected dataset)
⚠️ The risk per trade and other values can be customized. Users are encouraged to adapt these to their individual needs and broker conditions.
Trading Parameters & Considerations
VIDYA Length: 10
VIDYA Momentum: 20
Distance factor for upper/lower bands: 2
Source: close
Visual Support
Trend zones, entry points, and directional shifts are clearly plotted on the chart. These visual cues enhance the analytical experience and support faster decision-making.
Visual elements are designed to improve interpretability and are not intended as financial advice or trade signals.
Strategy Improvements & Uniqueness
Inspired by the public work of BigBeluga, this script evolves the original concept with meaningful enhancements. By combining VIDYA and ATR bands, it offers greater adaptability and practical value compared to conventional trend-following strategies.
This adaptation is original work and not a direct copy. Improvements are designed to enhance usability, risk control, and market responsiveness.
Summary
This strategy offers a responsive and adaptive approach to trend trading, built on momentum detection and volatility-adjusted risk management. It balances clarity, precision, and practicality—making it a powerful tool for traders seeking reliable trend signals.
⚠️ All results are based on historical data and are subject to change under different market conditions. This script does not guarantee profit and should be used with caution and proper risk management.
Triangular Hull Moving Average [BigBeluga X PineIndicators]This strategy is based on the original Triangular Hull Moving Average (THMA) + Volatility indicator by BigBeluga. Full credit for the concept and design goes to BigBeluga.
The strategy blends smoothed trend-following logic using a Triangular Hull Moving Average with dynamic volatility overlays, providing actionable trade signals with responsive visual feedback. It's designed for traders who want a non-lagging trend filter while also monitoring market volatility in real time.
How the Strategy Works
1. Triangular Hull Moving Average (THMA) Core
At its core, the strategy uses a Triangular Hull Moving Average (THMA) — a variation of the traditional Hull Moving Average with triple-smoothing logic:
It combines multiple weighted moving averages (WMAs) to create a faster and smoother trend line.
This reduces lag without compromising trend accuracy.
The THMA reacts more responsively to price movements than classic MAs.
THMA Formula:
thma(_src, _length) =>
ta.wma(ta.wma(_src,_length / 3) * 3 - ta.wma(_src, _length / 2) - ta.wma(_src, _length), _length)
This logic filters out short-term noise while still being sensitive to genuine trend shifts.
2. Volatility-Enhanced Candle Plotting
An optional volatility mode overlays the chart with custom candles that incorporate volatility bands:
Wicks expand and contract dynamically based on market volatility.
The volatility value is computed using a HMA of high-low range over a user-defined length.
The candle bodies reflect THMA values, while the wicks reflect the current volatility spread.
This feature allows traders to visually gauge the strength of price moves and anticipate possible breakouts or slowdowns.
3. Trend Reversal Signal Detection
The strategy identifies trend reversals when the THMA line crosses over/under its own past value:
A bullish signal is triggered when THMA crosses above its value from two bars ago.
A bearish signal is triggered when THMA crosses below its value from two bars ago.
These shifts are marked on the chart with triangle-shaped signals for clear visibility.
This logic helps detect momentum shifts early and enables reactive trade entries.
Trade Entry & Exit Logic
Trade Modes Supported
Users can choose between:
Only Long – Enters long trades only.
Only Short – Enters short trades only.
Long & Short – Enables both directions.
Entry Conditions
Long Entry:
Triggered when a bullish crossover is detected.
Active only if the strategy mode allows long trades.
Short Entry:
Triggered when a bearish crossover is detected.
Active only if the strategy mode allows short trades.
Exit Conditions
In Only Long mode, the strategy closes long positions when a bearish signal appears.
In Only Short mode, the strategy closes short positions when a bullish signal appears.
In Long & Short mode, the strategy does not auto-close positions — instead, it opens new positions on each confirmed signal.
Dashboard Visualization
In the bottom-right corner of the chart, a live dashboard displays:
The current trend direction (🢁 for bullish, 🢃 for bearish).
The current volatility level as a percentage.
This helps traders quickly assess market status and adjust their decisions accordingly.
Customization Options
THMA Length: Adjust how smooth or reactive the trend detection should be.
Volatility Toggle & Length: Enable or disable volatility visualization and set sensitivity.
Color Settings: Choose colors for up/down trend visualization.
Trade Direction Mode: Limit the strategy to long, short, or both types of trades.
Use Cases & Strategy Strengths
1. Trend Following
Use the THMA-based candles and triangle signals to enter with momentum. The indicator adapts quickly, reducing lag and improving trade timing.
2. Volatility Monitoring
Visualize the strength of the trend with volatility wicks. Use expanding bands to confirm breakouts and contracting ones to detect weakening moves.
3. Signal Confirmation
Combine this tool with other indicators or use the trend shift triangles as confirmations for manual entries.
Conclusion
The THMA + Volatility Strategy is a non-repainting trend-following system that integrates:
Triangular Hull MA for advanced trend detection.
Real-time volatility visualization.
Clear entry signals based on trend reversals.
Configurable trade direction settings.
It is ideal for traders who:
Prefer smoothed price analysis.
Want to follow trends with precision.
Value visual volatility feedback for breakout detection.
Full credit for the original concept and indicator goes to BigBeluga.
Strategy Stats [presentTrading]Hello! it's another weekend. This tool is a strategy performance analysis tool. Looking at the TradingView community, it seems few creators focus on this aspect. I've intentionally created a shared version. Welcome to share your idea or question on this.
█ Introduction and How it is Different
Strategy Stats is a comprehensive performance analytics framework designed specifically for trading strategies. Unlike standard strategy backtesting tools that simply show cumulative profits, this analytics suite provides real-time, multi-timeframe statistical analysis of your trading performance.
Multi-timeframe analysis: Automatically tracks performance metrics across the most recent time periods (last 7 days, 30 days, 90 days, 1 year, and 4 years)
Advanced statistical measures: Goes beyond basic metrics to include Information Coefficient (IC) and Sortino Ratio
Real-time feedback: Updates performance statistics with each new trade
Visual analytics: Color-coded performance table provides instant visual feedback on strategy health
Integrated risk management: Implements sophisticated take profit mechanisms with 3-step ATR and percentage-based exits
BTCUSD Performance
The table in the upper right corner is a comprehensive performance dashboard showing trading strategy statistics.
Note: While this presentation uses Vegas SuperTrend as the underlying strategy, this is merely an example. The Stats framework can be applied to any trading strategy. The Vegas SuperTrend implementation is included solely to demonstrate how the analytics module integrates with a trading strategy.
⚠️ Timeframe Limitations
Important: TradingView's backtesting engine has a maximum storage limit of 10,000 bars. When using this strategy stats framework on smaller timeframes such as 1-hour or 2-hour charts, you may encounter errors if your backtesting period is too long.
Recommended Timeframe Usage:
Ideal for: 4H, 6H, 8H, Daily charts and above
May cause errors on: 1H, 2H charts spanning multiple years
Not recommended for: Timeframes below 1H with long history
█ Strategy, How it Works: Detailed Explanation
The Strategy Stats framework consists of three primary components: statistical data collection, performance analysis, and visualization.
🔶 Statistical Data Collection
The system maintains several critical data arrays:
equityHistory: Tracks equity curve over time
tradeHistory: Records profit/loss of each trade
predictionSignals: Stores trade direction signals (1 for long, -1 for short)
actualReturns: Records corresponding actual returns from each trade
For each closed trade, the system captures:
float tradePnL = strategy.closedtrades.profit(tradeIndex)
float tradeReturn = strategy.closedtrades.profit_percent(tradeIndex)
int tradeType = entryPrice < exitPrice ? 1 : -1 // Direction
🔶 Performance Metrics Calculation
The framework calculates several key performance metrics:
Information Coefficient (IC):
The correlation between prediction signals and actual returns, measuring forecast skill.
IC = Correlation(predictionSignals, actualReturns)
Where Correlation is the Pearson correlation coefficient:
Correlation(X,Y) = (nΣXY - ΣXY) / √
Sortino Ratio:
Measures risk-adjusted return focusing only on downside risk:
Sortino = (Avg_Return - Risk_Free_Rate) / Downside_Deviation
Where Downside Deviation is:
Downside_Deviation = √
R_i represents individual returns, T is the target return (typically the risk-free rate), and n is the number of observations.
Maximum Drawdown:
Tracks the largest percentage drop from peak to trough:
DD = (Peak_Equity - Trough_Equity) / Peak_Equity * 100
🔶 Time Period Calculation
The system automatically determines the appropriate number of bars to analyze for each timeframe based on the current chart timeframe:
bars_7d = math.max(1, math.round(7 * barsPerDay))
bars_30d = math.max(1, math.round(30 * barsPerDay))
bars_90d = math.max(1, math.round(90 * barsPerDay))
bars_365d = math.max(1, math.round(365 * barsPerDay))
bars_4y = math.max(1, math.round(365 * 4 * barsPerDay))
Where barsPerDay is calculated based on the chart timeframe:
barsPerDay = timeframe.isintraday ?
24 * 60 / math.max(1, (timeframe.in_seconds() / 60)) :
timeframe.isdaily ? 1 :
timeframe.isweekly ? 1/7 :
timeframe.ismonthly ? 1/30 : 0.01
🔶 Visual Representation
The system presents performance data in a color-coded table with intuitive visual indicators:
Green: Excellent performance
Lime: Good performance
Gray: Neutral performance
Orange: Mediocre performance
Red: Poor performance
█ Trade Direction
The Strategy Stats framework supports three trading directions:
Long Only: Only takes long positions when entry conditions are met
Short Only: Only takes short positions when entry conditions are met
Both: Takes both long and short positions depending on market conditions
█ Usage
To effectively use the Strategy Stats framework:
Apply to existing strategies: Add the performance tracking code to any strategy to gain advanced analytics
Monitor multiple timeframes: Use the multi-timeframe analysis to identify performance trends
Evaluate strategy health: Review IC and Sortino ratios to assess predictive power and risk-adjusted returns
Optimize parameters: Use performance data to refine strategy parameters
Compare strategies: Apply the framework to multiple strategies to identify the most effective approach
For best results, allow the strategy to generate sufficient trade history for meaningful statistical analysis (at least 20-30 trades).
█ Default Settings
The default settings have been carefully calibrated for cryptocurrency markets:
Performance Tracking:
Time periods: 7D, 30D, 90D, 1Y, 4Y
Statistical measures: Return, Win%, MaxDD, IC, Sortino Ratio
IC color thresholds: >0.3 (green), >0.1 (lime), <-0.1 (orange), <-0.3 (red)
Sortino color thresholds: >1.0 (green), >0.5 (lime), <0 (red)
Multi-Step Take Profit:
ATR multipliers: 2.618, 5.0, 10.0
Percentage levels: 3%, 8%, 17%
Short multiplier: 1.5x (makes short take profits more aggressive)
Stop loss: 20%
