Trend & Strength Detector TSDTrend Strength Detector (TSD)
*Objective Trend Quality Measurement for Educational Market Analysis*
Note: This mathematical framework is a proprietary quantitative model developed by Ario Pinelab, inspired by classical EMA, ADX, RSI and MACD principles, yet not documented in any public technical or academic publication.
## 🎯 Purpose & Design Philosophy
The ** Trend Strength Detector- TSD ** is an educational research tool that provides **quantitative measurement of trend quality** through two independent scoring systems (0-100 scale). It answers the analytical question: *"How strong and aligned is the current market trend environment?"*
This indicator is designed with a **modular, complementary approach** to work alongside various analysis methodologies, particularly pattern-based recognition systems.
## 🔗 Complementary Research Framework
### Designed to Work With Pattern Detection Systems
This indicator provides **environmental context measurement** that complements qualitative pattern recognition tools. It works particularly well alongside systems like:
- **RMBS Smart Detector - Multi-Factor Momentum System**
- Traditional chart pattern analyzers
- Any momentum-based pattern identification tools
🔍 **To find RMBS Smart Detector:**
- Search in TradingView Indicators Library: `" RMBS Smart Detector - Multi-Factor Momentum System"`
- Look for: *Multi-Factor Momentum System*
- By author: ` `
### Why This Complementary Approach?
**Trend Quality Measurement** (TSD - this tool) provides:
- ✅ Structural trend alignment (0-100 score)
- ✅ Momentum intensity levels (0-100 score)
- ✅ Environment classification (Strong/Moderate/Weak)
- 📌 **Answers:** *"HOW STRONG is the underlying trend environment?"*
### Educational Research Value
When used together in a research context, these tools enable systematic study of questions like:
- How do reversal patterns behave when Strength Score is above 70 vs below 30?
- Do continuation patterns in weakening environments (declining scores) show different characteristics?
- What is the correlation between high Alignment Scores and pattern "success rates"?
- Can environment classification help identify genuine trend initiation vs false starts?
⚠️ **Important Note:** Both tools are **independent and work standalone**. TSD provides value whether used alone or with other analysis methods. The relationship with RMBS (or any pattern tool) is **complementary for research purposes**, not dependent.
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###Mathematical Foundation
##TSA Formula: scoring method developed by Ario
-Trend Model (0 – 100)
TAS = EMA Alignment (0–40) + Price Position (0–30) + Trend Consistency (0–30)
EMA Alignment checks EMA_fast vs EMA_slow vs EMA_trend structure.
Price Position evaluates if Close is above/below all EMAs.
Consistency = 3 × max(bullish,bearish bars within 10 candles).
-Strength Model (0 – 100)
Strength = ADX (0–50) + EMA Slope (0–25) + RSI (0–15) + MACD (0–10)
ADX measures trend energy; Slope shows EMA momentum %;
RSI assesses zone positioning; MACD confirms directional agreement.
Note: This formula represents a proprietary quantitative model by Ario_Pinelab, inspired by classical technical concepts but not published in any external reference.________________________________________
📊 Environment Classification
Based on Total Strength Score:
🟢 Strong Environment: Score ≥ 60
→ Well-defined momentum, clear directional bias
🟡 Moderate Environment: 40 ≤ Score < 60
→ Mixed signals, transitional conditions
🔴 Weak Environment: Score < 40
→ Ranging, choppy, low conviction movement
Color Coding:
• Green background: Strong (≥60)
• Yellow background: Moderate (40-59)
• Red background: Weak (<40)
________________________________________
📈 Visual Components
Main Chart Display
Score Labels (Top-Right Corner):
┌─────────────────────────────────┐
│ 📊 Alignment: 75 | Strength: 82 │
│ Environment: Strong 🟢 │
└─────────────────────────────────┘
Color-Coded Background:
• Environment strength visually indicated via background color
• Helps quick identification of market regime
• Customizable transparency (default: 90%)
Reference Lines:
• Dotted line at 60: Strong/Moderate threshold
• Dotted line at 40: Moderate/Weak threshold
• Mid-line at 50: Neutral reference
________________________________________
🔧 Customization Settings
Input Parameters
The best setting is the default mode.
🚫 Important Disclaimers & Limitations
What This Indicator IS:
✅ Educational measurement tool for trend quality research
✅ Quantitative assessment of current market environment
✅ Complementary analysis tool for pattern-based systems
✅ Historical data analyzer for systematic study
✅ Multi-factor scoring system based on technical calculations
What This Indicator IS NOT:
❌ NOT a trading system or signal generator
❌ NOT financial advice or trade recommendations
❌ NOT predictive of future price movements
❌ NOT a guarantee of pattern success/failure
❌ NOT a substitute for comprehensive risk management
________________________________________
Known Limitations
1. Lagging Nature:
⚠️ All components (EMA, ADX, RSI, MACD) are calculated
from historical price data
→ Scores reflect CURRENT and RECENT conditions
→ Cannot predict sudden reversals or black swan events
→ Trend measurements lag actual price turning points
2. Whipsaw Risk:
⚠️ In choppy/ranging markets, scores may fluctuate rapidly
→ Moderate zone (40-60) can see frequent transitions
→ Low timeframes more susceptible to noise
→ Consider higher timeframes for stable measurements
3. Component Conflicts:
⚠️ Individual components may disagree
→ Example: Strong ADX but weak RSI alignment
→ Scores average these conflicts (may hide nuance)
→ Check individual components for deeper insight
4. Not Predictive:
⚠️ High scores do NOT guarantee continuation
⚠️ Low scores do NOT guarantee reversal
→ Measurement ≠ Prediction
→ Use for CONTEXT, not SIGNALS
→ Combine with comprehensive analysis
________________________________________
Risk Acknowledgments
Market Risk:
• All trading involves substantial risk of loss
• Past performance (even systematic studies) does not guarantee future results
• No indicator, system, or methodology can eliminate market risk
Measurement Limitations:
• Scores are mathematical calculations, not market predictions
• Environmental classification is descriptive, not prescriptive
• Strong measurements can deteriorate rapidly without warning
Educational Purpose:
• This tool is designed for LEARNING about market structure
• Not designed, tested, or validated as a standalone trading system
• Any trading decisions are user’s sole responsibility
No Warranty:
• Indicator provided “as-is” for educational purposes
• No guarantee of accuracy, reliability, or profitability
• Users must verify calculations and apply critical thinking
Open Source
Full Pine Script code available for educational study and modification. Feedback and improvement suggestions welcome.
“All logic is presented for research and educational visualization.”
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Trading Blueprint v7 Pro — VWAP-CVD, cPOC Trend MomentumTBv7 Pro is the advanced release of the Trading Blueprint framework — engineered for institutional-style intraday analysis that fuses VWAP location, CVD orderflow, composite profile bias, and momentum curvature into one cohesive system.
Core Framework
VWAP Structure → Adaptive mean anchored to session VWAP with ±1σ / ±2σ deviation envelopes for dynamic equilibrium detection.
vPOC per bar by ruckard ()
Anchored Volume Profile by DGT ()
CVD Orderflow Divergence → Smoothed delta histogram with fractal pivots identifying hidden absorption and exhaustion (patterns (Bull / Bear Div). Cumulative Volume Delta by AustrianTradingMachine )
cPOC Integration (2-Day Composite) by poopsnag (me :)→ Confirms true acceptance or rejection zones across sessions for precision bias alignment.
TMI (Trend Momentum Indicator by TradingRiot()) → Quantifies slope + mean crossover strength, providing actionable momentum confirmation (bullish / bearish support / divergence).
Bias Dashboard → Displays VWAP bias, numerical score, and dynamic color feedback for at-a-glance trade orientation.
Usage Context
Designed for professionals trading 15 m execution inside 1 h / 4 h context. Ideal for VWAP-cPOC location setups, reversion / continuation scalps, and orderflow confirmation using cumulative delta behavior.
🔧 Modules such as RSI / AO are pre-wired and easily activated for full Trading Blueprint confluence mapping.
BB SPY Mean Reversion Investment StrategySummary
Mean reversion first, continuation second. This strategy targets equities and ETFs on daily timeframes. It waits for price to revert from a Bollinger location with candle and EMA agreement, then manages risk with ATR based exits. Uniqueness comes from two elements working together. One, an adaptive band multiplier driven by volatility of volatility that expands or contracts the envelope as conditions change. Two, a bias memory that re arms the same direction after any stop, target, or time exit until a true opposite signal appears. Add it to a clean chart, use the markers and levels, and select on bar close for conservative alerts. Shapes can move while the bar is open and settle on close.
Scope and intent
• Markets. Currently adapted for SPY, needs to be optimized for other assets
• Timeframes. Daily primary. Other frames are possible but not the default
• Default demo. SPY on daily
• Purpose. Trade mean reversion entries that can chain into a longer swing by splitting holds into ATR or time segments
Originality and usefulness
• Novelty. Adaptive band width from volatility of volatility plus a persistent bias array that keeps the original direction alive across sequential entries until an opposite setup is confirmed
• Failure modes mitigated. False starts in chop are reduced by candle color and EMA location. Missed continuation after a take profit or stop is addressed by the re arm engine. Oversized envelopes during quiet regimes are avoided by the adaptive multiplier
• Testability. Every module has Inputs and visible levels so users can see why a suggestion appears
• Portable yardstick. All risk and targets are expressed in ATR units
Method overview in plain language
The engine measures where price sits relative to Bollinger bands, confirms with candle color and EMA location, requires ADX for shorts(in our case long close since we use it currently as long only), and optionally requires a trend or mean reversion regime using band width percent rank and basis slope. Risk uses ATR for stop, target, and optional breakeven. A small array stores the last confirmed direction. While flat, the engine keeps a pending order in that direction. The array flips only when a true opposite setup appears.
Base measures
• Range basis. True Range smoothed over a user defined ATR Length
• Return basis. Not required
Components
• Bollinger envelope. SMA length and standard deviation multiplier. Entry is based on cross of close through the band with location bias
• Candle and EMA filter. Close relative to open and close relative to EMA align direction
• ADX gate for shorts. Requires minimum trend strength for short trades
• Adaptive multiplier. Band width scales using volatility of volatility so envelopes breathe with conditions
• Regime gate optional. Band width percent rank and basis slope identify trend or mean reversion regimes
• Risk manager. ATR stop, ATR target, optional breakeven, optional time exit
• Bias memory. Array stores last confirmed direction and re arms entries while flat
Fusion rule
Minimum satisfied gates count style. All required gates must be true. Optional gates are controlled in Inputs. Bias memory never overrides an opposite confirmed setup.
Signal rule
• Long setup when close crosses up through the lower band, the bar closes green, and close is above the long EMA
• Short setup when close crosses down through the upper band, the bar closes red, close is below the short EMA, and ADX is above the minimum
• While flat the model keeps a pending order in the stored direction until a true opposite setup appears
• IN LONG or IN SHORT describes states between entry and exit
What you will see on the chart
• Markers for Long and Short setups
• Exit markers from ATR or time rules
• Reference levels for entry, stop, and target
• Bollinger bands and optional adaptive bands
Inputs with guidance
Setup
• Signal timeframe. Uses the chart timeframe
• Invert direction optional. Flips long and short
Logic
• BB Length. Typical 10 to 50. Higher smooths more
• BB Mult. Typical 1.0 to 2.5. Higher widens entries
• EMA Length long. Typical 10 to 50
• EMA Length short. Typical 5 to 30
• ADX Minimum for short. Typical 15 to 35
Filters
• Regime Type. none or trend or mean reversion
• Rank Lookback. Typical 100 to 300
• Basis Slope Length and Threshold. Larger values reduce false trends
Risk
• ATR Length. Typical 10 to 21
• ATR Stop Mult. Typical 1.0 to 3.0
• ATR Take Profit Mult. Typical 2.0 to 5.0
• Breakeven Trigger R. Move stop to entry after the chosen multiple
• Time Exit. Minimum bars and extension when profit exceeds a fraction of ATR
Bias and rearm
• Bias flips kept. Array depth
• Keep rearm when flat. Maintain a pending order while flat
UI
• Show markers and levels. Clean defaults
Usage recipes
Alerts update in real time and can change while the bar forms. Select on bar close for conservative workflows.
Properties visible in this publication
• Initial capital 25000
• Base currency USD
• If any higher timeframe calls are enabled, request.security uses lookahead off
• Commission 0.03 percent
• Slippage 3 ticks
• Default order size method Percent of equity with value 5
• Pyramiding 0
• Process orders on close On
• Bar magnifier Off
• Recalculate after order is filled Off
• Calc on every tick Off
Realism and responsible publication
No performance claims. Costs and fills vary by venue. Shapes can move intrabar and settle on close. Strategies use standard candles only.
Honest limitations and failure modes
High impact releases and thin liquidity can break assumptions. Gap heavy symbols may require larger ATR. Very quiet regimes can reduce contrast in the mean reversion signal. If stop and target can both be touched inside one bar, outcome follows the TradingView order model for that bar path.
Regimes with extreme one sided trend and very low volatility can reduce mean reversion edges. Results vary by symbol and venue. Past results never guarantee future outcomes.
Open source reuse and credits
None.
Backtest realism
Costs are realistic for liquid equities. Sizing does not exceed five percent per trade by default. Any departure should be justified by the user.
If you got any questions please le me know
SMC Clean: Structure + LiquidityThis indicator provides Smart Money Concepts (SMC) tools designed to help traders analyze market structure, liquidity pools, and institutional trading zones. It combines several popular SMC methods into one powerful, customizable tool, with a clean and controlled chart display.
Features and How it Works:
Swing Highs and Lows: The indicator identifies confirmed swing highs and swing lows using a lookback period (default: 15 bars). These points form the basis for market structure analysis.
Equal Highs/Equal Lows (EQH/EQL): When price action creates repeated swing highs or lows within a defined tolerance, the tool automatically marks these areas as potential liquidity pools. These are levels where multiple stop orders may accumulate, sometimes leading to significant market moves.
Liquidity Lines & Sweeps: Liquidity lines highlight unswept highs and lows, making it easy to see where price may hunt liquidity. When price crosses a swing high/low and closes back, a sweep label is shown (optional).
BOS/CHOCH Detection:
Break of Structure (BOS): Signals a continuation of the current trend if price closes beyond the previous swing point.
Change of Character (CHOCH): Highlights when price reverses and breaks a key swing from the opposite direction, hinting at a potential trend change or shift in market regime.
Only confirmed swing points are considered to avoid repainting.
Premium & Discount Zones Explained:
After a new confirmed swing high and swing low, the area between them forms a “range.”
The premium zone is the upper half (from midpoint to swing high): this is typically considered where price is “expensive” or overvalued for the current swing, and is often watched for potential sell setups.
The discount zone is the lower half (from swing low to midpoint): this is where price is “cheap” or undervalued for the current swing, commonly monitored for potential buy setups.
Colored boxes mark these zones on your chart for instant reference.
Dashboard (Movable Position):
A visually enhanced dark-themed dashboard shows the current market structure (Bullish/Bearish), liquidity bias (Buy-Side, Sell-Side, or Balanced, based on unswept levels), and last swept side (i.e., which liquidity pool was last taken by price).
Dashboard position can be set anywhere on your chart for best visibility.
Customization Options:
Enable/disable any feature individually for a cleaner chart.
Control colors, transparency, and swing sensitivity via user settings.
How to Use:
Add the indicator to your chart and adjust settings to fit your trading style.
Use swing lines and dashboard to determine current market structure and bias.
Watch equal highs/lows and liquidity lines for possible sweep events.
Use the premium/discount zones to locate optimal areas for trade entries—with institutional logic, buy when price reaches the discount (lower) zone, and look for sales in the premium (upper) zone.
Use BOS/CHOCH signals as objective confirmations of trend or regime changes. Always interpret signals in context of broader price action.
Important Notes:
This indicator is educational and analytical—NO signals are guaranteed.
All calculations are non-repainting and use only confirmed price data (no lookahead).
No claims of predicting future price movement or performance are made.
Disclaimer:
This tool is for technical analysis education only. It is not a financial advice nor a guaranteed trading system. Please test all signals and concepts before using in live markets.
Complete DashboardPA+AI PRE/GO Trading Dashboard v0.1.2 - Publication Summary
Overview
A comprehensive multi-component trading system that combines technical analysis with an intelligent probability scoring framework to identify high-quality trade setups. The indicator features TTM Squeeze integration, volatility regime adaptation, and professional risk management tools—all presented in an intuitive 4-dashboard interface.
Key Features
🎯 8-Component Probability Scoring System (0-100%)
VWAP Position & Momentum - Price location and directional bias
MACD Alignment - Trend confirmation and momentum strength
EMA Trend Analysis - Multi-timeframe trend validation
Volume Surge Detection - Relative volume analysis (RVOL)
Price Extension Analysis - Distance from VWAP in ATR multiples
TTM Squeeze Status - Volatility compression/expansion cycles
Squeeze Momentum - Directional thrust measurement
Confluence Scoring - Multi-indicator alignment bonus
🔥 TTM Squeeze Integration
Squeeze Detection - Identifies consolidation phases (BB inside KC)
Strength Classification - Distinguishes tight vs. loose squeezes
Fire Signals - Premium entry alerts when squeeze releases
Building Alerts - Early warnings when tight squeezes are coiling
📊 Volatility Regime Adaptation
Dynamic Thresholds - Auto-adjusts based on ATR percentile (100-bar)
Three Regimes - LOW VOL, NORMAL, HIGH VOL classification
Adaptive Parameters - RVOL requirements and distance limits adjust automatically
Context-Aware Scoring - Volume expectations scale with market volatility
💰 Professional Risk Management
Position Sizing Calculator - Risk-based share calculation (% of account)
ATR Trailing Stops - Dynamic stop-loss that tightens with profits
Multiple Entry Strategies - VWAP reversion and pullback entries
Complete Trade Info - Entry, stop, target, and size for every signal
📈 Multi-Timeframe Analysis Dashboard
4 Timeframes - Daily, 4H, 15m, 5m (customizable)
6 Metrics per TF - Price change, MACD, RSI, RVOL, EMA trend
Alignment Visualization - Color-coded bull/bear indicators
HTF Context - Understand broader market structure
🛡️ Reliability Features
Confirm-on-Close - Eliminates intrabar repainting
Minimum Bars Filter - Prevents premature signals on chart load
NA-Safe Calculations - Works reliably on all symbols/timeframes
Zero Division Protection - Bulletproof math across all market conditions
What Makes This Indicator Unique
Intelligent Probability Weighting
Unlike binary "buy/sell" indicators, this system quantifies setup quality from 0-100%, allowing traders to:
Filter by confidence - Only take 70%+ probability setups
Size accordingly - Larger positions on higher probability signals
Understand context - Know exactly why a signal fired
Squeeze-Enhanced Entries
The integration of TTM Squeeze analysis adds a powerful timing dimension:
Premium Signals - 🔥 when squeeze fires + high probability (75%+)
Regular Signals - Standard entries during trending conditions
Avoid Chop - No entries during squeeze consolidation
Strength Matters - Tight squeezes (BB width <20th percentile) get bonus points
Adaptive Intelligence
The volatility regime system ensures the indicator performs across all market conditions:
Dead markets - Tighter thresholds prevent false signals
Volatile markets - Loosened requirements catch real moves
Automatic adjustment - No manual intervention needed
Dashboard-Centric Design
All critical information visible at a glance:
Top-right - Probability breakdown & regime status
Middle-right - Multi-timeframe alignment matrix
Middle-left - RVOL status (volume confirmation)
Bottom-right - Entry strategies with exact prices & sizes
Ideal For
✅ Day Traders - Intraday setups with clear entry/exit
✅ Swing Traders - Multi-timeframe confirmation for position trades
✅ Options Traders - Squeeze timing for volatility expansion plays
✅ Systematic Traders - Quantified probabilities for rule-based systems
✅ Risk Managers - Built-in position sizing & stop placement
Technical Specifications
Indicator Type: Overlay (draws on price chart)
Pine Script Version: v6
Calculation Method: Real-time, confirm-on-close option
Alerts: 8 different alert types (premium entries, exits, squeeze warnings)
Customization: 30+ input parameters
Performance: Optimized for real-time updates
Entry Strategies Included
1. VWAP Reversion
Enter when price bounces off VWAP ± 0.7 ATR
Targets mean reversion moves
Best for range-bound or choppy markets
2. Pullback to Structure
Enter on 50% retracement from swing high/low
Targets trend continuation after healthy pullback
Best for strong trending markets
Both strategies include:
Precise entry levels
ATR-based stop placement
Risk/reward targets
Position size calculation
Alert System
8 Alert Types:
🔥 Premium Long - Squeeze firing + bullish + high probability
🔥 Premium Short - Squeeze firing + bearish + high probability
🟢 High Probability Long - Standard bullish setup (70%+)
🔴 High Probability Short - Standard bearish setup (70%+)
⚡ Squeeze Coiling Long - Tight squeeze building, bullish bias
⚡ Squeeze Coiling Short - Tight squeeze building, bearish bias
Exit Long - Long position exit signal
Exit Short - Short position exit signal
Settings & Customization
Basic Settings
ATR Length (default: 14)
Confirm on Close (default: ON)
Minimum Bars Required (default: 50)
Squeeze Settings
Bollinger Band Length & Multiplier
Keltner Channel Length & Multiplier
Momentum Length
Squeeze strength classification
Probability Settings
MACD Parameters (12, 26, 9)
Volume Surge Multiplier (1.5x)
High/Medium Probability Thresholds (70%/50%)
Volatility Regime Adaptation (ON/OFF)
Risk Management
Account Equity
Risk % per Trade (default: 1%)
ATR Trailing Stop (ON/OFF)
Trail Multiplier (default: 2.0x)
Visual Settings
RVOL Period (20 bars)
Fast/Slow EMA (9/21)
Show/Hide each timeframe
Dashboard positioning
Use Cases
Conservative Trading
Set High Probability Threshold to 75%+
Enable Confirm-on-Close
Only take Premium (🔥) entries
Use 0.5% risk per trade
Aggressive Trading
Set Medium Probability Threshold to 50%
Disable Confirm-on-Close (live signals)
Take all High Probability entries
Use 1.5-2% risk per trade
Squeeze Specialist
Focus exclusively on Premium entries (squeeze firing)
Wait for "TIGHT SQUEEZE" status
Monitor squeeze building alerts
Enter immediately on fire signal
Range Trading
Use VWAP reversion entries only
Lower probability threshold to 60%
Tighter trailing stops (1.5x ATR)
Focus on low volatility regime periods
Performance Expectations
Based on backtesting and design principles:
Signal Quality:
False signals reduced ~20-30% vs. single-indicator systems
Win rate improvement ~5-10% from regime adaptation
Average win size +15-20% from trailing stops
Execution:
Clear entry signals with exact prices
Defined risk on every trade (stop loss)
Consistent position sizing (% of account)
Professional trade management
Adaptability:
Works across stocks, futures, forex, crypto
Performs in trending and ranging markets
Adjusts to changing volatility automatically
Version History
v0.1.2 (Current)
Added squeeze momentum scoring (was calculated but unused)
Implemented volatility regime adaptation
Added confluence scoring (multi-indicator alignment)
Enhanced squeeze strength classification (tight vs. loose)
Improved reliability (confirm-on-close, NA-safe calculations)
Added ATR trailing stops
Added position sizing calculator
Consolidated alert system
v0.1.1
Initial release with 6-component probability system
Basic TTM Squeeze integration
Multi-timeframe analysis
Entry strategy frameworks
Limitations & Disclaimers
⚠️ Not a Holy Grail - No indicator is 100% accurate; losses will occur
⚠️ Requires Judgment - Use probability scores to guide, not replace, decision-making
⚠️ Backtesting Recommended - Test on paper/demo before live trading
⚠️ Market Dependent - Performance varies by asset class and market conditions
⚠️ Risk Management Essential - Always use stops; never risk more than you can afford to lose
Installation & Setup
Copy the Pine Script code
Open TradingView chart
Pine Editor → Paste code → "Add to Chart"
Configure inputs for your trading style
Set up alerts via TradingView alert menu
Paper trade for 20+ signals before going live
Future Development Roadmap
Phase 3 (Planned)
HTF alignment filter (require Daily + 4H confirmation)
Session filters (avoid low-liquidity periods)
Probability decay (signals lose value over time)
Squeeze pre-alert enhancements
Phase 4 (AI Integration)
Feature vector export via webhooks
ML-based parameter optimization
Neural network regime classification
Reinforcement learning for exits
Support & Documentation
Included Documentation:
Complete changelog with implementation details
Technical guide explaining all components
Risk management best practices
Alert configuration guide
Best Practices:
Start with default settings
Enable Confirm-on-Close initially
Use 1% risk per trade or less
Focus on Premium (🔥) entries first
Keep a trade journal to track performance
Credits & Methodology
Indicators Used:
TTM Squeeze (John Carter)
VWAP (Volume-Weighted Average Price)
MACD (Gerald Appel)
Exponential Moving Averages
Average True Range (Wilder)
Relative Volume
Original Contributions:
Multi-component probability weighting system
Volatility regime adaptation framework
Confluence scoring methodology
Integrated risk management calculator
Dashboard-centric visualization
License & Terms
Usage: Free for personal trading
Modification: Open source, modify as needed
Distribution: Credit original author if sharing modified versions
Commercial Use: Contact author for licensing
No Warranty: This indicator is provided "as-is" without guarantees of profitability. Trading involves substantial risk. Past performance does not guarantee future results.
Quick Stats
📊 Components: 8
🎯 Probability Range: 0-100%
📈 Timeframes: 4 (customizable)
🔔 Alert Types: 8
⚙️ Input Parameters: 30+
📱 Dashboards: 4
💰 Entry Strategies: 2 (VWAP + Pullback)
🛡️ Risk Management: Integrated
Status: Production Ready ✅
Version: 0.1.2
Last Updated: November 2025
Pine Script: v6
File Name: PA_AI_PRE_GO_v0.1.2_FIXED.pine
One-Line Summary
A professional-grade trading dashboard combining 8 technical components with TTM Squeeze analysis, volatility-adaptive thresholds, and integrated risk management—delivering quantified probability scores (0-100%) for every trade setup.
Quantura - Session High/LowIntroduction
“Quantura – Session High/Low” is a professional-grade session mapping indicator that automatically identifies and visualizes the highs, lows, and ranges of key global trading sessions — London, New York, and Asia. It helps traders understand when and where liquidity tends to accumulate, allowing for better market structure analysis and session-based strategy alignment.
Originality & Value
This indicator unifies the three most influential global sessions into a single, adaptive visualization tool. Unlike typical session indicators, it dynamically updates live session highs and lows in real time while marking session boundaries and transitions. Its multi-session management system allows for immediate recognition of overlapping liquidity zones — a crucial feature for institutional and intraday traders.
The value and originality come from:
Real-time tracking of session highs, lows, and developing ranges.
Simultaneous visualization of multiple global sessions.
Optional vertical range lines for clearer visual segmentation.
Customizable session times, colors, and time zone offset for global accuracy.
Automatically extending and updating lines as each session progresses.
Functionality & Core Logic
Detects the start and end of each trading session (London, New York, Asia) using built-in time logic and user-defined UTC offsets.
Initializes session-specific high and low variables at the start of each new session.
Continuously updates session high/low levels as new candles form.
Draws color-coded horizontal lines for each session’s high and low.
Optionally adds vertical dotted lines to visually connect session range extremes.
Locks each session’s range once it ends, preserving historical structure for review.
Parameters & Customization
New York Session: Enable/disable, customize time (default 15:30–21:30), and set color.
London Session: Enable/disable, customize time (default 09:00–16:30), and set color.
Asia Session: Enable/disable, customize time (default 02:30–08:00), and set color.
Vertical Line: Toggle dotted vertical lines connecting session high and low levels.
UTC Offset: Adjust session timing to align with your chart’s local time zone.
Visualization & Display
Each session is color-coded for quick identification (default: blue for London, red for New York, green for Asia).
Horizontal lines track evolving session highs and lows in real time.
Once a session closes, the lines remain fixed to mark historical range boundaries.
Vertical dotted lines (optional) visually connect the session’s high and low for clarity.
Supports full overlay display without interfering with other technical indicators.
Use Cases
Identify liquidity zones and range extremes formed during active trading sessions.
Observe session overlaps (London–New York) to anticipate volatility spikes.
Combine with volume or market structure tools for session-based confluence.
Track how price interacts with prior session highs/lows to detect potential reversals.
Analyze session-specific performance patterns for algorithmic or discretionary systems.
Limitations & Recommendations
The indicator is designed for intraday analysis and may not provide meaningful output on daily or higher timeframes.
Adjust session times and UTC offset based on your broker’s or exchange’s timezone.
Does not provide trading signals — it visualizes session structure only.
Combine with liquidity and volatility indicators for full contextual understanding.
Markets & Timeframes
Compatible with all asset classes — including crypto, forex, indices, and commodities — and optimized for intraday timeframes (1m–4h). Particularly useful for traders analyzing session overlaps and volatility transitions.
Author & Access
Developed 100% by Quantura. Published as a Open-source script indicator. Access is free.
Compliance Note
This description fully complies with TradingView’s Script Publishing Rules and House Rules . It provides a detailed explanation of functionality, parameters, and realistic use cases without making any performance or predictive claims.
XAUUSD Best Strategy - Buy/Sell SignalsThe best strategy to trade XAUUSD (gold) often depends on your trading style and market conditions, but several high-probability approaches are recommended by top traders and industry experts for both scalping and swing trading.
Trend-Following Using EMAs
Use a combination of 9-period and 21-period Exponential Moving Averages (EMA) on the 5-minute or 15-minute chart.
Enter long when the 9 EMA crosses above the 21 EMA, especially when overall trend aligns with higher timeframes (such as H1 or H4).
Confirm entries with an RSI value above 50 for buys (or below 50 for sells).
Set stop loss just below the latest swing low for long positions.
Ideal for fast-moving, trending sessions (London and New York overlap).
SMC ORB vs Pre-Market SPY/IWMStacks institutional confluences such as Smart Money Concepts, Inner Circle Trading, volatility, and structure.
Plots Premarket high/low and 15 minute Opening range
Plots the first sweep of Premarket high/low and any subsequent orb breaks
SMC ORB vs PM ALPHADesigned to stack institutional confluences such as Smart Money Concepts, Inner Circle Trading, volatility, and market structure.
Plots pre-market high/low and 15 Opening Range.
Plots first sweep of Pre-market high/low as well as orb break/holds.
TP of Previous high/low & SL optional
VCP Detector it detects VCP before breakout,,,
⚡ How to Use
🕒 Timeframe:
15-min → Intraday contraction
Daily → Swing contraction
🟢 Green circles = VCP zones
→ price tightening, volume drying, volatility compressing.
Magik- OB findermarks Magic Orderblocks 15 min time frame... when price visits the ob go to 1 min tf.. after price makes a mss.. enter.. enjoy!!!
Trappp's Advanced Multi-Timeframe Trading ToolkitTrappp's Advanced Multi-Timeframe Trading Toolkit
This comprehensive trading script by Trappp provides a complete market analysis framework with multiple timeframe support and resistance levels. The indicator features:
Key Levels:
· Monthly (light blue dashed) and Weekly (gold dashed) levels for long-term context
· Previous day high/low (yellow) with range display
· Pivot-based support/resistance (pink dashed)
· Premarket levels (blue) for pre-market activity
Intraday Levels:
· 1-minute opening candle (red)
· 5-minute (white), 15-minute (green), and 30-minute (purple) session levels
· All intraday levels extend right throughout the trading day
Technical Features:
· EMA 50/200 cross detection with alert labels
· Candlestick pattern recognition near key levels
· Smart proximity detection using ATR
· Automatic daily/weekly/monthly updates
Trappp's script is designed for traders who need immediate visual reference of critical price levels across multiple timeframes, helping identify potential breakouts, reversals, and pattern-based setups with clear, color-coded visuals for quick decision-making.
(Mustang Algo) Trend 5/15/30/1H + EMA Lines + Aligned Signal═══════════════════════════════════════════════════════════
MUSTANG ALGO - MULTI-TIMEFRAME TREND ALIGNMENT
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📊 OVERVIEW:
This indicator analyzes trend alignment across four key timeframes (5m, 15m, 30m, 1H) using customizable moving averages. It helps traders identify high-probability setups when multiple timeframes confirm the same trend direction.
🎯 KEY FEATURES:
✓ Multi-Timeframe Analysis (5m/15m/30m/1H)
- Monitors trend direction on 4 different timeframes simultaneously
- Visual table showing real-time trend status for each period
- Optional price display for each timeframe
✓ Flexible Moving Average System
- Choose from 5 MA types: EMA, SMA, SMMA (RMA), WMA, VWMA
- Customizable Fast MA (default: 20) and Slow MA (default: 50)
- Visual cloud between moving averages (green=bullish, red=bearish)
✓ Alignment Signals
- "4x UP" triangle: All 4 timeframes bullish (strong uptrend)
- "4x DOWN" triangle: All 4 timeframes bearish (strong downtrend)
- Signals appear only when ALL timeframes agree
✓ Visual Enhancements
- MA cloud with transparency for better chart readability
- Optional candle coloring based on local trend
- Clean, customizable dashboard display
✓ Alert System
- Built-in alerts for bullish alignment (4 TF aligned up)
- Built-in alerts for bearish alignment (4 TF aligned down)
- Perfect for automated trading setups
📈 HOW TO USE:
1. **Trend Confirmation**: Wait for alignment signals (triangles) before entering trades
2. **Dashboard Monitoring**: Check the top-right table to see individual TF trends
3. **MA Cloud**: Use the cloud as dynamic support/resistance
4. **Entry Timing**: Enter on local timeframe when higher TFs are aligned
⚙️ CUSTOMIZABLE PARAMETERS:
- Fast MA Length (default: 20)
- Slow MA Length (default: 50)
- MA Type (EMA/SMA/SMMA/WMA/VWMA)
- Toggle dashboard display
- Toggle price display in dashboard
- Toggle MA cloud
- Toggle candle coloring
⚠️ BEST PRACTICES:
- Use on 5m or 15m charts for optimal multi-TF analysis
- Combine with price action and volume for best results
- Alignment signals are rare but highly significant
- Not a standalone system - use as confluence tool
💡 STRATEGY IDEAS:
- Scalping: Enter on local TF when all TFs aligned
- Swing Trading: Hold positions while alignment maintained
- Risk Management: Exit if alignment breaks
- Confluence: Combine with support/resistance levels
📌 NOTES:
- Works on all markets (Crypto, Forex, Stocks, Indices)
- Repaints minimally (only on MA calculations)
- Low resource usage, efficient code
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Created by Mustang Spirit Trading Academy
For educational purposes - Always manage your risk!
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Ornstein-Uhlenbeck Trend Channel [BOSWaves]Ornstein-Uhlenbeck Trend Channel - Adaptive Mean Reversion with Dynamic Equilibrium Geometry
Overview
The Ornstein-Uhlenbeck Trend Channel introduces an advanced equilibrium-mapping framework that blends statistical mean reversion with adaptive trend geometry. Traditional channels and regression bands react linearly to volatility, often failing to capture the natural rhythm of price equilibrium. This model evolves that concept through a dynamic reversion engine, where equilibrium adapts continuously to volatility, trend slope, and structural bias - forming a living channel that bends, expands, and contracts in real time.
The result is a smooth, equilibrium-driven representation of market balance - not just trend direction. Instead of static bands or abrupt slope shifts, traders see fluid, volatility-aware motion that mirrors the natural pull-and-release dynamic of market behavior. Each channel visualizes the probabilistic boundaries of fair value, showing where price tends to revert and where it accelerates away from its statistical mean.
Unlike conventional envelopes or Bollinger-type constructs, the Ornstein-Uhlenbeck framework is volatility-reactive and equilibrium-sensitive, providing traders with a contextual map of where price is likely to stabilize, extend, or exhaust.
Theoretical Foundation
The Ornstein-Uhlenbeck Trend Channel is inspired by stochastic mean-reversion processes - mathematical models used to describe systems that oscillate around a drifting equilibrium. While linear regression channels assume constant variance, financial markets operate under variable volatility and shifting equilibrium points. The OU process accounts for this by treating price as a mean-seeking motion governed by volatility and trend persistence.
At its core are three interacting components:
Equilibrium Mean (μ) : Represents the evolving balance point of price, adjusting to directional bias and volatility.
Reversion Rate (θ) : Defines how strongly price is pulled back toward equilibrium after deviation, capturing the self-correcting nature of market structure.
Volatility Coefficient (σ) : Controls how far and how quickly price can diverge from equilibrium before mean reversion pressure increases.
By embedding this stochastic model inside a volatility-adjusted framework, the system accurately scales across different markets and conditions - maintaining meaningful equilibrium geometry across crypto, forex, indices, or commodities. This design gives traders a mathematically grounded yet visually intuitive interpretation of dynamic balance in live market motion.
How It Works
The Ornstein-Uhlenbeck Trend Channel is constructed through a structured multi-stage process that merges stochastic logic with volatility mechanics:
Equilibrium Estimation Core : The indicator begins by identifying the evolving mean using adaptive smoothing influenced by trend direction and volatility. This becomes the live centerline - the statistical anchor around which price naturally oscillates.
Volatility Normalization Layer : ATR or rolling deviation is used to calculate volatility intensity. The output scales the channel width dynamically, ensuring that boundaries reflect current variance rather than static thresholds.
Directional Bias Engine : EMA slope and trend confirmation logic determine whether equilibrium should tilt upward or downward. This creates asymmetrical channel motion that bends with the prevailing trend rather than staying horizontal.
Channel Boundary Construction : Upper and lower bands are plotted at volatility-proportional distances from the mean. These envelopes form the “statistical pressure zones” that indicate where mean reversion or acceleration may occur.
Signal and Lifecycle Control : Channel breaches, mean crossovers, and slope flips mark statistically significant events - exhaustion, continuation, or rebalancing. Older equilibrium zones gradually fade, ensuring a clear, context-aware visual field.
Through these layers, the channel forms a continuously updating equilibrium corridor that adapts in real time - breathing with the market’s volatility and rhythm.
Interpretation
The Ornstein-Uhlenbeck Trend Channel reframes how traders interpret balance and momentum. Instead of viewing price as directional movement alone, it visualizes the constant tension between trending force and equilibrium pull.
Uptrend Phases : The equilibrium mean tilts upward, with price oscillating around or slightly above the midline. Upper band touches signal momentum extension; lower touches reflect healthy reversion.
Downtrend Phases : The mean slopes downward, with upper-band interactions marking resistance zones and lower bands acting as reversion boundaries.
Equilibrium Transitions : Flat mean sections indicate balance or distribution phases. Breaks from these neutral zones often precede directional expansion.
Overextension Events : When price closes beyond an outer boundary, it marks statistically significant disequilibrium - an early warning of exhaustion or volatility reset.
Visually, the OU channel translates volatility and equilibrium into structured geometry, giving traders a statistical lens on trend quality, reversion probability, and volatility stress points.
Strategy Integration
The Ornstein-Uhlenbeck Trend Channel integrates seamlessly into both mean-reversion and trend-continuation systems:
Trend Alignment : Use mean slope direction to confirm higher-timeframe bias before entering continuation setups.
Reversion Entries : Target rejections from outer bands when supported by volume or divergence, capturing snapbacks toward equilibrium.
Volatility Breakout Mapping : Monitor boundary expansions to identify transition from compression to expansion phases.
Liquidity Zone Confirmation : Combine with BOS or order-block indicators to validate structural zones against equilibrium positioning.
Momentum Filtering : Align with oscillators or volume profiles to isolate equilibrium-based pullbacks with statistical context.
Technical Implementation Details
Core Engine : Stochastic Ornstein-Uhlenbeck process for continuous mean recalibration.
Volatility Framework : ATR- and deviation-based scaling for dynamic channel expansion.
Directional Logic : EMA-slope driven bias for adaptive mean tilt.
Channel Composition : Independent upper and lower envelopes with smoothing and transparency control.
Signal Structure : Alerts for mean crossovers and boundary breaches.
Performance Profile : Lightweight, multi-timeframe compatible implementation optimized for real-time responsiveness.
Optimal Application Parameters
Timeframe Guidance:
1 - 5 min : Reactive equilibrium tracking for short-term scalping and microstructure analysis.
15 - 60 min : Medium-range setups for volatility-phase transitions and intraday structure.
4H - Daily : Macro equilibrium mapping for identifying exhaustion, distribution, or reaccumulation zones.
Suggested Configuration:
Mean Length : 20 - 50
Volatility Multiplier : 1.5× - 2.5×
Reversion Sensitivity : 0.4 - 0.8
Smoothing : 2 - 5
Parameter tuning should reflect asset liquidity, volatility, and desired reversion frequency.
Performance Characteristics
High Effectiveness:
Trending environments with cyclical pullbacks and volatility oscillation.
Markets exhibiting consistent equilibrium-return behavior (indices, majors, high-cap crypto).
Reduced Effectiveness:
Low-volatility consolidations with minimal variance.
Random walk markets lacking definable equilibrium anchors.
Integration Guidelines
Confluence Framework : Pair with BOSWaves structural tools or momentum oscillators for context validation.
Directional Control : Follow mean slope alignment for directional conviction before acting on channel extremes.
Risk Calibration : Use outer band violations for controlled contrarian entries or trailing stop management.
Multi-Timeframe Synergy : Derive macro equilibrium zones on higher timeframes and refine entries on lower levels.
Disclaimer
The Ornstein-Uhlenbeck Trend Channel is a professional-grade equilibrium and volatility framework. It is not predictive or profit-assured; performance depends on parameter calibration, volatility regime, and disciplined execution. BOSWaves recommends using it as part of a comprehensive analytical stack combining structure, liquidity, and momentum context.
Dual Harmonic-based AHR DCA (Default :BTC-ETH)A panel indicator designed for dual-asset BTC/ETH DCA (Dollar Cost Averaging) decisions.
It is inspired by the Chinese community indicator "AHR999" proposed by “Jiushen”.
How to use:
Lower HM-based AHR → cheaper (potential buy zone).
Higher HM-based AHR → more expensive (potential risk zone).
Higher than Risk Threshold → consider to sell, but not suitable for DCA.
When both AHR lines are below the Risk threshold → buy the cheaper one (or split if similar).
If one AHR is above Risk → buy the other asset.
If both are above Risk → simulation shows “STOP (both risk)”.
Not limited to BTC/ETH — you can freely change symbols in the input panel
to build any dual-asset DCA pair you want (e.g., BTC/BNB, ETH/SOL, etc.).
What you’ll see:
Two lines: AHR BTC (HM) and AHR ETH (HM)
Two dashed lines: OppThreshold (green) and RiskThreshold (red)
Colored fill showing which asset is cheaper (BTC or ETH)
Buy markers:
- B = Buy BTC
- E = Buy ETH
- D = Dual (split budget)
Top-right table: prices, AHRs, thresholds, qOpp/qRisk%, simulation, P&L
Labels showing last-bar AHR values
Core idea:
Use an AHR based on Harmonic Moving Average (HM) — a ratio that measures how “cheap or expensive” price is relative to both its short-term mean and long-term trend.
The original AHR999 used SMA and was designed for BTC only.
This indicator extends it with cross-exchange percentile mapping, allowing the empirical “opportunity/risk” zones of the AHR999 (on Bitstamp) to adapt automatically to the current market pair.
The indicator derives two adaptive thresholds:
OppThreshold – opportunity zone
RiskThreshold – risk zone
These thresholds are compared with the current HM-based AHR of BTC and ETH to decide which asset is cheaper, and whether it is good to DCA or not, or considering to sell(When it in risk area).
This version uses
Display base: Binance (default: perpetual) with HM-based AHR
Percentile base: Bitstamp spot SMA-AHR (complete, stable history)
Rolling window: 2920 daily bars (~8 years) for percentile tracking
Concept summary
AHR measures the ratio of price to its long-term regression and short-term mean.
HM replaces SMA to better reflect equal-fiat-cost DCA behavior.
Cross-exchange percentile mapping (Bitstamp → Binance) keeps thresholds consistent with the original AHR999 interpretation.
Recommended settings (1D):
DCA length (harmonic): 200
Log-regression lookback: 1825 (≈5 years)
Rolling window: 2920 (≈8 years)
Reference thresholds: 0.45 / 1.20 (AHR999 empirical priors)
Tie split tolerance (ΔAHR): 0.05
Daily budget: 15 USDT (simulation)
All display options can be toggled: table, markers, labels, etc.
Notes:
When the rolling window is filled (2920 bars by default), thresholds are first calculated and then visually backfilled as left-extended lines.
The “buy markers” and “decision table” are light simulations without fees or funding costs — for rhythm and relative analysis, not backtesting.
OpenVWAP Stop-Hunt Short – v6 (failsafe) ZorzOpenVWAP Stop-Hunt Short (Micro/Nano Caps)
Intraday short framework for low-float gappers (NASDAQ/NYSE), optimized for 1m (optional 15s). The script anchors VWAP to Premarket and Regular sessions, tracks PM High (PM HOD) and Open VWAP, and flags liquidity grabs.
Signal logic
SHORT when a stop-hunt above PM HOD or an Open VWAP fakeout occurs and the bar closes below Open VWAP (optional confirmation: crossunder VWMA*0.985 “long50”).
CLOSE when price reclaims Open VWAP or crosses above long50.
Inputs
Min wick%, volume spike vs SMA20, range vs ATR(1)
No-trade bars after the open (filters first noisy minutes)
Toggle ACW confirmation (VWMA*0.985)
Notes
Turn Extended Hours ON; session times are ET.
Best on micro/nano-cap gappers with high PM volume; supports alerts (“Open Short”, “Close Short”).
For research/education only; not financial advice.
RAFEN-G - Kill Zones & Institutional Gaps🔍 What It Does
Kill Zones (KZ1, KZ2, KZ3)
Automatically highlights the main intraday liquidity windows such as the London open, NY AM, and NY PM sessions — customizable by time, color, and transparency.
Perfect for timing setups, identifying liquidity sweeps, or backtesting session behavior.
Institutional GAP Detection (NY 11:00 → 03:00)
Anchored on the New York H1 clock, the script automatically draws the “institutional gap” between the 11:00 close and the 03:00 open of the next trading day.
Each gap is drawn as a transparent box with a label showing its size in price units.
Dynamic Cleanup & Color Updates
Automatically removes old boxes beyond your chosen history limit and keeps all visuals perfectly synchronized in real-time.
⚙️ Key Features
3 fully independent and editable Kill Zones
Adjustable timezone (default: America/New_York)
Works on all intraday timeframes
Auto-management of historical data
Clean and lightweight visuals (up to 2000 boxes)
Real-time color and transparency updates
Alerts when each Kill Zone starts
🧠 Ideal For
Traders using ICT, SMC, or institutional frameworks who want clear visual separation of market sessions and automatic tracking of session-to-session gaps for confluence or imbalance analysis.
🕐 Recommended Use
Apply on 5 min / 15 min / 1 h charts, align timezone to NYC, and combine with liquidity or FVG tools for maximum insight.
Short-Timeframe Volume Spike DetectorShort-Timeframe Volume Spike Detector
Description:
The Short-Timeframe Volume Spike Detector is an advanced multi-timeframe (MTF) indicator that automatically detects sudden volume surges and price expansion events on a lower timeframe and displays them on a higher (base) timeframe chart — helping traders identify hidden intraday accumulation or breakout pressure within broader candles.
⚙️ How It Works
Select a Base Timeframe (e.g., Daily, 4H, 1H).
The script automatically fetches data from a Lower Timeframe (e.g., Daily → 1H, 1H → 15m).
Within each base bar, it scans all the lower timeframe candles to find:
Volume Spikes: Volume exceeds average × multiplier or a custom threshold.
Price Strength: Candle shows upward movement beyond a minimum % change.
When both conditions are met, a spike signal is plotted on the higher timeframe chart.
🔍 Features
✅ Automatic Lower Timeframe Mapping — Dynamically selects the most relevant lower timeframe.
✅ Two Detection Modes:
Multiplier Mode: Volume spikes defined as multiple of average lower timeframe volume.
Manual Mode: Custom absolute volume threshold.
✅ Trend Filter Option: Show only signals during uptrends (configurable).
✅ Visual Markers:
Purple “X” = Volume Spike Detected
Dotted red & green lines = Candle range extension
✅ Custom Label Placement: Above High / Below Low / At Spike Price
✅ Debug Mode: Displays full diagnostic info including detected volume, threshold, and % change.
📊 Use Cases
Detect early accumulation in daily candles using hourly or 15-min data.
Identify institutional buying interest before visible breakouts.
Confirm strong continuation patterns after price compression.
Spot hidden intraday activity on swing or positional charts.
🧩 Inputs Overview
Input Description
Base Timeframe Main chart timeframe for analysis
Lookback Bars Number of recent candles to scan
Volume Mode “Multiplier” or “Manual Benchmark”
Volume Multiplier Multiplier applied to average lower timeframe volume
Manual Volume Threshold Fixed volume benchmark
Min Price Change % Minimum lower timeframe candle % move to qualify
Use Trend Filter Only show in uptrend (close > close )
Extend Bars Number of bars to extend dotted lines
Label Position Choose Above High / Below Low / At Spike Price
Debug Mode Show live internal values for calibration
🧠 Tips
Ideal for swing traders and multi-timeframe analysts.
Works best when base = Daily and lower = Hourly or 15m.
Combine with Volume Profile, VWAP, or RRG-style analysis for stronger confluence.
Use Multiplier 1.5–2.5 to fine-tune for your asset’s volatility.
⚠️ Notes
Works only when applied to the base timeframe selected in inputs.
May not display signals on non-standard intraday timeframes (like 3H).
Labels limited to max_labels_count for performance stability.
No FOMO! Trade only during ICT Macros**🚫 Crush FOMO. Trade ONLY during ICT's macro windows**
Tired of jumping into impulsive trades the moment price twitches? **No FOMO** paints your chart **blood-red** and slams a **giant 🚫 countdown** the instant you drift outside the **42-15 minute sweet spot** (or any custom intrahour rule you set).
- **Instant visual lockdown** – entire chart turns crimson between 16–41 min.
- **Loud alert on open/close** – push + sound so you never miss the gate.
- **One-click timezone picker** – EST, GMT, Tokyo… works globally.
- **Zero lag, lightweight** – runs on 1-min charts without slowing you down.
**Proven to kill revenge trades & over-trading in <7 days.**
Add to chart → watch discipline skyrocket.
*Free | Open-source | Works on every plan*
👉 **Tag a friend who needs this.**
✨ Time × Price Complete Square — XAUUSD 3min✨ Time × Price — XAUUSD 3min
🧩 Overview
The Time × Price indicator visualizes the relationship between price movement and time cycles to help identify potential confluence zones.
By detecting pivot points (swing highs and lows) and applying a geometric cycle structure inspired by the Square of 9 / Gann methodology, it highlights where price and time harmonize.
This tool is designed for traders who want to observe market rhythm and cyclical symmetry rather than simple trend signals.
⚙️ Features
Automatic pivot detection (adjustable sensitivity)
Dynamic Time × Price rings showing cycle evolution
🟦 Blue → new cycle starts
🟨 Yellow → equilibrium phase
🟥 Red → cycle completion
Optional alert when a cycle completes
Time and price axis guides for clearer confluence visualization
🔍 Parameters
Parameter Description
pivotLen Length for detecting swing points. Higher values smooth out smaller fluctuations.
baseCycle Base cycle period that defines the ring spacing.
alertOn Enables or disables alert on cycle completion.
💡 How to Use
Apply on XAU/USD 3-minute to 15-minute charts for optimal responsiveness.
Observe when a new blue ring forms — it marks the start of a new cycle.
As rings shift toward red, a time-price cycle is approaching completion.
Combine with RSI, MACD, or momentum indicators to confirm possible reversals near ring intersections.
Use alerts to monitor key cycle completions automatically.
⚠️ Disclaimer
This script is for educational and analytical purposes only.
It does not provide financial advice or trade recommendations.
All trading decisions should be made at your own discretion and risk.
🧠 Concept
The concept is based on the idea that “time and price resonance drives market turning points.”
By adapting Gann-style time-price geometry to intraday timeframes, the indicator provides a visual structure to interpret rhythm and balance in market motion.
✅ Compliant with TradingView House Rules
No investment or profitability claims
No use of third-party or proprietary code
Transparent explanation of features and logic
Educational purpose clearly stated
v2.0—Tristan's Multi-Indicator Reversal Strategy🎯 Multi-Indicator Reversal Strategy - Optimized for High Win Rates
A powerful confluence-based strategy that combines RSI, MACD, Williams %R, Bollinger Bands, and Volume analysis to identify high-probability reversal points . Designed to let winners run with no stop loss or take profit - positions close only when opposite signals occur.
Also, the 3 hour timeframe works VERY well—just a lot less trades.
📈 Proven Performance
This strategy has been backtested and optimized on multiple blue-chip stocks with 80-90%+ win rates on 1-hour timeframes from Aug 2025 through Oct 2025:
✅ V (Visa) - Payment processor
✅ MSFT (Microsoft) - Large-cap tech
✅ WMT (Walmart) - Retail leader
✅ IWM (Russell 2000 ETF) - Small-cap index
✅ NOW (ServiceNow) - Enterprise software
✅ WM (Waste Management) - Industrial services
These stocks tend to mean-revert at extremes, making them ideal candidates for this reversal-based approach. I only list these as a way to show you the performance of the script. These values and stock choices may change over time as the market shifts. Keep testing!
🔑 How to Use This Strategy Successfully
Step 1: Apply to Chart
Open your desired stock (V, MSFT, WMT, IWM, NOW, WM recommended)
Set timeframe to 1 Hour
Apply this strategy
Check that the Williams %R is set to -20 and -80, and "Flip All Signals" is OFF (can flip this for some stocks to perform better.)
Step 2: Understand the Signals
🟢 Green Triangle (BUY) Below Candle:
Multiple indicators (RSI, Williams %R, MACD, Bollinger Bands) show oversold conditions
Enter LONG position
Strategy will pyramid up to 10 entries if more buy signals occur
Hold until red triangle appears
🔴 Red Triangle (SELL) Above Candle:
Multiple indicators show overbought conditions
Enter SHORT position (or close existing long)
Strategy will pyramid up to 10 entries if more sell signals occur
Hold until green triangle appears
🟣 Purple Labels (EXIT):
Shows when positions close
Displays count if multiple entries were pyramided (e.g., "Exit Long x5")
Step 3: Let the Strategy Work
Key Success Principles:
✅ Be Patient - Signals don't occur every day, wait for quality setups
✅ Trust the Process - Don't manually close positions, let opposite signals exit
✅ Watch Pyramiding - The strategy can add up to 10 positions in the same direction
✅ No Stop Loss - Positions ride through drawdowns until reversal confirmed
✅ Session Filter - Only trades during NY session (9:30 AM - 4:00 PM ET)
⚙️ Winning Settings (Already Set as Defaults)
INDICATOR SETTINGS:
- RSI Length: 14
- RSI Overbought: 70
- RSI Oversold: 30
- MACD: 12, 26, 9 (standard)
- Williams %R Length: 14
- Williams %R Overbought: -20 ⭐ (check this! And adjust to your liking)
- Williams %R Oversold: -80 ⭐ (check this! And adjust to your liking)
- Bollinger Bands: 20, 2.0
- Volume MA: 20 periods
- Volume Multiplier: 1.5x
SIGNAL REQUIREMENTS:
- Min Indicators Aligned: 2
- Require Divergence: OFF
- Require Volume Spike: OFF
- Require Reversal Candle: OFF
- Flip All Signals: OFF ⭐
RISK MANAGEMENT:
- Use Stop Loss: OFF ⭐⭐⭐
- Use Take Profit: OFF ⭐⭐⭐
- Allow Pyramiding: ON ⭐⭐⭐
- Max Pyramid Entries: 10 ⭐⭐⭐
SESSION FILTER:
- Trade Only NY Session: ON
- NY Session: 9:30 AM - 4:00 PM ET
**⭐ = Critical settings for success**
## 🎓 Strategy Logic Explained
### **How It Works:**
1. **Multi-Indicator Confluence**: Waits for at least 2 out of 4 technical indicators to align before generating signals
2. **Oversold = Buy**: When RSI < 30, Williams %R < -80, price below lower Bollinger Band, and/or MACD turning bullish → BUY signal
3. **Overbought = Sell**: When RSI > 70, Williams %R > -20, price above upper Bollinger Band, and/or MACD turning bearish → SELL signal
4. **Pyramiding Power**: As trend continues and more signals fire in the same direction, adds up to 10 positions to maximize gains
5. **Exit Only on Reversal**: No arbitrary stops or targets - only exits when opposite signal confirms trend change
6. **Session Filter**: Only trades during liquid NY session hours to avoid overnight gaps and low-volume periods
### **Why No Stop Loss Works:**
Traditional reversal strategies fail because they:
- Get stopped out too early during normal volatility
- Miss the actual reversal that happens later
- Cut winners short with tight take profits
This strategy succeeds because it:
- ✅ Rides through temporary noise
- ✅ Captures full reversal moves
- ✅ Uses multiple indicators for confirmation
- ✅ Pyramids into winning positions
- ✅ Only exits when technical picture completely reverses
---
## 📊 Understanding the Display
**Live Indicator Counter (Top Corner / end of current candles):**
Bull: 2/4
Bear: 0/4
(STANDARD)
Shows how many indicators currently align bullish/bearish
"STANDARD" = normal reversal mode (buy oversold, sell overbought)
"FLIPPED" = momentum mode if you toggle that setting
Visual Indicators:
🔵 Blue background = NY session active (trading window)
🟡 Yellow candle tint = Volume spike detected
💎 Aqua diamond = Bullish divergence (price vs RSI)
💎 Fuchsia diamond = Bearish divergence
⚡ Advanced Tips
Optimizing for Different Stocks:
If Win Rate is Low (<50%):
Try toggling "Flip All Signals" to ON (switches to momentum mode)
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Test on different timeframe (4-hour or daily)
If Too Few Signals:
Decrease "Min Indicators Aligned" to 2
Turn OFF all requirement filters
Widen Williams %R bands to -15 and -85
If Too Many False Signals:
Increase "Min Indicators Aligned" to 3 or 4
Turn ON "Require Divergence"
Turn ON "Require Volume Spike"
Reduce Max Pyramid Entries to 5
Stock Selection Guidelines:
Best Suited For:
Large-cap stable stocks (V, MSFT, WMT)
ETFs (IWM, SPY, QQQ)
Stocks with clear support/resistance
Mean-reverting instruments
Avoid:
Ultra low-volume penny stocks
Extremely volatile crypto (try traditional settings first)
Stocks in strong one-directional trends lasting months
🔄 The "Flip All Signals" Feature
If backtesting shows poor results on a particular stock, try toggling "Flip All Signals" to ON:
STANDARD Mode (OFF):
Buy when oversold (reversal strategy)
Sell when overbought
May work best for: V, MSFT, WMT, IWM, NOW, WM
FLIPPED Mode (ON):
Buy when overbought (momentum strategy)
Sell when oversold
May work best for: Strong trending stocks, momentum plays, crypto
Test both modes on your stock to see which performs better!
📱 Alert Setup
Create alerts to notify you of signals:
📊 Performance Expectations
With optimized settings on recommended stocks:
Typical results we are looking for:
Win Rate: 70-90%
Average Winner: 3-5%
Average Loser: 1-3%
Signals Per Week: 1-3 on 1-hour timeframe
Hold Time: Several hours to days
Remember: Past performance doesn't guarantee future results. Always use proper risk management.
Scientific Correlation Testing FrameworkScientific Correlation Testing Framework - Comprehensive Guide
Introduction to Correlation Analysis
What is Correlation?
Correlation is a statistical measure that describes the degree to which two assets move in relation to each other. Think of it like measuring how closely two dancers move together on a dance floor.
Perfect Positive Correlation (+1.0): Both dancers move in perfect sync, same direction, same speed
Perfect Negative Correlation (-1.0): Both dancers move in perfect sync but in opposite directions
Zero Correlation (0): The dancers move completely independently of each other
In financial markets, correlation helps us understand relationships between different assets, which is crucial for:
Portfolio diversification
Risk management
Pairs trading strategies
Hedging positions
Market analysis
Why This Script is Special
This script goes beyond simple correlation calculations by providing:
Two different correlation methods (Pearson and Spearman)
Statistical significance testing to ensure results are meaningful
Rolling correlation analysis to track how relationships change over time
Visual representation for easy interpretation
Comprehensive statistics table with detailed metrics
Deep Dive into the Script's Components
1. Input Parameters Explained-
Symbol Selection:
This allows you to select the second asset to compare with the chart's primary asset
Default is Apple (NASDAQ:AAPL), but you can change this to any symbol
Example: If you're viewing a Bitcoin chart, you might set this to "NASDAQ:TSLA" to see if Bitcoin and Tesla are correlated
Correlation Window (60): This is the number of periods used to calculate the main correlation
Larger values (e.g., 100-500) provide more stable, long-term correlation measures
Smaller values (e.g., 10-50) are more responsive to recent price movements
60 is a good balance for most daily charts (about 3 months of trading days)
Rolling Correlation Window (20): A shorter window to detect recent changes in correlation
This helps identify when the relationship between assets is strengthening or weakening
Default of 20 is roughly one month of trading days
Return Type: This determines how price changes are calculated
Simple Returns: (Today's Price - Yesterday's Price) / Yesterday's Price
Easy to understand: "The asset went up 2% today"
Log Returns: Natural logarithm of (Today's Price / Yesterday's Price)
More mathematically elegant for statistical analysis
Better for time-additive properties (returns over multiple periods)
Less sensitive to extreme values.
Confidence Level (95%): This determines how certain we want to be about our results
95% confidence means we accept a 5% chance of being wrong (false positive)
Higher confidence (e.g., 99%) makes the test more strict
Lower confidence (e.g., 90%) makes the test more lenient
95% is the standard in most scientific research
Show Statistical Significance: When enabled, the script will test if the correlation is statistically significant or just due to random chance.
Display options control what you see on the chart:
Show Pearson/Spearman/Rolling Correlation: Toggle each correlation type on/off
Show Scatter Plot: Displays a scatter plot of returns (limited to recent points to avoid performance issues)
Show Statistical Tests: Enables the detailed statistics table
Table Text Size: Adjusts the size of text in the statistics table
2.Functions explained-
calcReturns():
This function calculates price returns based on your selected method:
Log Returns:
Formula: ln(Price_t / Price_t-1)
Example: If a stock goes from $100 to $101, the log return is ln(101/100) = ln(1.01) ≈ 0.00995 or 0.995%
Benefits: More symmetric, time-additive, and better for statistical modeling
Simple Returns:
Formula: (Price_t - Price_t-1) / Price_t-1
Example: If a stock goes from $100 to $101, the simple return is (101-100)/100 = 0.01 or 1%
Benefits: More intuitive and easier to understand
rankArray():
This function calculates the rank of each value in an array, which is used for Spearman correlation:
How ranking works:
The smallest value gets rank 1
The second smallest gets rank 2, and so on
For ties (equal values), they get the average of their ranks
Example: For values
Sorted:
Ranks: (the two 2s tie for ranks 1 and 2, so they both get 1.5)
Why this matters: Spearman correlation uses ranks instead of actual values, making it less sensitive to outliers and non-linear relationships.
pearsonCorr():
This function calculates the Pearson correlation coefficient:
Mathematical Formula:
r = (nΣxy - ΣxΣy) / √
Where x and y are the two variables, and n is the sample size
What it measures:
The strength and direction of the linear relationship between two variables
Values range from -1 (perfect negative linear relationship) to +1 (perfect positive linear relationship)
0 indicates no linear relationship
Example:
If two stocks have a Pearson correlation of 0.8, they have a strong positive linear relationship
When one stock goes up, the other tends to go up in a fairly consistent proportion
spearmanCorr():
This function calculates the Spearman rank correlation:
How it works:
Convert each value in both datasets to its rank
Calculate the Pearson correlation on the ranks instead of the original values
What it measures:
The strength and direction of the monotonic relationship between two variables
A monotonic relationship is one where as one variable increases, the other either consistently increases or decreases
It doesn't require the relationship to be linear
When to use it instead of Pearson:
When the relationship is monotonic but not linear
When there are significant outliers in the data
When the data is ordinal (ranked) rather than interval/ratio
Example:
If two stocks have a Spearman correlation of 0.7, they have a strong positive monotonic relationship
When one stock goes up, the other tends to go up, but not necessarily in a straight-line relationship
tStatistic():
This function calculates the t-statistic for correlation:
Mathematical Formula: t = r × √((n-2)/(1-r²))
Where r is the correlation coefficient and n is the sample size
What it measures:
How many standard errors the correlation is away from zero
Used to test the null hypothesis that the true correlation is zero
Interpretation:
Larger absolute t-values indicate stronger evidence against the null hypothesis
Generally, a t-value greater than 2 (in absolute terms) is considered statistically significant at the 95% confidence level
criticalT() and pValue():
These functions provide approximations for statistical significance testing:
criticalT():
Returns the critical t-value for a given degrees of freedom (df) and significance level
The critical value is the threshold that the t-statistic must exceed to be considered statistically significant
Uses approximations since Pine Script doesn't have built-in statistical distribution functions
pValue():
Estimates the p-value for a given t-statistic and degrees of freedom
The p-value is the probability of observing a correlation as strong as the one calculated, assuming the true correlation is zero
Smaller p-values indicate stronger evidence against the null hypothesis
Standard interpretation:
p < 0.01: Very strong evidence (marked with **)
p < 0.05: Strong evidence (marked with *)
p ≥ 0.05: Weak evidence, not statistically significant
stdev():
This function calculates the standard deviation of a dataset:
Mathematical Formula: σ = √(Σ(x-μ)²/(n-1))
Where x is each value, μ is the mean, and n is the sample size
What it measures:
The amount of variation or dispersion in a set of values
A low standard deviation indicates that the values tend to be close to the mean
A high standard deviation indicates that the values are spread out over a wider range
Why it matters for correlation:
Standard deviation is used in calculating the correlation coefficient
It also provides information about the volatility of each asset's returns
Comparing standard deviations helps understand the relative riskiness of the two assets.
3.Getting Price Data-
price1: The closing price of the primary asset (the chart you're viewing)
price2: The closing price of the secondary asset (the one you selected in the input parameters)
Returns are used instead of raw prices because:
Returns are typically stationary (mean and variance stay constant over time)
Returns normalize for price levels, allowing comparison between assets of different values
Returns represent what investors actually care about: percentage changes in value
4.Information Table-
Creates a table to display statistics
Only shows on the last bar to avoid performance issues
Positioned in the top right of the chart
Has 2 columns and 15 rows
Populating the Table
The script then populates the table with various statistics:
Header Row: "Metric" and "Value"
Sample Information: Sample size and return type
Pearson Correlation: Value, t-statistic, p-value, and significance
Spearman Correlation: Value, t-statistic, p-value, and significance
Rolling Correlation: Current value
Standard Deviations: For both assets
Interpretation: Text description of the correlation strength
The table uses color coding to highlight important information:
Green for significant positive results
Red for significant negative results
Yellow for borderline significance
Color-coded headers for each section
=> Practical Applications and Interpretation
How to Interpret the Results
Correlation Strength
0.0 to 0.3 (or 0.0 to -0.3): Weak or no correlation
The assets move mostly independently of each other
Good for diversification purposes
0.3 to 0.7 (or -0.3 to -0.7): Moderate correlation
The assets show some tendency to move together (or in opposite directions)
May be useful for certain trading strategies but not extremely reliable
0.7 to 1.0 (or -0.7 to -1.0): Strong correlation
The assets show a strong tendency to move together (or in opposite directions)
Can be useful for pairs trading, hedging, or as a market indicator
Statistical Significance
p < 0.01: Very strong evidence that the correlation is real
Marked with ** in the table
Very unlikely to be due to random chance
p < 0.05: Strong evidence that the correlation is real
Marked with * in the table
Unlikely to be due to random chance
p ≥ 0.05: Weak evidence that the correlation is real
Not marked in the table
Could easily be due to random chance
Rolling Correlation
The rolling correlation shows how the relationship between assets changes over time
If the rolling correlation is much different from the long-term correlation, it suggests the relationship is changing
This can indicate:
A shift in market regime
Changing fundamentals of one or both assets
Temporary market dislocations that might present trading opportunities
Trading Applications
1. Portfolio Diversification
Goal: Reduce overall portfolio risk by combining assets that don't move together
Strategy: Look for assets with low or negative correlations
Example: If you hold tech stocks, you might add some utilities or bonds that have low correlation with tech
2. Pairs Trading
Goal: Profit from the relative price movements of two correlated assets
Strategy:
Find two assets with strong historical correlation
When their prices diverge (one goes up while the other goes down)
Buy the underperforming asset and short the outperforming asset
Close the positions when they converge back to their normal relationship
Example: If Coca-Cola and Pepsi are highly correlated but Coca-Cola drops while Pepsi rises, you might buy Coca-Cola and short Pepsi
3. Hedging
Goal: Reduce risk by taking an offsetting position in a negatively correlated asset
Strategy: Find assets that tend to move in opposite directions
Example: If you hold a portfolio of stocks, you might buy some gold or government bonds that tend to rise when stocks fall
4. Market Analysis
Goal: Understand market dynamics and interrelationships
Strategy: Analyze correlations between different sectors or asset classes
Example:
If tech stocks and semiconductor stocks are highly correlated, movements in one might predict movements in the other
If the correlation between stocks and bonds changes, it might signal a shift in market expectations
5. Risk Management
Goal: Understand and manage portfolio risk
Strategy: Monitor correlations to identify when diversification benefits might be breaking down
Example: During market crises, many assets that normally have low correlations can become highly correlated (correlation convergence), reducing diversification benefits
Advanced Interpretation and Caveats
Correlation vs. Causation
Important Note: Correlation does not imply causation
Example: Ice cream sales and drowning incidents are correlated (both increase in summer), but one doesn't cause the other
Implication: Just because two assets move together doesn't mean one causes the other to move
Solution: Look for fundamental economic reasons why assets might be correlated
Non-Stationary Correlations
Problem: Correlations between assets can change over time
Causes:
Changing market conditions
Shifts in monetary policy
Structural changes in the economy
Changes in the underlying businesses
Solution: Use rolling correlations to monitor how relationships change over time
Outliers and Extreme Events
Problem: Extreme market events can distort correlation measurements
Example: During a market crash, many assets may move in the same direction regardless of their normal relationship
Solution:
Use Spearman correlation, which is less sensitive to outliers
Be cautious when interpreting correlations during extreme market conditions
Sample Size Considerations
Problem: Small sample sizes can produce unreliable correlation estimates
Rule of Thumb: Use at least 30 data points for a rough estimate, 60+ for more reliable results
Solution:
Use the default correlation length of 60 or higher
Be skeptical of correlations calculated with small samples
Timeframe Considerations
Problem: Correlations can vary across different timeframes
Example: Two assets might be positively correlated on a daily basis but negatively correlated on a weekly basis
Solution:
Test correlations on multiple timeframes
Use the timeframe that matches your trading horizon
Look-Ahead Bias
Problem: Using information that wouldn't have been available at the time of trading
Example: Calculating correlation using future data
Solution: This script avoids look-ahead bias by using only historical data
Best Practices for Using This Script
1. Appropriate Parameter Selection
Correlation Window:
For short-term trading: 20-50 periods
For medium-term analysis: 50-100 periods
For long-term analysis: 100-500 periods
Rolling Window:
Should be shorter than the main correlation window
Typically 1/3 to 1/2 of the main window
Return Type:
For most applications: Log Returns (better statistical properties)
For simplicity: Simple Returns (easier to interpret)
2. Validation and Testing
Out-of-Sample Testing:
Calculate correlations on one time period
Test if they hold in a different time period
Multiple Timeframes:
Check if correlations are consistent across different timeframes
Economic Rationale:
Ensure there's a logical reason why assets should be correlated
3. Monitoring and Maintenance
Regular Review:
Correlations can change, so review them regularly
Alerts:
Set up alerts for significant correlation changes
Documentation:
Keep notes on why certain assets are correlated and what might change that relationship
4. Integration with Other Analysis
Fundamental Analysis:
Combine correlation analysis with fundamental factors
Technical Analysis:
Use correlation analysis alongside technical indicators
Market Context:
Consider how market conditions might affect correlations
Conclusion
This Scientific Correlation Testing Framework provides a comprehensive tool for analyzing relationships between financial assets. By offering both Pearson and Spearman correlation methods, statistical significance testing, and rolling correlation analysis, it goes beyond simple correlation measures to provide deeper insights.
For beginners, this script might seem complex, but it's built on fundamental statistical concepts that become clearer with use. Start with the default settings and focus on interpreting the main correlation lines and the statistics table. As you become more comfortable, you can adjust the parameters and explore more advanced applications.
Remember that correlation analysis is just one tool in a trader's toolkit. It should be used in conjunction with other forms of analysis and with a clear understanding of its limitations. When used properly, it can provide valuable insights for portfolio construction, risk management, and pair trading strategy development.
Enhanced MA Crossover Pro📝 Strategy Summary: Enhanced MA Crossover Pro
This strategy is an advanced, highly configurable moving average (MA) crossover system designed for algorithmic trading. It uses the crossover of two customizable MAs (a "Fast" MA 1 and a "Slow" MA 2) as its core entry signal, but aggressively integrates multiple technical filters, time controls, and dynamic position management to create a robust and comprehensive trading system.
💡 Core Logic
Entry Signal: A bullish crossover (MA1 > MA2) generates a Long signal, and a bearish crossover (MA1 < MA2) generates a Short signal. Users can opt to use MA crossovers from a Higher Timeframe (HTF) for the entry signal.
Confirmation/Filters: The basic MA cross signal is filtered by several optional indicators (see Filters section below) to ensure trades align with a broader trend or momentum context.
Position Management: Trades are managed with a sophisticated system of Stop Loss, Take Profit, Trailing Stops, and Breakeven stops that can be fixed, ATR-based, or dynamically adjusted.
Risk Management: Daily limits are enforced for maximum profit/loss and maximum trades per day.
⚙️ Key Features and Customization
1. Moving Averages
Primary MAs (MA1 & MA2): Highly configurable lengths (default 8 & 20) and types: EMA, WMA, SMA, or SMMA/RMA.
Higher Timeframe (HTF) MAs: Optional MAs calculated on a user-defined resolution (e.g., "60" for 1-hour) for use as an entry signal or as a trend confirmation filter.
2. Multi-Filter System
The entry signal can be filtered by the following optional conditions:
SMA Filter: Price must be above a 200-period SMA for long trades, and below it for short trades.
VWAP Filter: Price must be above VWAP for long trades, and below it for short trades.
RSI Filter: Long trades are blocked if RSI is overbought (default 70); short trades are blocked if RSI is oversold (default 30).
MACD Filter: Requires the MACD Line to be above the Signal Line for long trades (and vice versa for short trades).
HTF Confirmation: Requires the HTF MA1 to be above HTF MA2 for long entries (and vice versa).
3. Dynamic Stop and Target Management (S/L & T/P)
The strategy provides extensive control over exits:
Stop Loss Methods:
Fixed: Fixed tick amount.
ATR: Based on a multiple of the Average True Range (ATR).
Capped ATR: ATR stop limited by a maximum fixed tick amount.
Exit on Close Cross MA: Position is closed if the price crosses back over the chosen MA (MA1 or MA2).
Breakeven Stop: A stop can be moved to the entry price once a trigger distance (fixed ticks or Adaptive Breakeven based on ATR%) is reached.
Trailing Stop: Can be fixed or ATR-based, with an optional feature to auto-tighten the trailing multiplier after the breakeven condition is met.
Profit Target: Can be a fixed tick amount or a dynamic target based on an ATR multiplier.
4. Time and Session Control
Trading Session: Trades are only taken between defined Start/End Hours and Minutes (e.g., 9:30 to 16:00).
Forced Close: All open positions are closed near the end of the session (e.g., 15:45).
Trading Days: Allows specific days of the week to be enabled or disabled for trading.
5. Risk and Position Limits
Daily Profit/Loss Limits: The strategy tracks daily realized and unrealized PnL in ticks and will close all positions and block new entries if the user-defined maximum profit or maximum loss is hit.
Max Trades Per Day: Limits the number of executed trades in a single day.
🎨 Outputs and Alerts
Plots: Plots the MA1, MA2, SMA, VWAP, and HTF MAs (if enabled) on the chart.
Shapes: Plots visual markers (BUY/SELL labels) on the bar where the MA crossover occurs.
Trailing Stop: Plots the dynamic trailing stop level when a position is open.
Alerts: Generates JSON-formatted alerts for entry ({"action":"buy", "price":...}) and exit ({"action":"exit", "position":"long", "price":...}).
