Fusion Trend Pulse V2SCRIPT TITLE
Adaptive Fusion Trend Pulse V2 - Multi-Regime Strategy
DETAILED DESCRIPTION FOR PUBLICATION
🚀 INNOVATION SUMMARY
The Adaptive Fusion Trend Pulse V2 represents a breakthrough in algorithmic trading by introducing real-time market regime detection that automatically adapts strategy parameters based on current market conditions. Unlike static indicator combinations, this system dynamically adjusts its behavior across trending, choppy, and volatile market environments, providing a sophisticated multi-layered approach to market analysis.
🎯 CORE INNOVATIONS JUSTIFYING PROTECTED STATUS
1. Adaptive Market Regime Engine
Trending Market Detection: Uses ADX >25 with directional movement analysis
Volatile Market Classification: ATR-based volatility regime scoring (>1.2 threshold)
Choppy Market Identification: ADX <20 combined with volatility patterns
Dynamic Parameter Adjustment: All thresholds adapt based on detected regime
2. Multi-Component Fusion Algorithm
McGinley Dynamic Trend Baseline: Self-adjusting moving average that adapts to price velocity
Adaptive RMI (Relative Momentum Index): Enhanced RSI with momentum period adaptation
Zero-Lag EMA Smoothed CCI: Custom implementation reducing lag while maintaining signal quality
Hull MA Gradient Analysis: Slope strength normalized by ATR for trend confirmation
Volume Spike Detection: Regime-adjusted volume confirmation (0.8x-1.3x multipliers)
3. Intelligence Layer Features
Cooldown System: Prevents overtrading with regime-specific waiting periods (1-3 bars)
Performance Tracking: Real-time adaptation based on recent trade outcomes
Multi-Exchange Alert Integration: JSON-formatted alerts for automated trading
Comprehensive Dashboard: 16-metric real-time performance monitoring
📊 TECHNICAL SPECIFICATIONS
Market Regime Detection Philosophy:
The system continuously monitors market structure through volatility analysis and directional strength measurements. Rather than applying fixed thresholds, it creates dynamic response profiles that adjust the strategy's sensitivity, timing, and filtering based on the current market environment.
Adaptive Parameter Concept:
All strategy components modify their behavior based on regime classification. Volume requirements become more or less stringent, momentum thresholds shift to match market character, and exit timing adjusts to prevent whipsaws in different market conditions.
Entry Conditions (Both Long/Short):
McGinley trend alignment (close vs trend line)
Hull MA slope confirmation with ATR-normalized strength
Adaptive CCI above/below regime-specific thresholds
RMI momentum confirmation (>50 for long, <50 for short)
Volume spike exceeding regime-adjusted threshold
Regime-specific additional filters
Exit Strategy:
Dual take-profit system (2% and 4% default, customizable)
Momentum weakness detection (CCI reversal)
Trend breakdown (close below/above McGinley line)
Regime-specific urgency multipliers for faster exits in choppy markets
🎛️ USER CUSTOMIZATION OPTIONS
Core Parameters:
RMI Length & Momentum periods
CCI smoothing length
McGinley Dynamic length
Hull MA period for gradient analysis
Volume spike detection (length & multiplier)
Take profit levels (separate for long/short)
Adaptive Settings:
Market regime detection period (21 bars default)
Adaptation period for performance tracking (60 bars)
Volatility adaptation toggle
Trend strength filtering toggle
Momentum sensitivity multiplier (0.5-2.0 range)
Dashboard & Alerts:
Dashboard position (4 corners)
Dashboard size (Small/Normal/Large)
Transparency settings (0-100%)
Custom alert messages for bot integration
Date range filtering
🏆 UNIQUE VALUE PROPOSITIONS
1. Market Intelligence: First Pine Script strategy to implement comprehensive regime detection with parameter adaptation - most strategies use static settings regardless of market conditions.
2. Fusion Methodology: Combines 5+ distinct technical approaches (trend-following, momentum, volatility, volume, regime analysis) in a cohesive adaptive framework rather than simple indicator stacking.
3. Performance Optimization: Built-in learning system tracks recent performance and adjusts sensitivity - providing evolution rather than static rule-following.
4. Professional Integration: Enterprise-ready with JSON alert formatting, multi-exchange compatibility, and comprehensive performance tracking suitable for institutional use.
5. Visual Intelligence: Advanced dashboard provides 16 real-time metrics including regime classification, signal strength, and performance analytics - far beyond basic P&L displays.
🔧 TECHNICAL IMPLEMENTATION HIGHLIGHTS
Primary Applications:
Swing Trading: 4H-1D timeframes with regime-adapted entries
Algorithmic Trading: Automated execution via webhook alerts
Portfolio Management: Multi-timeframe analysis across different market conditions
Risk Management: Regime-aware position sizing and exit timing
Target Markets:
Cryptocurrency pairs (high volatility adaptation)
Forex majors (trending market optimization)
Stock indices (choppy market handling)
Commodities (volatile regime management)
🎯 WHY THIS ISN'T JUST AN INDICATOR MASHUP
Integrated Adaptation Framework: Unlike scripts that simply combine multiple indicators with static settings, this system creates a unified intelligence layer where each component influences and adapts to the others. The McGinley trend baseline doesn't just provide signals - it dynamically adjusts its sensitivity based on market regime detection. The momentum components modify their thresholds based on trend strength analysis.
Feedback Loop Architecture: The strategy incorporates a closed-loop learning system where recent performance influences future parameter selection. This creates evolution rather than static rule application. Most indicator combinations lack this adaptive learning capability.
Contextual Decision Making: Rather than treating each signal independently, the system uses contextual analysis where the same technical setup may generate different responses based on the current market regime. A momentum signal in a trending market triggers different behavior than the identical signal in choppy conditions.
Unified Risk Management: The regime detection doesn't just affect entries - it creates a comprehensive risk framework that adjusts exit timing, cooldown periods, and position management based on market character. This holistic approach distinguishes it from simple indicator stacking.
Custom Implementation Depth: Each component uses proprietary implementations (custom McGinley calculation, zero-lag CCI smoothing, enhanced RMI) rather than standard built-in functions, creating a cohesive algorithmic ecosystem rather than disconnected indicator outputs.
Custom Functions:
mcginley(): Proprietary implementation of McGinley Dynamic MA
rmi(): Enhanced Relative Momentum Index with custom parameters
zlema(): Zero-lag EMA for CCI smoothing
Regime classification algorithms with multi-factor analysis
Performance Optimizations:
Efficient variable management with proper scoping
Minimal repainting through careful historical referencing
Optimized calculations to prevent timeout issues
Memory-efficient tracking systems
Alert System:
JSON-formatted messages for API integration
Dynamic symbol/exchange substitution
Separate entry/exit/TP alert conditions
Customizable message formatting
⚡ WHY THIS REQUIRES PROTECTION
This strategy represents months of research into adaptive trading systems and market regime analysis. The specific combination of:
Proprietary regime detection algorithms
Custom adaptive parameter calculations
Multi-indicator fusion methodology
Performance-based learning system
Professional-grade implementation
Creates intellectual property that provides genuine competitive advantage. The methodology is not available in existing open-source scripts and represents original research into algorithmic trading adaptation.
🎯 EDUCATIONAL VALUE
Users gain exposure to:
Advanced market regime analysis techniques
Adaptive parameter optimization concepts
Multi-timeframe indicator fusion
Professional strategy development practices
Automated trading integration methods
The comprehensive dashboard and parameter explanations serve as a learning tool for understanding how professional algorithms adapt to changing market conditions.
CATEGORY SELECTION
Primary: Strategy
Secondary: Trend Analysis
SUGGESTED TAGS
adaptive, trend, momentum, regime, strategy, alerts, dashboard, mcginley, rmi, cci, professional
MANDATORY DISCLAIMER
Disclaimer: This strategy is for educational and informational purposes only. It does not constitute financial advice. Trading cryptocurrencies involves substantial risk, and past performance is not indicative of future results. Always backtest and forward-test before using on a live account. Use at your own risk.
스크립트에서 "bar"에 대해 찾기
EUR/USD Multi-Layer Statistical Regression StrategyStrategy Overview
This advanced EUR/USD trading system employs a triple-layer linear regression framework with statistical validation and ensemble weighting. It combines short, medium, and long-term regression analyses to generate high-confidence directional signals while enforcing strict risk controls.
Core Components
Multi-Layer Regression Engine:
Parallel regression analysis across 3 customizable timeframes (short/medium/long)
Projects future price values using prediction horizons
Statistical significance filters (R-squared, correlation, slope thresholds)
Signal Validation System:
Lookback validation tests historical prediction accuracy
Ensemble weighting of layer signals (adjustable influence per timeframe)
Confidence scoring combining statistical strength, layer agreement, and validation accuracy
Risk Management:
Position sizing scaled by signal confidence (1%-100% of equity)
Daily loss circuit breaker (halts trading at user-defined threshold)
Forex-tailored execution (pip slippage, percentage-based commissions)
Visual Intelligence:
Real-time regression line plots (3 layered colors)
Projection markers for short-term forecasts
Background coloring for market bias indication
Comprehensive statistics dashboard (R-squared metrics, validation scores, P&L)
Key Parameters
Category Settings
Regression Short/Med/Long lengths (20/50/100 bars)
Statistics Min R² (0.65), Correlation (0.7), Slope (0.0001)
Validation 30-bar lookback, 10-bar projection
Risk Controls 50% position size, 12% daily loss limit, 75% confidence threshold
Trading Logic
Entries require:
Ensemble score > |0.5|
Confidence > threshold
Short & medium-term significance
Active daily loss limit not breached
Exits triggered by:
Opposite high-confidence signals
Daily loss limit violation (emergency exit)
The strategy blends quantitative finance techniques with practical trading safeguards, featuring a self-optimizing design where signal quality directly impacts position sizing. The visual dashboard provides real-time feedback on model performance and market conditions.
KST Strategy [Skyrexio]Overview
KST Strategy leverages Know Sure Thing (KST) indicator in conjunction with the Williams Alligator and Moving average to obtain the high probability setups. KST is used for for having the high probability to enter in the direction of a current trend when momentum is rising, Alligator is used as a short term trend filter, while Moving average approximates the long term trend and allows trades only in its direction. Also strategy has the additional optional filter on Choppiness Index which does not allow trades if market is choppy, above the user-specified threshold. Strategy has the user specified take profit and stop-loss numbers, but multiplied by Average True Range (ATR) value on the moment when trade is open. The strategy opens only long trades.
Unique Features
ATR based stop-loss and take profit. Instead of fixed take profit and stop-loss percentage strategy utilizes user chosen numbers multiplied by ATR for its calculation.
Configurable Trading Periods. Users can tailor the strategy to specific market windows, adapting to different market conditions.
Optional Choppiness Index filter. Strategy allows to choose if it will use the filter trades with Choppiness Index and set up its threshold.
Methodology
The strategy opens long trade when the following price met the conditions:
Close price is above the Alligator's jaw line
Close price is above the filtering Moving average
KST line of Know Sure Thing indicator shall cross over its signal line (details in justification of methodology)
If the Choppiness Index filter is enabled its value shall be less than user defined threshold
When the long trade is executed algorithm defines the stop-loss level as the low minus user defined number, multiplied by ATR at the trade open candle. Also it defines take profit with close price plus user defined number, multiplied by ATR at the trade open candle. While trade is in progress, if high price on any candle above the calculated take profit level or low price is below the calculated stop loss level, trade is closed.
Strategy settings
In the inputs window user can setup the following strategy settings:
ATR Stop Loss (by default = 1.5, number of ATRs to calculate stop-loss level)
ATR Take Profit (by default = 3.5, number of ATRs to calculate take profit level)
Filter MA Type (by default = Least Squares MA, type of moving average which is used for filter MA)
Filter MA Length (by default = 200, length for filter MA calculation)
Enable Choppiness Index Filter (by default = true, setting to choose the optional filtering using Choppiness index)
Choppiness Index Threshold (by default = 50, Choppiness Index threshold, its value shall be below it to allow trades execution)
Choppiness Index Length (by default = 14, length used in Choppiness index calculation)
KST ROC Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #2 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #3 (by default = 20, value used in KST indicator calculation, more information in Justification of Methodology)
KST ROC Length #4 (by default = 30, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #1 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #2 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #3 (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
KST SMA Length #4 (by default = 15, value used in KST indicator calculation, more information in Justification of Methodology)
KST Signal Line Length (by default = 10, value used in KST indicator calculation, more information in Justification of Methodology)
User can choose the optimal parameters during backtesting on certain price chart.
Justification of Methodology
Before understanding why this particular combination of indicator has been chosen let's briefly explain what is KST, Williams Alligator, Moving Average, ATR and Choppiness Index.
The KST (Know Sure Thing) is a momentum oscillator developed by Martin Pring. It combines multiple Rate of Change (ROC) values, smoothed over different timeframes, to identify trend direction and momentum strength. First of all, what is ROC? ROC (Rate of Change) is a momentum indicator that measures the percentage change in price between the current price and the price a set number of periods ago.
ROC = 100 * (Current Price - Price N Periods Ago) / Price N Periods Ago
In our case N is the KST ROC Length inputs from settings, here we will calculate 4 different ROCs to obtain KST value:
KST = ROC1_smooth × 1 + ROC2_smooth × 2 + ROC3_smooth × 3 + ROC4_smooth × 4
ROC1 = ROC(close, KST ROC Length #1), smoothed by KST SMA Length #1,
ROC2 = ROC(close, KST ROC Length #2), smoothed by KST SMA Length #2,
ROC3 = ROC(close, KST ROC Length #3), smoothed by KST SMA Length #3,
ROC4 = ROC(close, KST ROC Length #4), smoothed by KST SMA Length #4
Also for this indicator the signal line is calculated:
Signal = SMA(KST, KST Signal Line Length)
When the KST line rises, it indicates increasing momentum and suggests that an upward trend may be developing. Conversely, when the KST line declines, it reflects weakening momentum and a potential downward trend. A crossover of the KST line above its signal line is considered a buy signal, while a crossover below the signal line is viewed as a sell signal. If the KST stays above zero, it indicates overall bullish momentum; if it remains below zero, it points to bearish momentum. The KST indicator smooths momentum across multiple timeframes, helping to reduce noise and provide clearer signals for medium- to long-term trends.
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
The next indicator is Moving Average. It has a lot of different types which can be chosen to filter trades and the Least Squares MA is used by default settings. Let's briefly explain what is it.
The Least Squares Moving Average (LSMA) — also known as Linear Regression Moving Average — is a trend-following indicator that uses the least squares method to fit a straight line to the price data over a given period, then plots the value of that line at the most recent point. It draws the best-fitting straight line through the past N prices (using linear regression), and then takes the endpoint of that line as the value of the moving average for that bar. The LSMA aims to reduce lag and highlight the current trend more accurately than traditional moving averages like SMA or EMA.
Key Features:
It reacts faster to price changes than most moving averages.
It is smoother and less noisy than short-term EMAs.
It can be used to identify trend direction, momentum, and potential reversal points.
ATR (Average True Range) is a volatility indicator that measures how much an asset typically moves during a given period. It was introduced by J. Welles Wilder and is widely used to assess market volatility, not direction.
To calculate it first of all we need to get True Range (TR), this is the greatest value among:
High - Low
abs(High - Previous Close)
abs(Low - Previous Close)
ATR = MA(TR, n) , where n is number of periods for moving average, in our case equals 14.
ATR shows how much an asset moves on average per candle/bar. A higher ATR means more volatility; a lower ATR means a calmer market.
The Choppiness Index is a technical indicator that quantifies whether the market is trending or choppy (sideways). It doesn't indicate trend direction — only the strength or weakness of a trend. Higher Choppiness Index usually approximates the sideways market, while its low value tells us that there is a high probability of a trend.
Choppiness Index = 100 × log10(ΣATR(n) / (MaxHigh(n) - MinLow(n))) / log10(n)
where:
ΣATR(n) = sum of the Average True Range over n periods
MaxHigh(n) = highest high over n periods
MinLow(n) = lowest low over n periods
log10 = base-10 logarithm
Now let's understand how these indicators work in conjunction and why they were chosen for this strategy. KST indicator approximates current momentum, when it is rising and KST line crosses over the signal line there is high probability that short term trend is reversing to the upside and strategy allows to take part in this potential move. Alligator's jaw (blue) line is used as an approximation of a short term trend, taking trades only above it we want to avoid trading against trend to increase probability that long trade is going to be winning.
Almost the same for Moving Average, but it approximates the long term trend, this is just the additional filter. If we trade in the direction of the long term trend we increase probability that higher risk to reward trade will hit the take profit. Choppiness index is the optional filter, but if it turned on it is used for approximating if now market is in sideways or in trend. On the range bounded market the potential moves are restricted. We want to decrease probability opening trades in such condition avoiding trades if this index is above threshold value.
When trade is open script sets the stop loss and take profit targets. ATR approximates the current volatility, so we can make a decision when to exit a trade based on current market condition, it can increase the probability that strategy will avoid the excessive stop loss hits, but anyway user can setup how many ATRs to use as a stop loss and take profit target. As was said in the Methodology stop loss level is obtained by subtracting number of ATRs from trade opening candle low, while take profit by adding to this candle's close.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2025.05.01. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 60%
Maximum Single Position Loss: -5.53%
Maximum Single Profit: +8.35%
Net Profit: +5175.20 USDT (+51.75%)
Total Trades: 120 (56.67% win rate)
Profit Factor: 1.747
Maximum Accumulated Loss: 1039.89 USDT (-9.1%)
Average Profit per Trade: 43.13 USDT (+0.6%)
Average Trade Duration: 27 hours
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 1h BTC/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrexio commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation.
Reversal Trap Sniper – Verified VersionReversal Trap Sniper
Overview
Reversal Trap Sniper is a counterintuitive momentum-following strategy that identifies "reversal traps"—situations where traders expect a market reversal based on RSI, but the price continues trending. By detecting these failed reversal signals, the strategy enters trades in the trend direction, often catching strong follow-through moves.
How It Works
The system monitors the Relative Strength Index (RSI). When RSI moves above the overbought level (e.g., 70) and then drops back below it, many traders interpret this as a sell signal.
However, this strategy treats such moves with caution. If the RSI pulls back below the overbought threshold but the price continues to rise, the system considers it a "reversal trap"—a fakeout.
In such cases, instead of going short, the strategy enters a long position, assuming that the trend is still valid and those betting on a reversal may fuel a breakout.
Similarly, if RSI rises above the oversold level from below, but price continues falling, a short trade is triggered.
Entries are followed by ATR-based stop-loss and dynamic take-profit (2× risk), with a fallback time-based exit after 30 bars.
Key Features
- Detects failed RSI-based reversals ("traps")
- Follows momentum after the trap is triggered
- Uses ATR for dynamic stop-loss and take-profit
- Auto-exit after a fixed bar count (30 bars)
- Visual markers on chart for transparency
- Realistic trading assumptions: 0.05% commission, slippage, and capped pyramiding
Parameter Explanation
RSI Length (14): Standard RSI calculation period
Overbought/Oversold Levels (70/30): Common thresholds used by many traders
ATR Length (14): Used to define stop-loss and target dynamically
Risk-Reward Ratio (2.0): Take-profit is set at 2× the stop-loss distance
Max Holding Bars (30): Ensures trades don’t remain open indefinitely
Pyramiding (10): Allows scaling into trades, simulating real-world strategy stacking
Originality Note
This strategy inverts traditional RSI logic. Instead of treating overbought/oversold conditions as signals for reversal, it waits for those signals to fail. Only after such failures, confirmed by continued price action in the same direction, does the system enter trades. This logic is based on the behavioral observation that failed reversal signals often trigger stronger trend continuation—making this strategy uniquely positioned to exploit trap scenarios.
Disclaimer
This script is for educational and research purposes only. Trading involves risk, and past performance does not guarantee future results. Always test thoroughly before applying with live capital.
The VoVix Experiment The VoVix Experiment
The VoVix Experiment is a next-generation, regime-aware, volatility-adaptive trading strategy for futures, indices, and more. It combines a proprietary VoVix (volatility-of-volatility) anomaly detector with price structure clustering and critical point logic, only trading when multiple independent signals align. The system is designed for robustness, transparency, and real-world execution.
Logic:
VoVix Regime Engine: Detects pre-move volatility anomalies using a fast/slow ATR ratio, normalized by Z-score. Only trades when a true regime spike is detected, not just random volatility.
Cluster & Critical Point Filters: Price structure and volatility clustering must confirm the VoVix signal, reducing false positives and whipsaws.
Adaptive Sizing: Position size scales up for “super-spikes” and down for normal events, always within user-defined min/max.
Session Control: Trades only during user-defined hours and days, avoiding illiquid or high-risk periods.
Visuals: Aurora Flux Bands (From another Original of Mine (Options Flux Flow): glow and change color on signals, with a live dashboard, regime heatmap, and VoVix progression bar for instant insight.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 15 min (but works on all timeframes)
Order size: Adaptive, 1–2 contracts
Session: 5:00–15:00 America/Chicago (default, fully adjustable)
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for MNQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Forward Testing: (This is no guarantee. I've provided these results to show that executions perform as intended. Test were done on Tradovate)
ALL TRADES
Gross P/L: $12,907.50
# of Trades: 64
# of Contracts: 186
Avg. Trade Time: 1h 55min 52sec
Longest Trade Time: 55h 46min 53sec
% Profitable Trades: 59.38%
Expectancy: $201.68
Trade Fees & Comm.: $(330.95)
Total P/L: $12,576.55
Winning Trades: 59.38%
Breakeven Trades: 3.12%
Losing Trades: 37.50%
Link: www.dropbox.com
Inputs & Tooltips
VoVix Regime Execution: Enable/disable the core VoVix anomaly detector.
Volatility Clustering: Require price/volatility clusters to confirm VoVix signals.
Critical Point Detector: Require price to be at a statistically significant distance from the mean (regime break).
VoVix Fast ATR Length: Short ATR for fast volatility detection (lower = more sensitive).
VoVix Slow ATR Length: Long ATR for baseline regime (higher = more stable).
VoVix Z-Score Window: Lookback for Z-score normalization (higher = smoother, lower = more reactive).
VoVix Entry Z-Score: Minimum Z-score for a VoVix spike to trigger a trade.
VoVix Exit Z-Score: Z-score below which the regime is considered decayed (exit).
VoVix Local Max Window: Bars to check for local maximum in VoVix (higher = stricter).
VoVix Super-Spike Z-Score: Z-score for “super” regime events (scales up position size).
Min/Max Contracts: Adaptive position sizing range.
Session Start/End Hour: Only trade between these hours (exchange time).
Allow Weekend Trading: Enable/disable trading on weekends.
Session Timezone: Timezone for session filter (e.g., America/Chicago for CME).
Show Trade Labels: Show/hide entry/exit labels on chart.
Flux Glow Opacity: Opacity of Aurora Flux Bands (0–100).
Flux Band EMA Length: EMA period for band center.
Flux Band ATR Multiplier: Width of bands (higher = wider).
Compliance & Transparency
* No hidden logic, no repainting, no pyramiding.
* All signals, sizing, and exits are fully explained and visible.
* Backtest settings are stricter than most real accounts.
* All visuals are directly tied to the strategy logic.
* This is not a mashup or cosmetic overlay; every component is original and justified.
Disclaimer
Trading is risky. This script is for educational and research purposes only. Do not trade with money you cannot afford to lose. Past performance is not indicative of future results. Always test in simulation before live trading.
Proprietary Logic & Originality Statement
This script, “The VoVix Experiment,” is the result of original research and development. All core logic, algorithms, and visualizations—including the VoVix regime detection engine, adaptive execution, volatility/divergence bands, and dashboard—are proprietary and unique to this project.
1. VoVix Regime Logic
The concept of “volatility of volatility” (VoVix) is an original quant idea, not a standard indicator. The implementation here (fast/slow ATR ratio, Z-score normalization, local max logic, super-spike scaling) is custom and not found in public TradingView scripts.
2. Cluster & Critical Point Logic
Volatility clustering and “critical point” detection (using price distance from a rolling mean and standard deviation) are general quant concepts, but the way they are combined and filtered here is unique to this script. The specific logic for “clustered chop” and “critical point” is not a copy of any public indicator.
3. Adaptive Sizing
The adaptive sizing logic (scaling contracts based on regime strength) is custom and not a standard TradingView feature or public script.
4. Time Block/Session Control
The session filter is a common feature in many strategies, but the implementation here (with timezone and weekend control) is written from scratch.
5. Aurora Flux Bands (From another Original of Mine (Options Flux Flow)
The “glowing” bands are inspired by the idea of volatility bands (like Bollinger Bands or Keltner Channels), but the visual effect, color logic, and integration with regime signals are original to this script.
6. Dashboard, Watermark, and Metrics
The dashboard, real-time Sharpe/Sortino, and VoVix progression bar are all custom code, not copied from any public script.
What is “standard” or “common quant practice”?
Using ATR, EMA, and Z-score are standard quant tools, but the way they are combined, filtered, and visualized here is unique. The structure and logic of this script are original and not a mashup of public code.
This script is 100% original work. All logic, visuals, and execution are custom-coded for this project. No code or logic is directly copied from any public or private script.
Use with discipline. Trade your edge.
— Dskyz, for DAFE Trading Systems
Dskyz (DAFE) GENESIS Dskyz (DAFE) GENESIS: Adaptive Quant, Real Regime Power
Let’s be honest: Most published strategies on TradingView look nearly identical—copy-paste “open-source quant,” generic “adaptive” buzzwords, the same shallow explanations. I’ve even fallen into this trap with my own previously posted strategies. Not this time.
What Makes This Unique
GENESIS is not a black-box mashup or a pre-built template. It’s the culmination of DAFE’s own adaptive, multi-factor, regime-aware quant engine—built to outperform, survive, and visualize live edge in anything from NQ/MNQ to stocks and crypto.
True multi-factor core: Volume/price imbalances, trend shifts, volatility compression/expansion, and RSI all interlock for signal creation.
Adaptive regime logic: Trades only in healthy, actionable conditions—no “one-size-fits-all” signals.
Momentum normalization: Uses rolling, percentile-based fast/slow EMA differentials, ALWAYS normalized, ALWAYS relevant—no “is it working?” ambiguity.
Position sizing that adapts: Not fixed-lot, not naive—not a loophole for revenge trading.
No hidden DCA or pyramiding—what you see is what you trade.
Dashboard and visual system: Directly connected to internal logic. If it’s shown, it’s used—and nothing cosmetic is presented on your chart that isn’t quantifiable.
📊 Inputs and What They Mean (Read Carefully)
Maximum Raw Score: How many distinct factors can contribute to regime/trade confidence (default 4). If you extend the quant logic, increase this.
RSI Length / Min RSI for Shorts / Max RSI for Longs: Fine-tunes how “overbought/oversold” matters; increase the length for smoother swings, tighten floors/ceilings for more extreme signals.
⚡ Regime & Momentum Gates
Min Normed Momentum/Score (Conf): Raise to demand only the strongest trends—your filter to avoid algorithmic chop.
🕒 Volatility & Session
ATR Lookback, ATR Low/High Percentile: These control your system’s awareness of when the market is dead or ultra-volatile. All sizing and filter logic adapts in real time.
Trading Session (hours): Easy filter for when entries are allowed; default is regular trading hours—no surprise overnight fills.
📊 Sizing & Risk
Max Dollar Risk / Base-Max Contracts: All sizing is adaptive, based on live regime and volatility state—never static or “just 1 contract.” Control your max exposures and real $ risk. ATR will effect losses in high volatility times.
🔄 Exits & Scaling
Stop/Trail/Scale multipliers: You choose how dynamic/flexible risk controls and profit-taking need to be. ATR-based, so everything auto-adjusts to the current market mode.
Visuals That Actually Matter
Dashboard (Top Right): Shows only live, relevant stats: scoring, status, position size, win %, win streak, total wins—all from actual trade engine state (not “simulated”).
Watermark (Bottom Right): Momentum bar visual is always-on, regime-aware, reflecting live regime confidence and momentum normalization. If the bar is empty, you’re truly in no-momentum. If it glows lime, you’re riding the strongest possible edge.
*No cosmetics, no hidden code distractions.
Backtest Settings
Initial capital: $10,000
Commission: Conservative, realistic roundtrip cost:
15–20 per contract (including slippage per side) I set this to $25
Slippage: 3 ticks per trade
Symbol: CME_MINI:NQ1!
Timeframe: 1 min (but works on all timeframes)
Order size: Adaptive, 1–3 contracts
No pyramiding, no hidden DCA
Why these settings?
These settings are intentionally strict and realistic, reflecting the true costs and risks of live trading. The 10,000 account size is accessible for most retail traders. 25/contract including 3 ticks of slippage are on the high side for NQ, ensuring the strategy is not curve-fit to perfect fills. If it works here, it will work in real conditions.
Why It Wins
While others put out “AI-powered” strategies with little logic or soul, GENESIS is ruthlessly practical. It is built around what keeps traders alive:
- Context-aware signals, not just patterns
- Tight, transparent risk
- Inputs that adapt, not confuse
- Visuals that clarify, not distract
- Code that runs clean, efficient, and with minimal overfitting risk (try it on QQQ, AMD, SOL, etc. out of the box)
Disclaimer (for TradingView compliance):
Trading is risky. Futures, stocks, and crypto can result in significant losses. Do not trade with funds you cannot afford to lose. This is for educational and informational purposes only. Use in simulation/backtest mode before live trading. No past performance is indicative of future results. Always understand your risk and ownership of your trades.
This will not be my last—my goal is to keep raising the bar until DAFE is a brand or I’m forced to take this private.
Use with discipline, use with clarity, and always trade smarter.
— Dskyz , powered by DAFE Trading Systems.
G-Bot v3Overview:
G-Bot is an invite-only Pine Script tailored for traders seeking a precise, automated breakout strategy. This closed-source script integrates with 3Commas via API to execute trades seamlessly, combining classic indicators with proprietary logic to identify high-probability breakouts. G-Bot stands out by filtering market noise through a unique confluence of signals, offering adaptive risk management, and employing advanced alert deduplication to ensure reliable automation. Its purpose-built design delivers actionable signals for traders prioritizing consistency and efficiency in trending markets.
What It Does and How It Works:
G-Bot generates trade signals by evaluating four key market dimensions—trend, price action, momentum, and volume—on each 60-minute bar. The script’s core components and their roles are:
Trend Detection (EMAs): Confirms trend direction by checking if the 5-period EMA is above (bullish) or below (bearish) the 6-period EMA, with the price positioned accordingly (above the 5-period EMA for longs, below for shorts). The tight EMA pairing is optimized for the 60-minute timeframe to capture sustained trends while minimizing lag.
Price Action Trigger (Swing Highs/Lows): Identifies breakouts when the price crosses above the previous swing high (for longs) or below the previous swing low (for shorts), using a period lookback to focus on recent price pivots. This ensures entries align with significant market moves.
Momentum Filter (RSI): Validates breakouts by requiring RSI to fall within moderated ranges. These ranges avoid overbought/oversold extremes, prioritizing entries with balanced momentum to enhance trade reliability.
Volume Confirmation (3-period SMA): Requires volume to exceed its 3-period SMA, confirming that breakouts are driven by strong market participation, reducing the risk of false moves.
Risk Management (14-period ATR): Calculates stop-loss distances (ATR) and trailing stops (ATR and ATR-point offset) to align trades with current volatility, protecting capital and locking in profits.
These components work together to create a disciplined system: the EMAs establish trend context, swing breaks confirm price momentum, RSI filters for optimal entry timing, and volume ensures market conviction. This confluence minimizes false signals, a critical advantage for hourly breakout trading.
Why It’s Original and Valuable:
G-Bot’s value lies in its meticulous integration of standard indicators into a non-standard, automation-focused system. Its unique features include:
Curated Signal Confluence: Unlike generic breakout scripts that rely on single-indicator triggers (e.g., EMA crossovers), G-Bot requires simultaneous alignment of trend, price action, momentum, and volume. This multi-layered approach, reduces noise and prioritizes high-conviction setups, addressing a common flaw in simpler strategies.
Proprietary Alert Deduplication: G-Bot employs a custom mechanism to prevent redundant alerts, using a 1-second minimum gap and bar-index tracking. This ensures signals are actionable and compatible with 3Commas’ high-frequency automation, a feature not found in typical Pine Scripts.
Adaptive Position Sizing: The script calculates trade sizes based on user inputs (1-5% equity risk, max USD cap, equity threshold) and ATR-derived stop distances, ensuring positions reflect both account size and market conditions. This dynamic approach enhances risk control beyond static sizing methods.
3Commas API Optimization: G-Bot generates JSON-formatted alerts with precise position sizing and exit instructions, enabling seamless integration with 3Commas bots. This level of automation, paired with detailed Telegram alerts for monitoring, streamlines the trading process.
Visual Clarity: On-chart visuals—green triangles for long entries, red triangles for shorts, orange/teal lines for swing levels, yellow circles for price crosses—provide immediate insight into signal triggers, allowing traders to validate setups without accessing the code.
G-Bot is not a repackaging of public code but a specialized tool that transforms familiar indicators into a robust, automated breakout system. Its originality lies in the synergy of its components, proprietary alert handling, and trader-centric automation, justifying its invite-only status.
How to Use:
Setup: Apply G-Bot to BITGET’s BTCUSDT.P chart on a 60-minute timeframe.
3Commas Configuration: Enter your 3Commas API Secret Key and Bot UUID in the script’s input settings to enable webhook integration.
Risk Parameters: Adjust Risk % (1-5%), Max Risk ($), and Equity Threshold ($) to align position sizing with your account and risk tolerance.
Webhook Setup: Configure 3Commas to receive JSON alerts for automated trade execution. Optionally, connect Telegram for detailed signal notifications.
Monitoring: Use on-chart visuals to track signals:
Green triangles (below bars) mark long entries; red triangles (above bars) mark shorts.
Orange lines show swing highs; teal lines show swing lows.
Yellow circles indicate price crosses; purple crosses highlight volume confirmation.
Testing: Backtest G-Bot in a demo environment to validate performance and ensure compatibility with your trading strategy.
Setup Notes : G-Bot is a single, self-contained script for BTCUSDT.P on 60-minute charts, with all features accessible via user inputs. No additional scripts or passwords are required, ensuring compliance with TradingView’s single-publication rule.
Disclaimer: Trading involves significant risks, and past performance is not indicative of future results. Thoroughly test G-Bot in a demo environment before deploying it in live markets.
Full setup support will be provided
PowerHouse SwiftEdge AI v2.10 StrategyOverview
The PowerHouse SwiftEdge AI v2.10 Strategy is a sophisticated trading system designed to identify high-probability trade setups in forex, stocks, and cryptocurrencies. By combining multi-timeframe trend analysis, momentum signals, volume confirmation, and smart money concepts (Change of Character and Break of Structure ), this strategy offers traders a robust tool to capitalize on market trends while minimizing false signals. The strategy’s unique “AI” component analyzes trends across multiple timeframes to provide a clear, actionable dashboard, making it accessible for both novice and experienced traders. The strategy is fully customizable, allowing users to tailor its filters to their trading style.
What It Does
This strategy generates Buy and Sell signals based on a confluence of technical indicators and smart money concepts. It uses:
Multi-Timeframe Trend Analysis: Confirms the market’s direction by analyzing trends on the 1-hour (60M), 4-hour (240M), and daily (D) timeframes.
Momentum Filter: Ensures trades align with strong price movements to avoid choppy markets.
Volume Filter: Validates signals with above-average volume to confirm market participation.
Breakout Filter: Requires price to break key levels for added confirmation.
Smart Money Signals (CHoCH/BOS): Identifies reversals (CHoCH) and trend continuations (BOS) based on pivot points.
AI Trend Dashboard: Summarizes trend strength, confidence, and predictions across timeframes, helping traders make informed decisions without needing to analyze complex data manually.
The strategy also plots dynamic support and resistance trendlines, take-profit (TP) levels, and “Get Ready” signals to alert users of potential setups before they fully develop. Trades are executed with predefined take-profit and stop-loss levels for disciplined risk management.
How It Works
The strategy integrates multiple components to create a cohesive trading system:
Multi-Timeframe Trend Analysis:
The strategy evaluates trends on three timeframes (1H, 4H, Daily) using Exponential Moving Averages (EMA) and Volume-Weighted Average Price (VWAP). A trend is considered bullish if the price is above both the EMA and VWAP, bearish if below, or neutral otherwise.
Signals are only generated when the trend on the user-selected higher timeframe aligns with the trade direction (e.g., Buy signals require a bullish higher timeframe trend). This reduces noise and ensures trades follow the broader market context.
Momentum Filter:
Measures the percentage price change between consecutive bars and compares it to a volatility-adjusted threshold (based on the Average True Range ). This ensures trades are taken only during significant price movements, filtering out low-momentum conditions.
Volume Filter (Optional):
Checks if the current volume exceeds a long-term average and shows positive short-term volume change. This confirms strong market participation, reducing the risk of false breakouts.
Breakout Filter (Optional):
Requires the price to break above (for Buy) or below (for Sell) recent highs/lows, ensuring the signal aligns with a structural shift in the market.
Smart Money Concepts (CHoCH/BOS):
Change of Character (CHoCH): Detects potential reversals when the price crosses under a recent pivot high (for Sell) or over a recent pivot low (for Buy) with a bearish or bullish candle, respectively.
Break of Structure (BOS): Confirms trend continuations when the price breaks below a recent pivot low (for Sell) or above a recent pivot high (for Buy) with strong momentum.
These signals are plotted as horizontal lines with labels, making it easy to visualize key levels.
AI Trend Dashboard:
Combines trend direction, momentum, and volatility (ATR) across timeframes to calculate a trend score. Scores above 0.5 indicate an “Up” trend, below -0.5 indicate a “Down” trend, and otherwise “Neutral.”
Displays a table summarizing trend strength (as a percentage), AI confidence (based on trend alignment), and Cumulative Volume Delta (CVD) for market context.
A second table (optional) shows trend predictions for 1H, 4H, and Daily timeframes, helping traders anticipate future market direction.
Dynamic Trendlines:
Plots support and resistance lines based on recent swing lows and highs within user-defined periods (shortTrendPeriod, longTrendPeriod). These lines adapt to market conditions and are colored based on trend strength.
Why This Combination?
The PowerHouse SwiftEdge AI v2.10 Strategy is original because it seamlessly integrates traditional technical analysis (EMA, VWAP, ATR, volume) with smart money concepts (CHoCH, BOS) and a proprietary AI-driven trend analysis. Unlike standalone indicators, this strategy:
Reduces False Signals: By requiring confluence across trend, momentum, volume, and breakout filters, it minimizes trades in choppy or low-conviction markets.
Adapts to Market Context: The ATR-based momentum threshold adjusts dynamically to volatility, ensuring signals remain relevant in both trending and ranging markets.
Simplifies Decision-Making: The AI dashboard distills complex multi-timeframe data into a user-friendly table, eliminating the need for manual analysis.
Leverages Smart Money: CHoCH and BOS signals capture institutional price action patterns, giving traders an edge in identifying reversals and continuations.
The combination of these components creates a balanced system that aligns short-term trade entries with longer-term market trends, offering a unique blend of precision, adaptability, and clarity.
How to Use
Add to Chart:
Apply the strategy to your TradingView chart on a liquid symbol (e.g., EURUSD, BTCUSD, AAPL) with a timeframe of 60 minutes or lower (e.g., 15M, 60M).
Configure Inputs:
Pivot Length: Adjust the number of bars (default: 5) to detect pivot highs/lows for CHoCH/BOS signals. Higher values reduce noise but may delay signals.
Momentum Threshold: Set the base percentage (default: 0.01%) for momentum confirmation. Increase for stricter signals.
Take Profit/Stop Loss: Define TP and SL in points (default: 10 each) for risk management.
Higher/Lower Timeframe: Choose timeframes (60M, 240M, D) for trend filtering. Ensure the chart timeframe is lower than or equal to the higher timeframe.
Filters: Enable/disable momentum, volume, or breakout filters to suit your trading style.
Trend Periods: Set shortTrendPeriod (default: 30) and longTrendPeriod (default: 100) for trendline plotting. Keep below 2000 to avoid buffer errors.
AI Dashboard: Toggle Enable AI Market Analysis to show/hide the prediction table and adjust its position.
Interpret Signals:
Buy/Sell Labels: Green "Buy" or red "Sell" labels indicate trade entries with predefined TP/SL levels plotted.
Get Ready Signals: Yellow "Get Ready BUY" or orange "Get Ready SELL" labels warn of potential setups.
CHoCH/BOS Lines: Aqua (CHoCH Sell), lime (CHoCH Buy), fuchsia (BOS Sell), or teal (BOS Buy) lines mark key levels.
Trendlines: Green/lime (support) or fuchsia/purple (resistance) dashed lines show dynamic support/resistance.
AI Dashboard: Check the top-right table for trend strength, confidence, and CVD. The optional bottom table shows trend predictions (Up, Down, Neutral).
Backtest and Trade:
Use TradingView’s Strategy Tester to evaluate performance. Adjust TP/SL and filters based on results.
Trade manually based on signals or automate with TradingView alerts (set alerts for Buy/Sell labels).
Originality and Value
The PowerHouse SwiftEdge AI v2.10 Strategy stands out by combining multi-timeframe analysis, smart money concepts, and an AI-driven dashboard into a single, user-friendly system. Its adaptive momentum threshold, robust filtering, and clear visualizations empower traders to make confident decisions without needing advanced technical knowledge. Whether you’re a day trader or swing trader, this strategy provides a versatile, data-driven approach to navigating dynamic markets.
Important Notes:
Risk Management: Always use appropriate position sizing and risk management, as the strategy’s TP/SL levels are customizable.
Symbol Compatibility: Test on liquid symbols with sufficient historical data (at least 2000 bars) to avoid buffer errors.
Performance: Backtest thoroughly to optimize settings for your market and timeframe.
Gaussian Channel StrategyGaussian Channel Strategy — User Guide
1. Concept
This strategy builds trades around the Gaussian Channel. Based on Pine Script v4 indicator originally published by Donovan Wall. With rework to v6 Pine Script and adding entry and exit functions.
The channel consists of three dynamic lines:
Line Formula Purpose
Filter (middle) N-pole Gaussian filter applied to price Market "equilibrium"
High Band Filter + (Filtered TR × mult) Dynamic upper envelope
Low Band Filter − (Filtered TR × mult) Dynamic lower envelope
A position is opened when price crosses a user-selected line in a user-selected direction.
When the smoothed True Range (Filtered TR) becomes negative, the raw bands can flip (High drops below Low).
The strategy automatically reorders them so the upper band is always above the lower band.
Visual colors still flip, but signals stay correct.
2. Entry Logic
Choose a signal line for longs and/or shorts: Filter, Upper band, or Lower band.
Choose a cross direction (Cross Up or Cross Down).
A signal remains valid for Lookback bars after the actual cross, as long as price is still on the required side of the line.
When the opposite signal appears, the current position is closed or reversed depending on Reverse on opposite.
3. Parameters
Group Setting Meaning
Source & Filter Source Price series used (close, hlc3, etc.)
Poles (N) Number of Gaussian filter poles (1-9). More poles ⇒ smoother but laggier
Sampling Period Main period length of the channel
Filtered TR Multiplier Width of the bands in fractions of smoothed True Range
Reduced Lag Mode Adds a lag-compensation term (faster but noisier)
Fast Response Mode Blends 1-pole & N-pole outputs for quicker turns
Signals Long → signal line / Short → signal line Which line generates signals
Long when price / Short when price Direction of the cross
Lookback bars for late entry Bars after the cross that still allow an entry
Trading Enable LONG/SHORT-side trades Turn each side on/off
On opposite signal: reverse True: reverse -- False: flat
Misc Start trading date Ignores signals before this timestamp (back-test focus)
4. Quick Start
Add the strategy to a chart. Default: hlc3, N = 4, Period = 144.
Select your signal lines & directions.
Example: trend trading – Long: Filter + Cross Up, Short: Filter + Cross Down.
Disable either side if you want long-only or short-only.
Tune Lookback (e.g. 3) to catch gaps and strong impulses.
Run Strategy Tester, optimise period / multiplier / stops (add strategy.exit blocks if needed).
When satisfied, connect alerts via TradingView webhooks or use the builtin broker panel.
5. Notes
Commission & slippage are not preset – adjust them in Properties → Commission & Slippage.
Works on any market and timeframe, but you should retune Sampling Period and Multiplier for each symbol.
No stop-loss / take-profit is included by default – feel free to add with strategy.exit.
Start trading date lets you back-test only recent history (e.g. last two years).
6. Disclaimer
This script is for educational purposes only and does not constitute investment advice.
Use entirely at your own risk. Back-test thoroughly and apply sound risk management before trading real capital.
Alpha Trigger CoreAlpha Trigger Core — Trend Momentum Strategy with Dual Take Profit System
Alpha Trigger Core is a precision-engineered trend-following strategy developed for crypto and altcoin markets. Unlike simple indicator mashups, this system was built from the ground up with a specific logic framework that integrates trend, momentum, volatility, and structure validation into a single unified strategy.
It is not a random combination of indicators, but rather a coordinated system of filters that work together to increase signal quality and minimize false positives. This makes it especially effective on trending assets like BTC, ETH, AVAX, and SOL on the 1-hour chart.
🔍 How It Works
This strategy fuses multiple advanced filters into a cohesive signal engine:
🔹 Trend Identification
A hybrid model combining:
Kalman Filter — Smooths price noise with predictive tracking.
SuperTrend Overlay — Confirms directional bias using ATR.
ZLEMA Envelope — Defines dynamic upper/lower bounds based on price velocity.
🔹 Momentum Filter
Uses a ZLEMA-smoothed CCI to identify accelerating moves.
Long entries require a rising 3-bar CCI sequence.
Short entries require a falling 3-bar CCI sequence.
🔹 Volatility Strength Filter (Vortex Indicator)
Validates entries only when Vortex Diff exceeds a customizable threshold.
Prevents low-volatility "chop zone" trades.
🔹 Wick Trap Filter
Filters out false breakouts driven by liquidity wicks.
Validates that body structure supports the breakout.
📈 Entry & Exit Logic
Long Entry: All trend, momentum, volatility filters must align bullishly and wick traps must be absent.
Short Entry: All filters must align bearishly, with no wick rejection.
Early Exit: Uses ZLEMA slope crossover to exit before a full trend reversal is confirmed.
🎯 Take Profit System
TP1: Takes 50% profit at a user-defined % target.
TP2: Closes remaining 100% at second target.
Cooldown: Prevents immediate reentry and ensures clean position transitions.
📊 Real-Time Strategy Dashboard
Tracks and displays:
Position status (Long, Short, Flat)
Entry Price
TP1/TP2 Hit status
Win Rate (%)
Profit Factor
Bars Since Entry
Fully customizable position & font size
🤖 Bot-Ready Multi-Exchange Alerts
Compatible with WonderTrading, 3Commas, Binance, Bybit, and more.
Customizable comment= tags for entry, exit, TP1, and TP2.
Fully alert-compatible for webhook integrations.
📌 Suggested Use
Best used on trending crypto pairs with moderate-to-high volatility. Recommended on the 1H timeframe for altcoins and majors. Can be used for manual confirmation or automated trading.
🔒 Script Transparency
This is a closed-source script. However, the description above provides a transparent breakdown of the strategy’s core logic, filters, and execution model — ensuring compliance with TradingView’s publishing guidelines.
⚠️ Trading Disclaimer
This script is for educational purposes only and is not financial advice. Always conduct your own analysis before making investment decisions. Past performance does not guarantee future results. Use this strategy at your own risk.
Phantom Trigger Phantom Trigger – Precision Trend Execution with TP1/TP2 and Weak Trend Exits
Phantom Trigger is a professional-grade trend-following strategy designed for crypto and high-volatility assets. It combines advanced trend detection with precise risk-managed exits using a multi-level take-profit system.
🔍 What It Does
Identifies strong directional moves using a multi-stage smoothed trend model
Confirms entries using structure-based logic and volume pressure
Filters trades using bias zones, confirmation levels, and trend acceleration
Automatically manages trades with two-stage take-profits (TP1 and TP2)
Exits early on trend weakness before reversal
Includes a styled real-time dashboard and bar coloring for visual guidance
Sends bot-compatible alerts for multi-exchange automation
⚙️ Core Components
Trend Engine: A smoothed dynamic filter detects real-time trend direction and momentum shifts
Bias Structure: Mid-high/low range-based logic determines if price is favoring bullish or bearish structure
Confirmation Levels: Short- and long-term zone crossovers confirm directional alignment
Volume Filter: Detects volume expansion spikes to validate strong breakout potential
TP1/TP2 Logic: Dynamically sets two profit targets and executes partial and full exits automatically
Weak Trend Exit: Closes positions one bar before reversal using directional filters
🧠 How to Use
Works best on crypto (1H, 4H) and high-volume instruments
Use dashboard stats to monitor position status, PnL, and TP1/TP2 progression
Alerts are pre-labeled and compatible with bots like 3Commas, Wunderbit, etc.
Can be adapted for both scalping and swing trading
📊 Dashboard
The built-in real-time dashboard displays current trade status, entry price, TP1/TP2 progress, win rate, profit factor, and bars since entry. It updates live with every candle and provides a quick-glance overview to support your decision-making during active trades.
🧠 How to Use
Works best on crypto (1H, 4H) and high-volume instruments
Use dashboard stats to monitor position status, PnL, and TP1/TP2 progression
Alerts are pre-labeled and compatible with bots like 3Commas, Wunderbit, etc.
Can be adapted for both scalping and swing trading
⚠️ Disclaimer
This script is for educational purposes only and does not constitute financial advice. Always test strategies thoroughly using demo or backtesting environments before applying to live markets. Past performance is not indicative of future results.
Trend MatrixFinal TradingView-Compliant Description for Trend Matrix
Trend Matrix is a precision-engineered trend-following strategy built for high-confidence entries and tactical trade management.
This strategy combines multiple non-repainting filters, each with a distinct role, to form a unified "trend matrix" that confirms directional bias, volume commitment, and momentum strength — all before entry is considered.
🔍 Core Components & Why They’re Used
🧠 Gaussian Filter (Custom)
A smoothed Gaussian-weighted moving average is used to detect trend direction changes. Unlike standard EMAs, this filter minimizes lag while retaining smooth transitions — ideal for confirming trend shifts without false reversals.
📈 RMI Trend Memory
A Relative Momentum Index is used to validate trend direction persistence. RMI's ability to filter out short-term oscillations makes it ideal for confirming whether a trend is still active.
📊 Gradient Filter (ZLEMA-based)
Measures the slope of a ZLEMA-smoothed close. If slope flips, it signals a potential trend weakness. This provides real-time confirmation for entry or exit bias.
📉 Volume Spike Detection
Confirms that breakouts or trend continuations are supported by volume commitment. Uses a dynamic SMA-based volume filter with a user-defined multiplier.
🟦 White Line (Bias Midpoint)
This structural component calculates the midpoint of the highest high and lowest low over a range — providing directional context and helping eliminate trades in consolidation zones.
🎯 Entry Conditions
Long entries require:
Gaussian trend flip to the upside
RMI > 50 (bullish memory)
Volume spike confirmation
Positive gradient (ZLEMA slope)
Price above White Line (bias filter)
Short entries use the inverse logic.
All entries enforce a cooldown bar to prevent same-bar reversals or whipsaw trades.
🎯 Exit Conditions
Take Profit 1: 50% of position at +2%
Take Profit 2: Remaining 50% at +4%
Early Exit on Trend Weakness:
Position closes fully if the trend weakens (RMI flip or gradient reversal)
📊 Dashboard + Performance Tracking
The built-in dashboard shows:
Current Position
Entry Price
TP1/TP2 Hit Status
Bars Since Entry
Win Rate (%)
Profit Factor
Useful for manual tracking or live trading review.
🌐 Multi-Exchange Bot Compatibility
Trend Matrix is built with universal trade alerts using customizable comment= fields. This makes it compatible with any exchange-connected bot platform such as:
WunderTrading
3Commas
Alertatron
Cornix
Or any webhook-based trading system
Alerts are sent using the {{strategy.order.comment}} placeholder, allowing you to route entries and exits through your preferred exchange account on Binance, Bybit, OKX, Kraken, and others.
🛠️ Customization
All components are modular:
TP1/TP2 levels
Gaussian length & sigma
Volume spike filter sensitivity
Gradient & White Line length
RMI settings
You can tailor the strategy for different assets or timeframes — optimized for crypto 1H, but works with stocks, FX, or lower timeframes with adjusted parameters.
✅ Final Notes
Trend Matrix is not just a mashup — it's a synchronized system of filters with clear roles, designed to maximize trade confidence and minimize noise. Every layer of confirmation serves a purpose, making this a highly adaptive trend-following tool for any market environment.
⚠️ Disclaimer (as required by TradingView)
This script is for educational purposes only and does not constitute financial advice. Use at your own risk. Always test strategies thoroughly before applying them in live trading environments. Past performance is not indicative of future results.
Tactical FlowTactical Flow – Altcoin Swing Strategy with Trend Logic & Dynamic TP System
(Built for 1H timeframe altcoin trading)
🎯 Purpose
Tactical Flow is a swing trading strategy purpose-built for altcoins on the 1-hour timeframe. It targets clean trend continuation setups by combining non-repainting filters for direction, momentum, and volume with a real-time execution engine that strictly avoids same-bar reversals. It includes a dynamic take-profit system with real-time trade tracking and an integrated visual dashboard.
⚙️ Strategy Core Components
Each module was chosen for precision, trend clarity, and altcoin-specific price behavior.
🔹 1. White Line Bias
Defines market structure using the midpoint of recent high/low range.
→ Keeps you trading with the dominant structure.
🔹 2. Tether Trend Engine
Two mid-range bands (Fast & Slow Tether) act like a dynamic trend cloud.
→ Ensures trend direction is confirmed with structural layering.
🔹 3. ZLEMA Gradient Filter
A Zero Lag EMA of price that’s compared to its previous value for momentum slope.
→ Confirms the trend has actual energy behind it.
🔹 4. TEMA Micro-Flow
A smoothed directional signal to confirm price is accelerating, not just trending.
→ Filters out late or fading entries.
🔹 5. Volume Spike Filter
Confirms that breakouts are real by requiring volume > 1.5× median of previous candles.
→ Designed for altcoins to avoid fakeouts during random volatility.
🔹 6. RMI Trend Memory
Keeps track of the trend state over time, allowing for smoother transitions and fewer whipsaws.
→ Helps the strategy stay in trend longer and only reverse when confirmation is strong.
🔹 7. Reversal Cooldown Logic
Exits a trade, then waits 1 full bar before taking a reversal entry.
→ Avoids common backtest false positives where entries and exits occur on the same candle.
💸 Trade Management – TP1/TP2 Logic
TP1 = 50% closed when price hits target 1
TP2 = full exit
Exits early if trend weakens
Supports dynamic reentry after TP2 if trend resumes
→ Keeps risk controlled while allowing position scaling in volatile altcoin swings.
📊 Strategy Dashboard
Visual interface shows:
Current Position (Long / Short / Flat)
Entry Price
TP1 and TP2 hit status
Bars since entry
Real-time Win Rate
Profit Factor
🧪 Backtesting & Execution Compliance
✅ Fully non-repainting
✅ Compatible with TradingView's deep backtesting
✅ Uses strategy.exit with limit logic for accurate TP tracking
✅ No stop-loss — closes trades on trend weakening only
🔥 Best Use Case
Altcoin swing trades on 1H chart
Works well during trending periods with volume
Not designed for choppy or sideways conditions
Pairs well with watchlist scanners and heatmaps
Dskyz Adaptive Futures Elite (DAFE)Dskyz Adaptive Futures Edge (DAFE)
imgur.com
A Dynamic Futures Trading Strategy
DAFE adapts to market volatility and price action using technical indicators and advanced risk management. It’s built for high-stakes futures trading (e.g., MNQ, BTCUSDT.P), offering modular logic for scalpers and swing traders alike.
Key Features
Adaptive Moving Averages
Dynamic Logic: Fast and slow SMAs adjust lengths via ATR, reacting to momentum shifts and smoothing in calm markets.
Signals: Long entry on fast SMA crossing above slow SMA with price confirmation; short on cross below.
RSI Filtering (Optional)
Momentum Check: Confirms entries with RSI crossovers (e.g., above oversold for longs). Toggle on/off with custom levels.
Fine-Tuning: Adjustable lookback and thresholds (e.g., 60/40) for precision.
Candlestick Pattern Recognition
Eng|Enhanced Detection: Identifies strong bullish/bearish engulfing patterns, validated by volume and range strength (vs. 10-period SMA).
Conflict Avoidance: Skips trades if both patterns appear in the lookback window, reducing whipsaws.
Multi-Timeframe Trend Filter
15-Minute Alignment: Syncs intrabar trades with 15-minute SMA trends; optional for flexibility.
Dollar-Cost Averaging (DCA) New!
Scaling: Adds up to a set number of entries (e.g., 4) on pullbacks/rallies, spaced by ATR multiples.
Control: Caps exposure and resets on exit, enhancing trend-following potential.
Trade Execution & Risk Management
Entry Rules: Prioritizes moving averages or patterns (user choice), with volume, volatility, and time filters.
Stops & Trails:
Initial Stop: ATR-based (2–3.5x, volatility-adjusted).
Trailing Stop: Locks profits with configurable ATR offset and multiplier.
Discipline
Cooldown: Pauses post-exit (e.g., 0–5 minutes).
Min Hold: Ensures trades last a set number of bars (e.g., 2–10).
Visualization & Tools
Charts: Overlays MAs, stops, and signals; trend shaded in background.
Dashboard: Shows position, P&L, win rate, and more in real-time.
Debugging: Logs signal details for optimization.
Input Parameters
Parameter Purpose Suggested Use
Use RSI Filter - Toggle RSI confirmation *Disable 4 price-only
trading
RSI Length - RSI period (e.g., 14) *7–14 for sensitivity
RSI Overbought/Oversold - Adjust for market type *Set levels (e.g., 60/40)
Use Candlestick Patterns - Enables engulfing signals *Disable for MA focus
Pattern Lookback - Pattern window (e.g., 19) *10–20 bars for balance
Use 15m Trend Filter - Align with 15-min trend *Enable for trend trades
Fast/Slow MA Length - Base MA lengths (e.g., 9/19) *10–25 / 30–60 per
timeframe
Volatility Threshold - Filters volatile spikes *Max ATR/close (e.g., 1%)
Min Volume - Entry volume threshold *Avoid illiquid periods
(e.g., 10)
ATR Length - ATR period (e.g., 14) *Standard volatility
measure
Trailing Stop ATR Offset - Trail distance (e.g., 0.5) *0.5–1.5 for tightness
Trailing Stop ATR Multi - Trail multiplier (e.g., 1.0) *1–3 for trend room
Cooldown Minutes - Post-exit pause (e.g., 0–5) *Prevents overtrading
Min Bars to Hold - Min trade duration (e.g., 2) *5–10 for intraday
Trading Hours - Active window (e.g., 9–16) *Focus on key sessions
Use DCA - Toggle DCA *Enable for scaling
Max DCA Entries - Cap entries (e.g., 4) *Limit risk exposure
DCA ATR Multiplier Entry spacing (e.g., 1.0) *1–2 for wider gaps
Compliance
Realistic Testing: Fixed quantities, capital, and slippage for accurate backtests.
Transparency: All logic is user-visible and adjustable.
Risk Controls: Cooldowns, stops, and hold periods ensure stability.
Flexibility: Adapts to various futures and timeframes.
Summary
DAFE excels in volatile futures markets with adaptive logic, DCA scaling, and robust risk tools. Currently in prop account testing, it’s a powerful framework for precision trading.
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
Dow Theory Trend StrategyDow Theory Trend Strategy (Pine Script)
Overview
This Pine Script implements a trading strategy based on the core principles of Dow Theory. It visually identifies trends (uptrend, downtrend) by analyzing pivot highs and lows and executes trades when the trend direction changes. This script is an improved version that features refined trend determination logic and strategy implementation.
Core Concept: Dow Theory
The script uses a fundamental Dow Theory concept for trend identification:
Uptrend: Characterized by a series of Higher Highs (HH) and Higher Lows (HL).
Downtrend: Characterized by a series of Lower Highs (LH) and Lower Lows (LL).
How it Works
Pivot Point Detection:
It uses the built-in ta.pivothigh() and ta.pivotlow() functions to identify significant swing points (potential highs and lows) in the price action.
The pivotLookback input determines the number of bars to the left and right required to confirm a pivot. Note that this introduces a natural lag (equal to pivotLookback bars) before a pivot is confirmed.
Improved Trend Determination:
The script stores the last two confirmed pivot highs and the last two confirmed pivot lows.
An Uptrend (trendDirection = 1) is confirmed only when the latest pivot high is higher than the previous one (HH) AND the latest pivot low is higher than the previous one (HL).
A Downtrend (trendDirection = -1) is confirmed only when the latest pivot high is lower than the previous one (LH) AND the latest pivot low is lower than the previous one (LL).
Key Improvement: If neither a clear uptrend nor a clear downtrend is confirmed based on the latest pivots, the script maintains the previous trend state (trendDirection := trendDirection ). This differs from simpler implementations that might switch to a neutral/range state (e.g., trendDirection = 0) more frequently. This approach aims for smoother trend following, acknowledging that trends often persist through periods without immediate new HH/HL or LH/LL confirmations.
Trend Change Detection:
The script monitors changes in the trendDirection variable.
changedToUp becomes true when the trend shifts to an Uptrend (from Downtrend or initial state).
changedToDown becomes true when the trend shifts to a Downtrend (from Uptrend or initial state).
Visualizations
Background Color: The chart background is colored to reflect the currently identified trend:
Blue: Uptrend (trendDirection == 1)
Red: Downtrend (trendDirection == -1)
Gray: Initial state or undetermined (trendDirection == 0)
Pivot Points (Optional): Small triangles (shape.triangledown/shape.triangleup) can be displayed above pivot highs and below pivot lows if showPivotPoints is enabled.
Trend Change Signals (Optional): Labels ("▲ UP" / "▼ DOWN") can be displayed when a trend change is confirmed (changedToUp / changedToDown) if showTrendChange is enabled. These visually mark the potential entry points for the strategy.
Strategy Logic
Entry Conditions:
Enters a long position (strategy.long) using strategy.entry("L", ...) when changedToUp becomes true.
Enters a short position (strategy.short) using strategy.entry("S", ...) when changedToDown becomes true.
Position Management: The script uses strategy.entry(), which automatically handles position reversal. If the strategy is long and a short signal occurs, strategy.entry() will close the long position and open a new short one (and vice-versa).
Inputs
pivotLookback: The number of bars on each side to confirm a pivot high/low. Higher values mean pivots are confirmed later but may be more significant.
showPivotPoints: Toggle visibility of pivot point markers.
showTrendChange: Toggle visibility of the trend change labels ("▲ UP" / "▼ DOWN").
Key Improvements from Original
Smoother Trend Logic: The trend state persists unless a confirmed reversal pattern (opposite HH/HL or LH/LL) occurs, reducing potential whipsaws in choppy markets compared to logic that frequently resets to neutral.
Strategy Implementation: Converted from a pure indicator to a strategy capable of executing backtests and potentially live trades based on the Dow Theory trend changes.
Disclaimer
Dow Theory signals are inherently lagging due to the nature of pivot confirmation.
The effectiveness of the strategy depends heavily on the market conditions and the chosen pivotLookback setting.
This script serves as a basic template. Always perform thorough backtesting and implement proper risk management (e.g., stop-loss, take-profit, position sizing) before considering any live trading.
Hierarchical + K-Means Clustering Strategy===== USER GUIDE =====
Hierarchical + K-Means Clustering Strategy
OVERVIEW:
This strategy combines hierarchical clustering and K-means algorithms to analyze market volatility patterns
and generate trading signals. It uses a modified SuperTrend indicator with ATR-based volatility clustering
to identify potential trend changes and market conditions.
KEY FEATURES:
- Advanced volatility analysis using hierarchical clustering and K-means algorithms
- Modified SuperTrend indicator for trend identification
- Multiple filter options including moving average and ADX trend strength
- Volume-based exit mechanism to protect profits
- Customizable appearance settings
SETTINGS EXPLANATION:
1. SuperTrend Settings:
- ATR Length: Period for ATR calculation (default: 11)
- SuperTrend Factor: Multiplier for ATR to determine trend bands (default: 3)
2. Hierarchical Clustering Settings:
- Training Data Length: Number of bars used for clustering analysis (default: 200)
3. Appearance Settings:
- Transparency 1 & 2: Control the opacity of trend lines and fills
- Bullish/Bearish Color: Colors for uptrend and downtrend visualization
4. Time Settings:
- Start Year/Month: Define when the strategy should start executing trades
5. Filter Settings:
- Moving Average Filter: Uses SMA to filter trades (only enter when price is on correct side of MA)
- Trend Strength Filter: Uses ADX to ensure trades are taken in strong trend conditions
6. Volume Stop Loss Settings:
- Volume Ratio Threshold: Controls sensitivity of volume-based exits
- Monitoring Delay Bars: Number of bars to wait before monitoring volume for exit signals
HOW TO USE:
1. Apply the indicator to your chart
2. Adjust settings according to your trading preferences and timeframe
3. Long signals appear when price crosses above the SuperTrend line (▲k marker)
4. Short signals appear when price crosses below the SuperTrend line (▼k marker)
5. The strategy automatically manages exits based on volume balance conditions
INTERPRETATION:
- Green line/area: Bullish trend - consider long positions
- Red line/area: Bearish trend - consider short positions
- Yellow line: Moving average for additional trend confirmation
- Volume balance exits occur when buying/selling pressure equalizes
RECOMMENDED TIMEFRAMES:
This strategy works best on 1H, 4H, and daily charts for most markets.
For highly volatile assets, shorter timeframes may also be effective.
RISK MANAGEMENT:
Always use proper position sizing and consider setting additional stop losses
beyond the strategy's built-in exit mechanisms.
===== END OF USER GUIDE =====
Divergence IQ [TradingIQ]Hello Traders!
Introducing "Divergence IQ"
Divergence IQ lets traders identify divergences between price action and almost ANY TradingView technical indicator. This tool is designed to help you spot potential trend reversals and continuation patterns with a range of configurable features.
Features
Divergence Detection
Detects both regular and hidden divergences for bullish and bearish setups by comparing price movements with changes in the indicator.
Offers two detection methods: one based on classic pivot point analysis and another that provides immediate divergence signals.
Option to use closing prices for divergence detection, allowing you to choose the data that best fits your strategy.
Normalization Options:
Includes multiple normalization techniques such as robust scaling, rolling Z-score, rolling min-max, or no normalization at all.
Adjustable normalization window lets you customize the indicator to suit various market conditions.
Option to display the normalized indicator on the chart for clearer visual comparison.
Allows traders to take indicators that aren't oscillators, and convert them into an oscillator - allowing for better divergence detection.
Simulated Trade Management:
Integrates simulated trade entries and exits based on divergence signals to demonstrate potential trading outcomes.
Customizable exit strategies with options for ATR-based or percentage-based stop loss and profit target settings.
Automatically calculates key trade metrics such as profit percentage, win rate, profit factor, and total trade count.
Visual Enhancements and On-Chart Displays:
Color-coded signals differentiate between bullish, bearish, hidden bullish, and hidden bearish divergence setups.
On-chart labels, lines, and gradient flow visualizations clearly mark divergence signals, entry points, and exit levels.
Configurable settings let you choose whether to display divergence signals on the price chart or in a separate pane.
Performance Metrics Table:
A performance table dynamically displays important statistics like profit, win rate, profit factor, and number of trades.
This feature offers an at-a-glance assessment of how the divergence-based strategy is performing.
The image above shows Divergence IQ successfully identifying and trading a bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a bearish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bullish divergence between an indicator and price action!
The image above shows Divergence IQ successfully identifying and trading a hidden bearish divergence between an indicator and price action!
The performance table is designed to provide a clear summary of simulated trade results based on divergence setups. You can easily review key metrics to assess the strategy’s effectiveness over different time periods.
Customization and Adaptability
Divergence IQ offers a wide range of configurable settings to tailor the indicator to your personal trading approach. You can adjust the lookback and lookahead periods for pivot detection, select your preferred method for normalization, and modify trade exit parameters to manage risk according to your strategy. The tool’s clear visual elements and comprehensive performance metrics make it a useful addition to your technical analysis toolbox.
The image above shows Divergence IQ identifying divergences between price action and OBV with no normalization technique applied.
While traders can look for divergences between OBV and price, OBV doesn't naturally behave like an oscillator, with no definable upper and lower threshold, OBV can infinitely increase or decrease.
With Divergence IQ's ability to normalize any indicator, traders can normalize non-oscillator technical indicators such as OBV, CVD, MACD, or even a moving average.
In the image above, the "Robust Scaling" normalization technique is selected. Consequently, the output of OBV has changed and is now behaving similar to an oscillator-like technical indicator. This makes spotting divergences between the indicator and price easier and more appropriate.
The three normalization techniques included will change the indicator's final output to be more compatible with divergence detection.
This feature can be used with almost any technical indicator.
Stop Type
Traders can select between ATR based profit targets and stop losses, or percentage based profit targets and stop losses.
The image above shows options for the feature.
Divergence Detection Method
A natural pitfall of divergence trading is that it generally takes several bars to "confirm" a divergence. This makes trading the divergence complicated, because the entry at time of the divergence might look great; however, the divergence wasn't actually signaled until several bars later.
To circumvent this issue, Divergence IQ offers two divergence detection mechanisms.
Pivot Detection
Pivot detection mode is the same as almost every divergence indicator on TradingView. The Pivots High Low indicator is used to detect market/indicator highs and lows and, consequently, divergences.
This method generally finds the "best looking" divergences, but will always take additional time to confirm the divergence.
Immediate Detection
Immediate detection mode attempts to reduce lag between the divergence and its confirmation to as little as possible while avoiding repainting.
Immediate detection mode still uses the Pivots Detection model to find the first high/low of a divergence. However, the most recent high/low does not utilize the Pivot Detection model, and instead immediately looks for a divergence between price and an indicator.
Immediate Detection Mode will always signal a divergence one bar after it's occurred, and traders can set alerts in this mode to be alerted as soon as the divergence occurs.
TradingView Backtester Integration
Divergence IQ is fully compatible with the TradingView backtester!
Divergence IQ isn’t designed to be a “profitable strategy” for users to trade. Instead, the intention of including the backtester is to let users backtest divergence-based trading strategies between the asset on their chart and almost any technical indicator, and to see if divergences have any predictive utility in that market.
So while the backtester is available in Divergence IQ, it’s for users to personally figure out if they should consider a divergence an actionable insight, and not a solicitation that Divergence IQ is a profitable trading strategy. Divergence IQ should be thought of as a Divergence backtesting toolkit, not a full-feature trading strategy.
Strategy Properties Used For Backtest
Initial Capital: $1000 - a realistic amount of starting capital that will resonate with many traders
Amount Per Trade: 5% of equity - a realistic amount of capital to invest relative to portfolio size
Commission: 0.02% - a conservative amount of commission to pay for trade that is standard in crypto trading, and very high for other markets.
Slippage: 1 tick - appropriate for liquid markets, but must be increased in markets with low activity.
Once more, the backtester is meant for traders to personally figure out if divergences are actionable trading signals on the market they wish to trade with the indicator they wish to use.
And that's all!
If you have any cool features you think can benefit Divergence IQ - please feel free to share them!
Thank you so much TradingView community!
[3Commas] Turtle StrategyTurtle Strategy
🔷 What it does: This indicator implements a modernized version of the Turtle Trading Strategy, designed for trend-following and automated trading with webhook integration. It identifies breakout opportunities using Donchian channels, providing entry and exit signals.
Channel 1: Detects short-term breakouts using the highest highs and lowest lows over a set period (default 20).
Channel 2: Acts as a confirmation filter by applying an offset to the same period, reducing false signals.
Exit Channel: Functions as a dynamic stop-loss (wait for candle close), adjusting based on market structure (default 10 periods).
Additionally, traders can enable a fixed Take Profit level, ensuring a systematic approach to profit-taking.
🔷 Who is it for:
Trend Traders: Those looking to capture long-term market moves.
Bot Users: Traders seeking to automate entries and exits with bot integration.
Rule-Based Traders: Operators who prefer a structured, systematic trading approach.
🔷 How does it work: The strategy generates buy and sell signals using a dual-channel confirmation system.
Long Entry: A buy signal is generated when the close price crosses above the previous high of Channel 1 and is confirmed by Channel 2.
Short Entry: A sell signal occurs when the close price falls below the previous low of Channel 1, with confirmation from Channel 2.
Exit Management: The Exit Channel acts as a trailing stop, dynamically adjusting to price movements. To exit the trade, wait for a full bar close.
Optional Take Profit (%): Closes trades at a predefined %.
🔷 Why it’s unique:
Modern Adaptation: Updates the classic Turtle Trading Strategy, with the possibility of using a second channel with an offset to filter the signals.
Dynamic Risk Management: Utilizes a trailing Exit Channel to help protect gains as trades move favorably.
Bot Integration: Automates trade execution through direct JSON signal communication with your DCA Bots.
🔷 Considerations Before Using the Indicator:
Market & Timeframe: Best suited for trending markets; higher timeframes (e.g., H4, D1) are recommended to minimize noise.
Sideways Markets: In choppy conditions, breakouts may lead to false signals—consider using additional filters.
Backtesting & Demo Testing: It is crucial to thoroughly backtest the strategy and run it on a demo account before risking real capital.
Parameter Adjustments: Ensure that commissions, slippage, and position sizes are set accurately to reflect real trading conditions.
🔷 STRATEGY PROPERTIES
Symbol: BINANCE:ETHUSDT (Spot).
Timeframe: 4h.
Test Period: All historical data available.
Initial Capital: 10000 USDT.
Order Size per Trade: 1% of Capital, you can use a higher value e.g. 5%, be cautious that the Max Drawdown does not exceed 10%, as it would indicate a very risky trading approach.
Commission: Binance commission 0.1%, adjust according to the exchange being used, lower numbers will generate unrealistic results. By using low values e.g. 5%, it allows us to adapt over time and check the functioning of the strategy.
Slippage: 5 ticks, for pairs with low liquidity or very large orders, this number should be increased as the order may not be filled at the desired level.
Margin for Long and Short Positions: 100%.
Indicator Settings: Default Configuration.
Period Channel 1: 20.
Period Channel 2: 20.
Period Channel 2 Offset: 20.
Period Exit: 10.
Take Profit %: Disable.
Strategy: Long & Short.
🔷 STRATEGY RESULTS
⚠️Remember, past results do not guarantee future performance.
Net Profit: +516.87 USDT (+5.17%).
Max Drawdown: -100.28 USDT (-0.95%).
Total Closed Trades: 281.
Percent Profitable: 40.21%.
Profit Factor: 1.704.
Average Trade: +1.84 USDT (+1.80%).
Average # Bars in Trades: 29.
🔷 How to Use It:
🔸 Adjust Settings:
Select your asset and timeframe suited for trend trading.
Adjust the periods for Channel 1, Channel 2, and the Exit Channel to align with the asset’s historical behavior. You can visualize these channels by going to the Style tab and enabling them.
For example, if you set Channel 2 to 40 with an offset of 40, signals will take longer to appear but will aim for a more defined trend.
Experiment with different values, a possible exit configuration is using 20 as well. Compare the results and adjust accordingly.
Enable the Take Profit (%) option if needed.
🔸Results Review:
It is important to check the Max Drawdown. This value should ideally not exceed 10% of your capital. Consider adjusting the trade size to ensure this threshold is not surpassed.
Remember to include the correct values for commission and slippage according to the symbol and exchange where you are conducting the tests. Otherwise, the results will not be realistic.
If you are satisfied with the results, you may consider automating your trades. However, it is strongly recommended to use a small amount of capital or a demo account to test proper execution before committing real funds.
🔸Create alerts to trigger the DCA Bot:
Verify Messages: Ensure the message matches the one specified by the DCA Bot.
Multi-Pair Configuration: For multi-pair setups, enable the option to add the symbol in the correct format.
Signal Settings: Enable the option to receive long or short signals (Entry | TP | SL), copy and paste the messages for the DCA Bots configured.
Alert Setup:
When creating an alert, set the condition to the indicator and choose "alert() function call only".
Enter any desired Alert Name.
Open the Notifications tab, enable Webhook URL, and paste the Webhook URL.
For more details, refer to the section: "How to use TradingView Custom Signals".
Finalize Alerts: Click Create, you're done! Alerts will now be sent automatically in the correct format.
🔷 INDICATOR SETTINGS
Period Channel 1: Period of highs and lows to trigger signals
Period Channel 2: Period of highs and lows to filter signals
Offset: Move Channel 2 to the right x bars to try to filter out the favorable signals.
Period Exit: It is the period of the Donchian channel that is used as trailing for the exits.
Strategy: Order Type direction in which trades are executed.
Take Profit %: When activated, the entered value will be used as the Take Profit in percentage from the entry price level.
Use Custom Test Period: When enabled signals only works in the selected time window. If disabled it will use all historical data available on the chart.
Test Start and End: Once the Custom Test Period is enabled, here you select the start and end date that you want to analyze.
Check Messages: Check Messages: Enable this option to review the messages that will be sent to the bot.
Entry | TP | SL: Enable this options to send Buy Entry, Take Profit (TP), and Stop Loss (SL) signals.
Deal Entry and Deal Exit: Copy and paste the message for the deal start signal and close order at Market Price of the DCA Bot. This is the message that will be sent with the alert to the Bot, you must verify that it is the same as the bot so that it can process properly.
DCA Bot Multi-Pair: You must activate it if you want to use the signals in a DCA Bot Multi-pair in the text box you must enter (using the correct format) the symbol in which you are creating the alert, you can check the format of each symbol when you create the bot.
👨🏻💻💭 We hope this tool helps enhance your trading. Your feedback is invaluable, so feel free to share any suggestions for improvements or new features you'd like to see implemented.
__
The information and publications within the 3Commas TradingView account are not meant to be and do not constitute financial, investment, trading, or other types of advice or recommendations supplied or endorsed by 3Commas and any of the parties acting on behalf of 3Commas, including its employees, contractors, ambassadors, etc.
IronBot v4IronBot v4 – Trading Strategy Overview
1. Quick Context
IronBot v4 is a trading strategy designed for users who want a simple yet effective approach to reading the markets. It uses a combination of Fibonacci retracement levels, custom logic triggers, and innovative modules (EMA validation, Iron Impulse Shield and Iron Auto Volume Detector) to identify potential entry and exit points, strengthening the strategy’s detection of sudden market volatility or shifts in trading volume.
2. Theoretical Details
Fibonacci Analysis
The script identifies recent market highs and lows, then calculates key Fibonacci levels (high- and low-based). These levels can help confirm potential reversals or trends.
EMA Option
When enabled, the exponential moving average (EMA) offers additional validation for trade entries. If the current price remains above a certain EMA threshold, long positions may be favored; conversely, if it stays below the EMA, short positions may be initiated.
IIS (Iron Impulse Shield)
IIS helps to filter out risky trades by measuring recent price shocks or surges. If an extreme movement is detected, the strategy may temporarily disable longs or shorts to avoid false signals.
IAVD (Iron Auto Volume Detector)
This functionality automatically detects the average market volume over a defined period (regardless of the market, since it relies on real data). When entering a position, it ensures that overall volume is high enough to confirm a genuinely active, robust market. By providing an additional filter, it can strengthen the decision-making process whenever the market’s participation level is in question.
Panel
IronBot v4 displays a real-time backtest panel that summarizes the selected configuration (including the current pair, analysis window, enabled filters), as well as showing net profit, applicable exchange fees, country taxes, and the final net balance. This gives traders an immediate overview of strategy performance and risk metrics.
What Pinescript Adds Visually
The script plots:
Fibonacci levels (highlighting potential reversal zones)
Trend lines indicating bullish (green) or bearish (red) lean
Optional EMA line
Optional Fibonacci forecast lines for anticipating future moves
Automatic labeling of entry, take-profit, and stop-loss levels, indicating the profit percentage of each trade.
3. Explanation of Inputs
The strategy exposes multiple inputs that can be toggled or configured by the user:
Analysis Window : Dictates how many bars to consider for high/low calculations and the fib retracement thresholds.
TRADES
Display TP/SL: For displaying Take profits and Stop loss.
Display Forecast: When enabled, this feature calculates and projects possible future Fibonacci retracements using historical data, helping traders anticipate potential upcoming trade setups.
Leverage: Only used for the Panel and not for trades. Lets you amplify your position size; higher leverage increases potential gains but also heightens risk. TradingView strategy is using properties for doing this.
Exchange Maker Fees & Exchange Taker Fees: Only used for the Panel and not for trades. Define the percentage cost applied by your exchange for maker and taker trades, respectively. These fees are accounted for in final profit calculations of the Panel.
Country Tax: Only used for the Panel and not for trades. Specifies a tax percentage to be deducted from net profits.
STOP LOSS and TAKE PROFITS
Stop-Loss & Take-Profit Parameters: Controls the percentage distances at which the strategy will exit positions. Additionally, you can configure up to four distinct take-profit levels (TP1 through TP4). Each level should be higher target than the previous one, and you can assign a specific percentage of the total position to close at each TP, ensuring the sum equals 100%. A break-even feature is also available when multiple TPs are used.
EMA
EMA (Exponential Moving Average) Option: When enabled, the strategy opens long trades only if the current price is above the specified EMA length, and opens short trades only if it is below that threshold.
PANELS
Show Panel: For displaying the backtest integrated panel.
IRON IMPULSE SHIELD (IIS)
IIS (Iron Impulse Shield) Option: When enabled, IIS continuously monitors recent price volatility depending on the analysis window set. If the market experiences an extreme surge or drop beyond a specified threshold, IIS temporarily blocks new long or short positions.
IRON AUTO VOLUME DETECTOR (IAVD)
IAVD (Iron Auto Volume Detector) Option: When enabled, it continuously measures the average market volume over a special period, irrespective of the specific trading pair. This ensures that IronBot v4 focuses on markets with robust participation, reducing the likelihood of entering trades during low-liquidity conditions.
By changing these values, IronBot v4 reacts differently to market structure and risk management requirements. Stop-loss and take-profit levels will adjust accordingly, while advanced filters (like EMA or IIS) influence when trades can open.
4. TradingView Strategy Properties
IronBot v4 uses the built-in TradingView “strategy” functionality. In particular:
Order Placement: The code calls strategy.entry() and strategy.close() for direct orders, ensuring signals are sent immediately (no limit orders are used). This helps connect with exchange signal bots for automated execution.
Initial Capital: The code uses initial capital defined in properties for calculating Net balance in the integrated panel.
On bar close: This strategy fill orders on bar close.
Pyramiding: This strategy can take only 1 successive trade in the same direction
Be careful to configure your leverage input depending on your strategy properties.
5. Visualization
5. Purpose & Disclaimer
This script is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always confirm your own risk tolerance and consult a financial professional before placing live trades. Trading leveraged products can involve substantial risk of loss.
TSI Long/Short for BTC 2HThe TSI Long/Short for BTC 2H strategy is an advanced trend-following system designed specifically for trading Bitcoin (BTC) on a 2-hour timeframe. It leverages the True Strength Index (TSI) to identify momentum shifts and executes both long and short trades in response to dynamic market conditions.
Unlike traditional moving average-based strategies, this script uses a double-smoothed momentum calculation, enhancing signal accuracy and reducing noise. It incorporates automated position sizing, customizable leverage, and real-time performance tracking, ensuring a structured and adaptable trading approach.
🔹 What Makes This Strategy Unique?
Unlike simple crossover strategies or generic trend-following approaches, this system utilizes a customized True Strength Index (TSI) methodology that dynamically adjusts to market conditions.
🔸 True Strength Index (TSI) Filtering – The script refines the TSI by applying double exponential smoothing, filtering out weak signals and capturing high-confidence momentum shifts.
🔸 Adaptive Entry & Exit Logic – Instead of fixed thresholds, it compares the TSI value against a dynamically determined high/low range from the past 100 bars to confirm trade signals.
🔸 Leverage & Risk Optimization – Position sizing is dynamically adjusted based on account equity and leverage settings, ensuring controlled risk exposure.
🔸 Performance Monitoring System – A built-in performance tracking table allows traders to evaluate monthly and yearly results directly on the chart.
📊 Core Strategy Components
1️⃣ Momentum-Based Trade Execution
The strategy generates long and short trade signals based on the following conditions:
✅ Long Entry Condition – A buy signal is triggered when the TSI crosses above its 100-bar highest value (previously set), confirming bullish momentum.
✅ Short Entry Condition – A sell signal is generated when the TSI crosses below its 100-bar lowest value (previously set), indicating bearish pressure.
Each trade execution is fully automated, reducing emotional decision-making and improving trading discipline.
2️⃣ Position Sizing & Leverage Control
Risk management is a key focus of this strategy:
🔹 Dynamic Position Sizing – The script calculates position size based on:
Account Equity – Ensuring trade sizes adjust dynamically with capital fluctuations.
Leverage Multiplier – Allows traders to customize risk exposure via an adjustable leverage setting.
🔹 No Fixed Stop-Loss – The strategy relies on reversals to exit trades, meaning each position is closed when the opposite signal appears.
This design ensures maximum capital efficiency while adapting to market conditions in real time.
3️⃣ Performance Visualization & Tracking
Understanding historical performance is crucial for refining strategies. The script includes:
📌 Real-Time Trade Markers – Buy and sell signals are visually displayed on the chart for easy reference.
📌 Performance Metrics Table – Tracks monthly and yearly returns in percentage form, helping traders assess profitability over time.
📌 Trade History Visualization – Completed trades are displayed with color-coded boxes (green for long trades, red for short trades), visually representing profit/loss dynamics.
📢 Why Use This Strategy?
✔ Advanced Momentum Detection – Uses a double-smoothed TSI for more accurate trend signals.
✔ Fully Automated Trading – Removes emotional bias and enforces discipline.
✔ Customizable Risk Management – Adjust leverage and position sizing to suit your risk profile.
✔ Comprehensive Performance Tracking – Integrated reporting system provides clear insights into past trades.
This strategy is ideal for Bitcoin traders looking for a structured, high-probability system that adapts to both bullish and bearish trends on the 2-hour timeframe.
📌 How to Use: Simply add the script to your 2H BTC chart, configure your leverage settings, and let the system handle trade execution and tracking! 🚀
Stochastic-Dynamic Volatility Band ModelThe Stochastic-Dynamic Volatility Band Model is a quantitative trading approach that leverages statistical principles to model market volatility and generate buy and sell signals. The strategy is grounded in the concepts of volatility estimation and dynamic market regimes, where the core idea is to capture price fluctuations through stochastic models and trade around volatility bands.
Volatility Estimation and Band Construction
The volatility bands are constructed using a combination of historical price data and statistical measures, primarily the standard deviation (σ) of price returns, which quantifies the degree of variation in price movements over a specific period. This methodology is based on the classical works of Black-Scholes (1973), which laid the foundation for using volatility as a core component in financial models. Volatility is a crucial determinant of asset pricing and risk, and it plays a pivotal role in this strategy's design.
Entry and Exit Conditions
The entry conditions are based on the price’s relationship with the volatility bands. A long entry is triggered when the price crosses above the lower volatility band, indicating that the market may have been oversold or is experiencing a reversal to the upside. Conversely, a short entry is triggered when the price crosses below the upper volatility band, suggesting overbought conditions or a potential market downturn.
These entry signals are consistent with the mean reversion theory, which asserts that asset prices tend to revert to their long-term average after deviating from it. According to Poterba and Summers (1988), mean reversion occurs due to overreaction to news or temporary disturbances, leading to price corrections.
The exit condition is based on the number of bars that have elapsed since the entry signal. Specifically, positions are closed after a predefined number of bars, typically set to seven bars, reflecting a short-term trading horizon. This exit mechanism is in line with short-term momentum trading strategies discussed in literature, where traders capitalize on price movements within specific timeframes (Jegadeesh & Titman, 1993).
Market Adaptability
One of the key features of this strategy is its dynamic nature, as it adapts to the changing volatility environment. The volatility bands automatically adjust to market conditions, expanding in periods of high volatility and contracting when volatility decreases. This dynamic adjustment helps the strategy remain robust across different market regimes, as it is capable of identifying both trend-following and mean-reverting opportunities.
This dynamic adaptability is supported by the adaptive market hypothesis (Lo, 2004), which posits that market participants evolve their strategies in response to changing market conditions, akin to the adaptive nature of biological systems.
References:
Black, F., & Scholes, M. (1973). The Pricing of Options and Corporate Liabilities. Journal of Political Economy, 81(3), 637-654.
Bollinger, J. (1980). Bollinger on Bollinger Bands. Wiley.
Jegadeesh, N., & Titman, S. (1993). Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency. Journal of Finance, 48(1), 65-91.
Lo, A. W. (2004). The Adaptive Markets Hypothesis: Market Efficiency from an Evolutionary Perspective. Journal of Portfolio Management, 30(5), 15-29.
Poterba, J. M., & Summers, L. H. (1988). Mean Reversion in Stock Prices: Evidence and Implications. Journal of Financial Economics, 22(1), 27-59.
Volatility Momentum Breakout StrategyDescription:
Overview:
The Volatility Momentum Breakout Strategy is designed to capture significant price moves by combining a volatility breakout approach with trend and momentum filters. This strategy dynamically calculates breakout levels based on market volatility and uses these levels along with trend and momentum conditions to identify trade opportunities.
How It Works:
1. Volatility Breakout:
• Methodology:
The strategy computes the highest high and lowest low over a defined lookback period (excluding the current bar to avoid look-ahead bias). A multiple of the Average True Range (ATR) is then added to (or subtracted from) these levels to form dynamic breakout thresholds.
• Purpose:
This method helps capture significant price movements (breakouts) while ensuring that only past data is used, thereby maintaining realistic signal generation.
2. Trend Filtering:
• Methodology:
A short-term Exponential Moving Average (EMA) is applied to determine the prevailing trend.
• Purpose:
Long trades are considered only when the current price is above the EMA, indicating an uptrend, while short trades are taken only when the price is below the EMA, indicating a downtrend.
3. Momentum Confirmation:
• Methodology:
The Relative Strength Index (RSI) is used to gauge market momentum.
• Purpose:
For long entries, the RSI must be above a mid-level (e.g., above 50) to confirm upward momentum, and for short entries, it must be below a similar threshold. This helps filter out signals during overextended conditions.
Entry Conditions:
• Long Entry:
A long position is triggered when the current closing price exceeds the calculated long breakout level, the price is above the short-term EMA, and the RSI confirms momentum (e.g., above 50).
• Short Entry:
A short position is triggered when the closing price falls below the calculated short breakout level, the price is below the EMA, and the RSI confirms momentum (e.g., below 50).
Risk Management:
• Position Sizing:
Trades are sized to risk a fixed percentage of account equity (set here to 5% per trade in the code, with each trade’s stop loss defined so that risk is limited to approximately 2% of the entry price).
• Stop Loss & Take Profit:
A stop loss is placed a fixed ATR multiple away from the entry price, and a take profit target is set to achieve a 1:2 risk-reward ratio.
• Realistic Backtesting:
The strategy is backtested using an initial capital of $10,000, with a commission of 0.1% per trade and slippage of 1 tick per bar—parameters chosen to reflect conditions faced by the average trader.
Important Disclaimers:
• No Look-Ahead Bias:
All breakout levels are calculated using only past data (excluding the current bar) to ensure that the strategy does not “peek” into future data.
• Educational Purpose:
This strategy is experimental and provided solely for educational purposes. Past performance is not indicative of future results.
• User Responsibility:
Traders should thoroughly backtest and paper trade the strategy under various market conditions and adjust parameters to fit their own risk tolerance and trading style before live deployment.
Conclusion:
By integrating volatility-based breakout signals with trend and momentum filters, the Volatility Momentum Breakout Strategy offers a unique method to capture significant price moves in a disciplined manner. This publication provides a transparent explanation of the strategy’s components and realistic backtesting parameters, making it a useful tool for educational purposes and further customization by the TradingView community.
Consecutive Bearish Candle Strategy█ STRATEGY DESCRIPTION
The "Consecutive Bearish Candle Strategy" is a momentum-based strategy designed to identify potential reversals after a sustained bearish move. It enters a long position when a specific number of consecutive bearish candles occur and exits when the price shows strength by exceeding the previous bar's high. This strategy is optimized for use on various timeframes and instruments.
█ SIGNAL GENERATION
1. LONG ENTRY
A Buy Signal is triggered when:
The close price has been lower than the previous close for at least `Lookback` consecutive bars. This indicates a sustained bearish move, suggesting a potential reversal.
The signal occurs within the specified time window (between `Start Time` and `End Time`).
2. EXIT CONDITION
A Sell Signal is generated when the current closing price exceeds the high of the previous bar (`close > high `). This indicates that the price has shown strength, potentially confirming the reversal and prompting the strategy to exit the position.
█ ADDITIONAL SETTINGS
Lookback: The number of consecutive bearish bars required to trigger a Buy Signal. Default is 3.
Start Time and End Time: The time window during which the strategy is allowed to execute trades.
█ PERFORMANCE OVERVIEW
This strategy is designed for markets with frequent momentum shifts.
It performs best in volatile conditions where price movements are significant.
Backtesting results should be analysed to optimize the `Lookback` parameter for specific instruments.
