Trend Vector Pro v2.0Trend Vector Pro v2.0
👨💻 Developed by: Mohammed Bedaiwi
💡 Strategy Overview & Coherence
Trend Vector Pro (TVPro) is a momentum-based trend & reversal strategy that uses a custom smoothed oscillator, an optional ADX filter, and classic Pivot Points to create a single, coherent trading framework.
Instead of stacking random indicators, TVPro is built around these integrated components:
A custom momentum engine (signal generation)
An optional ADX filter (trend quality control)
Daily Pivot Points (context, targets & S/R)
Swing-based “Golden Bar” trailing stops (trade management)
Optional extended bar detection (overextension alerts)
All parts are designed to work together and are documented below to address originality & usefulness requirements.
🔍 Core Components & Justification
1. Custom Momentum Engine (Main Signal Source)
TVPro’s engine is a custom oscillator derived from the bar midpoint ( hl2 ), similar in spirit to the Awesome Oscillator but adapted and fully integrated into the strategy. It measures velocity and acceleration of price, letting the script distinguish between strong impulses, weakening trends, and pure noise.
2. ADX Filter (Trend Strength Validation – Optional)
Uses Average Directional Index (ADX) as a gatekeeper.
Why this matters: This prevents the strategy from firing signals in choppy, non-trending environments (when ADX is below the threshold) and keeps trades focused on periods of clear directional strength.
3. Classic Pivot Points (Context & Targets)
Calculates Daily Pivot Points ( PP, R1-R3, S1-S3 ) via request.security() using prior session data.
Why this matters: Momentum gives the signal, ADX validates the environment, and Pivots add external structure for risk and target planning. This is a designed interaction, not a random mashup.
🧭 Trend State Logic (5-State Bar Coloring)
The strategy uses the momentum's value + slope to define five states, turning the chart into a visual momentum map:
🟢 STRONG BULL (Bright Green): Momentum accelerating UP. → Strong upside impulse.
🌲 WEAK BULL (Dark Green): Momentum decelerating DOWN (while positive). → Pullback/pause zone.
🔴 STRONG BEAR (Bright Red): Momentum accelerating DOWN. → Strong downside impulse.
🍷 WEAK BEAR (Dark Red): Momentum decelerating UP (while negative). → Rally/short-covering zone.
🔵 NEUTRAL / CHOP (Cyan): Momentum is near zero (based on noise threshold). → Consolidation / low volatility.
🎯 Signal Logic Modes
TVPro provides two selectable entry styles, controlled by input:
Reversals Only (Cleaner Mode – Default): Targets trend flips. Entry triggers when the current state is Bullish (or Bearish) and the previous state was not. This reduces noise and over-trading.
All Strong Pulses (Aggressive Mode): Targets acceleration phases. Entry triggers when the bar turns to STRONG BULL or STRONG BEAR after any other state. This mode produces more trades.
📌 Risk Management Tools
🟡 Golden Bars – Trailing Stops: Yellow “Trail” Arrows mark confirmed Swing Highs/Lows. These are used as logical trailing stop levels based on market structure.
Extended Bars: Detects when price closes outside a 2-standard-deviation channel, flagging overextension where a pullback is more likely.
Pivot Points: Used as external targets for Take Profit and structural stop placement.
⚙️ Strategy Defaults (Crucial for Publication Compliance)
To keep backtest results realistic and in line with House Rules, TVPro is published with the following fixed default settings:
Order Size: 5% of equity per trade ( default_qty_value = 5 )
Commission: 0.04% per order ( commission_value = 0.04 )
Slippage: 2 ticks ( slippage = 2 )
Initial Capital: 10,000
📘 How to Trade with Trend Vector Pro
Entry: Take Long when a Long signal appears and confirm the bar is Green (Bull state). Short for Red (Bear state).
Stop Loss: Place the initial SL near the latest swing High/Low, or near a relevant Pivot level.
Trade Management: Follow Golden (Trail) Arrows to trail your stop behind structure.
Exits: Exit when: the trailing stop is hit, Price reaches a major Pivot level, or an opposite signal prints.
🛑 Disclaimer
This script is for educational purposes only and does not constitute financial advice. Past performance does not guarantee future results. Always forward-test and use proper risk management before applying any strategy to live trading.
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Advanced Breakout System v2.0Advanced Breakout System v2.0
Developed by: Mohammed Bedaiwi
This script hunts for high-probability breakouts by combining price consolidation zones, volume spikes vs. average volume, smart money flow (OBV), and a Momentum Override for explosive moves that skip consolidation. Additionally, it automatically identifies and plots Support and Resistance levels with price labels to help you visualize market structure.
The system follows a "Watch & Confirm" logic: it first prints a WATCH setup, then a BUY only if price confirms strength.
💡 JUSTIFICATION OF CONCEPTS (MASHUP & ORIGINALITY)
This script is an original mashup combining several analytical concepts to address common breakout failures:
Volatility Compression Engine: Uses built-in functions like ta.highest() and ta.lowest() to mathematically define the setup phase where price volatility is compressed below a user-defined threshold.
Volume Spike Confirmation: The breakout must be confirmed by a volume increase greater than a moving average of volume, signaling strong market interest.
Smart Volume Filter (OBV): This is the key component. By checking if ta.obv is above its own Moving Average, we confirm that accumulation has been occurring during the consolidation period, suggesting institutional positioning before the price break.
Multi-Exit Risk System: Employs dynamic exits (EMA cross, volume dump, bearish pattern) instead of static stop-losses to manage risk adaptively based on real-time market action.
Market Structure Visualization: The script also includes a Support & Resistance engine to plot key swing pivots and price labels for visual context.
✅ STRATEGY RESULTS & POLICY COMPLIANCE
To ensure non-misleading and transparent backtesting results, this strategy is published with the following fully compliant properties:
Dataset Compliance: The backtest is performed on the CMTL Daily (1D) chart across a long history, generating 201 total trades. This significantly exceeds the minimum requirement of 100 trades, providing a robust test dataset.
Risk Control: The strategy uses a conservative order size set to 2% of equity (default_qty_value=2), strictly adhering to the sustainable risk recommendation of 5-10% of equity per trade.
Transaction Costs: Realistic trading conditions are modeled using 0.07% commission and 3 ticks slippage to prevent the overestimation of profitability.
⚙️ VISUAL GUIDE & SIGNAL LOGIC
Key Color Legend (Visual Guide):
WATCH – Setup (Yellow Arrow Down): Potential breakout setup detected.
BUY – Confirmation (Green Arrow Up): Confirmed breakout, triggered when price trades above the high of the WATCH candle.
SELL – Break (Orange Arrow): Short-term trend weakness, triggered when price closes below the Fast EMA (9).
SELL – Dump (Dark Red Arrow): Distribution / volume dump, triggered by a bearish candle with abnormally high volume.
SELL – Pattern (Purple Arrow): Bearish price-action pattern (such as a bearish engulfing).
Support & Resistance Lines (Red/Green): Small horizontal lines plotted at key swing points with exact price labels.
⌨️ INPUTS (DEFAULT SETTINGS)
Entry settings: Consolidation Lookback (default 20) = bars used to detect consolidation. Consolidation Range % (default 12%) = max allowed range size. Volume Spike Multiplier (default 1.2) = factor above average volume to count as a spike. Force Signal on Big Moves (default ON) = forces a WATCH signal on high-momentum moves.
Exit settings: Enable Fast Exit (EMA 9) toggles the SELL – Break signal. Dump Volume Multiplier defines what counts as “dump” volume.
Support & Resistance: Adjustable Pivot Left/Right bars control the sensitivity of the support and resistance lines.
⚠️ Disclaimer Trading involves significant risk of loss. This script is for educational and informational purposes only and is not financial advice or a recommendation to buy or sell any asset. BUY and SELL signals are rule-based and derived from historical behavior and do not guarantee future performance. Always use your own analysis and risk management. This is an open-source strategy; users are encouraged to test it across different symbols and timeframes.
ALT Risk Metric StrategyHere's a professional write-up for your ALT Risk Strategy script:
ALT/BTC Risk Strategy - Multi-Crypto DCA with Bitcoin Correlation Analysis
Overview
This strategy uses Bitcoin correlation as a risk indicator to time entries and exits for altcoins. By analyzing how your chosen altcoin performs relative to Bitcoin, the strategy identifies optimal accumulation periods (when alt/BTC is oversold) and profit-taking opportunities (when alt/BTC is overbought). Perfect for traders who want to outperform Bitcoin by strategically timing altcoin positions.
Key Innovation: Why Alt/BTC Matters
Most traders focus solely on USD price, but Alt/BTC ratios reveal true altcoin strength:
When Alt/BTC is low → Altcoin is undervalued relative to Bitcoin (buy opportunity)
When Alt/BTC is high → Altcoin has outperformed Bitcoin (take profits)
This approach captures the rotation between BTC and alts that drives crypto cycles
Key Features
📊 Advanced Technical Analysis
RSI (60% weight): Primary momentum indicator on weekly timeframe
Long-term MA Deviation (35% weight): Measures distance from 150-period baseline
MACD (5% weight): Minor confirmation signal
EMA Smoothing: Filters noise while maintaining responsiveness
All calculations performed on Alt/BTC pairs for superior market timing
💰 3-Tier DCA System
Level 1 (Risk ≤ 70): Conservative entry, base allocation
Level 2 (Risk ≤ 50): Increased allocation, strong opportunity
Level 3 (Risk ≤ 30): Maximum allocation, extreme undervaluation
Continuous buying: Executes every bar while below threshold for true DCA behavior
Cumulative sizing: L3 triggers = L1 + L2 + L3 amounts combined
📈 Smart Profit Management
Sequential selling: Must complete L1 before L2, L2 before L3
Percentage-based exits: Sell portions of position, not fixed amounts
Auto-reset on re-entry: New buy signals reset sell progression
Prevents premature full exits during volatile conditions
🤖 3Commas Automation
Pre-configured JSON webhooks for Custom Signal Bots
Multi-exchange support: Binance, Coinbase, Kraken, Bitfinex, Bybit
Flexible quote currency: USD, USDT, or BUSD
Dynamic order sizing: Automatically adjusts to your tier thresholds
Full webhook documentation compliance
🎨 Multi-Asset Support
Pre-configured for popular altcoins:
ETH (Ethereum)
SOL (Solana)
ADA (Cardano)
LINK (Chainlink)
UNI (Uniswap)
XRP (Ripple)
DOGE
RENDER
Custom option for any other crypto
How It Works
Risk Metric Calculation (0-100 scale):
Fetches weekly Alt/BTC price data for stability
Calculates RSI, MACD, and deviation from 150-period MA
Normalizes MACD to 0-100 range using 500-bar lookback
Combines weighted components: (MACD × 0.05) + (RSI × 0.60) + (Deviation × 0.35)
Applies 5-period EMA smoothing for cleaner signals
Color-Coded Risk Zones:
Green (0-30): Extreme buying opportunity - Alt heavily oversold vs BTC
Lime/Yellow (30-70): Accumulation range - favorable risk/reward
Orange (70-85): Caution zone - consider taking initial profits
Red/Maroon (85-100+): Euphoria zone - aggressive profit-taking
Entry Logic:
Buys execute every candle when risk is below threshold
As risk decreases, position sizing automatically scales up
Example: If risk drops from 60→25, you'll be buying at L1 rate until it hits 50, then L2 rate, then L3 rate
Exit Logic:
Sells only trigger when in profit AND risk exceeds thresholds
Sequential execution ensures partial profit-taking
If new buy signal occurs before all sells complete, sell levels reset to L1
Configuration Guide
Choosing Your Altcoin:
Select crypto from dropdown (or use CUSTOM for unlisted coins)
Pick your exchange
Choose quote currency (USD, USDT, BUSD)
Risk Metric Tuning:
Long Term MA (default 150): Higher = more extreme signals, Lower = more frequent
RSI Length (default 10): Lower = more volatile, Higher = smoother
Smoothing (default 5): Increase for less noise, decrease for faster reaction
Buy Settings (Aggressive DCA Example):
L1 Threshold: 70 | Amount: $5
L2 Threshold: 50 | Amount: $6
L3 Threshold: 30 | Amount: $7
Total L3 buy = $18 per candle when deeply oversold
Sell Settings (Balanced Exit Example):
L1: 70 threshold, 25% position
L2: 85 threshold, 35% position
L3: 100 threshold, 40% position (final exit)
3Commas Setup
Bot Configuration:
Create Custom Signal Bot in 3Commas
Set trading pair to your altcoin/USD (e.g., ETH/USD, SOL/USDT)
Order size: Select "Send in webhook, quote" to use strategy's dollar amounts
Copy Bot UUID and Secret Token
Script Configuration:
Paste credentials into 3Commas section inputs
Check "Enable 3Commas Alerts"
Save and apply to chart
TradingView Alert:
Create Alert → Condition: "alert() function calls only"
Webhook URL: api.3commas.io
Enable "Webhook URL" checkbox
Expiration: Open-ended
Strategy Advantages
✅ Outperform Bitcoin: Designed specifically to beat BTC by timing alt rotations
✅ Capture Alt Seasons: Automatically accumulates when alts lag, sells when they pump
✅ Risk-Adjusted Sizing: Buys more when cheaper (better risk/reward)
✅ Emotional Discipline: Systematic approach removes fear and FOMO
✅ Multi-Asset: Run same strategy across multiple altcoins simultaneously
✅ Proven Indicators: Combines RSI, MACD, and MA deviation - battle-tested tools
Backtesting Insights
Optimal Timeframes:
Daily chart: Best for backtesting and signal generation
Weekly data is fetched internally regardless of display timeframe
Historical Performance Characteristics:
Accumulates heavily during bear markets and BTC dominance periods
Captures explosive altcoin rallies when BTC stagnates
Sequential selling preserves capital during extended downtrends
Works best on established altcoins with multi-year history
Risk Considerations:
Requires capital reserves for extended accumulation periods
Some altcoins may never recover if fundamentals deteriorate
Past correlation patterns may not predict future performance
Always size positions according to personal risk tolerance
Visual Interface
Indicator Panel Displays:
Dynamic color line: Green→Lime→Yellow→Orange→Red as risk increases
Horizontal threshold lines: Dashed lines mark your buy/sell levels
Entry/Exit labels: Green labels for buys, Orange/Red/Maroon for sells
Real-time risk value: Numerical display on price scale
Customization:
All threshold lines are adjustable via inputs
Color scheme clearly differentiates buy zones (green spectrum) from sell zones (red spectrum)
Line weights emphasize most extreme thresholds (L3 buy and L3 sell)
Strategy Philosophy
This strategy is built on the principle that altcoins move in cycles relative to Bitcoin. During Bitcoin rallies, alts often bleed against BTC (high sell, accumulate). When Bitcoin consolidates, alts pump (take profits). By measuring risk on the Alt/BTC chart instead of USD price, we time these rotations with precision.
The 3-tier system ensures you're always averaging in at better prices and scaling out at better prices, maximizing your Bitcoin-denominated returns.
Advanced Tips
Multi-Bot Strategy:
Run this on 5-10 different altcoins simultaneously to:
Diversify correlation risk
Capture whichever alt is pumping
Smooth equity curve through rotation
Pairing with BTC Strategy:
Use alongside the BTC DCA Risk Strategy for complete portfolio coverage:
BTC strategy for core holdings
ALT strategies for alpha generation
Rebalance between them based on BTC dominance
Threshold Calibration:
Check 2-3 years of historical data for your chosen alt
Note where risk metric sat during major bottoms (set buy thresholds)
Note where it peaked during euphoria (set sell thresholds)
Adjust for your risk tolerance and holding period
Credits
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Technical Analysis Framework: RSI, MACD, Moving Average theory
Implementation: pommesUNDwurst
Disclaimer
This strategy is for educational purposes only. Cryptocurrency trading involves substantial risk of loss. Altcoins are especially volatile and many fail completely. The strategy assumes liquid markets and reliable Alt/BTC price data. Always do your own research, understand the fundamentals of any asset you trade, and never risk more than you can afford to lose. Past performance does not guarantee future results. The authors are not financial advisors and assume no liability for trading decisions.
Additional Warning: Using leverage or trading illiquid altcoins amplifies risk significantly. This strategy is designed for spot trading of established cryptocurrencies with deep liquidity.
Tags: Altcoin, Alt/BTC, DCA, Risk Metric, Dollar Cost Averaging, 3Commas, ETH, SOL, Crypto Rotation, Bitcoin Correlation, Automated Trading, Alt Season
Feel free to modify any sections to better match your style or add specific backtesting results you've observed! 🚀Claude is AI and can make mistakes. Please double-check responses. Sonnet 4.5
BTC DCA Risk Metric StrategyBTC DCA Risk Strategy - Automated Dollar Cost Averaging with 3Commas Integration
Overview
This strategy combines the proven Oakley Wood Risk Metric with an intelligent tiered Dollar Cost Averaging (DCA) system, designed to help traders systematically accumulate Bitcoin during periods of low risk and take profits during high-risk conditions.
Key Features
📊 Multi-Component Risk Assessment
4-Year SMA Deviation: Measures Bitcoin's distance from its long-term mean
20-Week MA Analysis: Tracks medium-term momentum shifts
50-Day/50-Week MA Ratio: Captures short-to-medium term trend strength
All metrics are normalized by time to account for Bitcoin's maturing market dynamics
💰 3-Tier DCA Buy System
Level 1 (Low Risk): Conservative entry with base allocation
Level 2 (Lower Risk): Increased allocation as opportunity improves
Level 3 (Extreme Low Risk): Maximum allocation during rare buying opportunities
Buys execute every bar while risk remains below thresholds, enabling true DCA accumulation
📈 Progressive Profit Taking
Sell Level 1: Take initial profits as risk increases
Sell Level 2: Scale out further positions during elevated risk
Sell Level 3: Final exit during extreme market conditions
Sell levels automatically reset when new buy signals occur, allowing flexible re-entry
🤖 3Commas Integration
Fully automated webhook alerts for Custom Signal Bots
JSON payloads formatted per 3Commas API specifications
Supports multiple exchanges (Binance, Coinbase, Kraken, Gemini, Bybit)
Configurable quote currency (USD, USDT, BUSD)
How It Works
The strategy calculates a composite risk metric (0-1 scale):
0.0-0.2: Extreme buying opportunity (green zone)
0.2-0.5: Favorable accumulation range (yellow zone)
0.5-0.8: Neutral to cautious territory (orange zone)
0.8-1.0+: High risk, profit-taking zone (red zone)
Buy Logic: As risk decreases, position sizes increase automatically. If risk drops from L1 to L3 threshold, the strategy combines all three tier allocations for maximum exposure.
Sell Logic: Sequential profit-taking ensures you capture gains progressively. The system won't advance to Sell L2 until L1 completes, preventing premature full exits.
Configuration
Risk Metric Parameters:
All calculations use Bitcoin price data (any BTC chart works)
Time-normalized formulas adapt to market maturity
No manual parameter tuning required
Buy Settings:
Set risk thresholds for each tier (default: 0.20, 0.10, 0.00)
Define dollar amounts per tier (default: $10, $15, $20)
Fully customizable to your risk tolerance and capital
Sell Settings:
Configure risk thresholds for profit-taking (default: 1.00, 1.50, 2.00)
Set percentage of position to sell at each level (default: 25%, 35%, 40%)
3Commas Setup:
Create a Custom Signal Bot in 3Commas
Copy Bot UUID and Secret Token into strategy inputs
Enable 3Commas Alerts checkbox
Create TradingView alert: Condition → "alert() function calls only", Webhook → api.3commas.io
Backtesting Results
Strengths:
Systematically buys dips without emotion
Averages down during extended bear markets
Captures explosive bull run profits through tiered exits
Pyramiding (1000 max orders) allows true DCA behavior
Considerations:
Requires sufficient capital for multiple buys during prolonged downtrends
Backtest on Daily timeframe for most reliable signals
Past performance does not guarantee future results
Visual Design
The indicator pane displays:
Color-coded risk metric line: Changes from white→red→orange→yellow→green as risk decreases
Background zones: Green (buy), yellow (hold), red (sell) areas
Dashed threshold lines: Clear visual markers for each buy/sell level
Entry/Exit labels: Green buy labels and orange/red sell labels mark all trades
Credits
Original Risk Metric: Oakley Wood
Strategy Development & 3Commas Integration: Claude AI (Anthropic)
Modifications: pommesUNDwurst
Disclaimer
This strategy is for educational and informational purposes only. Cryptocurrency trading carries substantial risk of loss. Always conduct your own research and never invest more than you can afford to lose. The authors are not financial advisors and assume no responsibility for trading decisions made using this tool.
Hash Ratings EngineHash Ratings Engine - Technical Consensus Strategy
A systematic trading strategy that harnesses TradingView's Technical Ratings to generate high-conviction entries with institutional-grade risk management.
What It Does
This strategy aggregates the consensus of 26+ technical indicators (RSI, MACD, Stochastics, multiple Moving Averages, etc.) into a single actionable signal. When enough indicators align bullish or bearish, the engine triggers an entry. Built-in trend filtering and ATR-based exits keep you on the right side of the market.
Key Features
Trend Filter - Only takes longs in uptrends, shorts in downtrends. This single filter typically improves results by 20-40% by avoiding counter-trend trades.
ATR-Based Risk Management - Stop loss and trailing stops adapt to current market volatility. Tight stops in calm markets, wider stops in volatile conditions.
Cooldown System - After a losing trade, the strategy waits before re-entering. This prevents the consecutive loss streaks that destroy accounts.
Clean Visuals - Fluorescent entry/exit signals with price level references. See exactly where you got in and out.
Settings Guide
Indicator Timeframe: Leave blank for current chart. Use higher timeframe for fewer, higher-quality signals.
Rating Source: "All" for balanced approach. "MAs" for trend-following. "Oscillators" for mean-reversion.
Entry Thresholds
Strong Signal Threshold: Higher = fewer trades but better conviction. Start at 0.5, test 0.4-0.6.
Risk Management
ATR Period: 12 is responsive, 14 is standard, 20+ is smoother.
Stop Loss: 2-3x ATR for tight stops, 3.5-4x for moderate, 5x+ for wide.
Trail Activation: How far price must move in profit before trailing begins.
Trail Offset: How closely the trail follows price.
Trend Filter
EMA Length: 150 works well on 4H charts. Use 100 for lower timeframes, 200 for daily.
Trade Timing
Cooldown: Keep enabled. 5 bars is a good starting point.
Best Practices
Start with default settings and backtest on your preferred instrument. Adjust the Strong Signal Threshold first - this has the biggest impact on trade frequency. Then tune the EMA length to match your timeframe. Finally, optimize the ATR multipliers for your risk tolerance.
Works on any liquid market - crypto, forex, stocks, futures. Higher timeframes (4H, Daily) tend to produce cleaner signals than lower timeframes.
Disclaimer
Past performance does not guarantee future results. Always backtest thoroughly and use proper position sizing. This strategy is for educational purposes - trade at your own risk.
MA Strategy: Dual Entry FilterConfigurable MA Dual-Filter Strategy
This strategy is an enhanced and highly configurable Moving Average (MA) Crossover system designed to mitigate false signals and align trades with the prevailing market trend. It is built to offer traders granular control over entry criteria, elevating it beyond basic, built-in MA crossover indicators.
Originality & Key Features
The script's originality and utility lie in the combination of its two primary, optional filtering mechanics:
Dual Entry Mode (Key Filter): Users can choose between two distinct methods for trade entry:
Crossover (Classic): Immediate entry when the price crosses the main MA.
Full Candle Confirmation (Unique Feature): This mode requires the entire candle body (open, high, low, and close) to be completely above or below the main MA after a crossover event to confirm the signal before entry. This strict confirmation helps to filter out weak crossovers, reducing whipsaws in choppy markets.
Optional Trend Filter: A second, slower MA (Trend Filter MA) can be activated. Trades are only permitted when the faster main MA is aligned with the slower Trend MA (i.e., long only if main MA > Trend MA), ensuring trades are executed with the established higher-timeframe direction.
How to Use the Strategy
The strategy logic is built on simple MA principles but utilizes Pine Script's switch function to allow users to select from six different MA types for both the main signal and the trend filter: SMA, EMA, WMA, HMA, VWMA, and RMA.
Core Logic:
Signal: A cross of the price over the Main MA (filtered by the chosen Entry Mode).
Directional Filter: The Trend Filter must confirm the direction (if enabled).
Exit: Trades are exited on the opposite price crossover of the Main MA.
Customizable Settings Include:
Main MA Type & Length (Default: 40 EMA): The primary signal generator.
Trend Filter MA Type & Length (Default: 70 EMA): The optional, slower trend bias.
Entry Mode: Switch between Crossover or Full Candle Confirmation.
Strategy Results and High-Risk Disclaimer
The default setting for trade size is set to 40% of equity for backtesting demonstration purposes only. This high value is used to generate a large and diverse sample size of trades for historical review on the chart.
This 40% value is NOT a recommended setting for live trading. Per TradingView guidelines, traders are strongly advised to change this input to a sustainable risk level, typically 5% to 10% of equity per trade. Past performance is not a guarantee of future results.
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.
ChronoPulse MS-MACD Resonance StrategyChronoPulse MS-MACD Resonance Strategy
A systematic trading strategy that combines higher-timeframe market structure analysis with dual MACD momentum confirmation, ATR-based risk management, and real-time quality assurance monitoring.
Core Principles
The strategy operates on the principle of multi-timeframe confluence, requiring agreement between:
Market structure breaks (CHOCH/BOS) on a higher timeframe
Dual MACD momentum confirmation (classic and crypto-tuned profiles)
Trend alignment via directional EMAs
Volatility and volume filters
Quality score composite threshold
Strategy Components
Market Structure Engine : Detects Break of Structure (BOS) and Change of Character (CHOCH) events using confirmed pivots on a configurable higher timeframe. Default structure timeframe is 240 minutes (4H).
Dual MACD Fusion : Requires agreement between two MACD configurations:
Classic MACD: 12/26/9 (default)
Fusion MACD: 8/21/5 (default, optimized for crypto volatility)
Both must agree on direction before trade execution. This can be disabled to use single MACD confirmation.
Trend Alignment : Uses two EMAs for directional bias:
Directional EMA: 55 periods (default)
Execution Trend Guide: 34 periods (default)
Both must align with trade direction.
ATR Risk Management : All risk parameters are expressed in ATR multiples:
Stop Loss: 1.5 × ATR (default)
Take Profit: 3.0 × ATR (default)
Trail Activation: 1.0 × ATR profit required (default)
Trail Distance: 1.5 × ATR behind price (default)
Volume Surge Filter : Optional gate requiring current volume to exceed a multiple of the volume SMA. Default threshold is 1.4× the 20-period volume SMA.
Quality Score Gate : Composite score (0-1) combining:
Structure alignment (0.0-1.0)
Momentum strength (0.0-1.0)
Trend alignment (0.0-1.0)
ATR volatility score (0.0-1.0)
Volume intensity (0.0-1.0)
Default threshold: 0.62. Trades only execute when quality score exceeds this threshold.
Execution Discipline : Trade budgeting system:
Maximum trades per session: 6 (default)
Cooldown bars between entries: 5 (default)
Quality Assurance Console : Real-time monitoring panel displaying:
Structure status (pass/fail)
Momentum confirmation (pass/fail)
Volatility readiness (pass/fail)
Quality score (pass/fail)
Discipline compliance (pass/fail)
Performance metrics (win rate, profit factor)
Net PnL
Certification requires: Win Rate ≥ 40%, Profit Factor ≥ 1.4, Minimum 25 closed trades, and positive net profit.
Integrity Suite : Optional validation panel that audits:
Configuration sanity checks
ATR data readiness
EMA hierarchy validity
Performance realism checks
Strategy Settings
strategy(
title="ChronoPulse MS-MACD Resonance Strategy",
shorttitle="ChronPulse",
overlay=true,
max_labels_count=500,
max_lines_count=500,
initial_capital=100000,
currency=currency.USD,
pyramiding=0,
commission_type=strategy.commission.percent,
commission_value=0.015,
slippage=2,
default_qty_type=strategy.percent_of_equity,
default_qty_value=2.0,
calc_on_order_fills=true,
calc_on_every_tick=true,
process_orders_on_close=true
)
Key Input Parameters
Structure Timeframe : 240 (4H) - Higher timeframe for structure analysis
Structure Pivot Left/Right : 3/3 - Pivot confirmation periods
Structure Break Buffer : 0.15% - Buffer for structure break confirmation
MACD Fast/Slow/Signal : 12/26/9 - Classic MACD parameters
Fusion MACD Fast/Slow/Signal : 8/21/5 - Crypto-tuned MACD parameters
Directional EMA Length : 55 - Primary trend filter
Execution Trend Guide : 34 - Secondary trend filter
ATR Length : 14 - ATR calculation period
ATR Stop Multiplier : 1.5 - Stop loss in ATR units
ATR Target Multiplier : 3.0 - Take profit in ATR units
Trail Activation : 1.0 ATR - Profit required before trailing
Trail Distance : 1.5 ATR - Distance behind price
Volume Threshold : 1.4× - Volume surge multiplier
Quality Threshold : 0.62 - Minimum quality score (0-1)
Max Trades Per Session : 6 - Daily trade limit
Cooldown Bars : 5 - Bars between entries
Win-Rate Target : 40% - Minimum for QA certification
Profit Factor Target : 1.4 - Minimum for QA certification
Minimum Trades for QA : 25 - Required closed trades
Signal Generation Logic
A trade signal is generated when ALL of the following conditions are met:
Higher timeframe structure shows bullish (CHOCH/BOS) or bearish structure break
Both MACD profiles agree on direction (if fusion enabled)
Price is above both EMAs for longs (below for shorts)
ATR data is ready and above minimum threshold
Volume exceeds threshold × SMA (if volume gate enabled)
Quality score ≥ quality threshold
Trade budget available (under max trades per day)
Cooldown period satisfied
Risk Management
Stop loss and take profit are set immediately on entry
Trailing stop activates after 1.0 ATR of profit
Trailing stop maintains 1.5 ATR distance behind highest profit point
Position sizing uses 2% of equity per trade (default)
No pyramiding (single position per direction)
Limitations and Considerations
The strategy requires sufficient historical data for higher timeframe structure analysis
Quality gate may filter out many potential trades, reducing trade frequency
Performance metrics are based on historical backtesting and do not guarantee future results
Commission and slippage assumptions (0.015% + 2 ticks) may vary by broker
The strategy is optimized for trending markets with clear structure breaks
Choppy or ranging markets may produce false signals
Crypto markets may require different parameter tuning than traditional assets
Optimization Notes
The strategy includes several parameters that can be tuned for different market conditions:
Quality Threshold : Lower values (0.50-0.60) allow more trades but may reduce average quality. Higher values (0.70+) are more selective but may miss opportunities.
Structure Timeframe : Use 240 (4H) for intraday trading, Daily for swing trading, Weekly for position trading
Volume Gate : Disable for low-liquidity pairs or when volume data is unreliable
Dual MACD Fusion : Disable for mean-reverting markets where single MACD may be more responsive
Trade Discipline : Adjust max trades and cooldown based on your risk tolerance and market volatility
Non-Repainting Guarantee
All higher timeframe data requests use lookahead=barmerge.lookahead_off to prevent repainting. Pivot detection waits for full confirmation before registering structure breaks. All visual elements (tables, labels) update only on closed bars.
Alerts
Three alert conditions are available:
ChronoPulse Long Setup : Fires when all long entry conditions are met
ChronoPulse Short Setup : Fires when all short entry conditions are met
ChronoPulse QA Certification : Fires when Quality Assurance console reaches CERTIFIED status
Configure alerts with "Once Per Bar Close" delivery to match the non-repainting design.
Visual Elements
Structure Labels : CHOCH↑, CHOCH↓, BOS↑, BOS↓ markers on structure breaks
Directional EMA : Orange line showing trend bias
Trailing Stop Lines : Green (long) and red (short) trailing stop levels
Dashboard Panel : Real-time status display (structure, MACD, ATR, quality, PnL)
QA Console : Quality assurance monitoring panel
Integrity Suite Panel : Optional validation status display
Recommended Usage
Forward test with paper trading before live deployment
Monitor the QA console until it reaches CERTIFIED status
Adjust parameters based on your specific market and timeframe
Respect the trade discipline limits to avoid over-trading
Review quality scores and adjust threshold if needed
Use appropriate commission and slippage settings for your broker
Technical Implementation
The strategy uses Pine Script v6 with the following key features:
Multi-timeframe data requests with lookahead protection
Confirmed pivot detection for structure analysis
Dynamic trailing stop management
Real-time quality score calculation
Trade budgeting and cooldown enforcement
Comprehensive dashboard and monitoring panels
All source code is open and available for review and modification.
Disclaimer
This script is for educational and informational purposes only. It is not intended as financial, investment, or trading advice. Past performance does not guarantee future results. Trading involves substantial risk of loss and is not suitable for all investors. Always conduct your own research and consult with a qualified financial advisor before making any trading decisions. The author and TradingView are not responsible for any losses incurred from using this strategy.
ATR ZigZag BreakoutATR ZigZag Breakout
This strategy uses my ATR ZigZag indicator (powered by the ZigZagCore library) to scalp breakouts at volatility-filtered highs and lows.
Everyone knows stops cluster around clear swing highs and lows. Breakout traders often pile in there, too. These levels are predictable areas where aggressive orders hit the tape. The idea here is simple:
→ Let ATR ZigZag define clean, volatility-filtered pivots
→ Arm a stop market order at those pivots
→ Join the breakout when the crowd hits the level
The key to greater success in this simple strategy lies in the ZigZag. Because the pivots are filtered by ATR instead of fixed bar counts or fractals, the levels tend to be more meaningful and less noisy.
This approach is especially suited for intraday trading on volatile instruments (e.g., NQ, GC, liquid crypto pairs).
How It Works
1. Pivot detection
The ATR ZigZag uses an ATR-based threshold to confirm swing highs and lows. Only when price has moved far enough in the opposite direction does a pivot become “official.”
2. Candidate breakout level
When a new swing direction is detected and the most recent high/low has not yet been broken in the current leg, the strategy arms a stop market order at that pivot.
• Long candidate → most recent swing high
• Short candidate → most recent swing low
These “candidate trades” are shown as dotted lines.
3. Entry, SL, and TP
If price breaks through the level, the stop order is filled and a bracket is placed:
• Stop loss = ATR × SL multiplier
• Take profit = SL distance × RR multiplier
Once a level has traded, it is not reused in the same swing leg.
4. Cancel & rotate
If the market reverses and forms a new swing in the opposite direction before the level is hit, the pending order is cancelled and a new candidate is considered in the new direction.
Additional Features
• Optional session filter for backtesting specific trading hours
Reversal WaveThis is the type of quantitative system that can get you hated on investment forums, now that the Random Walk Theory is back in fashion. The strategy has simple price action rules, zero over-optimization, and is validated by a historical record of nearly a century on both Gold and the S&P 500 index.
Recommended Markets
SPX (Weekly, Monthly)
SPY (Monthly)
Tesla (Weekly)
XAUUSD (Weekly, Monthly)
NVDA (Weekly, Monthly)
Meta (Weekly, Monthly)
GOOG (Weekly, Monthly)
MSFT (Weekly, Monthly)
AAPL (Weekly, Monthly)
System Rules and Parameters
Total capital: $10,000
We will use 10% of the total capital per trade
Commissions will be 0.1% per trade
Condition 1: Previous Bearish Candle (isPrevBearish) (the closing price was lower than the opening price).
Condition 2: Midpoint of the Body The script calculates the exact midpoint of the body of that previous bearish candle.
• Formula: (Previous Open + Previous Close) / 2.
Condition 3: 50% Recovery (longCondition) The current candle must be bullish (green) and, most importantly, its closing price must be above the midpoint calculated in the previous step.
Once these parameters are met, the system executes a long entry and calculates the exit parameters:
Stop Loss (SL): Placed at the low of the candle that generated the entry signal.
Take Profit (TP): Calculated by projecting the risk distance upward.
• Calculation: Entry Price + (Risk * 1).
Risk:Reward Ratio of 1:1.
About the Profit Factor
In my experience, TradingView calculates profits and losses based on the percentage of movement, which can cause returns to not match expectations. This doesn’t significantly affect trending systems, but it can impact systems with a high win rate and a well-defined risk-reward ratio. It only takes one large entry candle that triggers the SL to translate into a major drop in performance.
For example, you might see a system with a 60% win rate and a 1:1 risk-reward ratio generating losses, even though commissions are under control relative to the number of trades.
My recommendation is to manually calculate the performance of systems with a well-defined risk-reward ratio, assuming you will trade using a fixed amount per trade and limit losses to a fixed percentage.
Remember that, even if candles are larger or smaller in size, we can maintain a fixed loss percentage by using leverage (in cases of low volatility) or reducing the capital at risk (when volatility is high).
Implementing leverage or capital reduction based on volatility is something I haven’t been able to incorporate into the code, but it would undoubtedly improve the system’s performance dramatically, as it would fix a consistent loss percentage per trade, preventing losses from fluctuating with volatility swings.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to exit or SL
And if volatility is high and exceeds the fixed percentage we want to expose per trade (if SL is hit), we could reduce the position size.
For example, imagine we only want to risk 15% per SL on Tesla, where volatility is high and would cause a 23.57% loss. In this case, we subtract 23.57% from 15% (the loss percentage we’re willing to accept per trade), then subtract the result from our usual position size.
23.57% - 15% = 8.57%
Suppose I use $200 per trade.
To calculate 8.57% of $200, simply multiply 200 by 8.57/100. This simple calculation shows that 8.57% equals about $17.14 of the $200. Then subtract that value from $200:
$200 - $17.14 = $182.86
In summary, if we reduced the position size to $182.86 (from the usual $200, where we’re willing to lose 15%), no matter whether Tesla moves up or down 23.57%, we would still only gain or lose 15% of the $200, thus respecting our risk management.
Final Notes
The code is extremely simple, and every step of its development is detailed within it.
If you liked this strategy, which complements very well with others I’ve already published, stay tuned. Best regards.
MACD Zero-Line Strategy (Long Only)Strategy to Open order when Mac-D Signal Cross up 0, Sell when it cross down 0
Katik EMA BUY SELLThis strategy uses EMA 9, EMA 20, and EMA 200 to generate Buy and Sell signals.
BUY Conditions
EMA 9 crosses above EMA 20
Stoploss: Recent Swing Low
Target: EMA 9 touches or crosses EMA 200
SELL Conditions
EMA 9 crosses below EMA 20
Stoploss: Recent Swing High
Target: EMA 9 touches or crosses EMA 200
Features
Automatic Long & Short entries
Dynamic swing-based stoploss
Clear EMA plots with line width 3
Works on all timeframes
Profitable Pair Correlation Divergence Scanner v6This strategy identifies divergence opportunities between two correlated assets using a combination of Z-Score spread analysis, trend confirmation, RSI & MACD momentum checks, correlation filters, and ATR-based stop-loss/take-profit management. It’s optimized for positive P&L and realistic trade execution.
Key Features:
Pair Divergence Detection:
Measures deviation between returns of two assets and identifies overbought/oversold spread conditions using Z-Score.
Trend Alignment:
Trades only in the direction of the primary asset’s trend using a fast EMA vs slow EMA filter.
Momentum Confirmation:
Confirms trades with RSI and MACD to reduce false signals.
Correlation Filter:
Ensures the pair is strongly correlated before taking trades, avoiding noisy signals.
Risk Management:
Dynamic ATR-based stop-loss and take-profit ensures proper reward-to-risk ratio.
Exit Conditions:
Automatically closes positions when Z-Score normalizes, or ATR-based exits are hit.
How It Works:
Calculate Returns:
Computes returns for both assets over the selected timeframe.
Z-Score Spread:
Calculates the spread between returns and normalizes it using moving average and standard deviation.
Trend Filter:
Only takes long trades if the fast EMA is above the slow EMA, and short trades if the fast EMA is below the slow EMA.
Momentum Confirmation:
Confirms trade direction with RSI (>50 for longs, <50 for shorts) and MACD alignment.
Correlation Check:
Ensures the pair’s recent correlation is strong enough to validate divergence signals.
Trade Execution:
Opens positions when Z-Score crosses thresholds and all conditions align. Positions close when Z-Score normalizes or ATR-based SL/TP is hit.
Plot Explanation:
Z-Score: Blue line shows divergence magnitude.
Entry Levels: Red/Green lines mark long/short thresholds.
Exit Zone: Gray lines show normalization zone.
EMA Trend Lines: Purple (fast), Orange (slow) for trend alignment.
Correlation: Teal overlay shows current correlation strength.
Usage Tips:
Use highly correlated pairs for best results (e.g., EURUSD/GBPUSD).
Run on higher timeframe charts (1h or 4h) to reduce noise.
Adjust ATR multiplier based on volatility to avoid premature stops.
Combine with alerts for automated notifications or webhook execution.
Conclusion:
The Profitable Pair Correlation Divergence Scanner v6 is designed for traders who want systematic, low-risk, positive P&L trading opportunities with minimal manual monitoring. By combining trend alignment, momentum confirmation, correlation filters, and dynamic exits, it reduces false signals and improves execution reliability.
Run it on TradingView and watch how it captures divergence opportunities while maintaining positive P&L across trades.
specific breakout FiFTOStrategy Description: 10:14 Breakout Only
Overview This is a time-based intraday trading strategy designed to capture momentum bursts that occur specifically after the 10:14 AM candle closes. It operates on the logic that if price breaks the high of this specific candle within a short window, a trend continuation is likely.
Core Logic & Rules
The Setup Candle (10:14 AM)
The strategy waits specifically for the minute candle at 10:14 to complete.
Once this candle closes, the strategy records its High price.
Defining the Entry Level
It calculates a trigger price by taking the 10:14 High and adding a user-defined Buffer (e.g., +1 point).
Formula: Entry Level = 10:14 High + Buffer
The "Active Window" (Expiry)
The trade setup does not remain open all day. It has a strict time limit.
By default, the setup is valid from 10:15 to 10:20.
If the price does not break the Entry Level by the expiry time (default 10:20), the setup is cancelled and no trade is taken for the day.
Entry Trigger
If a candle closes above the Entry Level while the window is open, a Long (Buy) position is opened immediately.
Exits (Risk Management)
Stop Loss: A fixed number of points below the entry price.
Target: A fixed number of points above the entry price.
Visual & Automation Features
Visual Boxes: Upon entry, the strategy draws a "Long Position" style visual on the chart. A green box highlights the profit zone, and a red box highlights the loss zone. These boxes extend automatically until the trade closes.
JSON Alerts: The strategy is pre-configured to send data-rich alerts for automation (e.g., Telegram bots).
Entry Alert: Includes Symbol, Entry Price, SL, and TP.
Exit Alerts: Specific messages for "Target Hit" or "SL Hit".
Summary of User Inputs
Entry Buffer: Extra points added to the high to filter false breaks.
Fixed Stop Loss: Risk per trade in points.
Fixed Target: Reward per trade in points.
Expiry Minute: The minute (10:xx) at which the setup becomes invalid if not triggered.
BTC Dynamic Volatility Trend Backtested from 2017 to present, this strategy has delivered a staggering 7100%+ cumulative return. It doesn't just track the market; it dominates it. By capturing major trends and strictly limiting drawdowns, it has significantly outperformed the standard 'Buy & Hold' BTC strategy, proving its ability to generate massive alpha across multiple bull and bear cycles.
自 2017 年至今，本策略实现了惊人的 7100%+ 累计收益率。它不仅仅是跟随市场，更是超越了市场。通过精准捕捉主升浪并严格控制回撤，该策略在穿越多轮牛熊周期后，大幅度跑赢了比特币‘买入持有’（Buy & Hold）的基准收益，展现了极致的阿尔法（Alpha）捕捉能力。"
Introduction ：Simplicity is the ultimate sophistication. This strategy is designed specifically for Bitcoin (BTC), capturing its unique characteristics: high volatility, frequent fakeouts, and massive trend persistence. It abandons complex indicators in favor of a robust logic: "Follow the Trend, Filter the Noise, Let Profits Run."
Core Logic
Trend Filter (Fibonacci EMA 144): We use the 144-period Exponential Moving Average as the baseline. Longs are only taken above this line, and shorts only below. This keeps you on the right side of the major trend.
Volatility Breakout (Donchian Channel 20): Entries are triggered only when price breaks the 20-day high (for longs) or low (for shorts). This confirms momentum and avoids trading in chop.
Dynamic Risk Management (ATR Chandelier Exit):
Instead of fixed % stops, we use Average True Range (ATR) to calculate stop losses.
The Ratchet Mechanism: The stop loss moves up with the price but never moves down (for longs). This locks in profits automatically as the trend develops and exits immediately when volatility turns against you.
Why Use This Strategy?
Zero Repainting: All signals are confirmed.
No Curve Fitting: Uses classic parameters (144, 20) that have worked for decades.
Mental Peace: The strategy handles the exit. You don't need to guess where to sell. It holds through minor corrections and exits only when the trend truly reverses.
Settings
Leverage %: Adjust your position size based on equity (default 100% = 1x).
Timeframe: Recommended for 4H charts.
中文版 (Chinese Version)
简介 ：大道至简。本策略专为 比特币 (BTC) 设计，针对其高波动、假突破多但趋势爆发力强的特点，摒弃了复杂的过度拟合指标，回归交易本质：“顺大势，滤噪音，截断亏损，让利润奔跑”。
核心逻辑
趋势过滤器 (斐波那契 EMA 144)： 使用 144 周期指数移动平均线作为多空分水岭。价格在均线之上只做多，之下只做空。这能有效过滤掉大部分震荡市的噪音。
波动率突破 (唐奇安通道 20)： 只有当价格突破过去 20 根 K 线的最高价（做多）或最低价（做空）时才进场。这确保了我们只在趋势确立的瞬间入场。
动态风控 (ATR 吊灯止损)：
拒绝固定点数止损，使用 ATR（平均真实波幅）根据市场热度动态计算安全距离。
棘轮机制： 止损线会跟随价格上涨而上移，但绝不会下移（做多时）。这实现了自动化的“利润锁定”，既能扛住正常的波动回调，又能在大势反转时果断离场。
策略优势
绝不重绘： 所有信号均为收盘确认或实时触价。
拒绝拟合： 使用经过数十年市场验证的经典参数组合。
心态管理： 策略全自动管理出场。你不需要纠结何时止盈，它会帮你吃到完整的鱼身，直到趋势结束。
使用建议
资金管理： 可通过参数调整仓位占比（默认 100% = 1倍杠杆）。
推荐周期： 建议在4小时 图表上运行效果最佳。
US Market Long Horizon Momentum Summary in one paragraph
US Market Long Horizon Momentum is a trend following strategy for US index ETFs and futures built around a single eighteen month time series momentum measure. It helps you stay long during persistent bull regimes and step aside or flip short when long term momentum turns negative.
Scope and intent
• Markets. Large cap US equity indices, liquid US index ETFs, index futures
• Timeframes. 4h/ Daily charts
• Default demo used in the publication. SPY on 4h timeframe chart
• Purpose. Provide a minimal long bias index timing model that can reduce deep drawdowns and capture major cycles without parameter mining
• Limits. This is a strategy. Orders are simulated on standard candles only
Originality and usefulness
• Unique concept or fusion. One unscaled multiple month log return of an external benchmark symbol drives all entries and exits, with optional volatility targeting as a single risk control switch.
• Failure mode addressed. Fully passive buy and hold ignores the sign of long horizon momentum and can sit through multi year drawdowns. This script offers a way to step down risk in prolonged negative momentum without chasing short term noise.
• Testability. All parameters are visible in Inputs and the momentum series is plotted so users can verify every regime change in the Tester and on price history.
• Portable yardstick. The log return over a fixed window is a unit that can be applied to any liquid symbol with daily data.
Method overview in plain language
The method looks at how far the benchmark symbol has moved in log return terms over an eighteen month window in our example. If that long horizon return is positive the strategy allows a long stance on the traded symbol. If it is negative and shorts are enabled the strategy can flip short, otherwise it goes flat. There is an optional realised volatility estimate on the traded symbol that can scale position size toward a target annual volatility, but in the default configuration the model uses unit leverage and only the sign of momentum matters.
Base measures
Return basis. The core yardstick is the natural log of close divided by the close eighteen months ago on the benchmark symbol. Daily log returns of the traded symbol feed the realised volatility estimate when volatility targeting is enabled.
Components
• Component one Momentum eighteen months. Log of benchmark close divided by its close mom_lookback bars ago. Its sign defines the trend regime. No extra smoothing is applied beyond the long window itself.
• Component two Realised volatility optional. Standard deviation of daily log returns on the traded symbol over sixty three days. Annualised by the square root of 252. Used only when volatility targeting is enabled.
• Optional component Volatility targeting. Converts target annual volatility and realised volatility into a leverage factor clipped by a maximum leverage setting.
Fusion rule
The model uses a simple gate. First compute the sign of eighteen month log momentum on the benchmark symbol. Optionally compute leverage from volatility. The sign decides whether the strategy wants to be long, short, or flat. Leverage only rescales position size when enabled and does not change direction.
Signal rule
• Long suggestion. When eighteen month log momentum on the benchmark symbol is greater than zero, the strategy wants to be long.
• Short suggestion. When that log momentum is less than zero and shorts are allowed, the strategy wants to be short. If shorts are disabled it stays flat instead.
• Wait state. When the log momentum is exactly zero or history is not long enough the strategy stays flat.
• In position. In practice the strategy sits IN LONG while the sign stays positive and flips to IN SHORT or flat only when the sign changes.
Inputs with guidance
Setup
• Momentum Lookback (months). Controls the horizon of the log return on the benchmark symbol. Typical range 6 to 24 months. Raising it makes the model slower and more selective. Lowering it makes it more reactive and sensitive to medium term noise.
• Symbol. External symbol used for the momentum calculation, SPY by default. Changing it lets you time other indices or run signals from a benchmark while trading a correlated instrument.
Logic
• Allow Shorts. When true the strategy will open short positions during negative momentum regimes. When false it will stay flat whenever momentum is negative. Practical setting is tied to whether you use a margin account or an ETF that supports shorting.
Internal risk parameters (not exposed as inputs in this version) are:
• Target Vol (annual). Target annual volatility for volatility targeting, default 0.2.
• Vol Lookback (days). Window for realised volatility, default 63 trading days.
• Max Leverage. Cap on leverage when volatility targeting is enabled, default 2.
Usage recipes
Swing continuation
• Signal timeframe. Use the daily chart.
• Benchmark symbol. Leave at SPY for US equity index exposure.
• Momentum lookback. Eighteen months as a default, with twelve months as an alternative preset for a faster swing bias.
Properties visible in this publication
• Initial capital. 100000
• Base currency. USD
• Default order size method. 5% of the total capital in this example
• Pyramiding. 0
• Commission. 0.03 percent
• Slippage. 3 ticks
• Process orders on close. On
• Bar magnifier. Off
• Recalculate after order is filled. Off
• Calc on every tick. Off
• All request.security calls use lookahead = barmerge.lookahead_off
Realism and responsible publication
The strategy is for education and research only. It does not claim any guaranteed edge or future performance. All results in Strategy Tester are hypothetical and depend on the data vendor, costs, and slippage assumptions. Intrabar motion is not modeled inside daily bars so extreme moves and gaps can lead to fills that differ from live trading. The logic is built for standard candles and should not be used on synthetic chart types for execution decisions.
Performance is sensitive to regime structure in the US equity market, which may change over time. The strategy does not protect against single day crash risk inside bars and does not model gap risk explicitly. Past behavior of SPY and the momentum effect does not guarantee future persistence.
Honest limitations and failure modes
• Long sideways regimes with small net change over eighteen months can lead to whipsaw around the zero line.
• Very sharp V shaped reversals after deep declines will often be missed because the model waits for momentum to turn positive again.
• The sample size in a full SPY history is small because regime changes are infrequent, so any test must be interpreted as indicative rather than statistically precise.
• The model is highly dependent on the chosen lookback. Users should test nearby values and validate that behavior is qualitatively stable.
Legal
Education and research only. Not investment advice. You are responsible for your own decisions. Always test on historical data and in simulation with realistic costs before any live use.
Gold Mastermind Pro v6EMA50 / EMA200 trend (UP / DOWN / FLAT)
VWAP + ATR + RSI filters for entries
ATR-based stop & 2R target
Risk-based position sizing with max 5 contracts
Cooldown in bars after each entry
Long arrows = baby blue, Short arrows = bright orange
Simple dashboard label showing trend, qty, stop & target
Indian Scalper 2025 – PSAR + SMA50 + RSI≤50 + High Volume (75%)Best 1-min / 2-min scalping strategy for NIFTY, BANKNIFTY, FINNIFTY & liquid stocks in 2025
✓ PSAR flip + SMA-50 trend filter
✓ RSI ≤50 (avoids chasing)
✓ Only high-volume candles (bright colour)
✓ Loud mobile alerts with price & SL
✓ 1:2+ RR with PSAR trailing
Works like magic 9:15–11:30 AM and 2–3:20 PM
Made with love for the Indian trading community ♥
Momentum Reversal / Dip Buyer [Score Based]Strategy Overview
Momentum Reversal / Dip Buyer is a quantitative reversal engine designed to fade stretched moves and buy dips / sell rallies when multiple momentum and context factors line up. It’s built for liquid instruments especially for ticker CME_MINI:ES1! and works best on intraday timeframes like the 5-minute or 1-minute chart.
Core Logic
This strategy builds a composite Momentum Score by combining:
Price Location: Relative to 100 SMA, 1000 EMA, and VWAP (trend / regime filter).
RSI: Overbought/oversold and mid-zone strength.
VWMO (Volume-Weighted Momentum): Direction and strength of volume-weighted price drift.
ADX: Trend strength filter (high vs low trend environment).
Full Stoch (%K): Short-term exhaustion and mean-reversion context.
CCI: Overbought/oversold turns (key trigger).
MFI: Volume-confirmed buying/selling pressure.
ATR Regime: High vs low volatility environment.
Cumulative Delta: Whether net aggressor flow is rising or falling.
From this, a single Momentum Score is computed each bar:
Longs: Taken when the score is depressed (scoreLow) and CCI crosses up from oversold.
Shorts: Taken when the score is elevated (scoreHigh) and CCI crosses down from overbought.
Risk Management & Trade Logic
Max Daily Trades: Hard cap on entries per day.
Hard Stop: Fixed % stop based on entry price.
Profit Target: Target ATR Multiplier × main ATR from entry.
Breakeven Logic: Optional; moves stop to breakeven (plus optional offset) after price moves a configurable multiple of the main ATR in your favor.
Trailing Stop (Separate ATR): Optional; uses its own ATR length and ATR-based trigger and distance. This lets you run slower ATR for targets while using a tighter, more reactive ATR for the trail.
Session Control
Trading Window: Optional session filter (e.g., 09:30–16:00). Entries are only allowed inside the defined window.
Force Flat at Session End: Option to automatically close all open positions when the session ends.
Visuals
The script plots entry arrows and a compact dashboard displaying: current Momentum Score, daily trade usage, and CCI status.
Disclaimer:
This script is for educational and research purposes only and is not financial advice. Past performance does not guarantee future results. Always forward-test and adjust parameters to your own risk tolerance and market.
Shoutout and all credit goes to AuclairsCapital for building the base foundation of this strategy on ThinkScript
Ashok 07 Dec 25 updated scriptTried to fix the bugs in previous script. Even now improvements are needed, but for now it looks reasonably profiting.
CPR + EMA(20/50/200) Strategy (5m) - NIFTY styleindicator best suited for nifty for 5 minute time frame.
Inyerneck Quiet Bottom Hunter v36 — Last Sorta-Working VersionQuiet Bottom Hunter v36 — Accurate Description (the sorta-working version that fires signals)
Overview
A mean-reversion bottom-hunting strategy for small-cap stocks (<$2B market cap). Designed to catch slow-bleed stocks that quietly bottom out and rebound 20–60%+. Good for beginners because signals are infrequent and the setup is easy to understand.
Timeframe
Daily (D) — best results on 1-day charts. Works on weekly too, but signals are rarer.
Triggers / Conditions (all must be true at bar close)
Drop from high ≥ 25% from the highest high in the last 100 bars (previous bars only — no repainting)
Volume ≤ 80% of the 50-day average (quiet accumulation, no panic selling left)
RSI(14) ≤ 38 (oversold territory)
Green/flat streak ≥ 2 consecutive days where close ≥ open (shows sellers are exhausted)
When all four line up → tiny green “QB” triangle below the bar
Firing Frequency
1–4 signals per month on an average small-cap stock (depends on market conditions). Some months zero, some months a handful. Not spammy, but not ultra-rare either.
Usage Parameters
Position size: 10% of equity per trade (default — change to 5–20% depending on risk tolerance)
Profit target: 40%
Stop loss: 12%
Hold time: usually 2–8 weeks
Best on low-float, high-volatility small caps (TLRY, SNDL, MVIS, SOUN, INHD, etc.)
Expected Performance (backtested on 2025 small caps)
Win rate: ~80–85%
Average rebound on winners: +30–40%
Some losers when the bottom isn't "quiet" enough
How to use
Add to daily charts of your small-cap watchlist
When “QB” arrow appears, buy at next open or market
Set 40% target / 12% stop or trail it
Wait for the rebound — no day-trading needed
