Gyspy Bot Trade Engine - V1.2B - Strategy 12-7-25 - SignalLynxGypsy Bot Trade Engine (MK6 V1.2B) - Ultimate Strategy & Backtest
Brought to you by Signal Lynx | Automation for the Night-Shift Nation 🌙
1. Executive Summary & Architecture
Gypsy Bot (MK6 V1.2B) is not merely a strategy; it is a massive, modular Trade Engine built specifically for the TradingView Pine Script environment. While most strategies rely on a single dominant indicator (like an RSI cross or a MACD flip) to generate signals, Gypsy Bot functions as a sophisticated Consensus Algorithm.
The engine calculates data from up to 12 distinct Technical Analysis Modules simultaneously on every bar closing. It aggregates these signals into a "Vote Count" and only executes a trade entry when a user-defined threshold of concurring signals is met. This "Voting System" acts as a noise filter, requiring multiple independent mathematical models—ranging from volume flow and momentum to cyclical harmonics and trend strength—to agree on market direction before capital is committed.
Beyond entries, Gypsy Bot features a proprietary Risk Management suite called the Dump Protection Team (DPT). This logic layer operates independently of the entry modules, specifically scanning for "Moon" (Parabolic) or "Nuke" (Crash) volatility events to force-exit positions, overriding standard stops to preserve capital during Black Swan events.
2. ⚠️ The Philosophy of "Curve Fitting" (Must Read)
One must be careful when applying Gypsy Bot to new pairs or charts.
To be fully transparent: Gypsy Bot is, by definition, a very advanced curve-fitting engine. Because it grants the user granular control over 12 modules, dozens of thresholds, and specific voting requirements, it is extremely easy to "over-fit" the data. You can easily toggle switches until the backtest shows a 100% win rate, only to have the strategy fail immediately in live markets because it was tuned to historical noise rather than market structure.
To use this engine successfully, you must adopt a specific optimization mindset:
Ignore Raw Net Profit: Do not tune for the highest dollar amount. A strategy that makes $1M in the backtest but has a 40% drawdown is useless.
Prioritize Stability: Look for a high Profit Factor (1.5+), a high Percent Profitable, and a smooth equity curve.
Regular Maintenance is Mandatory: Markets shift regimes (e.g., from Bull Trend to Crab Range). Parameters that worked perfectly in 2021 may fail in 2024. Gypsy Bot settings should be reviewed and adjusted at regular intervals (e.g., quarterly) to ensure the voting logic remains aligned with current market volatility.
Timeframe Recommendations:
Gypsy Bot is optimized for High Time Frame (HTF) trend following. It generally produces the most reliable results on charts ranging from 1-Hour to 12-Hours, with the 4-Hour timeframe historically serving as the "sweet spot" for most major cryptocurrency assets.
3. The Voting Mechanism: How Entries Are Generated
The heart of the Gypsy Bot engine is the ActivateOrders input (found in the "Order Signal Modifier" settings).
The engine constantly monitors the output of all enabled Modules.
Long Votes: GoLongCount
Short Votes: GoShortCount
If you have 10 Modules enabled, and you set ActivateOrders to 7:
The engine will ONLY trigger a Buy Entry if 7 or more modules return a valid "Buy" signal on the same closed candle.
If only 6 modules agree, the trade is rejected.
This allows you to mix "Leading" indicators (Oscillators) with "Lagging" indicators (Moving Averages) to create a high-probability entry signal that requires momentum, volume, and trend to all be in alignment.
4. Technical Deep Dive: The 12 Modules
Gypsy Bot allows you to toggle the following modules On/Off individually to suit the asset you are trading.
Module 1: Modified Slope Angle (MSA)
Logic: Calculates the geometric angle of a moving average relative to the timeline.
Function: It filters out "lazy" trends. A trend is only considered valid if the slope exceeds a specific steepness threshold. This helps avoid entering trades during weak drifts that often precede a reversal.
Module 2: Correlation Trend Indicator (CTI)
Logic: Based on John Ehlers' work, this measures how closely the current price action correlates to a straight line (a perfect trend).
Function: It outputs a confidence score (-1 to 1). Gypsy Bot uses this to ensure that we are not just moving up, but moving up with high statistical correlation, reducing fake-outs.
Module 3: Ehlers Roofing Filter
Logic: A sophisticated spectral filter that combines a High-Pass filter (to remove long-term drift) with a Super Smoother (to remove high-frequency noise).
Function: It attempts to isolate the "Roof" of the price action. It is excellent at catching cyclical turning points before standard moving averages react.
Module 4: Forecast Oscillator
Logic: Uses Linear Regression forecasting to predict where price "should" be relative to where it is.
Function: When the Forecast Oscillator crosses its zero line, it indicates that the regression trend has flipped. We offer both "Aggressive" and "Conservative" calculation modes for this module.
Module 5: Chandelier ATR Stop
Logic: A volatility-based trend follower that hangs a "leash" (ATR multiple) from the highest high (for longs) or lowest low (for shorts).
Function: Used here as an entry filter. If price is above the Chandelier line, the trend is Bullish. It also includes a "Bull/Bear Qualifier" check to ensure structural support.
Module 6: Crypto Market Breadth (CMB)
Logic: This is a macro-filter. It pulls data from multiple major tickers (BTC, ETH, and Perpetual Contracts) across different exchanges.
Function: It calculates a "Market Health" percentage. If Bitcoin is rising but the rest of the market is dumping, this module can veto a trade, ensuring you don't buy into a "fake" rally driven by a single asset.
Module 7: Directional Index Convergence (DIC)
Logic: Analyzes the convergence/divergence between Fast and Slow Directional Movement indices.
Function: Identifies when trend strength is expanding. A buy signal is generated only when the positive directional movement overpowers the negative movement with expanding momentum.
Module 8: Market Thrust Indicator (MTI)
Logic: A volume-weighted breadth indicator. It uses Advance/Decline data and Up/Down Volume data.
Function: This is one of the most powerful modules. It confirms that price movement is supported by actual volume flow. We recommend using the "SSMA" (Super Smoother) MA Type for the cleanest signals on the 4H chart.
Module 9: Simple Ichimoku Cloud
Logic: Traditional Japanese trend analysis using the Tenkan-sen and Kijun-sen.
Function: Checks for a "Kumo Breakout." Price must be fully above the Cloud (for longs) or below it (for shorts). This is a classic "trend confirmation" module.
Module 10: Simple Harmonic Oscillator
Logic: Analyzes the harmonic wave properties of price action to detect cyclical tops and bottoms.
Function: Serves as a counter-trend or early-reversal detector. It tries to identify when a cycle has bottomed out (for buys) or topped out (for sells) before the main trend indicators catch up.
Module 11: HSRS Compression / Super AO
Logic: Two options in one.
HSRS: Hirashima Sugita Resistance Support. Detects volatility compression (squeezes) relative to dynamic support/resistance bands.
Super AO: A combination of the Awesome Oscillator and SuperTrend logic.
Function: Great for catching explosive moves that result from periods of low volatility (consolidation).
Module 12: Fisher Transform (MTF)
Logic: Converts price data into a Gaussian normal distribution.
Function: Identifies extreme price deviations. This module uses Multi-Timeframe (MTF) logic to look at higher-timeframe trends (e.g., looking at the Daily Fisher while trading the 4H chart) to ensure you aren't trading against the major trend.
5. Global Inhibitors (The Veto Power)
Even if 12 out of 12 modules vote "Buy," Gypsy Bot performs a final safety check using Global Inhibitors. If any of these are triggered, the trade is blocked.
Bitcoin Halving Logic:
Hardcoded dates for past and projected future Bitcoin halvings (up to 2040).
Trading is inhibited or restricted during the chaotic weeks immediately surrounding a Halving event to avoid volatility crushes.
Miner Capitulation:
Uses Hash Rate Ribbons (Moving averages of Hash Rate).
If miners are capitulating (Shutting down rigs due to unprofitability), the engine flags a "Bearish" regime and can flip logic to Short-only or flat.
ADX Filter (Flat Market Protocol):
If the Average Directional Index (ADX) is below a specific threshold (e.g., 20), the market is deemed "Flat/Choppy." The bot will refuse to open trend-following trades in a flat market.
CryptoCap Trend:
Checks the total Crypto Market Cap chart. If the broad market is in a downtrend, it can inhibit Long entries on individual altcoins.
6. Risk Management & The Dump Protection Team (DPT)
Gypsy Bot separates "Entry Logic" from "Risk Management Logic."
Dump Protection Team (DPT)
This is a specialized logic branch designed to save the account during Black Swan events.
Nuke Protection: If the DPT detects a volatility signature consistent with a flash crash, it overrides all other logic and forces an immediate exit.
Moon Protection: If a parabolic pump is detected that violates statistical probability (Bollinger deviations), DPT can force a profit take before the inevitable correction.
Advanced Adaptive Trailing Stop (AATS)
Unlike a static trailing stop (e.g., "trail by 5%"), AATS is dynamic.
Penthouse Level: If price is at the top of the HSRS channel (High Volatility), the stop loosens to allow for wicks.
Dungeon Level: If price is compressed at the bottom, the stop tightens to protect capital.
Staged Take Profits
TP1: Scalp a portion (e.g., 10%) to cover fees and secure a win.
TP2: Take the bulk of profit.
TP3: Leave a "Runner" position with a loose trailing stop to catch "Moon" moves.
7. Recommended Setup Guide
When applying Gypsy Bot to a new chart, follow this sequence:
Set Timeframe: 4 Hours (4H).
Reset: Turn OFF Trailing Stop, Stop Loss, and Take Profits. (We want to see raw entry performance first).
Tune DPT: Adjust "Dump/Moon Protection" inputs first. These have the highest impact on net performance.
Tune Module 8 (MTI): This module is a heavy filter. Experiment with the MA Type (SSMA is recommended).
Select Modules: Enable/Disable modules 1-12 based on the asset's personality (Trending vs. Ranging).
Voting Threshold: Adjust ActivateOrders. A lower number = More Trades (Aggressive). A higher number = Fewer, higher conviction trades (Conservative).
Final Polish: Re-enable Stop Losses, Trailing Stops, and Staged Take Profits to smooth the equity curve and define your max risk per trade.
8. Technical Specs
Engine Version: Pine Script V6
Repainting: This strategy uses Closed Candle data for all Risk Management and Entry decisions. This ensures that Backtest results align closely with real-time behavior (no repainting of historical signals).
Alerts: This script generates Strategy alerts. If you require visual-only alerts, see the source code header for instructions on switching to "Study" (Indicator) mode.
Disclaimer:
This script is a complex algorithmic tool for market analysis. Past performance is not indicative of future results. Use this tool to assist your own decision-making, not to replace it.
9. About Signal Lynx
Automation for the Night-Shift Nation 🌙
Signal Lynx focuses on helping traders and developers bridge the gap between indicator logic and real-world automation. The same RM engine you see here powers multiple internal systems and templates, including other public scripts like the Super-AO Strategy with Advanced Risk Management.
We provide this code open source under the Mozilla Public License 2.0 (MPL-2.0) to:
Demonstrate how Adaptive Logic and structured Risk Management can outperform static, one-layer indicators
Give Pine Script users a battle-tested RM backbone they can reuse, remix, and extend
If you are looking to automate your TradingView strategies, route signals to exchanges, or simply want safer, smarter strategy structures, please keep Signal Lynx in your search.
License: Mozilla Public License 2.0 (Open Source).
If you make beneficial modifications, please consider releasing them back to the community so everyone can benefit.
Harmonic Patterns
Mean-Reversion with CooldownThis strategy requires no indicators or fundamental analysis. It is designed for longer-term positions and works especially well on unleveraged instruments with strong long-term upward trends, such as precious metals. Feel free to experiment with different timeframes — I’ve found that 1-hour charts work particularly well for cryptocurrencies.
The idea is to filter out ongoing bear phases as effectively as possible and capitalize on long-term bull runs.
The script implements an idea that came to me in a state of complete sleep deprivation: open a random long position with a fixed take-profit (TP) and a tight stop-loss (SL).
If the TP is hit — great, we simply try again.
If the SL is triggered — too bad, we pause for a while and then try again.
## Cooldown (Waiting) Mechanism
The waiting mechanism is simple: the more consecutive SL hits we get, the longer we wait before opening the next trade. The waiting time is measured in closed candles, and thus depends on the timeframe you are using.
## Two cooldown calculation modes are currently supported:
### 1. FIBONACCI
The cooldown follows the Fibonacci sequence, based on the number of consecutive losses:
1st loss → wait 1 bar
2nd loss → wait 1 bar
3rd loss → wait 2 or 3 bars (depending on definition)
4th loss → wait 3 or 5 bars
etc.
### 2. POWER OF TWO
The cooldown increases exponentially:
1st loss → wait 2 bars
2nd loss → wait 4 bars
3rd loss → wait 8 bars
4th loss → wait 16 bars
and so on, using the formula 2ⁿ.
## Configurable Parameters
### Cooldown Pause Calculation
The settings allow you to define the SL and TP as percentages of the position value.
The "Cooldown Pause Calculation" option determines how the next cooldown duration is computed after a losing trade.
The system keeps track of how many consecutive losses have occurred since the last profitable trade. That counter is then used to compute how many bars we must wait before opening the next position.
### Maximum Cooldown
The "Max Cooldown Candles" setting defines the maximum number of bars we are allowed to wait before placing a new trade. This prevents the strategy from “locking itself out” for too long and mitigates the fear of missing out (FOMO).
Once the cooldown duration reaches this maximum, the system essentially wraps around and starts the progression again. In the script, this is handled using a simple modulo operation based on the chosen maximum.
FX Swing — Compact Auto-Sizing (Fixed)A compact Forex swing-trading strategy that combines higher-timeframe EMA trend bias, EMA pullback confirmation, and RSI momentum filtering. It automatically sizes positions using either risk-percentage or fixed-risk, adapts pip values for JPY and non-JPY pairs, and generates clear SL/TP levels with partial take-profit exits. The script also sends structured JSON alerts for webhooks or WhatsApp automation, making it ideal for fast, disciplined, and risk-controlled swing entries.
G. Santostasi Bitcoin Power Law StrategyG. Santostasi Bitcoin Power Law Strategy
Overview
The "G. Santostasi Bitcoin Power Law Strategy" is a TradingView strategy script built upon the foundational Bitcoin Power Law Theory by physicist Giovanni Santostasi.
Unlike the companion Monte Carlo indicator, this strategy focuses on generating actionable buy entry and exit signals for trading Bitcoin, leveraging the normalized "Daily Slopes" metric to detect deviations from the long-term power-law trend. It employs two moving windows to compute local means (mu) of the Daily Slopes—a short-term 3-day window for responsive signals and a longer 2-week (14-day) window for establishing baseline bands. By comparing the short-term mu against deviation bands derived from the longer window's parameters, the strategy identifies entry points during undervalued dips and exit points during overvalued peaks. This approach capitalizes on Bitcoin's scale-invariant behavior, where price follows a power law
P(t)= c t^n, with n~5.9.
since the Genesis Block, resulting in diminishing but predictable returns. Backtested over Bitcoin's full history, the strategy boasts a 77% winning rate and a profit factor of 3.2, making it a robust tool for trend-following with mean-reversion elements. It emphasizes Bitcoin's long-term stability while navigating short-term oscillations, treating cycles as temporary deviations from the core power-law "DNA.
"Core Concept: Daily Slopes
The strategy inherits the Daily Slopes metric from the power-law framework, which normalizes daily logarithmic returns to reveal a stable local slope that oscillates around the global value of ~5.9.Definition and Calculation:
Daily log returns: log(P2/P1)\, where P2 and P1 are consecutive closing prices.
Normalization: Divide by log((t+1)/t), where ( t ) is days since the Genesis Block, yielding:
Daily Slope=log(P2/P1)log((t+1)/t).
This produces a "local n" that remains stable over time, with no long-term drift observed in Bitcoin's 16+ years of data. The metric accounts for diminishing returns, showing constant relative volatility in recent years despite absolute price stabilization.
Distribution and Parameters:
Daily Slopes are fitted to a t-location scale distribution over moving windows, estimating:μ (mu): The location/mean, stable around 5.9 globally.
σ (sigma): Scale/volatility measure.
ν (nu): Degrees of freedom for tail heaviness.
For the strategy, focus is on mu and sigma from the windows, enabling deviation-based signals.
Strategy Logic: Dual Moving Window Mus and Deviation Bands
The strategy computes two mus via rolling fits to the t-distribution:
Short Window mu (3 days): A fast-moving average of Daily Slopes, sensitive to immediate price action for timely signals.
Long Window mu (2 weeks/14 days): A slower baseline, capturing medium-term trends and providing stability.
Deviation bands are derived from the long window's mu and sigma:
Upper Band: Long mu + Long sigma
Lower Band: Long mu - Long sigma
These bands represent 1-standard-deviation ranges around the longer-term mean, highlighting overbought and oversold conditions relative to the power-law trend. The short mu acts as a "signal line," crossing the bands to trigger trades.
Plotting:
Short mu: Responsive line for crossovers.
Long mu: Central baseline.
Bands: Upper (+σ) and lower (-σ) lines from the long window.
Additional elements: Raw Daily Slopes and strategy signals (arrows for entries/exits).
Entry and Exit Rules:
The strategy generates long-only signals (buy/sell) based on crossovers, assuming a single-position approach without leverage or shorting:
Buy Entry: Triggered when the short-window mu crosses above the lower band (long mu - long sigma). This detects potential local minima, signaling undervaluation and a reversion to the power-law mean.
Sell Exit: Triggered when the short-window mu meets or crosses below the upper band (long mu + long sigma). This identifies local maxima, indicating overvaluation and a potential pullback.
Trade Management:
No stop-loss or take-profit hardcoded; users can add via TradingView settings.
Positions close on exit signals, with re-entry on the next valid buy.
Filters for false signals: Optional confirmation from global slope (e.g., only trade if long mu > 5.0) to align with bullish regimes.
This crossover mechanic blends momentum (short mu) with mean-reversion (bands), exploiting Bitcoin's oscillatory nature around the power law without predicting bubbles or crashes explicitly.
Performance Metrics:
Backtested on BTCUSD daily data from the Genesis Block to present (assuming continuous updates):Winning Rate: 77% – A high hit rate due to the strategy's focus on statistically stable deviations.
Profit Factor: 3.2 – Gross profits are 3.2 times gross losses, reflecting asymmetric upside from power-law reversion.
Additional Stats (hypothetical based on historical fits): Average trade duration ~30-60 days; drawdown <20% in most cycles; outperforms buy-and-hold in volatile periods by avoiding peaks.
Caveats: Past performance is not indicative of future results. The strategy shines in trending markets but may underperform in prolonged sideways action. Transaction costs (e.g., fees, slippage) not included in base metrics.
Usage Notes Inputs: Customize window lengths (default: 3 days short, 14 days long), global slope (5.9), and signal thresholds. Enable alerts for entries/exits.
Visuals: Strategy overlays on log-scale BTCUSD charts; use with volume or RSI for confirmation.
Limitations: Designed for spot trading; not optimized for derivatives or high-frequency. Assumes power-law persistence—major regime shifts (e.g., adoption plateaus) could impact efficacy.
Extensions: Adapt for other power-law metrics like network addresses or hash rate for multi-signal confirmation.
This strategy operationalizes Santostasi's insights into a practical trading system, prioritizing data-driven decisions over speculation.
Elliott Wave Oscillator + PSAR + VolumeStrategy Logic
1. Indicators
Elliott Wave Oscillator (EWO): This oscillator measures the difference between a 5-period and a 35-period exponential moving average (EMA). It's used to identify momentum shifts and potential wave structures. A buy signal is triggered when the EWO crosses above its signal line (a 5-period simple moving average). A sell signal is triggered when it crosses below.
Parabolic SAR (PSAR): This indicator shows potential reversals in price direction. A buy signal requires the PSAR to be below the current price, indicating an uptrend. A sell signal requires the PSAR to be above the current price, indicating a downtrend.
Volume: The strategy checks for significant changes in volume compared to its 20-period simple moving average (SMA). A buy signal requires a volume increase of at least 20% above the SMA. A sell signal requires a volume decrease of at least 20% below the SMA.
EMA 200: This long-term moving average is used to determine the overall market trend. A buy signal is only considered when the EMA 200 is rising (uptrend). A sell signal is only considered when the EMA 200 is falling (downtrend).
2. Entry and Exit Conditions
Long (Buy) Entry: A long position is entered if all of the following conditions are met:
EWO crosses its signal line upwards.
PSAR is below the price.
Volume has increased significantly.
The EMA 200 is rising.
The current candle is a bullish candle (close > open).
Short (Sell) Entry: A short position is entered if all of the following conditions are met:
EWO crosses its signal line downwards.
PSAR is above the price.
Volume has decreased significantly.
The EMA 200 is falling.
The current candle is a bearish candle (close < open).
Exit Conditions: Both long and short positions have a fixed 1% take profit and a 1% stop loss to manage risk.
In summary, the strategy only enters trades when a combination of momentum (EWO), trend (PSAR, EMA 200), and volume indicators align in the same direction, with strict risk management in place.
Multi-Timeframe Wolfe Wave StrategyThis invite-only strategy implements an advanced multi-timeframe Wolfe Wave pattern recognition system specifically designed for institutional-grade algorithmic trading environments.
**Core Mathematical Framework:**
The strategy employs sophisticated mathematical calculations across 10 distinct timeframes (377, 233, 144, 89, 55, 34, 21, 13, 8, 5 periods), utilizing Elliott Wave ratio theory combined with proprietary algorithmic enhancements. Unlike standard Wolfe Wave implementations that rely on visual pattern recognition, this system uses quantitative analysis to identify precise entry and exit points.
**Technical Implementation:**
• **Pattern Detection Algorithm:** Calculates price relationships using configurable ratio sets including Fibonacci sequences, Elliott Wave ratios, Golden Ratio, Harmonic Patterns, Pi-based calculations, and custom mathematical progressions
• **Multi-Timeframe Confluence:** Simultaneously analyzes patterns across all timeframes to ensure signal reliability and reduce false positives
• **Dynamic Target Calculation:** Employs advanced mathematical modeling to project optimal profit targets based on historical price behavior and pattern completion theory
• **Risk Management Engine:** Implements position-based stop losses calculated as percentages of target profits, with liquidation price monitoring for leveraged positions
**Originality and Innovation:**
This implementation differs significantly from traditional Wolfe Wave indicators through several key innovations:
1. **Algorithmic Pattern Validation:** Uses mathematical confirmation across multiple timeframes rather than subjective visual analysis
2. **Adaptive Ratio Selection:** Offers 24 different ratio calculation methods, allowing optimization for various market conditions
3. **Institutional Integration:** Features comprehensive webhook messaging for automated execution via external trading systems
4. **Advanced Position Management:** Includes sophisticated position sizing controls with maximum concurrent position limits
**Strategy Logic:**
For bullish conditions, the algorithm identifies when price action meets specific mathematical criteria:
- Point validation through ratio analysis between swing highs/lows
- Confluence confirmation across multiple timeframes
- Minimum profit threshold filtering to ensure trade quality
- Dynamic stop-loss positioning based on pattern geometry
The mathematical approach uses proprietary calculations that extend beyond traditional Fibonacci levels, incorporating elements from chaos theory, fractal geometry, and advanced statistical analysis.
**Risk Management Features:**
• Configurable stop-loss percentages relative to profit targets
• Maximum position limits to control portfolio exposure
• Liquidation price monitoring for margin trading
• Time-based filtering options for market session control
• Minimum profit threshold settings to filter low-quality signals
**Intended Markets and Conditions:**
Optimized for cryptocurrency markets with high volatility and sufficient liquidity. Works effectively in trending and ranging market conditions due to its multi-timeframe approach. Best suited for assets with clear swing structure and adequate price movement.
**Performance Characteristics:**
The strategy is designed for active trading with frequent position entries across multiple timeframes. Position holding periods vary from short-term scalping to medium-term swing trading depending on pattern completion timeframes.
**Technical Requirements:**
Requires understanding of advanced pattern recognition theory, risk management principles, and algorithmic trading concepts. Users should be familiar with Wolfe Wave methodology and Elliott Wave theory fundamentals.
Gartley 222 Strategy (Final Full Version)Gartley 222 Strategy (Bullish Pattern) — Repaint-Free, Backtestable
This strategy is based on the classic Gartley 222 harmonic pattern, originally introduced by H.M. Gartley in Profits in the Stock Market (1935). It identifies potential bullish reversal zones by detecting a five-point retracement structure (X-A-B-C-D) using pivot points and Fibonacci confluence.
🧠 Strategy Logic:
Detects valid pivot-based X, A, B, C points
Validates Gartley ratios:
AB = 61.8%–78.6% of XA
CD = 78.6%–88.6% of AB
Enters long at point D only after pivot confirmation (non-repainting)
Exits at 127% Fibonacci extension of XA or on stop loss
🔍 Features:
✅ Repaint-free and fully backtestable
✅ Visual X–A–B–C–D pattern lines on chart
✅ Customizable pivot length, risk, and reward ratios
✅ Alerts for real-time Gartley Buy pattern completion
Ideal for swing traders using 4H or Daily timeframes on trending instruments like NIFTY, BANKNIFTY, or major stocks.
Dkoderweb repainting issue fix strategyHarmonic Pattern Recognition Trading Strategy
This TradingView strategy called "Dkoderweb repainting issue fix strategy" is designed to identify and trade harmonic price patterns with optimized entry and exit points using Fibonacci levels. The strategy implements various popular harmonic patterns including Bat, Butterfly, Gartley, Crab, Shark, ABCD, and their anti-patterns.
Key Features
Pattern Recognition: Identifies 17+ harmonic price patterns including standard and anti-patterns
Fibonacci-Based Entries and Exits: Uses customizable Fibonacci levels for precision entries, take profits, and stop losses
Alternative Timeframe Analysis: Option to use higher timeframes for pattern identification
Heiken Ashi Support: Optional use of Heiken Ashi candles instead of regular candlesticks
Visual Indicators:
Pattern visualization with ZigZag indicator
Buy/sell signal markers
Color-coded background to highlight active trade zones
Customizable Fibonacci level display
How It Works
The strategy uses a ZigZag-based pattern identification system to detect pivot points
When a valid harmonic pattern forms, the strategy calculates the optimal entry window using the specified Fibonacci level (default 0.382)
Entries trigger when price returns to the entry window after pattern completion
Take profit and stop loss levels are automatically set based on customizable Fibonacci ratios
Visual alerts notify you of entries and exits
The strategy tracks active trades and displays them with background color highlights
Customizable Settings
Trade size
Entry window Fibonacci level (default 0.382)
Take profit Fibonacci level (default 0.618)
Stop loss Fibonacci level (default -0.618)
Alert messages for entries and exits
Display options for specific Fibonacci levels
Alternative timeframe selection
This strategy is designed to fix repainting issues that are common in harmonic pattern strategies, ensuring more reliable signals and backtesting results.
123 Reversal Trading StrategyThe 123 Reversal Trading Strategy is a technical analysis approach that seeks to identify potential reversal points in the market by analyzing price patterns. This Pine Script™ code implements a version of this strategy, and here’s a detailed description:
Strategy Overview
Objective: The strategy aims to identify bullish reversal patterns using the 123 pattern and manage trades with a specified holding period and a 20-day moving average as an additional exit condition.
Key Components:
Holding Period: The number of days to hold a trade is adjustable, with the default set to 7 days.
Moving Average: A 200-day simple moving average (SMA) is used to determine an exitcondition based on the price crossing this average.
Pattern Recognition:
Condition 1: The low of the current day must be lower than the low of the previous day.
Condition 2: The low of the previous day must be lower than the low from three days ago.
Condition 3: The low two days ago must be lower than the low from four days ago.
Condition 4: The high two days ago must be lower than the high three days ago.
Entry Condition: All four conditions must be met for a buy signal.
Exit Condition: The position is closed either after the specified holding period or when the price reaches or exceeds the 200-day moving average.
Relevant Literature
Graham, B., & Dodd, D. L. (1934). Security Analysis. This classic work introduces fundamental analysis and technical analysis principles which are foundational to understanding patterns like the 123 reversal.
Murphy, J. J. (1999). Technical Analysis of the Financial Markets. Murphy provides an extensive overview of technical indicators and chart patterns, including reversal patterns similar to the 123 pattern.
Elder, A. (1993). Trading for a Living. Elder discusses various trading strategies and technical analysis techniques that complement the understanding of reversal patterns and their application in trading.
Risks and Considerations
Pattern Reliability: The 123 reversal pattern, like many technical patterns, is not foolproof. It can generate false signals, especially in volatile or trending markets. This may lead to losses if the pattern does not play out as expected.
Market Conditions: The strategy may perform differently under various market conditions. In strongly trending markets, reversal patterns might not be as reliable.
Lagging Indicators: The use of the 200-day moving average as an exit condition can be considered a lagging indicator. This means it reacts to price movements with a delay, which might result in late exits and missed profit opportunities.
Holding Period: The fixed holding period of 7 days may not be optimal for all market conditions or stocks. It is essential to adjust the holding period based on market dynamics and individual stock behavior.
Overfitting: The parameters used (like the number of days and moving average length) are set based on historical data. Overfitting can occur if these parameters are tailored too specifically to past data, leading to reduced performance in future scenarios.
Conclusion
The 123 Reversal Trading Strategy is designed to identify potential market reversals using specific conditions related to price lows and highs. While it offers a structured approach to trading, it is essential to be aware of its limitations and potential risks. As with any trading strategy, it should be tested thoroughly in various market conditions and adjusted according to the individual trading style and risk tolerance.
[strategy][1H] SPY slow stochastics
SPY slow stochastics
Overview
The "SPY Auto RSI Stochastics" strategy is designed to leverage a combination of Relative Strength Index (RSI) and Stochastic indicators to identify potential entry and exit points in trading the SPY $SP:SPX.
The technicals:
A simple yet effective strategy for identifying (reversal) trends on SPY (or any asset).
The logic is as follows:
1. Slow stochastics are effective at predicting momentum. They can also be used to effectively identify reversals.
2. A combination of slow and fast RSI (along with an SMA for the fast RSI) can be used to see potential changes in the directional trend of the underlying asset.
3. In order to reduce noise, a band in the middle of RSI values is ignored; think of this as the price converging and potential explosions (sometimes fake) on either side.
4. Outside this noise band, a crossover of fast RSI on slow RSI indicates an upward trend incoming.
5. A crossunder of fast RSI on slow RSI indicates a downward trend incoming.
Strategy Specific Notes -
1. Load this strategy on SPREADEX:SPX on an hourly chart for the best results.
2. This is a generic strategy, use it on anything - index, stocks, etc. You will need to adjust the parameters for the best results.
3. The RSI Upper defines the cutoff for two things -- threshold for entering a long AND exit signal for short. Likewise for RSI Lower.
4. To have alerts on the strategy, add this to your chart, be content with the backtesting results, select "strategy tester", the alert icon, replace the message body with "{{strategy.order.alert_message}}" without the ".
5. In my experience, the strategy won't be immediately profitable upon a signal but it does get there in the backtested results. Intuitively, this makes sense. Reversals take some time to kick in completely.
Inputs
- **slowRSILength**: Length parameter for the slow RSI calculation.
- **fastRSILength**: Length parameter for the fast RSI calculation.
- **smaRSILength**: Length parameter for the Simple Moving Average (SMA) of the fast RSI.
- **RSIUpperThreshold**: Upper threshold for the RSI, used in exit conditions.
- **RSILowerThreshold**: Lower threshold for the RSI, used in exit conditions.
- **RSIUpperDeadzone**: Upper deadzone threshold for the RSI.
- **RSILowerDeadzone**: Lower deadzone threshold for the RSI.
Strategy Logic
- **RSI Calculation**: The script calculates both slow and fast RSI values based on the provided lengths.
- **Entry Condition**: Entry conditions for long and short positions are based on the crossing of fast RSI over slow RSI and SMA RSI, respectively, along with avoidance of RSI deadzones and validation of trade time.
- **Exit Condition**: Exit conditions for both long and short positions are based on crossing RSI thresholds or opposite entry conditions.
Trade Management
- **Position Entry**: Long and short positions are entered based on predefined entry conditions.
- **Position Exit**: Positions are exited based on predefined exit conditions.
- **Alerts**: The script provides alert messages for entry and exit points.
Plotting
- **Slow RSI**: Plots the slow RSI on the chart.
- **SMA RSI**: Plots the Simple Moving Average of fast RSI on the chart.
Example Usage
The defaults work well for SPY on a 1H timeframe.
If you apply this to anything else DAX, EUSTX50, FTSE, CAC (these are what i have); tweak the input parameters.
Plotting
plot(slowRSI, "Slow RSI", color=color.green) //or fastRSI
plot(smaRSI, "SMA RSI", color=color.white)
Conclusion
The "SPY Auto RSI Stochastics" strategy combines RSI and Stochastic indicators to provide potential trade signals for the SPY ETF. Traders can use this strategy with proper risk management and analysis to enhance their trading decisions.
Auto Harmonic Pattern - Backtester [Trendoscope]We are finally here with the implementation of backtesting tool for Auto-Harmonic-Pattern-UltimateX .
CAUTION: THIS IS NOT A STRATEGY AND SHOULD NOT BE FOLLOWED BLINDLY. WE ENCOURAGE USERS TO UTILISE THIS AS BACKTESTING TOOL FOR BUILDING THEIR STRATEGY BASED ON HARMONIC PATTERNS
This script is based on our premium indicator - Auto-Harmonic-Pattern-UltimateX . In this script, along with implementation of scanning harmonic patterns, we provide various options via settings which enables users to build their own strategy based on harmonic patterns, use them with custom coded filters, backtest them on various tickers and timeframes.
Harmonic Patterns is concept and we can trade harmonic pattern in many ways. While general interest around harmonic patterns is to find reversal zones and use them for short term swing trades. But, using it along trend following strategies can also be very rewarding. Here is one of the educational idea I shared about using harmonic patterns for trend following. These are just few possibilities where users can explore further on how they want to trade this. The settings of this script are crafted in such a way that it enables users to explore all these possibilities.
🎲 Components
Chart components of this script is lighter compared to Auto Harmonic Pattern - UltimateX. This is because we want to keep lighter interface in order to support seamless execution of emulator. Since pine strategy framework does most of the things such as calculating profitability, keeping track of trades and results etc, display with respect to - "Closed Trade Stats" are removed from this script and "Open Trade Stats" are made lighter.
🎲 Settings
🎯 Trade Settings : Few important settings under this section are
Due to pine limitations, we will not be able to support both long and short in a same setup. Hence, users need to chose either long or short trade setup.
Entry/Base/Target play important role in defining your strategy.
Confluence is another important factor which lets users use multiple patterns at once as confirmation.
🎯 Zigzag Settings : Zigzag settings determine the size of patterns being formed.
Please note that smaller patterns may not yield very good results and larger patterns may take time to complete trade. Similarly higher depth can cause runtime issues. Recursive zigzag option is alternative to deep search algorithm.
🎯 Filters :
Filters enable users to select trades based on specific conditions. Ability to use external filter even allows writing and using custom filters to be used with this algorithm. Here is a video which explains how this can be done. HOW-TO-Use-external-filters
Pattern filters allow users to pick and chose patterns they want to trade. This can be done either individually or based on category
🎯 Alerts :
Apart from strategy specific alerts, the script also implements customisable alerts via pine alert() function. Alerts can be configured to send upon three conditions
When new pattern is created
When an existing pattern updates entry/stop/target due to safe repaint of D (Only happens when Trail Entry Price is selected)
When a pattern in trade closes either due to hitting stop or target
Important Note: Alerts fired via this method may not match the trades shown on chart as trades which are controlled via pine strategy emulator depends on various other factors such as pyramiding.
Alert template is customisable and users can make use of available placeholders to get dynamic data in alerts. Valid placeholders are
{alertType} - Alert type - New/Update/Close
{id} - Pattern Id
{ticker} - Ticker
{timeframe} - Chart timeframe
{price} - Current price
{patterns} - Identified pattern names
{direction} - Direction - Long/Short
{entry} - Entry Price
{stop} - Stop Price
{target} - Target Price
{orderType} - Limit/Stop - applicable for only New and Update types
{status} - Trade status. Valid values are Pending/Cancelled/Stopped/Success
Template is common for all custom alert types. Hence, updating the template will impact all custom alerts - New/Update/Close
{
"alert" : "{alertType}",
"id" : {id},
"ticker" : "{ticker}",
"timeframe" : "{timeframe}",
"price" : {price},
"patterns" : "{patterns}",
"direction" : "{direction}",
"entry" : {entry},
"stop" : {stop},
"target" : {target},
"orderType" : {orderType}
"status" : {status}
}
Here is a video on how to customise the alerts using templates and placeholders - HOW-TO-Customize-Alerts-With-Placeholders
🎯 Miscellaneous :
These are simple settings to control display and backtest bars. If you are running alerts, we suggest turning of Open Trades and Drawings and limit backtest to minimal value in order to improve efficiency of
🎯 Backtest Engine Parameters :
Default settings are optimised for trend following. Users are encouraged to play around with settings and filters to build strategy out of this tool.
Position sizing is not leveraged. Margin settings makes sure that trades cannot exceed capital.
All measures are taken to avoid repainting. Script does not use request.security and real time bars. This drastically reduces the risk of repainting in scripts.
If you are premium user, please select "Bar Magnifier".
Wolfe Strategy [Trendoscope]Hello Everyone,
Wish you all Merry X-Mas and happy new year. Lets start 2023 with fresh new strategy built on Wolfe Indicator. Details of the indicator can be found here
🎲 Wolfe Concept
Wolfe concept is simple. Whenever a wedge is formed, draw a line joining pivot 1 and 4 as shown in the chart below:
For simplicity, we will only consider static value for Target and Stop. But, entry is done based on breaking the triangle. Revised strategy looks something like this:
🎲 Settings
Settings are simple and details of each are provided via tooltips.
Out of these, the most important one is minimum risk reward ratio. If you set lower risk reward threshold then losing few trades may generate more losses than more winning trades. Similarly higher value will filter out most of the trades and may not work efficiently. Default value set to 1 to make sure optimal risk reward is present before placing trade. Also make note that since the entry bar is always moving towards stop, as and when pattern progress, the RR will also increase. Hence, a pattern which is below RR threshold may become good to trade at certain point of time in future.
🎲 Strategy Parameters
Default strategy parameters are initialised via definition. Margins are set to 100 to disable leveraged trades. Appropriate values are chosen for other parameters. These can be altered based on individual strategy and trading plan.
As the strategy concentrates on the single pattern, number of trades generated are comparatively less. But, there is chance to increase the algorithm further to catch more such patterns on larger scale. Will try to work on them in next versions.
🎲 Pine Strategy limitations
Backtest can only be done on one direction as pine strategy cannot have both long and short open trades together. Hence, it is mandatory to chose either long/short trades in settings.
Since pyramiding is limited to 1, there is possibility of a pattern not generating trade even though the entry conditions are met. They are just based on pine limitations and not necessarily mean patterns are not good for placing trades.
Strategy Myth-Busting #20 - HalfTrend+HullButterfly - [MYN]#20 on the Myth-Busting bench, we are automating the " I Found Super Easy 1 Minute Scalping System And Backtest It 100 Times " strategy from " Jessy Trading " who claims 30.58% net profit over 100 trades in a couple of weeks with a 51% win rate and profit factor of 1.56 on EURUSD .
This one surprised us quite a bit. Despite the title of this strategy indicating this is on the 1 min timeframe, the author demonstrates the backtesting manually on the 5 minute timeframe. Given the simplicity of this strategy only incorporating a couple of indicators, it's robustness being able to be profitable in both low and high timeframes and on multiple symbols was quite refreshing.
The 3 settings which we need to pay most attention to here is the Hull Butterfly length, HalfTrend amplitude and the Max Number Of Bars Between Hull and HalfTrend Trigger. Depending on the timeframe and symbol, these settings greatly impact the performance outcomes of the strategy. I've listed a couple of these below.
And as always, If you know of or have a strategy you want to see myth-busted or just have an idea for one, please feel free to message me.
This strategy uses a combination of 3 open-source public indicators:
Hull Butterfly Oscillator by LuxAlgo
HalfTrend by Everget
Trading Rules
5 min candles but higher / lower candles work too.
Stop loss at swing high/low
Take Profit 1.5x the risk
Long
Hull Butterfly gives us green column, Wait for HalfTrend to present an up arrow and enter trade.
Short
Hull Butterfly gives us a red column , Wait for HalfTrend to present a down arrow and enter trade.
Alternative Trading Settings for different time frames
1 Minute Timeframe
Move the Hull Butterfly length from the default 11 to 9
Move the HalfTrend Amplitude from the default 2 to 1
Enabling ADX Filter with a 25 threshold
2 Hour Timeframe
Move the HalfTrend Amplitude from the default 2 to 1
Laddered Take Profits from 14.5% to 19% with an 8% SL
Hyper Bot | Self Optimizing Buy & SellThis strategy primarily uses Bollinger Bands with custom improvements and alterations in entry exit signals which i have learned over the past years.
How to use?
Visit strategy settings. You will see checkboxes before all options, meaning they can be turned ON and OFF.
For "Long SL %" to work, the "LONG" should be enabled aswell. If Long is not enabled, changing numbers in "Long SL%" won't make any difference.
Likewise if you want to test take profit, then either long or short or both should be enabled with "TP Long%" or "TP Short%"
This wide customization is being provided for you to be able to test all possible variations and choose whichever best is working for you. Play around with the numbers of SL% and TP% and find best ones that work for you in terms of drawdown, risk to profit etc.
Commission 0.1% by default is included, if however your commissions are lower, please change them to get better results.
This strategy is mainly optimized for Cryptocurrencies, however if you wish to use for indices and commodities please DM me, i will provide customization services.
Enjoy!
© Copyright 2022 "M Tahreem Alam"
Liquidity_Zone by SebasVentuLiquidity_Zone by SebasVentu It is a strategy that shows the liquidity zones and also has a simulator
Es una estrategia que muestra las zonas de liquidez y ademas cuenta con un simulador
[Herif's] Harmonic Patterns ProjectionBullish and bearish 5-point patterns are based on various Fibonacci retracement levels and signify potential reversal zones (PRZ).
As they become 0%-80% complete, the dashed-line pattern will appear, displaying the PRZ and giving you time to prepare for a reversal.
Different combinations of specific fib retracements and extensions result in different patterns, and each is named for identification.
Bullish patterns signify a potential turn to the upside are colored green.
Bearish patterns signify a potential turn to the downside are colored red.
1- Live harmonic patterns which are still in trade with XABCD and ratio with labels.
2- Entry, Stop and Target levels on chart for all patterns.
in Settings:
Error Percent - This is error tollerance for matching pattern ratios. Cannot expect price ratios to be exactly as per books. Hence, adding few error tolerance will help identify patterns better. In this indicator defatult 1%
When there are multiple patterns on chart, Entry, Stop, and Target labels and lines are created with specific distance from each other to provide clarity to the users.
Trailing and Targets
1-Trailing Start Stage - Defines when to start trailing stop-loss. It is recommended to set this value to either Target 1 or Target 2. Disabling the trailing or setting too far away may lead to being in trade on ranging market for too long. This may also result in drawing errors related to distance from current bar.
2- Custom Target Levels - Target and stop levels are set to optimal values based on individual patterns. If you want to override these levels, use the available input option to override targets and chose your custom Target1, Target2, Target3 and Target4
All Pending Patterns you can enable or disable
Classic Patterns : Gartley , Bat, Butterfly , Crab , Deep Crab , Cypher , Shark , Nenstar
Anti Patterns: Anti Nenstar, Anti Shark , Anti Cypher , Anti Crab , Anti Butterfly , Anti Bat, Anti Gartley , Navarro 200
This is a Strategy version of indicator below
