Smart Range Breakout System (Zeiierman)█ Overview
Smart Range Breakout System (Zeiierman) is a full breakout–trend–risk framework engineered around volatility compression, adaptive range detection, and a volatility-adaptive structural mapping layer that continuously reshapes itself as price migrates away from compression zones. Rather than reacting to simple line breaks, the system identifies statistically quiet regimes, models the expansion phase as momentum re-enters the market, and then deploys a unified architecture of trend projection, dynamic trailing stops, and risk–reward structuring that evolves in real time with the unfolding move.
This tool is designed for traders who want a self-contained breakout workflow: first detect valid ranges, then trade the expansion, then manage the trend and exits via automatically generated levels and alerts.
⚪ Why This One Is Unique
The core engine combines a custom price-contraction model with volatility-responsive boundary levels to detect when the market is transitioning between quiet and active phases. From this model, the script generates a smoothed synthetic average that acts as the reference point for identifying compression zones and validating breakout conditions. Using this foundation, the system builds a complete visual trade map: breakout boxes that mark consolidation, breakout markers that signal expansion, a trend cloud that tracks directional bias, adaptive trailing stops that follow price movement, and optional risk-reward levels that automatically adjust to each new breakout.
Unlike conventional breakout indicators that rely on a single high/low lookback, this system uses:
A price contraction engine that re-weights candle structure through a momentum-like transform, generating a stabilized price that better captures compression and release.
An adaptive low-volatility counter that waits for statistically quiet behavior before declaring a range.
█ Main Features
⚪ Breakout Signals With Dynamic Risk-Reward Levels
The system identifies meaningful breakouts emerging from compressed price zones and immediately maps a complete trade structure around each signal.
Each breakout generates:
Directional breakout markers to confirm expansion
Entry, Stop, TP1, and TP2 levels that are automatically projected
A dynamic trailing stop is added to lock in profits as the price moves
Risk and reward zones visualized through adaptive fills
Labels that update in real time as targets are reached or invalidated
This creates a clear, self-contained decision map that helps traders evaluate opportunities, manage risk, and track the progression of each breakout without manual calculations.
⚪ Trend Cloud
A continuously updating Trend Cloud highlights the active directional regime and offers immediate visual trend identification through its color-coded bias. It shows whether a breakout aligns with the prevailing direction, provides a smoother and more stable representation of the trend than raw price alone, and creates an intuitive backdrop for distinguishing trend-following opportunities from countertrend setups. By filtering out noise and emphasizing directional stability, the cloud helps improve timing, signal quality, and overall alignment with the dominant market structure.
█ How to Use
⚪ Breakout Trading from Range Boxes
1. Identify Compression Zones
Look for periods where the Range Breakout Box appears: this signals a statistically quiet regime where price has compressed around a bounded range.
The box top and bottom approximate the upper and lower bounds of the market’s recent equilibrium.
2. Trade the Expansion
Bullish Breakout:
Triggered when the synthetic price crosses above the box top.
A green breakout marker appears below the price (triangle up).
This signals that price is breaking out of the compression zone with enough momentum to establish a meaningful structural move to the upside.
Bearish Breakout:
Triggered when the price crosses below the box bottom.
A red breakout marker appears above the price (triangle down).
Signals a breakdown out of the range to the downside.
⚪ Trend Following with the Trend Cloud
The Trend Cloud is a volatility-responsive band that adjusts to the system’s internal trend. In bullish conditions, it shifts to the up-color beneath price, and in bearish conditions, it flips to the down-color above price, giving a clear visual read of market direction.
The cloud effectively separates impulsive trend legs from noise, so you can align breakout trades only with the dominant directional regime.
Long Setups
Favor long setups (Break Up) when the price is traveling above or inside a bullish cloud.
Short Steups
Favor short setups (Break Down) when the price is below or inside a bearish cloud.
Ignore counter-trend breakouts that form directly against a strong, stable cloud unless you are intentionally trading mean reversion.
⚪ Breakout Management and Risk-Reward
Once a breakout occurs, the system instantly activates a directional trailing stop that follows the trend. For long setups, the stop stays below the price and moves upward as momentum builds. For short setups, it stays above the price and moves downward as the trend strengthens. If price hits the trailing stop, an X-cross appears on the chart to mark the exit, and the stop is reset for the next signal. You can adjust the sensitivity to make the stop tighter or more relaxed, depending on your preference.
When Risk-Reward Levels are enabled, the script also builds a complete trade structure around the breakout. It places an entry line at the breakout close, and projects two target levels forward. The area between entry and stop is shaded as risk, while the area toward the targets is shaded as reward. Labels update automatically as targets are reached, turning into a clear confirmation mark when a level is hit and signaling with an icon if the stop is touched.
Together, the trailing stop and risk-reward ladder create a clear, real-time map of each breakout’s progression, helping you manage risk, monitor targets, and follow the move with structure and confidence.
█ How It Works
⚪ Compression Detection & Range Formation
The system identifies quiet market phases where price contracts into narrow zones and stabilizes around a synthetic equilibrium level. These zones form the foundation for valid breakout opportunities.
Calculation: Persistence-based boundary tracking with volatility-normalized change detection and equilibrium anchoring to identify statistically constrained price regimes.
⚪ Breakout Engine
Breakouts occur only when the internal average breaks out of a validated compression zone, confirming that the market is transitioning from containment to expansion.
Calculation: Boundary-crossing logic on dispersion-expanded structures with directional state shifts encoded through threshold-gated transitions.
⚪ Trend State
A dynamic trend state guides directional bias, while the Trend Cloud visually expresses this bias directly on the chart, shifting beneath or above the price depending on the active regime.
Calculation: Dual-regime state modeling using filtered directional vectors, volatility-responsive offsets, and continuity enforcement to avoid noise-driven flips.
-----------------
Disclaimer
The content provided in my scripts, indicators, ideas, algorithms, and systems is for educational and informational purposes only. It does not constitute financial advice, investment recommendations, or a solicitation to buy or sell any financial instruments. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
Cerca negli script per "track"
Prob Stats PPIBW Prob Stats PPIBW - Data-Driven Trading Decisions
Transform historical price patterns into actionable probabilities. This indicator analyzes thousands of periods to show you the real odds behind pivot hits, range
expansions, inside bars, and weekend breakouts.
What It Tracks
Pivot Hit Rates (D/W/M/Q/6M/Y)
What percentage of pivot points get touched during their period? Includes recent period comparison to spot regime changes.
Example: "Daily: 82.3% (450/547) | L30: 76.7% (23/30)"
Previous Period Levels (D/W/M)
How often does current period break previous period's high or low? Only counts actual range expansion, not equilibrium crossings. Helps gauge breakout probability.
Inside Bar Analysis (D/W/M)
When price consolidates inside previous period's range, what are the odds of a breakout? Only appears when currently in an inside bar.
Weekend Breakdown
When Sat/Sun breaks Mon-Fri range, does the following week continue? Critical for crypto traders and weekend gap analysis.
Key Features
- Recent Period Comparison: See if recent behavior differs from historical averages
- Self-Documenting: Hover over any header for instant explanations
- Color-Coded Sections: Yellow (Pivots), Orange (Prev Period), Pink (Inside Bar), Green (Weekend)
- Blue Background: Recent stats highlighted for easy identification
- Dynamic Layout: Adapts based on market conditions
- Real-Time Updates: Includes current period for live probability tracking
How To Use
1. Add to any chart (best on Daily+ for maximum historical data)
2. Hover over column headers to understand each statistic
3. Compare historical vs recent probabilities
4. Use probabilities to inform position sizing and expectations
Example: Weekly pivot shows 78% historical hit rate but only 60% in last 30 weeks. Recent regime change suggests lower probability of test.
Technical Details
- Pine Script v6
- Rolling window arrays track last 30/30/12 periods for D/W/M
- Previous Period excludes EQ crossings for accurate stats
- Works on all timeframes, optimized for Daily+
- Configurable table position
Perfect For
Traders seeking data-driven confirmation, those wanting to quantify probability vs guessing, regime change detection, and crypto traders analyzing weekend patterns.
Note: Past performance doesn't guarantee future results. Use these statistics as one input in your overall trading strategy.
Liquidity Void Zone Detector [PhenLabs]📊 Liquidity Void Zone Detector
Version: PineScript™v6
📌 Description
The Liquidity Void Zone Detector is a sophisticated technical indicator designed to identify and visualize areas where price moved with abnormally low volume or rapid momentum, creating "voids" in market liquidity. These zones represent areas where insufficient trading activity occurred during price movement, often acting as magnets for future price action as the market seeks to fill these gaps.
Built on PineScript v6, this indicator employs a dual-detection methodology that analyzes both volume depletion patterns and price movement intensity relative to ATR. The revolutionary 3D visualization system uses three-layer polyline rendering with adaptive transparency and vertical offsets, creating genuine depth perception where low liquidity zones visually recede and high liquidity zones protrude forward. This makes critical market structure immediately apparent without cluttering your chart.
🚀 Points of Innovation
Dual detection algorithm combining volume threshold analysis and ATR-normalized price movement sensitivity for comprehensive void identification
Three-layer 3D visualization system with progressive transparency gradients (85%, 78%, 70%) and calculated vertical offsets for authentic depth perception
Intelligent state machine logic that tracks consecutive void bars and only renders zones meeting minimum qualification requirements
Dynamic strength scoring system (0-100 scale) that combines inverted volume ratios with movement intensity for accurate void characterization
Adaptive ATR-based spacing calculation that automatically adjusts 3D layering depth to match instrument volatility
Efficient memory management system supporting up to 100 simultaneous void visualizations with automatic array-based cleanup
🔧 Core Components
Volume Analysis Engine: Calculates rolling volume averages and compares current bar volume against dynamic thresholds to detect abnormally thin trading conditions
Price Movement Analyzer: Normalizes bar range against ATR to identify rapid price movements that indicate liquidity exhaustion regardless of instrument or timeframe
Void Tracking State Machine: Maintains persistent tracking of void start bars, price boundaries, consecutive bar counts, and cumulative strength across multiple bars
3D Polyline Renderer: Generates three-layer rectangular polylines with precise timestamp-to-bar index conversion and progressive offset calculations
Strength Calculation System: Combines volume component (inverted ratio capped at 100) with movement component (ATR intensity × 30) for comprehensive void scoring
🔥 Key Features
Automatic Void Detection: Continuously scans price action for low volume conditions or rapid movements, triggering void tracking when thresholds are exceeded
Real-Time Visualization: Creates 3D rectangular zones spanning from void initiation to termination, with color-coded depth indicating liquidity type
Adjustable Sensitivity: Configure volume threshold multiplier (0.1-2.0x), price movement sensitivity (0.5-5.0x), and minimum qualifying bars (1-10) for customized detection
Dual Color Coding: Separate visual treatment for low liquidity voids (receding red) and high liquidity zones (protruding green) based on 50-point strength threshold
Optional Compact Labels: Toggle LV (Low Volume) or HV (High Volume) circular labels at void centers for quick identification without visual clutter
Lookback Period Control: Adjust analysis window from 5 to 100 bars to match your trading timeframe and market volatility characteristics
Memory-Efficient Design: Automatically manages polyline and label arrays, deleting oldest elements when user-defined maximum is reached
Data Window Integration: Plots void detection binary, current strength score, and average volume for detailed analysis in TradingView's data window
🎨 Visualization
Three-Layer Depth System: Each void is rendered as three stacked polylines with progressive transparency (85%, 78%, 70%) and calculated vertical offsets creating authentic 3D appearance
Directional Depth Perception: Low liquidity zones recede with back layer most transparent; high liquidity zones protrude with front layer most transparent for instant visual differentiation
Adaptive Offset Spacing: Vertical separation between layers calculated as ATR(14) × 0.001, ensuring consistent 3D effect across different instruments and volatility regimes
Color Customization: Fully configurable base colors for both low liquidity zones (default: red with 80 transparency) and high liquidity zones (default: green with 80 transparency)
Minimal Chart Clutter: Closed polylines with matching line and fill colors create clean rectangular zones without unnecessary borders or visual noise
Background Highlight: Subtle yellow background (96% transparency) marks bars where void conditions are actively detected in real-time
Compact Labeling: Optional tiny circular labels with 60% transparent backgrounds positioned at void center points for quick reference
📖 Usage Guidelines
Detection Settings
Lookback Period: Default: 10 | Range: 5-100 | Number of bars analyzed for volume averaging and void detection. Lower values increase sensitivity to recent changes; higher values smooth detection across longer timeframes. Adjust based on your trading timeframe: short-term traders use 5-15, swing traders use 20-50, position traders use 50-100.
Volume Threshold: Default: 1.0 | Range: 0.1-2.0 (step 0.1) | Multiplier applied to average volume. Bars with volume below (average × threshold) trigger void conditions. Lower values detect only extreme volume depletion; higher values capture more moderate low-volume situations. Start with 1.0 and decrease to 0.5-0.7 for stricter detection.
Price Movement Sensitivity: Default: 1.5 | Range: 0.5-5.0 (step 0.1) | Multiplier for ATR-normalized price movement detection. Values above this threshold indicate rapid price changes suggesting liquidity voids. Increase to 2.0-3.0 for volatile instruments; decrease to 0.8-1.2 for ranging or low-volatility conditions.
Minimum Void Bars: Default: 10 | Range: 1-10 | Minimum consecutive bars exhibiting void conditions required before visualization is created. Filters out brief anomalies and ensures only sustained voids are displayed. Use 1-3 for scalping, 5-10 for intraday trading, 10+ for swing trading to match your time horizon.
Visual Settings
Low Liquidity Color: Default: Red (80% transparent) | Base color for zones where volume depletion or rapid movement indicates thin liquidity. These zones recede visually (back layer most transparent). Choose colors that contrast with your chart theme for optimal visibility.
High Liquidity Color: Default: Green (80% transparent) | Base color for zones with relatively higher liquidity compared to void threshold. These zones protrude visually (front layer most transparent). Ensure clear differentiation from low liquidity color.
Show Void Labels: Default: True | Toggle display of compact LV/HV labels at void centers. Disable for cleaner charts when trading; enable for analysis and review to quickly identify void types across your chart.
Max Visible Voids: Default: 50 | Range: 10-100 | Maximum number of void visualizations kept on chart. Each void uses 3 polylines, so setting of 50 maintains 150 total polylines. Higher values preserve more history but may impact performance on lower-end systems.
✅ Best Use Cases
Gap Fill Trading: Identify unfilled liquidity voids that price frequently returns to, providing high-probability retest and reversal opportunities when price approaches these zones
Breakout Validation: Distinguish genuine breakouts through established liquidity from false breaks into void zones that lack sustainable volume support
Support/Resistance Confluence: Layer void detection over key horizontal levels to validate structural integrity—levels within high liquidity zones are stronger than those in voids
Trend Continuation: Monitor for new void formation in trend direction as potential continuation zones where price may accelerate due to reduced resistance
Range Trading: Identify void zones within consolidation ranges that price tends to traverse quickly, helping to avoid getting caught in rapid moves through thin areas
Entry Timing: Wait for price to reach void boundaries rather than entering mid-void, as voids tend to be traversed quickly with limited profit-taking opportunities
⚠️ Limitations
Historical Pattern Indicator: Identifies past liquidity voids but cannot predict whether price will return to fill them or when filling might occur
No Volume on Forex: Indicator uses tick volume for forex pairs, which approximates but doesn't represent true trading volume, potentially affecting detection accuracy
Lagging Confirmation: Requires minimum consecutive bars (default 10) before void is visualized, meaning detection occurs after void formation begins
Trending Market Behavior: Strong trends driven by fundamental catalysts may create voids that remain unfilled for extended periods or permanently
Timeframe Dependency: Detection sensitivity varies significantly across timeframes; settings optimized for one timeframe may not perform well on others
No Directional Bias: Indicator identifies liquidity characteristics but provides no predictive signal for price direction after void detection
Performance Considerations: Higher max visible void settings combined with small minimum void bars can generate numerous visualizations impacting chart rendering speed
💡 What Makes This Unique
Industry-First 3D Visualization: Unlike flat volume or liquidity indicators, the three-layer rendering with directional depth perception provides instant visual hierarchy of liquidity quality
Dual-Mode Detection: Combines both volume-based and movement-based detection methodologies, capturing voids that single-approach indicators miss
Intelligent Qualification System: State machine logic prevents premature visualization by requiring sustained void conditions, reducing false signals and chart clutter
ATR-Normalized Analysis: All detection thresholds adapt to instrument volatility, ensuring consistent performance across stocks, forex, crypto, and futures without constant recalibration
Transparency-Based Depth: Uses progressive transparency gradients rather than colors or patterns to create depth, maintaining visual clarity while conveying information hierarchy
Comprehensive Strength Metrics: 0-100 void strength calculation considers both the degree of volume depletion and the magnitude of price movement for nuanced zone characterization
🔬 How It Works
Phase 1: Real-Time Detection
On each bar close, the indicator calculates average volume over the lookback period and compares current bar volume against the volume threshold multiplier
Simultaneously measures current bar's high-low range and normalizes it against ATR, comparing the result to price movement sensitivity parameter
If either volume falls below threshold OR movement exceeds sensitivity threshold, the bar is flagged as exhibiting void characteristics
Phase 2: Void Tracking & Qualification
When void conditions first appear, state machine initializes tracking variables: start bar index, initial top/bottom prices, consecutive bar counter, and cumulative strength accumulator
Each subsequent bar with void conditions extends the tracking, updating price boundaries to envelope all bars and accumulating strength scores
When void conditions cease, system checks if consecutive bar count meets minimum threshold; if yes, proceeds to visualization; if no, discards the tracking and resets
Phase 3: 3D Visualization Construction
Calculates average void strength by dividing cumulative strength by number of bars, then determines if void is low liquidity (>50 strength) or high liquidity (≤50 strength)
Generates three polyline layers spanning from start bar to end bar and from top price to bottom price, each with calculated vertical offset based on ATR
Applies progressive transparency (85%, 78%, 70%) with layer ordering creating recession effect for low liquidity zones and protrusion effect for high liquidity zones
Creates optional center label and pushes all visual elements into arrays for memory management
Phase 4: Memory Management & Display
Continuously monitors polyline array size (each void creates 3 polylines); when total exceeds max visible voids × 3, deletes oldest polylines via array.shift()
Similarly manages label array, removing oldest labels when count exceeds maximum to prevent memory accumulation over extended chart history
Plots diagnostic data to TradingView’s data window (void detection binary, current strength, average volume) for detailed analysis without cluttering main chart
💡 Note:
This indicator is designed to enhance your market structure analysis by revealing liquidity characteristics that aren’t visible through standard price and volume displays. For best results, combine void detection with your existing support/resistance analysis, trend identification, and risk management framework. Liquidity voids are descriptive of past market behavior and should inform positioning decisions rather than serve as standalone entry/exit signals. Experiment with detection parameters across different timeframes to find settings that align with your trading style and instrument characteristics.
Global M2 Money Supply Growth (GDP-Weighted)📊 Global M2 Money Supply Growth (GDP-Weighted)
This indicator tracks the weighted aggregate M2 money supply growth across the world's four largest economies: United States, China, Eurozone, and Japan. These economies represent approximately 69.3 trillion USD in combined GDP and account for the majority of global liquidity, making this a comprehensive macro indicator for analyzing worldwide monetary conditions.
════════════════════════════════════════════
🔧 KEY FEATURES:
📈 GDP-Weighted Aggregation
Each economy is weighted proportionally by its nominal GDP using 2025 IMF World Economic Outlook data:
• United States: 44.2% (30.62 trillion USD)
• China: 28.0% (19.40 trillion USD)
• Eurozone: 21.6% (15.0 trillion USD)
• Japan: 6.2% (4.28 trillion USD)
The weights are fully adjustable through the indicator settings, allowing you to update them annually as new IMF forecasts are released (typically April and October).
⏱️ Multiple Time Period Options
Choose between three calculation methods to analyze different timeframes:
• YoY (Year-over-Year): 12-month growth rate for identifying long-term liquidity trends and cycles
• MoM (Month-over-Month): 1-month growth rate for detecting short-term monetary policy shifts
• QoQ (Quarter-over-Quarter): 3-month growth rate for medium-term trend analysis
🔄 Advanced Offset Function
Shift the entire indicator forward by 0-365 days to test lead/lag relationships between global liquidity and asset prices. Research suggests a 56-70 day lag between M2 changes and Bitcoin price movements, but you can experiment with different offsets for various assets (equities, gold, commodities, etc.).
🌍 Individual Country Breakdown
Real-time display of each economy's M2 growth rate with:
• Current percentage change (YoY/MoM/QoQ)
• GDP weight contribution
• Color-coded values (green = monetary expansion, red = contraction)
📊 Smart Overlay Capability
Displays directly on your main price chart with an independent left-side scale, allowing you to visually correlate global liquidity trends with any asset's price action without cluttering the chart.
🔧 Customizable GDP Weights
All GDP values can be adjusted through the indicator settings without editing code, making annual updates simple and accessible for all users.
════════════════════════════════════════════
📡 DATA SOURCES:
All M2 money supply data is sourced from ECONOMICS (Trading Economics) for consistency and reliability:
• ECONOMICS:USM2 (United States)
• ECONOMICS:CNM2 (China)
• ECONOMICS:EUM2 (Eurozone)
• ECONOMICS:JPM2 (Japan)
All values are normalized to USD using current daily exchange rates (USDCNY, EURUSD, USDJPY) before GDP-weighted aggregation, ensuring accurate cross-country comparisons.
══════════════════════════════════════════════
💡 USE CASES & APPLICATIONS:
🔹 Liquidity Cycle Analysis
Track global monetary expansion/contraction cycles to identify when central banks are coordinating loose or tight monetary policies.
🔹 Market Timing & Risk Assessment
High M2 growth (>10%) historically correlates with risk-on environments and rising asset prices across crypto, equities, and commodities. Negative M2 growth signals monetary tightening and potential market corrections.
🔹 Bitcoin & Crypto Correlation
Compare with Bitcoin price using the offset feature to identify the optimal lag period. Many traders use 60-70 day offsets to predict crypto market movements based on liquidity changes.
🔹 Macro Portfolio Allocation
Use as a regime filter to adjust portfolio exposure: increase risk assets during liquidity expansion, reduce during contraction.
🔹 Central Bank Policy Divergence
Monitor individual country metrics to identify when major central banks are pursuing divergent policies (e.g., Fed tightening while China eases).
🔹 Inflation & Economic Forecasting
Rapid M2 growth often leads inflation by 12-18 months, making this a leading indicator for future inflation trends.
🔹 Recession Early Warning
Negative M2 growth is extremely rare and has preceded major recessions, making this a valuable risk management tool.
════════════════════════════════════════════
📊 INTERPRETATION GUIDE:
🟢 +10% or Higher
Aggressive monetary expansion, typically during crises (2001, 2008, 2020). The COVID-19 period saw M2 growth reach 20-27%, which preceded significant inflation and asset price surges. Strong bullish signal for risk assets.
🟢 +6% to +10%
Above-average liquidity growth. Central banks are providing stimulus beyond normal levels. Generally favorable for equities, crypto, and commodities.
🟡 +3% to +6%
Normal/healthy growth rate, roughly in line with GDP growth plus 2% inflation targets. Neutral environment with moderate support for risk assets.
🟠 0% to +3%
Slowing liquidity, potential tightening phase beginning. Central banks may be raising rates or reducing balance sheets. Caution warranted for high-beta assets.
🔴 Negative Growth
Monetary contraction - extremely rare. Only occurred during aggressive Fed tightening in 2022-2023. Strong warning signal for risk assets, often precedes recessions or major market corrections.
════════════════════════════════════════════
🎯 OPTIMAL USAGE:
📅 Recommended Timeframes:
• Daily or Weekly charts for macro analysis
• Monthly charts for very long-term trends
💹 Compatible Asset Classes:
• Cryptocurrencies (especially Bitcoin, Ethereum)
• Equity indices (S&P 500, NASDAQ, global markets)
• Commodities (Gold, Silver, Oil)
• Forex majors (DXY correlation analysis)
⚙️ Suggested Settings:
• Default: YoY calculation with 0 offset for current liquidity conditions
• Bitcoin traders: YoY with 60-70 day offset for predictive analysis
• Short-term traders: MoM with 0 offset for recent policy changes
• Quarterly rebalancers: QoQ with 0 offset for medium-term trends
════════════════════════════════════════════
📋 VISUAL DISPLAY:
The indicator plots a blue line showing the selected growth metric (YoY/MoM/QoQ), with a dashed reference line at 0% to clearly identify expansion vs. contraction regimes.
A comprehensive table in the top-right corner displays:
• Current global M2 growth rate (large, prominent display)
• Individual country breakdowns with their GDP weights
• Color-coded growth rates (green for positive, red for negative)
════════════════════════════════════════════
🔄 MAINTENANCE & UPDATES:
GDP weights should be updated annually (ideally in April or October) when the IMF releases new World Economic Outlook forecasts. Simply adjust the four GDP input parameters in the indicator settings - no code editing required.
The relative GDP proportions between the Big 4 economies change very gradually (typically <1-2% per year), so even if you update weights once every 1-2 years, the impact on the indicator's accuracy is minimal.
════════════════════════════════════════════
💭 TRADING PHILOSOPHY:
This indicator embodies the principle that "liquidity drives markets." By tracking the combined M2 money supply of the world's largest economies, weighted by their economic size, you gain insight into the fundamental liquidity conditions that underpin all asset prices.
Unlike single-country M2 indicators, this GDP-weighted approach captures the true global picture, accounting for the fact that US monetary policy has 2x the impact of Japanese policy due to economic size differences.
Perfect for macro-focused traders, long-term investors, and anyone seeking to understand the "tide that lifts all boats" in financial markets.
════════════════════════════════════════════
Created for traders and investors who incorporate global liquidity trends into their decision-making process. Best used alongside other technical and fundamental analysis tools for comprehensive market assessment.
⚠️ Disclaimer: M2 money supply is a lagging macroeconomic indicator. Past correlations do not guarantee future results. Always use proper risk management and combine with other analysis methods.
Price Drop CounterThe Price Drop Counter is a very basic statistical indicator.
See it as an analytical tool that tracks how many times an asset's price has dropped by a specified percentage from its recent peak within a defined date range.
The indicator monitors the highest price reached and counts each occurrence when the price falls by your chosen threshold, then resets its peak tracking point after each drop is registered.
Uses
Volatility Assessment: Measure how frequently significant price corrections occur during specific periods
Market Behavior Analysis: Compare drop frequency across different timeframes or market conditions
Risk Evaluation: Identify assets or periods with higher downside volatility
Historical Pattern Recognition: Study how often major pullbacks happened during bull or bear markets
Backtesting Support: Analyze how your strategy would perform based on the frequency of drawdowns
How to use it
Add the indicator to your TradingView chart
Configure the Percent Drop (%) to define your threshold (default: 10%). The indicator will count each time price falls by this percentage from the most recent high
IMPORTANT Set your Start Date and End Date to analyze a specific period of interest
The blue step-line plot shows the cumulative count of drops within your date range
Adjust the percentage threshold based on your analysis needs - use smaller values (2-5%) for more frequent signals or larger values (15-20%) for major corrections only
The counter resets its high-water mark after each qualifying drop, allowing it to track multiple sequential drops within the same period.
macd sma20
### MACD_sma20 – Multi-Timeframe MACD Pullback & SMA20 Dashboard
This script is a complete trading toolkit built around a **MACD pullback strategy** combined with **multi-timeframe SMA20 filters**, volume analysis, and a compact information panel.
It is designed for traders who like to:
* Trade **MACD pullbacks above the moving average**
* Track **key SMA20 levels across multiple timeframes** (Daily, 3-Day, Weekly, Monthly)
* Quickly see whether **current price is above or below those reference levels**
* Use **clean visual signals** for entries and exits, instead of staring at raw indicator values
---
### Core Features
#### 1. MACD Pullback Long Signal (Green Triangle Up)
The script detects a **bullish MACD pullback** pattern:
* MACD line is still **above** the signal line
* Both MACD line and histogram **pull back** for several bars
* Then MACD turns back up again, with price trading **above the local SMA20**
When this “pullback and re-acceleration” is confirmed, a **green triangle below the bar** is plotted as a **long entry signal**.
There is also an optional filter:
* **Weekly SMA20 filter**:
If enabled, long signals are only triggered when **current price is above the Weekly SMA20**, helping you stay on the right side of the higher-timeframe trend.
---
#### 2. Bearish Pullback Confirmation Signal (Red Triangle Down)
On the short side, the script detects a **bearish pullback confirmation** based on:
* A recent **high-volume bearish candle** (large down bar with volume above a multiple of the 20-period volume average)
* At least a minimum number of **negative MACD histogram bars**
* MACD line moving closer to the signal line (loss of momentum)
* Price recovering back up near the **top of that high-volume bearish candle**, then starting to fall again while MACD stays positive
When all conditions align, the script prints a **red triangle above the bar**, indicating a **bearish pullback confirmation** – often a good area to take profits on longs or consider short/hedge setups.
---
#### 3. Signal History Tracking
For both long and short signals, the script internally tracks the **most recent three signals**:
* Timestamp of the signal
* Price at the signal
* Short-term percentage change into the signal
This is mainly for internal use and future expansion, but already gives you a structured signal history if you want to extend or connect the logic later.
---
### Multi-Timeframe SMA20 Dashboard (Bottom-Right Panel)
One of the most useful parts of this script is the **compact dashboard table** in the **bottom-right corner** of the chart. It updates in real time and shows:
1. **Current Price**
2. **Daily SMA20** – value + whether price is above/below
3. **3-Day SMA20** – value + whether price is above/below
4. **Weekly SMA20** – value + whether price is above/below
5. **Monthly SMA20** – value + whether price is above/below
6. **RSI** (current timeframe)
For each timeframe’s SMA20:
* If **price ≥ SMA20**, the status cell is **green** with a ✓
* If **price < SMA20**, the status cell is **red** with a ✗
This gives you, at a glance:
* Is the market in a **short-term uptrend or downtrend** (Daily SMA20)?
* Is the **swing / position trend** healthy (3D & Weekly SMA20)?
* Is the broader **macro structure** supportive (Monthly SMA20)?
You don’t need to manually switch timeframes or add multiple moving averages – the script does all of that for you automatically using `request.security`.
---
### Alerts
The script comes with two built-in alert conditions:
* **MACD回踩转多信号 (MACD pullback bullish signal)**
* **空头回抽确认信号 (Bearish pullback confirmation signal)**
You can attach TradingView alerts to these conditions to get notified whenever a new long or bearish-confirmation setup appears, even when you’re not watching the chart.
---
### How to Use It in Your Trading
1. **Choose your main trading timeframe**
* For intraday swing: 15m / 1h / 4h
* For swing / position: 4h / Daily
2. **Watch the bottom-right SMA20 panel**
* If most higher-timeframe SMA20 rows are **green**, you are trading **with the larger trend**.
* If they are **mixed or mostly red**, you’re either counter-trend or in a choppy transition zone.
3. **Use the green MACD pullback signals**
* Prefer long setups when:
* The **Weekly and Monthly SMA20 rows are green**, and
* The signal appears **above the Daily SMA20**
* This stacks multiple edges: trend + pullback + momentum re-acceleration.
4. **Use the red bearish confirmation signals for risk management**
* Take partial profits on longs when a red signal appears near resistance.
* Consider hedge/short opportunities if higher-timeframe SMA20 rows are already red or turning red.
5. **Use RSI as a context indicator**
* Combine with overbought/oversold zones or your own RSI thresholds for additional confirmation.
---
### Why This Script Is Useful
* **Trend awareness across timeframes**:
You always know where current price sits relative to the Daily / 3-Day / Weekly / Monthly SMA20 – without switching charts.
* **Clear, rule-based signals**:
The MACD logic is explicit and systematic, focused on **pullbacks within trends** rather than random crossovers.
* **Volume-aware bearish logic**:
High-volume bearish candles often mark important supply zones. The script builds this idea directly into the short-side confirmation logic.
* **Visual and intuitive**:
Green/Red triangles + Green/Red table cells make it easy to interpret even if you are not a heavy indicator user.
* **Flexible**:
All key parameters (MACD lengths, SMA length, volume threshold, lookback period, RSI length, weekly filter) are customizable, so you can adapt it to different markets (crypto, stocks, FX) and timeframes.
---
In short, this script is a **multi-timeframe MACD pullback system with an integrated SMA20 dashboard**, suitable for swing traders and position traders who want a structured, visually clean way to align entries with trend and momentum while keeping an eye on higher-timeframe levels.
Reversal Point Dynamics - Machine Learning⇋ Reversal Point Dynamics - Machine Learning
RPD Machine Learning: Self-Adaptive Multi-Armed Bandit Trading System
RPD Machine Learning is an advanced algorithmic trading system that implements genuine machine learning through contextual multi-armed bandits, reinforcement learning, and online adaptation. Unlike traditional indicators that use fixed rules, RPD learns from every trade outcome , automatically discovers which strategies work in current market conditions, and continuously adapts without manual intervention .
Core Innovation: The system deploys six distinct trading policies (ranging from aggressive trend-following to conservative range-bound strategies) and uses LinUCB contextual bandit algorithms with Random Fourier Features to learn which policy performs best in each market regime. After the initial learning phase (50-100 trades), the system achieves autonomous adaptation , automatically shifting between policies as market conditions evolve.
Target Users: Quantitative traders, algorithmic trading developers, systematic traders, and data-driven investors who want a system that adapts over time . Suitable for stocks, futures, forex, and cryptocurrency on any liquid instrument with >100k daily volume.
The Problem This System Solves
Traditional Technical Analysis Limitations
Most trading systems suffer from three fundamental challenges :
Fixed Parameters: Static settings (like "buy when RSI < 30") work well in backtests but may struggle when markets change character. What worked in low-volatility environments may not work in high-volatility regimes.
Strategy Degradation: Manual optimization (curve-fitting) produces systems that perform well on historical data but may underperform in live trading. The system never adapts to new market conditions.
Cognitive Overload: Running multiple strategies simultaneously forces traders to manually decide which one to trust. This leads to hesitation, late entries, and inconsistent execution.
How RPD Machine Learning Addresses These Challenges
Automated Strategy Selection: Instead of requiring you to choose between trend-following and mean-reversion strategies, RPD runs all six policies simultaneously and uses machine learning to automatically select the best one for current conditions. The decision happens algorithmically, removing human hesitation.
Continuous Learning: After every trade, the system updates its understanding of which policies are working. If the market shifts from trending to ranging, RPD automatically detects this through changing performance patterns and adjusts selection accordingly.
Context-Aware Decisions: Unlike simple voting systems that treat all conditions equally, RPD analyzes market context (ADX regime, entropy levels, volatility state, volume patterns, time of day, historical performance) and learns which combinations of context features correlate with policy success.
Machine Learning Architecture: What Makes This "Real" ML
Component 1: Contextual Multi-Armed Bandits (LinUCB)
What Is a Multi-Armed Bandit Problem?
Imagine facing six slot machines, each with unknown payout rates. The exploration-exploitation dilemma asks: Should you keep pulling the machine that's worked well (exploitation) or try others that might be better (exploration)? RPD solves this for trading policies.
Academic Foundation:
RPD implements Linear Upper Confidence Bound (LinUCB) from the research paper "A Contextual-Bandit Approach to Personalized News Article Recommendation" (Li et al., 2010, WWW Conference). This algorithm is used in content recommendation and ad placement systems.
How It Works:
Each policy (AggressiveTrend, ConservativeRange, VolatilityBreakout, etc.) is treated as an "arm." The system maintains:
Reward History: Tracks wins/losses for each policy
Contextual Features: Current market state (8-10 features including ADX, entropy, volatility, volume)
Uncertainty Estimates: Confidence in each policy's performance
UCB Formula: predicted_reward + α × uncertainty
The system selects the policy with highest UCB score , balancing proven performance (predicted_reward) with potential for discovery (uncertainty bonus). Initially, all policies have high uncertainty, so the system explores broadly. After 50-100 trades, uncertainty decreases, and the system focuses on known-performing policies.
Why This Matters:
Traditional systems pick strategies based on historical backtests or user preference. RPD learns from actual outcomes in your specific market, on your timeframe, with your execution characteristics.
Component 2: Random Fourier Features (RFF)
The Non-Linearity Challenge:
Market relationships are often non-linear. High ADX may indicate favorable conditions when volatility is normal, but unfavorable when volatility spikes. Simple linear models struggle to capture these interactions.
Academic Foundation:
RPD implements Random Fourier Features from "Random Features for Large-Scale Kernel Machines" (Rahimi & Recht, 2007, NIPS). This technique approximates kernel methods (like Support Vector Machines) while maintaining computational efficiency for real-time trading.
How It Works:
The system transforms base features (ADX, entropy, volatility, etc.) into a higher-dimensional space using random projections and cosine transformations:
Input: 8 base features
Projection: Through random Gaussian weights
Transformation: cos(W×features + b)
Output: 16 RFF dimensions
This allows the bandit to learn non-linear relationships between market context and policy success. For example: "AggressiveTrend performs well when ADX >25 AND entropy <0.6 AND hour >9" becomes naturally encoded in the RFF space.
Why This Matters:
Without RFF, the system could only learn "this policy has X% historical performance." With RFF, it learns "this policy performs differently in these specific contexts" - enabling more nuanced selection.
Component 3: Reinforcement Learning Stack
Beyond bandits, RPD implements a complete RL framework :
Q-Learning: Value-based RL that learns state-action values. Maps 54 discrete market states (trend×volatility×RSI×volume combinations) to 5 actions (4 policies + no-trade). Updates via Bellman equation after each trade. Converges toward optimal policy after 100-200 trades.
TD(λ) with Eligibility Traces: Extension of Q-Learning that propagates credit backwards through time . When a trade produces an outcome, TD(λ) updates not just the final state-action but all states visited during the trade, weighted by eligibility decay (λ=0.90). This accelerates learning from multi-bar trades.
Policy Gradient (REINFORCE): Learns a stochastic policy directly from 12 continuous market features without discretization. Uses gradient ascent to increase probability of actions that led to positive outcomes. Includes baseline (average reward) for variance reduction.
Meta-Learning: The system learns how to learn by adapting its own learning rates based on feature stability and correlation with outcomes. If a feature (like volume ratio) consistently correlates with success, its learning rate increases. If unstable, rate decreases.
Why This Matters:
Q-Learning provides fast discrete decisions. Policy Gradient handles continuous features. TD(λ) accelerates learning. Meta-learning optimizes the optimization. Together, they create a robust, multi-approach learning system that adapts more quickly than any single algorithm.
Component 4: Policy Momentum Tracking (v2 Feature)
The Recency Challenge:
Standard bandits treat all historical data equally. If a policy performed well historically but struggles in current conditions due to regime shift, the system may be slow to adapt because historical success outweighs recent underperformance.
RPD's Solution:
Each policy maintains a ring buffer of the last 10 outcomes. The system calculates:
Momentum: recent_win_rate - global_win_rate (range: -1 to +1)
Confidence: consistency of recent results (1 - variance)
Policies with positive momentum (recent outperformance) get an exploration bonus. Policies with negative momentum and high confidence (consistent recent underperformance) receive a selection penalty.
Effect: When markets shift, the system detects the shift more quickly through momentum tracking, enabling faster adaptation than standard bandits.
Signal Generation: The Core Algorithm
Multi-Timeframe Fractal Detection
RPD identifies reversal points using three complementary methods :
1. Quantum State Analysis:
Divides price range into discrete states (default: 6 levels)
Peak signals require price in top states (≥ state 5)
Valley signals require price in bottom states (≤ state 1)
Prevents mid-range signals that may struggle in strong trends
2. Fractal Geometry:
Identifies swing highs/lows using configurable fractal strength
Confirms local extremum with neighboring bars
Validates reversal only if price crosses prior extreme
3. Multi-Timeframe Confirmation:
Analyzes higher timeframe (4× default) for alignment
MTF confirmation adds probability bonus
Designed to reduce false signals while preserving valid setups
Probability Scoring System
Each signal receives a dynamic probability score (40-99%) based on:
Base Components:
Trend Strength: EMA(velocity) / ATR × 30 points
Entropy Quality: (1 - entropy) × 10 points
Starting baseline: 40 points
Enhancement Bonuses:
Divergence Detection: +20 points (price/momentum divergence)
RSI Extremes: +8 points (RSI >65 for peaks, <40 for valleys)
Volume Confirmation: +5 points (volume >1.2× average)
Adaptive Momentum: +10 points (strong directional velocity)
MTF Alignment: +12 points (higher timeframe confirms)
Range Factor: (high-low)/ATR × 3 - 1.5 points (volatility adjustment)
Regime Bonus: +8 points (trending ADX >25 with directional agreement)
Penalties:
High Entropy: -5 points (entropy >0.85, chaotic price action)
Consolidation Regime: -10 points (ADX <20, no directional conviction)
Final Score: Clamped to 40-99% range, classified as ELITE (>85%), STRONG (75-85%), GOOD (65-75%), or FAIR (<65%)
Entropy-Based Quality Filter
What Is Entropy?
Entropy measures randomness in price changes . Low entropy indicates orderly, directional moves. High entropy indicates chaotic, unpredictable conditions.
Calculation:
Count up/down price changes over adaptive period
Calculate probability: p = ups / total_changes
Shannon entropy: -p×log(p) - (1-p)×log(1-p)
Normalized to 0-1 range
Application:
Entropy <0.5: Highly ordered (ELITE signals possible)
Entropy 0.5-0.75: Mixed (GOOD signals)
Entropy >0.85: Chaotic (signals blocked or heavily penalized)
Why This Matters:
Prevents trading during choppy, news-driven conditions where technical patterns may be less reliable. Automatically raises quality bar when market is unpredictable.
Regime Detection & Market Microstructure - ADX-Based Regime Classification
RPD uses Wilder's Average Directional Index to classify markets:
Bull Trend: ADX >25, +DI > -DI (directional conviction bullish)
Bear Trend: ADX >25, +DI < -DI (directional conviction bearish)
Consolidation: ADX <20 (no directional conviction)
Transitional: ADX 20-25 (forming direction, ambiguous)
Filter Logic:
Blocks all signals during Transitional regime (avoids trading during uncertain conditions)
Blocks Consolidation signals unless ADX ≥ Min Trend Strength
Adds probability bonus during strong trends (ADX >30)
Effect: Designed to reduce signal frequency while focusing on higher-quality setups.
Divergence Detection
Bearish Divergence:
Price makes higher high
Velocity (price momentum) makes lower high
Indicates weakening upward pressure → SHORT signal quality boost
Bullish Divergence:
Price makes lower low
Velocity makes higher low
Indicates weakening downward pressure → LONG signal quality boost
Bonus: Adds probability points and additional acceleration factor. Divergence signals have historically shown higher success rates in testing.
Hierarchical Policy System - The Six Trading Policies
1. AggressiveTrend (Policy 0):
Probability Threshold: 60% (trades more frequently)
Entropy Threshold: 0.70 (tolerates moderate chaos)
Stop Multiplier: 2.5× ATR (wider stops for trends)
Target Multiplier: 5.0R (larger targets)
Entry Mode: Pyramid (scales into winners)
Best For: Strong trending markets, breakouts, momentum continuation
2. ConservativeRange (Policy 1):
Probability Threshold: 75% (more selective)
Entropy Threshold: 0.60 (requires order)
Stop Multiplier: 1.8× ATR (tighter stops)
Target Multiplier: 3.0R (modest targets)
Entry Mode: Single (one-shot entries)
Best For: Range-bound markets, low volatility, mean reversion
3. VolatilityBreakout (Policy 2):
Probability Threshold: 65% (moderate)
Entropy Threshold: 0.80 (accepts high entropy)
Stop Multiplier: 3.0× ATR (wider stops)
Target Multiplier: 6.0R (larger targets)
Entry Mode: Tiered (splits entry)
Best For: Compression breakouts, post-consolidation moves, gap opens
4. EntropyScalp (Policy 3):
Probability Threshold: 80% (very selective)
Entropy Threshold: 0.40 (requires extreme order)
Stop Multiplier: 1.5× ATR (tightest stops)
Target Multiplier: 2.5R (quick targets)
Entry Mode: Single
Best For: Low-volatility grinding moves, tight ranges, highly predictable patterns
5. DivergenceHunter (Policy 4):
Probability Threshold: 70% (quality-focused)
Entropy Threshold: 0.65 (balanced)
Stop Multiplier: 2.2× ATR (moderate stops)
Target Multiplier: 4.5R (balanced targets)
Entry Mode: Tiered
Best For: Divergence-confirmed reversals, exhaustion moves, trend climax
6. AdaptiveBlend (Policy 5):
Probability Threshold: 68% (balanced)
Entropy Threshold: 0.75 (balanced)
Stop Multiplier: 2.0× ATR (standard)
Target Multiplier: 4.0R (standard)
Entry Mode: Single
Best For: Mixed conditions, general trading, fallback when no clear regime
Policy Clustering (Advanced/Extreme Modes)
Policies are grouped into three clusters based on regime affinity:
Cluster 1 (Trending): AggressiveTrend, DivergenceHunter
High regime affinity (0.8): Performs well when ADX >25
Moderate vol affinity (0.6): Works in various volatility
Cluster 2 (Ranging): ConservativeRange, AdaptiveBlend
Low regime affinity (0.3): Better suited for ADX <20
Low vol affinity (0.4): Optimized for calm markets
Cluster 3 (Breakout): VolatilityBreakout
Moderate regime affinity (0.6): Works in multiple regimes
High vol affinity (0.9): Requires high volatility for optimal characteristics
Hierarchical Selection Process:
Calculate cluster scores based on current regime and volatility
Select best-matching cluster
Run UCB selection within chosen cluster
Apply momentum boost/penalty
This two-stage process reduces learning time - instead of choosing among 6 policies from scratch, system first narrows to 1-2 policies per cluster, then optimizes within cluster.
Risk Management & Position Sizing
Dynamic Kelly Criterion Sizing (Optional)
Traditional Fixed Sizing Challenge:
Using the same position size for all signal probabilities may be suboptimal. Higher-probability signals could justify larger positions, lower-probability signals smaller positions.
Kelly Formula:
f = (p × b - q) / b
Where:
p = win probability (from signal score)
q = loss probability (1 - p)
b = win/loss ratio (average_win / average_loss)
f = fraction of capital to risk
RPD Implementation:
Uses Fractional Kelly (1/4 Kelly default) for safety. Full Kelly is theoretically optimal but can recommend large position sizes. Fractional Kelly reduces volatility while maintaining adaptive sizing benefits.
Enhancements:
Probability Bonus: Normalize(prob, 65, 95) × 0.5 multiplier
Divergence Bonus: Additional sizing on divergence signals
Regime Bonus: Additional sizing during strong trends (ADX >30)
Momentum Adjustment: Hot policies receive sizing boost, cold policies receive reduction
Safety Rails:
Minimum: 1 contract (floor)
Maximum: User-defined cap (default 10 contracts)
Portfolio Heat: Max total risk across all positions (default 4% equity)
Multi-Mode Stop Loss System
ATR Mode (Default):
Stop = entry ± (ATR × base_mult × policy_mult)
Consistent risk sizing
Ignores market structure
Best for: Futures, forex, algorithmic trading
Structural Mode:
Finds swing low (long) or high (short) over last 20 bars
Identifies fractal pivots within lookback
Places stop below/above structure + buffer (0.1× ATR)
Best for: Stocks, instruments that respect structure
Hybrid Mode (Intelligent):
Attempts structural stop first
Falls back to ATR if:
Structural level is invalid (beyond entry)
Structural stop >2× ATR away (too wide)
Best for: Mixed instruments, adaptability
Dynamic Adjustments:
Breakeven: Move stop to entry + 1 tick after 1.0R profit
Trailing: Trail stop 0.8R behind price after 1.5R profit
Timeout: Force close after 30 bars (optional)
Tiered Entry System
Challenge: Equal sizing on all signals may not optimize capital allocation relative to signal quality.
Solution:
Tier 1 (40% of size): Enters immediately on all signals
Tier 2 (60% of size): Enters only if probability ≥ Tier 2 trigger (default 75%)
Example:
Calculated optimal size: 10 contracts
Signal probability: 72%
Tier 2 trigger: 75%
Result: Enter 4 contracts only (Tier 1)
Same signal at 80% probability
Result: Enter 10 contracts (4 Tier 1 + 6 Tier 2)
Effect: Automatically scales size to signal quality, optimizing capital allocation.
Performance Optimization & Learning Curve
Warmup Phase (First 50 Trades)
Purpose: Ensure all policies get tested before system focuses on preferred strategies.
Modifications During Warmup:
Probability thresholds reduced 20% (65% becomes 52%)
Entropy thresholds increased 20% (more permissive)
Exploration rate stays high (30%)
Confidence width (α) doubled (more exploration)
Why This Matters:
Without warmup, system might commit to early-performing policy without testing alternatives. Warmup forces thorough exploration before focusing on best-performing strategies.
Curriculum Learning
Phase 1 (Trades 1-50): Exploration
Warmup active
All policies tested
High exploration (30%)
Learning fundamental patterns
Phase 2 (Trades 50-100): Refinement
Warmup ended, thresholds normalize
Exploration decaying (30% → 15%)
Policy preferences emerging
Meta-learning optimizing
Phase 3 (Trades 100-200): Specialization
Exploration low (15% → 8%)
Clear policy preferences established
Momentum tracking fully active
System focusing on learned patterns
Phase 4 (Trades 200+): Maturity
Exploration minimal (8% → 5%)
Regime-policy relationships learned
Auto-adaptation to market shifts
Stable performance expected
Convergence Indicators
System is learning well when:
Policy switch rate decreasing over time (initially ~50%, should drop to <20%)
Exploration rate decaying smoothly (30% → 5%)
One or two policies emerge with >50% selection frequency
Performance metrics stabilizing over time
Consistent behavior in similar market conditions
System may need adjustment when:
Policy switch rate >40% after 100 trades (excessive exploration)
Exploration rate not decaying (parameter issue)
All policies showing similar selection (not differentiating)
Performance declining despite relaxed thresholds (underlying signal issue)
Highly erratic behavior after learning phase
Advanced Features
Attention Mechanism (Extreme Mode)
Challenge: Not all features are equally important. Trading hour might matter more than price-volume correlation, but standard approaches treat them equally.
Solution:
Each RFF dimension has an importance weight . After each trade:
Calculate correlation: sign(feature - 0.5) × sign(reward)
Update importance: importance += correlation × 0.01
Clamp to range
Effect: Important features get amplified in RFF transformation, less important features get suppressed. System learns which features correlate with successful outcomes.
Temporal Context (Extreme Mode)
Challenge: Current market state alone may be incomplete. Historical context (was volatility rising or falling?) provides additional information.
Solution:
Includes 3-period historical context with exponential decay (0.85):
Current features (weight 1.0)
1 bar ago (weight 0.85)
2 bars ago (weight 0.72)
Effect: Captures momentum and acceleration of market features. System learns patterns like "rising volatility with falling entropy" that may precede significant moves.
Transfer Learning via Episodic Memory
Short-Term Memory (STM):
Last 20 trades
Fast adaptation to immediate regime
High learning rate
Long-Term Memory (LTM):
Condensed historical patterns
Preserved knowledge from past regimes
Low learning rate
Transfer Mechanism:
When STM fills (20 trades), patterns consolidated into LTM . When similar regime recurs later, LTM provides faster adaptation than starting from scratch.
Practical Implementation Guide - Recommended Settings by Instrument
Futures (ES, NQ, CL):
Adaptive Period: 20-25
ML Mode: Advanced
RFF Dimensions: 16
Policies: 6
Base Risk: 1.5%
Stop Mode: ATR or Hybrid
Timeframe: 5-15 min
Forex Majors (EURUSD, GBPUSD):
Adaptive Period: 25-30
ML Mode: Advanced
RFF Dimensions: 16
Policies: 6
Base Risk: 1.0-1.5%
Stop Mode: ATR
Timeframe: 5-30 min
Cryptocurrency (BTC, ETH):
Adaptive Period: 20-25
ML Mode: Extreme (handles non-stationarity)
RFF Dimensions: 32 (captures complexity)
Policies: 6
Base Risk: 1.0% (volatility consideration)
Stop Mode: Hybrid
Timeframe: 15 min - 4 hr
Stocks (Large Cap):
Adaptive Period: 25-30
ML Mode: Advanced
RFF Dimensions: 16
Policies: 5-6
Base Risk: 1.5-2.0%
Stop Mode: Structural or Hybrid
Timeframe: 15 min - Daily
Scaling Strategy
Phase 1 (Testing - First 50 Trades):
Max Contracts: 1-2
Goal: Validate system on your instrument
Monitor: Performance stabilization, learning progress
Phase 2 (Validation - Trades 50-100):
Max Contracts: 2-3
Goal: Confirm learning convergence
Monitor: Policy stability, exploration decay
Phase 3 (Scaling - Trades 100-200):
Max Contracts: 3-5
Enable: Kelly sizing (1/4 Kelly)
Goal: Optimize capital efficiency
Monitor: Risk-adjusted returns
Phase 4 (Full Deployment - Trades 200+):
Max Contracts: 5-10
Enable: Full momentum tracking
Goal: Sustained consistent performance
Monitor: Ongoing adaptation quality
Limitations & Disclaimers
Statistical Limitations
Learning Sample Size: System requires minimum 50-100 trades for basic convergence, 200+ trades for robust learning. Early performance (first 50 trades) may not reflect mature system behavior.
Non-Stationarity Risk: Markets change over time. A system trained on one market regime may need time to adapt when conditions shift (typically 30-50 trades for adjustment).
Overfitting Possibility: With 16-32 RFF dimensions and 6 policies, system has substantial parameter space. Small sample sizes (<200 trades) increase overfitting risk. Mitigated by regularization (λ) and fractional Kelly sizing.
Technical Limitations
Computational Complexity: Extreme mode with 32 RFF dimensions, 6 policies, and full RL stack requires significant computation. May perform slowly on lower-end systems or with many other indicators loaded.
Pine Script Constraints:
No true matrix inversion (uses diagonal approximation for LinUCB)
No cryptographic RNG (uses market data as entropy)
No proper random number generation for RFF (uses deterministic pseudo-random)
These approximations reduce mathematical precision compared to academic implementations but remain functional for trading applications.
Data Requirements: Needs clean OHLCV data. Missing bars, gaps, or low liquidity (<100k daily volume) can degrade signal quality.
Forward-Looking Bias Disclaimer
Reward Calculation Uses Future Data: The RL system evaluates trades using an 8-bar forward-looking window. This means when a position enters at bar 100, the reward calculation considers price movement through bar 108.
Why This is Disclosed:
Entry signals do NOT look ahead - decisions use only data up to entry bar
Forward data used for learning only, not signal generation
In live trading, system learns identically as bars unfold in real-time
Simulates natural learning process (outcomes are only known after trades complete)
Implication: Backtested metrics reflect this 8-bar evaluation window. Live performance may vary if:
- Positions held longer than 8 bars
- Slippage/commissions differ from backtest settings
- Market microstructure changes (wider spreads, different execution quality)
Risk Warnings
No Guarantee of Profit: All trading involves substantial risk of loss. Machine learning systems can fail if market structure fundamentally changes or during unprecedented events.
Maximum Drawdown: With 1.5% base risk and 4% max total risk, expect potential drawdowns. Historical drawdowns do not predict future drawdowns. Extreme market conditions can exceed expectations.
Black Swan Events: System has not been tested under: flash crashes, trading halts, circuit breakers, major geopolitical shocks, or other extreme events. Such events can exceed stop losses and cause significant losses.
Leverage Risk: Futures and forex involve leverage. Adverse moves combined with leverage can result in losses exceeding initial investment. Use appropriate position sizing for your risk tolerance.
System Failures: Code bugs, broker API failures, internet outages, or exchange issues can prevent proper execution. Always monitor automated systems and maintain appropriate safeguards.
Appropriate Use
This System Is:
✅ A machine learning framework for adaptive strategy selection
✅ A signal generation system with probabilistic scoring
✅ A risk management system with dynamic sizing
✅ A learning system designed to adapt over time
This System Is NOT:
❌ A price prediction system (does not forecast exact prices)
❌ A guarantee of profits (can and will experience losses)
❌ A replacement for due diligence (requires monitoring and understanding)
❌ Suitable for complete beginners (requires understanding of ML concepts, risk management, and trading fundamentals)
Recommended Use:
Paper trade for 100 signals before risking capital
Start with minimal position sizing (1-2 contracts) regardless of calculated size
Monitor learning progress via dashboard
Scale gradually over several months only after consistent results
Combine with fundamental analysis and broader market context
Set account-level risk limits (e.g., maximum drawdown threshold)
Never risk more than you can afford to lose
What Makes This System Different
RPD implements academically-derived machine learning algorithms rather than simple mathematical calculations or optimization:
✅ LinUCB Contextual Bandits - Algorithm from WWW 2010 conference (Li et al.)
✅ Random Fourier Features - Kernel approximation from NIPS 2007 (Rahimi & Recht)
✅ Q-Learning, TD(λ), REINFORCE - Standard RL algorithms from Sutton & Barto textbook
✅ Meta-Learning - Learning rate adaptation based on feature correlation
✅ Online Learning - Real-time updates from streaming data
✅ Hierarchical Policies - Two-stage selection with clustering
✅ Momentum Tracking - Recent performance analysis for faster adaptation
✅ Attention Mechanism - Feature importance weighting
✅ Transfer Learning - Episodic memory consolidation
Key Differentiators:
Actually learns from trade outcomes (not just parameter optimization)
Updates model parameters in real-time (true online learning)
Adapts to changing market regimes (not static rules)
Improves over time through reinforcement learning
Implements published ML algorithms with proper citations
Conclusion
RPD Machine Learning represents a different approach from traditional technical analysis to adaptive, self-learning systems . Instead of manually optimizing parameters (which can overfit to historical data), RPD learns behavior patterns from actual trading outcomes in your specific market.
The combination of contextual bandits, reinforcement learning, random fourier features, hierarchical policy selection, and momentum tracking creates a multi-algorithm learning system designed to handle non-stationary markets better than static approaches.
After the initial learning phase (50-100 trades), the system achieves autonomous adaptation - automatically discovering which strategies work in current conditions and shifting allocation without human intervention. This represents an approach where systems adapt over time rather than remaining static.
Use responsibly. Paper trade extensively. Scale gradually. Understand that past performance does not guarantee future results and all trading involves risk of loss.
Taking you to school. — Dskyz, Trade with insight. Trade with anticipation.
Multi-Symbol EMA Crossover Scanner with Multi-Timeframe AnalysisDescription
What This Indicator Does:
This indicator is a comprehensive market scanner that monitors up to 10 symbols simultaneously across 4 different timeframes (15-minute, 1-hour, 4-hour, and daily) to detect exponential moving average (EMA) crossovers in real-time. Instead of manually checking multiple charts and timeframes for EMA crossover signals, this scanner automatically does the work for you and presents all detected signals in a clean, organized table that updates continuously throughout the trading session.
Key Features:
Multi-Symbol Monitoring: Scan up to 10 different symbols at once (stocks, forex, crypto, or any TradingView symbol)
Multi-Timeframe Analysis: Simultaneously tracks 4 timeframes (15m, 1H, 4H, 1D) with toggle options to enable/disable each
Comprehensive EMA Pairs: Detects crossovers between all major EMA combinations: 20×50, 20×100, 20×200, 50×100, 50×200, and 100×200
Real-Time Signal Feed: Displays the most recent signals in a sorted table (newest first) with timestamp, direction, price, and EMA pair information
Session Filter: Built-in time filter (default 10:00-18:00) to focus on specific trading hours and avoid pre-market/after-hours noise
Pagination System: Navigate through signals using a page selector when you have more signals than fit in one view
Signal Statistics: Footer displays total signals, bullish/bearish breakdown, and page navigation hints
Customizable Display: Choose table position (4 corners), signals per page (5-20), and maximum signal history (10-100)
How It Works:
The scanner uses the request.security() function to fetch EMA data from multiple symbols and timeframes simultaneously. For each symbol-timeframe combination, it calculates four exponential moving averages (20, 50, 100, and 200 periods) and monitors for crossovers:
Bullish Crossovers (▲ Green):
Faster EMA crosses above slower EMA
Indicates potential upward momentum
Common entry signals for long positions
Bearish Crossovers (▼ Red):
Faster EMA crosses below slower EMA
Indicates potential downward momentum
Common entry signals for short positions or exits
The scanner prioritizes crossovers involving faster EMAs (20×50) over slower ones (100×200), as faster crossovers typically generate more frequent signals. Each detected crossover is stored with its timestamp, allowing the scanner to sort signals chronologically and remove duplicates within the same timeframe.
Signal Table Columns:
Sym: Symbol name (abbreviated, e.g., "ASELS" instead of "BIST:ASELS")
TF: Timeframe where the crossover occurred (15m, 1h, 4h, 1D)
⏰: Exact time of the crossover (HH:MM format in Istanbul timezone)
↕: Direction indicator (▲ bullish green / ▼ bearish red)
₺: Price level where the crossover occurred (average of the two EMAs)
MA: Which EMA pair crossed (e.g., "20×50", "50×200")
How to Use:
For Day Traders:
Enable 15m and 1h timeframes
Monitor symbols from your watchlist
Use crossovers as entry timing signals in the direction of the larger trend
Adjust the time filter to match your trading session (e.g., market open to 2 hours before close)
For Swing Traders:
Enable 4h and 1D timeframes
Focus on 50×200 and 100×200 crossovers (golden/death crosses)
Look for multiple timeframe confluence (same symbol showing bullish crossovers on both 4h and 1D)
Use as a pre-market scanner to identify potential setups for the day
For Multi-Market Traders:
Mix symbols from different markets (stocks, forex, crypto)
Use the scanner to identify which markets are showing the most momentum
Track relative strength by comparing crossover frequency across symbols
Identify rotation opportunities when one asset shows bullish signals while another shows bearish
Setup Recommendations:
Default BIST (Turkish Stock Market) Setup:
The code comes pre-configured with 10 popular BIST stocks:
ASELS, EKGYO, THYAO, AKBNK, PGSUS, ASTOR, OTKAR, ALARK, ISCTR, BIMAS
For US Stocks:
Replace with symbols like: NASDAQ:AAPL, NASDAQ:TSLA, NASDAQ:NVDA, NYSE:JPM, etc.
For Forex:
Use pairs like: FX:EURUSD, FX:GBPUSD, FX:USDJPY, OANDA:XAUUSD, etc.
For Crypto:
Use exchanges like: BINANCE:BTCUSDT, COINBASE:ETHUSD, BINANCE:SOLUSDT, etc.
Settings Guide:
Symbol List (10 inputs):
Enter any valid TradingView symbol in "EXCHANGE:TICKER" format
Use symbols you actively trade or monitor
Mix different asset classes if desired
Timeframe Toggles:
15 Minutes: High-frequency signals, best for day trading
1 Hour: Balanced frequency, good for intraday swing trades
4 Hours: Lower frequency, quality swing trade signals
1 Day: Low frequency, major trend changes only
Time Filter:
Start Hour (10): Beginning of your trading session
End Hour (18): End of your trading session
Prevents signals during low-liquidity periods
Adjust to match your market's active hours
Display Settings:
Table Position: Choose corner placement (doesn't interfere with other indicators)
Max Signals (40): Total historical signals to keep in memory
Signals Per Page (10): How many rows to show at once
Page Number: Navigate through signal history (auto-adjusts to available pages)
What Makes This Original:
Multi-symbol scanners exist on TradingView, but this indicator's originality comes from:
Comprehensive EMA Pair Coverage: Most scanners focus on 1-2 EMA pairs, this monitors 6 different combinations simultaneously
Unified Multi-Timeframe View: Presents signals from 4 timeframes in a single, chronologically sorted feed rather than separate panels
Session-Aware Filtering: Built-in time filter prevents signal overload from 24-hour markets
Smart Pagination: Handles large signal volumes gracefully with page navigation instead of scrolling
Signal Deduplication: Prevents the same crossover from appearing multiple times if it persists across several bars
Price-at-Cross Recording: Captures the exact price where the crossover occurred, not just that it happened
Real-Time Statistics: Live tracking of bullish vs bearish signal distribution
Trading Strategy Examples:
Trend Confirmation Strategy:
Find a symbol showing bullish crossover on 1D (major trend change)
Wait for pullback
Enter when 1h shows bullish crossover (confirmation)
Exit when 1h shows bearish crossover
Multi-Timeframe Confluence:
Look for symbols appearing multiple times with same direction
Example: ASELS shows ▲ on both 4h and 1D = strong bullish signal
Avoid symbols showing conflicting signals (▲ on 1h but ▼ on 4h)
Rotation Scanner:
Monitor 10+ symbols from the same sector
Identify which are turning bullish (▲) first
Enter leaders, avoid laggards
Rotate out when crossovers turn bearish (▼)
Important Considerations:
Not a Complete System: EMA crossovers should be confirmed with price action, volume, and support/resistance analysis
Whipsaw Risk: During consolidation, EMAs can cross back and forth frequently (especially on 15m timeframe)
Lag: EMAs are lagging indicators; crossovers occur after the move has already begun
False Signals: More common during sideways markets; work best in trending environments
Symbol Limits: TradingView has limits on request.security() calls; this scanner uses 40 calls (10 symbols × 4 timeframes)
Performance: On lower-end devices, scanning 10 symbols across 4 timeframes may cause slight delays in chart updates
Best Practices:
Start with 5 symbols and 2 timeframes, then expand as you get comfortable
Use in conjunction with a main chart for price context
Don't trade every signal—filter for high-quality setups
Backtest your favorite EMA pairs on your symbols to understand their reliability
Adjust the time filter to exclude lunch hours if your market has low midday volume
Check the footer statistics—if you're getting 50+ signals per day, tighten your time filter or reduce symbols
Technical Notes:
Uses lookahead=barmerge.lookahead_off to prevent future data leakage
Signals are stored in arrays and sorted by timestamp (newest first)
Automatic daily reset clears old signals to prevent memory buildup
Table dynamically resizes based on signal count
All times displayed in Europe/Istanbul timezone (configurable in code)
Trend Bars with Counter Table# TradingView Trend Bar Indicator Explained
## Indicator Overview
This is a TradingView indicator designed to identify and count **Trend Bars**. It not only visually marks strong bullish and bearish bars on the chart but also displays a data table in the upper right corner that tracks the distribution of trend bars across different periods, helping traders quickly assess market bias.
## Core Concept: What is a Trend Bar?
The indicator defines two types of trend bars:
### Bull Trend Bar
- **Condition**: Close > Open (bullish candle)
- **Strength Requirement**: Body size ≥ 75% of total candle range
```
Body Length = |Close - Open|
Total Candle Range = High - Low
Criteria: Body Length ≥ 0.75 × Total Candle Range
```
This means both upper and lower wicks are very short, representing a very strong bullish candle.
### Bear Trend Bar
- **Condition**: Close < Open (bearish candle)
- **Strength Requirement**: Body size ≥ 75% of total candle range
Similarly, this represents a strong bearish candle with minimal wicks and a full body.
## Visual Markers
The indicator marks qualifying candles with:
- **Green upward arrow**: Bull trend bar, appears below the candle
- **Red downward arrow**: Bear trend bar, appears above the candle
## Statistical Function
The indicator uses a **rolling array** (storing up to 1000 trend bars) to track historical data, then counts trend bar distribution across 5 different periods:
| Period | Statistical Range |
|--------|------------------|
| Group 1 | Last 7 trend bars |
| Group 2 | Last 15 trend bars |
| Group 3 | Last 21 trend bars |
| Group 4 | Last 29 trend bars |
| Group 5 | Last 35 trend bars |
**Note**: This counts "the last N trend bars," not "the last N candles." Only candles meeting the trend bar criteria are included.
## Data Table Interpretation
The table in the upper right corner contains 5 columns:
1. **Last N**: The set statistical range (7, 15, 21, 29, 35)
2. **Total**: Actual number of trend bars counted (may be less than target initially)
3. **Bull**: Number of bull trend bars (displayed in green)
4. **Bear**: Number of bear trend bars (displayed in red)
5. **Bias**: Market bias
- "bull" (green): More bull trend bars
- "bear" (red): More bear trend bars
## Practical Applications
### 1. Assess Short-term Momentum
Check the distribution of the last 7 trend bars. If bull trend bars dominate (e.g., 5:2), it indicates strong short-term buying pressure.
### 2. Identify Trend Strength
If multiple periods show the same Bias direction, the trend is very clear. For example, all 5 periods showing "bull" is a strong upward signal.
### 3. Spot Trend Reversals
When short-term bias (7 bars) opposes long-term bias (35 bars), it may signal a trend change in progress.
### 4. Combine with Other Indicators
Use this indicator alongside moving averages, support/resistance levels, and other tools to improve trading decision accuracy.
## Technical Highlights
- **Dynamic Array Management**: Uses `array.unshift()` to add new data at the array's beginning, ensuring the latest trend bars are always first
- **Efficient Statistics**: Quickly calculates bull/bear distribution through loop iteration over specified array ranges
- **Adaptive Display**: Shows actual available count when historical data is insufficient
- **Real-time Updates**: Only updates the table on the last bar to avoid unnecessary calculations
## Conclusion
The core value of this indicator lies in **quantifying price action**. By identifying strong candles with full bodies and clear direction, then tracking their distribution, traders can quickly grasp the balance of market forces and make more informed trading decisions. Whether for intraday trading or swing trading, this tool provides valuable reference information.
Ultimate RSI Suite [BigBeluga]🔵 OVERVIEW
The Ultimate RSI Suite elevates the classic RSI into a full professional trading system.
It combines momentum analysis, advanced divergence detection, volatility-based RSI channels, multi-timeframe signals, deviation tracking, and reversal alerts into one powerful tool.
This is no ordinary RSI — it’s a complete momentum intelligence engine designed to identify trend strength, exhaustion, breakout conditions, and reliable reversal points with high precision.
⚠️ Note:
This suite enhances RSI with MTF dashboards, dynamic channels, deviation logic, and smart alerting — ideal for scalpers, swing traders, and institutional-style trend followers.
🔵 CONCEPTS
Measures market momentum to detect overbought/oversold zones and trend health
Tracks RSI behavior relative to dynamic channels (BB/Keltner/Donchian)
Identifies regular bullish & bearish divergences
Detects deviation moves after divergence to confirm trend continuation or exhaustion
Multi-timeframe RSI conditions reveal higher-timeframe confluence
Reversal triggers confirm early momentum shifts
Overbought/oversold gradients visually highlight exhaustion zones
🔵 FEATURES
Classic + Enhanced RSI with configurable lookback & price source
RSI-Channel System (Bollinger, Keltner, Donchian) for volatility-adaptive trend structure
RSI-Smoothing MA for trend direction filters
RSI Reversal Signals for early trend inflection detection
RSI Reversal Signals Deviation Levels +1 / +2 for advanced continuation confirmation
Overbought/Oversold Gradient Zones at 35/65 or user-defined levels
Divergence Engine for bullish & bearish momentum exhaustion signals
On-Chart Divergence & Signals (full overlay capability)
Divergence Engine Deviation Levels +1 / +2 for advanced continuation confirmation
Multi-Timeframe Dashboard (RSI OB/OS, signals, divergences, channel breaks)
• Hover your mouse over any signal cell to see how many bars ago it was triggered
• Signals automatically expire after 50 bars
Smart Alerts for divergence, reversals, channel breaks, and deviation triggers
🔵 HOW TO USE
Enter long when RSI reverses from oversold & prints bullish divergence or a ▲ signal
Enter short when RSI reverses from overbought & prints bearish divergence or ▼
Use channel breaks to confirm momentum expansions or trend shifts
Look for deviation crosses (+1 / +2) for strong confirmation after divergence
Track MTF table — more timeframe agreement = stronger conviction
Avoid trading against MTF RSI extremes (OB/OS stacked zones)
Combine with market structure or volume-based tools for maximum precision
🔵 ALERTS
Includes full automation suite:
Bullish / Bearish divergence
Reversal signals (▲ / ▼)
Channel breakouts (Up/Down)
Deviation +1 / +2 confirmation triggers
Extra RSI signal deviation alerts for precision continuation reads
Great for automated systems, confirmation models, and high-probability intraday/swing entries.
🔵 CONCLUSION
The Ultimate RSI Suite transforms RSI into a smart momentum-analysis system.
With multi-timeframe logic, dynamic channels, advanced divergence/deviation systems, and powerful visual cues, it offers institutional-grade trend, exhaustion, and reversal detection.
If you rely on RSI, this toolkit provides superior clarity, deeper context, and stronger execution timing — making it an elite upgrade for professional traders.
Script a pagamento
Structure Pro by MurshidfxInspired by the 'mentfx Structure' indicator created by Anton (mentfx) on TradingView,
## Overview
Structure Pro tracks market structure by maintaining an adaptive dealing range and its midpoint. Swing highs and lows become structural boundaries, and the script responds to confirmed breakouts by recalculating the active range. Labels highlight the latest trend flip so the chart stays readable while the range evolves.
## Core Logic
- Detects swing highs/lows using a configurable pivot strength and promotes confirmed pivots to structural levels.
- Applies a percentage buffer to decide when price truly breaks structure; once triggered, the opposite boundary is recalculated with an anchor search that looks back through historical bars.
- Computes equilibrium as the midpoint between the current structural high and low so you can gauge premium versus discount zones.
- Emits a single BULL or BEAR label when the trend state changes, keeping only the most recent signal on the chart.
## How to Use
1. Open a clean chart and apply only this script.
2. Select a swing strength that matches the scale you want to monitor (lower values for responsive intraday swings, higher values for broader moves).
3. Tune the structure sensitivity percentage if you prefer tighter or looser confirmation before declaring a breakout.
4. Track DRH/DRL for the current dealing range, use the equilibrium line as a mean-reversion guide, and look to the BULL/BEAR label for structure confirmation.
5. Combine the levels with your own execution, risk, and position rules—this script does not manage orders.
## Inputs
- Swing Point Strength: bars required on both sides to confirm a pivot.
- Structure Break Sensitivity: percentage buffer applied to the range before calling a breakout.
- Dealing Range display: toggles for visibility, line width/color, label text, and label size.
- Equilibrium display: line style, width, and color controls.
- Trend Signals: enable/disable labels, adjust text size, and pick label colors.
## Notes
- Designed for live structure tracking; the script relies on confirmed pivots and does not peek into future data.
- Built to be chart-agnostic for standard candles; non-standard chart types can distort the measurements.
- Published open-source so traders can review and verify the implementation details.
Zero Lag Trend Signals (MTF) [Quant Trading] V7Overview
The Zero Lag Trend Signals (MTF) V7 is a comprehensive trend-following strategy that combines Zero Lag Exponential Moving Average (ZLEMA) with volatility-based bands to identify high-probability trade entries and exits. This strategy is designed to reduce lag inherent in traditional moving averages while incorporating dynamic risk management through ATR-based stops and multiple exit mechanisms.
This is a longer term horizon strategy that takes limited trades. It is not a high frequency trading and therefore will also have limited data and not > 100 trades.
How It Works
Core Signal Generation:
The strategy uses a Zero Lag EMA (ZLEMA) calculated by applying an EMA to price data that has been adjusted for lag:
Calculate lag period: floor((length - 1) / 2)
Apply lag correction: src + (src - src )
Calculate ZLEMA: EMA of lag-corrected price
Volatility bands are created using the highest ATR over a lookback period multiplied by a band multiplier. These bands are added to and subtracted from the ZLEMA line to create upper and lower boundaries.
Trend Detection:
The strategy maintains a trend variable that switches between bullish (1) and bearish (-1):
Long Signal: Triggers when price crosses above ZLEMA + volatility band
Short Signal: Triggers when price crosses below ZLEMA - volatility band
Optional ZLEMA Trend Confirmation:
When enabled, this filter requires ZLEMA to show directional momentum before entry:
Bullish Confirmation: ZLEMA must increase for 4 consecutive bars
Bearish Confirmation: ZLEMA must decrease for 4 consecutive bars
This additional filter helps avoid false signals in choppy or ranging markets.
Risk Management Features:
The strategy includes multiple stop-loss and take-profit mechanisms:
Volatility-Based Stops: Default stop-loss is placed at ZLEMA ± volatility band
ATR-Based Stops: Dynamic stop-loss calculated as entry price ± (ATR × multiplier)
ATR Trailing Stop: Ratcheting stop-loss that follows price but never moves against position
Risk-Reward Profit Target: Take-profit level set as a multiple of stop distance
Break-Even Stop: Moves stop to entry price after reaching specified R:R ratio
Trend-Based Exit: Closes position when price crosses EMA in opposite direction
Performance Tracking:
The strategy includes optional features for monitoring and analyzing trades:
Floating Statistics Table: Displays key metrics including win rate, GOA (Gain on Account), net P&L, and max drawdown
Trade Log Labels: Shows entry/exit prices, P&L, bars held, and exit reason for each closed trade
CSV Export Fields: Outputs trade data for external analysis
Default Strategy Settings
Commission & Slippage:
Commission: 0.1% per trade
Slippage: 3 ticks
Initial Capital: $1,000
Position Size: 100% of equity per trade
Main Calculation Parameters:
Length: 70 (range: 70-7000) - Controls ZLEMA calculation period
Band Multiplier: 1.2 - Adjusts width of volatility bands
Entry Conditions (All Disabled by Default):
Use ZLEMA Trend Confirmation: OFF - Requires ZLEMA directional momentum
Re-Enter on Long Trend: OFF - Allows multiple entries during sustained trends
Short Trades:
Allow Short Trades: OFF - Strategy is long-only by default
Performance Settings (All Disabled by Default):
Use Profit Target: OFF
Profit Target Risk-Reward Ratio: 2.0 (when enabled)
Dynamic TP/SL (All Disabled by Default):
Use ATR-Based Stop-Loss & Take-Profit: OFF
ATR Length: 14
Stop-Loss ATR Multiplier: 1.5
Profit Target ATR Multiplier: 2.5
Use ATR Trailing Stop: OFF
Trailing Stop ATR Multiplier: 1.5
Use Break-Even Stop-Loss: OFF
Move SL to Break-Even After RR: 1.5
Use Trend-Based Take Profit: OFF
EMA Exit Length: 9
Trade Data Display (All Disabled by Default):
Show Floating Stats Table: OFF
Show Trade Log Labels: OFF
Enable CSV Export: OFF
Trade Label Vertical Offset: 0.5
Backtesting Date Range:
Start Date: January 1, 2018
End Date: December 31, 2069
Important Usage Notes
Default Configuration: The strategy operates in its most basic form with default settings - using only ZLEMA crossovers with volatility bands and volatility-based stop-losses. All advanced features must be manually enabled.
Stop-Loss Priority: If multiple stop-loss methods are enabled simultaneously, the strategy will use whichever condition is hit first. ATR-based stops override volatility-based stops when enabled.
Long-Only by Default: Short trading is disabled by default. Enable "Allow Short Trades" to trade both directions.
Performance Monitoring: Enable the floating stats table and trade log labels to visualize strategy performance during backtesting.
Exit Mechanisms: The strategy can exit trades through multiple methods: stop-loss hit, take-profit reached, trend reversal, or trailing stop activation. The trade log identifies which exit method was used.
Re-Entry Logic: When "Re-Enter on Long Trend" is enabled with ZLEMA trend confirmation, the strategy can take multiple long positions during extended uptrends as long as all entry conditions remain valid.
Capital Efficiency: Default setting uses 100% of equity per trade. Adjust "default_qty_value" to manage position sizing based on risk tolerance.
Realistic Backtesting: Strategy includes commission (0.1%) and slippage (3 ticks) to provide realistic performance expectations. These values should be adjusted based on your broker and market conditions.
Recommended Use Cases
Trending Markets: Best suited for markets with clear directional moves where trend-following strategies excel
Medium to Long-Term Trading: The default length of 70 makes this strategy more appropriate for swing trading rather than scalping
Risk-Conscious Traders: Multiple stop-loss options allow traders to customize risk management to their comfort level
Backtesting & Optimization: Comprehensive performance tracking features make this strategy ideal for testing different parameter combinations
Limitations & Considerations
Like all trend-following strategies, performance may suffer in choppy or ranging markets
Default 100% position sizing means full capital exposure per trade - consider reducing for conservative risk management
Higher length values (70+) reduce signal frequency but may improve signal quality
Multiple simultaneous risk management features may create conflicting exit signals
Past performance shown in backtests does not guarantee future results
Customization Tips
For more aggressive trading:
Reduce length parameter (minimum 70)
Decrease band multiplier for tighter bands
Enable short trades
Use lower profit target R:R ratios
For more conservative trading:
Increase length parameter
Enable ZLEMA trend confirmation
Use wider ATR stop-loss multipliers
Enable break-even stop-loss
Reduce position size from 100% default
For optimal choppy market performance:
Enable ZLEMA trend confirmation
Increase band multiplier
Use tighter profit targets
Avoid re-entry on trend continuation
Visual Elements
The strategy plots several elements on the chart:
ZLEMA line (color-coded by trend direction)
Upper and lower volatility bands
Long entry markers (green triangles)
Short entry markers (red triangles, when enabled)
Stop-loss levels (when positions are open)
Take-profit levels (when enabled and positions are open)
Trailing stop lines (when enabled and positions are open)
Optional ZLEMA trend markers (triangles at highs/lows)
Optional trade log labels showing complete trade information
Exit Reason Codes (for CSV Export)
When CSV export is enabled, exit reasons are coded as:
0 = Manual/Other
1 = Trailing Stop-Loss
2 = Profit Target
3 = ATR Stop-Loss
4 = Trend Change
Conclusion
Zero Lag Trend Signals V7 provides a robust framework for trend-following with extensive customization options. The strategy balances simplicity in its core logic with sophisticated risk management features, making it suitable for both beginner and advanced traders. By reducing moving average lag while incorporating volatility-based signals, it aims to capture trends earlier while managing risk through multiple configurable exit mechanisms.
The modular design allows traders to start with basic trend-following and progressively add complexity through ZLEMA confirmation, multiple stop-loss methods, and advanced exit strategies. Comprehensive performance tracking and export capabilities make this strategy an excellent tool for systematic testing and optimization.
Note: This strategy is provided for educational and backtesting purposes. All trading involves risk. Past performance does not guarantee future results. Always test thoroughly with paper trading before risking real capital, and adjust position sizing and risk parameters according to your risk tolerance and account size.
================================================================================
TAGS:
================================================================================
trend following, ZLEMA, zero lag, volatility bands, ATR stops, risk management, swing trading, momentum, trend confirmation, backtesting
================================================================================
CATEGORY:
================================================================================
Strategies
================================================================================
CHART SETUP RECOMMENDATIONS:
================================================================================
For optimal visualization when publishing:
Use a clean chart with no other indicators overlaid
Select a timeframe that shows multiple trade signals (4H or Daily recommended)
Choose a trending asset (crypto, forex major pairs, or trending stocks work well)
Show at least 6-12 months of data to demonstrate strategy across different market conditions
Enable the floating stats table to display key performance metrics
Ensure all indicator lines (ZLEMA, bands, stops) are clearly visible
Use the default chart type (candlesticks) - avoid Heikin Ashi, Renko, etc.
Make sure symbol information and timeframe are clearly visible
================================================================================
COMPLIANCE NOTES:
================================================================================
✅ Open-source publication with complete code visibility
✅ English-only title and description
✅ Detailed explanation of methodology and calculations
✅ Realistic commission (0.1%) and slippage (3 ticks) included
✅ All default parameters clearly documented
✅ Performance limitations and risks disclosed
✅ No unrealistic claims about performance
✅ No guaranteed results promised
✅ Appropriate for public library (original trend-following implementation with ZLEMA)
✅ Educational disclaimers included
✅ All features explained in detail
================================================================================
CandelaCharts - Session Opening📝 Overview
The CandelaCharts – Session Opening indicator highlights a custom session window, builds the live high/low as the session unfolds, and then publishes finalized Range High , Range Low , and Consequent Encroachment (Mid) levels once the window closes. A subtle one‑bar divider marks each new session start, and a shaded box visualizes the evolving range while the session is active.
📦 Features
Discover the core tools this indicator provides—from live range tracking to post‑session levels and alerts.
Custom Session Window – Track any intraday opening window you define (e.g., 09:00–10:00).
Timezone Control – Align sessions precisely with your market using selectable timezones (e.g., America/New_York, GMT±X).
Live Session Box – A translucent box expands in real time as highs/lows update during the session.
Post‑Session Levels – Finalized Range High , Range Low , and CE (Mid) lines print only after the session completes to avoid interim noise.
Session Divider – A one‑bar background tint clearly marks the first bar of each session.
Alerts – Receive notifications at session start and end.
⚙️ Settings
Configure timing, timezone alignment, visuals, and toggles to match your market and workflow.
Session – Defines the specific time range for the session window (e.g., 0900-1000). During this window the indicator tracks the running high/low.
Timezone – Specifies the timezone used to interpret the session window, ensuring alignment with exchange hours.
Colors – Selects the colors for Range High (Up), Range Low (Down), and the session Background box/divider.
Session Range – Shows the finalized Range High/Low/Mid lines outside of the session; lines appear starting one bar after the session closes.
Session Dividers – Enables the one‑bar background tint on the session’s first bar.
⚡️ Showcase
Preview a simple chart example with Session Opening applied.
🚨 Alerts
Set notifications for key moments: when a session begins and when it ends.
Session Start : Triggers on the first bar inside the configured session window.
Session End : Triggers on the first bar after the session window closes.
⚠️ Disclaimer
This section clarifies the risks and intended use.
Trading involves significant risk, and many participants may incur losses. The content on this site is not intended as financial advice and should not be interpreted as such. Decisions to buy, sell, hold, or trade securities, commodities, or other financial instruments carry inherent risks and are best made with guidance from qualified financial professionals. Past performance is not indicative of future results.
Previous Day & Week High/Low LevelsPrevious Day & Week High/Low Levels is a precision tool designed to help traders easily identify the most relevant price levels that often act as strong support or resistance areas in the market. It automatically plots the previous day’s and week’s highs and lows, as well as the current day’s developing internal high and low. These levels are crucial reference points for intraday, swing, and even position traders who rely on price action and liquidity behavior.
Key Features
Previous Day High/Low:
The indicator automatically draws horizontal lines marking the highest and lowest prices from the previous trading day.
These levels are widely recognized as potential zones where the market may react again — either rejecting or breaking through them.
Previous Week High/Low:
The script also tracks and displays the high and low from the last completed trading week.
Weekly levels tend to represent stronger liquidity pools and broader institutional zones, which makes them especially important when aligning higher timeframe context with lower timeframe entries.
Internal Daily High/Low (Real-Time Tracking):
While the day progresses, the indicator dynamically updates the current day’s internal high and low.
This allows traders to visualize developing market structure, identify intraday ranges, and anticipate potential breakouts or liquidity sweeps.
Multi-Timeframe Consistency:
All levels — daily and weekly — remain visible across any chart timeframe, from 1 minute to 1 day or higher.
This ensures traders can maintain perspective and avoid losing track of key zones when switching views.
Customizable Visuals:
The colors, line thickness, and label visibility can be easily adjusted to match personal charting preferences.
This makes the indicator adaptable to any trading style or layout, whether minimalistic or detailed.
How to Use
Identify Key Reaction Zones:
Observe how price interacts with the previous day and week levels. Rejections, consolidations, or clean breakouts around these lines often signal strong liquidity areas or potential directional moves.
Combine with Market Structure or Liquidity Concepts:
The indicator works perfectly with supply and demand analysis, liquidity sweeps, order block strategies, or simply classic support/resistance techniques.
Scalping and Intraday Trading:
On lower timeframes (1m–15m), the daily levels help identify intraday turning points.
On higher timeframes (1h–4h or daily), the weekly levels provide broader context and directional bias.
Risk Management and Planning:
Using these levels as reference points allows for more precise stop placement, target setting, and overall trade management.
Why This Indicator Helps
Markets often react strongly around previous highs and lows because these zones contain trapped liquidity, pending orders, or institutional decision points.
By having these areas automatically mapped out, traders gain a clear and objective view of where price is likely to respond — without needing to manually draw lines every day or week.
Whether you’re a beginner still learning about price structure, or an advanced trader refining entries within liquidity zones, this tool simplifies the process and keeps your charts clean, consistent, and data-driven.
ICT Essentials [LDT]ICT Essentials
Overview
ICT Essentials is an all-in-one trading utility built to create a natural and efficient workflow for ICT-based traders.
Every component has been designed to integrate seamlessly and update dynamically across timeframes.
The indicator focuses on clarity, performance and customization, allowing traders to tailor every part of their trading experience.
Equal Highs & Lows
This feature automatically detects and marks Equal Highs (EQH) and Equal Lows (EQL) with full control over visuals and behavior.
Users can customize line colors, widths, and styles, label size, color, background transparency and text offset.
The logic uses an optimized scanning and caching system that maintains smooth performance even on higher timeframes.
It provides a precise and adaptive way to identify structural liquidity points whilst keeping the chart clean and readable.
Killzones & Session Pivots
Plots the main trading sessions such as Asia, London and New York (AM, Lunch, PM) with full flexibility and styling options.
Each session can be enabled or disabled individually, with its own color, transparency and label preferences.
Session highs and lows are automatically tracked and plotted as pivots with extension modes like Until Mitigated or Past Mitigation.
This system gives traders the ability to organize market sessions exactly how they prefer whilst keeping the chart consistent and efficient.
Daily Pivots and Tier System
Alongside session pivots, the script tracks daily highs and lows to provide a broader structural view of price. These pivots are stored and displayed on the chart with their appearance updating automatically when price interacts with them.
The system includes a unique tier-based visibility filter that maintains a clean chart by preventing duplicate or overlapping pivots. Recent daily pivots are cached and compared to session pivots and when two levels fall within a defined proximity, the redundant one is automatically hidden. This creates a clear hierarchy of daily and session levels, keeping the most relevant structure visible whilst removing noise.
All aspects of the daily pivot system are fully customizable, including the number of tracked pivots, color, style settings and how mitigated levels are handled. The caching and filtering logic ensures smooth performance and a visually organized workspace even as the data updates in real time.
Key Times
Allows up to five custom key time markers such as the Midnight Open, 6:00 AM or 10:00 AM.
Each marker can be fully customized with its own text, color, line style and thickness.
This makes it simple to visualize key reaction points that align with each traders timing model.
Higher Timeframe Candles
Displays higher timeframe candles such as 1H, 4H or Daily directly on the active chart to provide context without switching views.
Users can customize body, wick and border colors, along with adding optional trace lines for the open, close, high and low and can also show the countdown timers for remaining candle time.
Adjustable spacing, positioning and label visibility makes the display blend naturally with any trading setup.
This module helps traders connect multiple timeframes visually in a clean and intuitive way.
Watermark
Adds a customizable watermark with title, subtitle and symbol or timeframe information.
Every element can be adjusted for color, size, transparency, alignment and position.
The result is a polished, professional chart layout that adapts to the user's personal style.
Optimization and Design
ICT Essentials is built for performance, using cached arrays and lightweight calculations to maintain responsiveness on all timeframes.
Each feature can be toggled individually to suit the traders focus or system performance.
The script delivers a fluid, customizable and highly optimized trading experience designed to feel natural and effortless in day-to-day use.
Credits
This script takes reference and inspiration from several open-source indicators:
Equal Highs and Lows by jzstur
ICT HTF Candles (fadi) by fadizeidan
ICT Killzones + Pivots EP by tradeforopp
AG FX - Watermark by AGFXTRADING
All components have been refactored, optimized and unified into a single framework for a smoother and more efficient workflow.
Session First 5-Min High/LowHere's a professional description for your indicator:
Session First 5-Min High/Low Marker
This indicator automatically identifies and marks the high and low price levels established during the first 5 minutes of major trading sessions, helping traders identify key intraday support and resistance zones.
Key Features:
Tracks three major trading sessions in IST (Indian Standard Time):
Asian Session: 5:30 AM - 5:35 AM
London Session: 12:30 PM - 12:35 PM
New York Session: 5:30 PM - 5:35 PM
Draws horizontal lines at the highest and lowest prices reached during each session's opening 5-minute window
Color-coded for easy identification (Yellow for Asian, Blue for London, Red for New York)
Lines extend across the chart to help track price reactions throughout the day
Clean, minimal design with optional labels
Best Used For:
Identifying key intraday support and resistance levels
Session breakout trading strategies
Understanding institutional order flow at market opens
Works on 1-minute timeframe for precise tracking
Customizable Settings:
Toggle line extensions on/off
Adjust line width (1-5)
Change colors for each session
Show/hide session labels
Perfect for day traders and scalpers who trade around major session openings and want to identify high-probability support/resistance zones established during peak liquidity periods.
This description explains what the indicator does, its practical applications, and its key features in a way that's clear for TradingView users.RetryClaude can make mistakes. Please double-check responses.
Auto Fibonacci Retracements with Alerts [SwissAlgo]AUTO-FIBONACCI RETRACEMENT: LEVELS, ALERTS & PD ZONES
Automatically maps Fibonacci retracement levels with Premium/Discount (PD) zones and configurable alerts for technical analysis study.
------------------------------------------------------------------
FEATURES
Automatic Fibonacci Levels Detection
Identifies swing extremes (reference high and low to map retracements) from a user-defined trend start date and trend indication automatically
Calculates 20 Fibonacci levels (from -2.618 to +2.618) automatically
Dynamically updates Fib levels as price action develops, anchoring the bottom (in case of uptrends) or the top (in case of downtrends)
Detects potential Trend's Change of Character automatically
Premium/Discount (PD) zone visualization based on trend and price extremes
Visual Components
Dotted horizontal lines for each Fibonacci level
'Premium' and 'discount' zone highlighting
Change of Character (CHoCH) marker when a trend anchor breaks (a bottom is broken after an uptrend, a top is broken after a downtrend)
Adaptive label colors for light/dark chart themes
Alert System
Configurable alerts for all Fibonacci levels
Requires 2 consecutive bar closes for confirmation (reduces false signals)
CHoCH alert when a locked extreme is broken
Set up using "Any alert() function call" option
------------------------------------------------------------------
USE CASES
Two Primary Use Cases:
1. PROSPECTIVE TREND MAPPING (Real-Time Tracking)
Set start date at or just before an anticipated swing extreme to track levels as the trend develops:
For Uptrend : Place start date near a bottom. The bottom level locks after consolidation, while the top updates in real-time as the price climbs higher
For Downtrend : Place start date near a top. The top-level locks after consolidation, while the bottom updates in real-time as the price falls lower
This mode tracks developing price action against Fibonacci levels as the swing unfolds.
2. RETROSPECTIVE ANALYSIS (Historical Swing Study)
Set the start date at a completed swing extreme to analyze how the price interacted (and is interacting) with the Fibonacci levels:
Both high and low are already established in the historical data
Levels remain static for analysis purposes
Useful for analyzing price behavior relative to Fibonacci levels, studying retracement dynamics, and assessing a trading posture
------------------------------------------------------------------
HOW TO USE
Set 'Start Date' : Select Start Date (anchor point) at or just before the swing extreme (bottom for uptrend, top for downtrend)
Choose Trend Direction (Up or Down): direction is known for retrospective analysis, uncertain for prospective analysis
Update the start date when significant structure breaks occur to begin analyzing a new swing cycle.
Configure alerts as needed for your analysis
------------------------------------------------------------------
TECHNICAL DETAILS
♦ Auto-Mapped Fibonacci Retracement Levels:
2.618, 2.000, 1.618, 1.414, 1.272, 1.000, 0.882, 0.786, 0.618, 0.500, 0.382, 0.236, 0.118, 0.000, -0.272, -0.618, -1.000, -1.618, -2.000, -2.618
♦ Premium/Discount (PD) Zones:
Uptrend: Green (discount zone) = levels 0 to 0.5 | Red (premium zone) = levels 0.5 to 1.0
Downtrend: Red (premium zone) = levels 0 to 0.5 | Green (discount zone) = levels 0.5 to 1.0
The yellow line represents the 0.5 equilibrium level
♦ Lock Mechanism:
The indicator monitors for new extremes to detect a Change of Character in the trend (providing visual feedback and alerts). It locks the anchor swing extreme after a timeframe-appropriate consolidation period has elapsed (varies from 200 bars on second charts to 1 bar on monthly charts) to detect such potentially critical events.
------------------------------------------------------------------
IMPORTANT NOTES
This is an educational tool for technical analysis study. It displays historical and current price relationships to Fibonacci levels but does not predict future price movements or provide trading recommendations.
DISCLAIMER: This indicator is for educational and informational purposes only. It does not constitute financial advice or trading signals. Past price patterns do not guarantee future results. Trading involves substantial risk of loss. Always conduct your own analysis and consult with qualified financial professionals before making trading decisions. By using this indicator, you acknowledge and agree to these limitations.
Pulse FlowPulse Flow is a market structure indicator that extracts the hidden rhythm of price. It combines micro-structure detection with a rule-based trend engine, making waves and turning points visible in real time. Instead of drawing swings by hand or guessing breakouts, Pulse Flow enforces strict, objective rules for what counts as structure.
What it shows
Micro-Structure (Fractals): Internal swings are extracted from baseline crosses (EMA or ALMA). These fractals show how price oscillates inside the wave, providing context for micro pullbacks and internal breaks.
Trend (HH, HL, LH, LL): Pulse Flow uses a finite state machine (FSM) to track the current trend. Every trend represents a wave.
- Confirmed higher highs and higher lows define bullish waves.
- Confirmed lower highs and lower lows define bearish waves.
- When a wave breaks, a new wave begins. Turning points are explicitly marked as WH (wave high) and WL (wave low).
Active Range (RL & RH): The indicator continuously maintains the current range, based on closing prices rather than wicks. This ensures consistent behavior during liquidity events, where extremes are often tested intrabar.
Retracement Levels (0.50 & 0.71): Inside each active range, Pulse Flow plots the midrange and the 0.71 “optimal entry zone,” highlighting areas where pullbacks most often react.
Breakout Confirmation: A breakout is only valid if:
- The close extends beyond RL or RH by at least an ATR-based threshold.
- A second candle confirms the move.
This filters false signals and ensures structural integrity.
How it helps
Pulse Flow helps traders by taking the guesswork out of structure. Instead of debating whether a high or low should count, the indicator applies objective rules and marks every confirmed swing directly on the chart. Each wave is highlighted the moment the trend flips, so you always see where the market has turned and which direction the active wave is heading. The internal fractal structure reveals how price moves within the range, while the explicit HH, HL, LH, and LL points define the external trend. This distinction allows you to make tactical decisions on internal breaks and strategic decisions on external breaks, giving you clarity across timeframes. Because ranges are calculated using closing prices, the levels remain stable even when liquidity sweeps occur, making the indicator reliable in volatile markets. Combined with automatically plotted retracement levels, you gain a consistent framework for spotting likely reaction zones without redrawing lines or relying on subjective judgment.
How it works
Under the hood, Pulse Flow combines two engines. The pivot engine extracts micro swings by tracking how price crosses a baseline, which can be either EMA or ALMA, depending on your settings. Each cross defines a candidate high or low, and together these pivots form the fractal zigzag that represents the market’s micro-structure. On top of this, a finite state machine manages the active range. It tracks the range high and range low, validates breakouts only when price closes beyond these levels with ATR-based confirmation, and waits for a pullback before locking in the new structure. When the FSM confirms a new trend, Pulse Flow explicitly marks the turning point as a wave high or wave low. In this way, every confirmed HH, HL, LH, and LL is not a guess but the logical outcome of strict structural rules. The interaction between pivots and the FSM creates a complete and consistent map of the market’s waves, from micro oscillations to macro trend shifts.
Summary
Pulse Flow extracts micro-structure, defines waves, and highlights turning points. It shows the active range with key retracement levels and confirms breakouts with ATR + candle logic. By using closing prices to define RL/RH, it stays consistent even through liquidity sweeps.
For traders who trade based on structure, Pulse Flow is not just another tool. It is a framework: a rule-based map of how markets actually move in waves.
Smart Structure Breaks & Order BlocksOverview (What it does)
The indicator “Smart Structure Breaks & Order Blocks” detects market structure using swing highs and lows, identifies Break of Structure (BOS) events, and automatically draws order blocks (OBs) from the origin candle. These zones extend to the right and change color/outline when mitigated or invalidated. By formalizing and automating part of discretionary analysis, it provides consistent zone recognition.
Main Components
Swing Detection: ta.pivothigh/ta.pivotlow identify confirmed swing points.
BOS Detection: Determines if the recent swing high/low is broken by close (strict mode) or crossover.
OB Creation: After a BOS, the opposite candle (bearish for bullish BOS, bullish for bearish BOS) is used to generate an order block zone.
Zone Management: Limits the number of zones, extends them to the right, and tracks tagged (mitigated) or invalidated states.
Input Parameters
Left/Right Pivot (default 6/6): Number of bars required on each side to confirm a swing. Higher values = smoother swings.
Max Zones (default 4): Maximum zones stored per direction (bull/bear). Oldest zones are overwritten.
Zone Confirmation Lookback (default 3): Ensures OB origin candle validity by checking recent highs/lows.
Show Swing Points (default ON): Displays triangles on swing highs/lows.
Require close for BOS? (default ON): Strict BOS (close required) vs loose BOS (line crossover).
Use candle body for zones (default OFF): Zones drawn from candle body (ON) or wick (OFF).
Signal Definition & Logic
Swing Updates: Latest confirmed pivots update lastHighLevel / lastLowLevel.
BOS (Break of Structure):
Bullish – close breaks last swing high.
Bearish – close breaks last swing low.
Only one valid BOS per swing (avoids duplicates).
OB Detection:
Bullish BOS → previous bearish candle with lowest low forms the OB.
Bearish BOS → previous bullish candle with highest high forms the OB.
Zones: Bull = green, Bear = red, semi-transparent, extended to the right.
Zone States:
Mitigated: Price touches the zone → border highlighted.
Invalidated:
Bull zone → close below → turns red.
Bear zone → close above → turns green.
Chart Appearance
Swing High: red triangle above bar
Swing Low: green triangle below bar
Bull OB: green zone (border highlighted on touch)
Bear OB: red zone (border highlighted on touch)
Invalid Zones: Bull zones turn reddish, Bear zones turn greenish
Practical Use (Trading Assistance)
Trend Following Entries: Buy pullbacks into green OBs in uptrends, sell rallies into red OBs in downtrends.
Focus on First Touch: First mitigation after BOS often has higher reaction probability.
Confluence: Combine with higher timeframe trend, volume, session levels, key price levels (previous highs/lows, VWAP, etc.).
Stops/Targets:
Bull – stop below zone, partial take profit at swing high or resistance.
Bear – stop above zone, partial take profit at swing low or support.
Parameter Tuning (per market/timeframe)
Pivot (6/6 → 4/4/8/8): Lower for scalping (3–5), medium for day trading (5–8), higher for swing trading (8–14). Increase to reduce noise.
Strict Break: ON to reduce false breaks in ranging markets; OFF for earlier signals.
Body Zones: ON for assets with long wicks, OFF for cleaner OBs in liquid instruments.
Zone Confirmation (default 3): Increase for stricter OB origin, fewer zones.
Max Zones (default 4 → 6–10): Increase for higher volatility, decrease to avoid clutter.
Strengths
Standardizes BOS and OB detection that is usually subjective.
Tracks mitigation and invalidation automatically.
Adaptable: allows body/wick zone switching for different instruments.
Limitations
Pivot-based: Signals appear only after pivots confirm (slight lag).
Zones reflect past balance: Can fail after new events (news, earnings, macro data).
Range-heavy markets: More false BOS; consider stricter settings.
Backtesting: This script is for drawing/visual aid; trading rules must be defined separately.
Workflow Example
Identify higher timeframe trend (4H/Daily).
On lower TF (15–60m), wait for BOS and new OB.
Enter on first mitigation with confirmation candle.
Stop beyond zone; targets based on R multiples and swing points.
FAQ
Q: Why are zones invalidated quickly?
A: Flow reversal after BOS. Adjust pivots higher, enable Strict mode, or switch to Body zones to reduce noise.
Q: What does “tagged” mean?
A: Price touched the zone once = mitigated. Implies some orders in that zone may have been filled.
Q: Body or Wick zones?
A: Wick zones are fine in clean markets. For volatile pairs with long wicks, body zones provide more realistic areas.
Customization Tips (Code perspective)
Zone storage: Currently ring buffer ((idx+1) % zoneLimit). Could prioritize keeping unmitigated zones.
Automated testing: Add strategy.entry/exit for rule-based backtests.
Multi-timeframe: Use request.security() for higher timeframe swings/BOS.
Visualization: Add labels for BOS bars, tag zones with IDs, count touches.
Summary
This indicator formalizes the cycle Swing → BOS → OB creation → Mitigation/Invalidation, providing consistent structure analysis and zone tracking. By tuning sensitivity and strictness, and combining with higher timeframe context, it enhances pullback/continuation trading setups. Always combine with proper risk management.
Key Session & LevelsThis indicator helps traders track key price levels for multiple timeframes and trading sessions. It plots:
Previous Day's High and Low (PD): Highlighting the high and low of the previous trading day.
Previous Week's High and Low (PW): Plotting the highest and lowest price levels for the past week.
Tokyo Session High and Low (Today): Displays the high and low levels for the Tokyo trading session (adjustable to your preferred time window).
London Session High and Low (Today): Tracks the high and low for the London trading session (also adjustable for your timezone and desired session window).
Features:
Customizable Time Zones: The indicator uses your preferred timezone to calculate session highs/lows.
Extendable Lines: Lines for each level extend to the right of the chart, providing continuous reference throughout the trading day.
Adjustable Settings: Fine-tune the visibility and width of the lines, and choose which levels to display (Previous Day, Previous Week, Tokyo, and London sessions).
Non-Repainting: This script uses historical data and only updates when new bars are confirmed, ensuring accurate and reliable signals.
Whether you're a day trader, swing trader, or just tracking key levels for strategic entries and exits, this tool provides quick visual reference to important price points across different trading sessions.
Key Session & LevelsThis indicator helps traders track key price levels for multiple timeframes and trading sessions. It plots:
Previous Day's High and Low (PD): Highlighting the high and low of the previous trading day.
Previous Week's High and Low (PW): Plotting the highest and lowest price levels for the past week.
Tokyo Session High and Low (Today): Displays the high and low levels for the Tokyo trading session (adjustable to your preferred time window).
London Session High and Low (Today): Tracks the high and low for the London trading session (also adjustable for your timezone and desired session window).
Features:
Customizable Time Zones: The indicator uses your preferred timezone to calculate session highs/lows.
Extendable Lines: Lines for each level extend to the right of the chart, providing continuous reference throughout the trading day.
Adjustable Settings: Fine-tune the visibility and width of the lines, and choose which levels to display (Previous Day, Previous Week, Tokyo, and London sessions).
Non-Repainting: This script uses historical data and only updates when new bars are confirmed, ensuring accurate and reliable signals.
Whether you're a day trader, swing trader, or just tracking key levels for strategic entries and exits, this tool provides quick visual reference to important price points across different trading sessions.
TCP | Market Session | Session Analyzer📌 TCP | Market Session Indicator | Crypto Version
A powerful, real-time market session visualization tool tailored for crypto traders. Track the heartbeat of Asia, Europe, and US trading hours directly on your chart with live session boxes, behavioral analysis, liquidity grab detection, and countdown timers. Know when the action starts, how the market behaves, and where the traps lie.
🔰 Introduction:
Trade the Right Hours with the Right Tools
Time matters in trading. Most significant moves happen during key sessions—and knowing when and how each session unfolds can give you a sharp edge. The TCP Market Session Indicator, developed by Trade City Pro (TCP), puts professional session tracking and behavioral insights at your fingertips.
Whether you're a scalper or swing trader, this indicator gives you the timing context to enter and exit trades with greater confidence and clarity.
🕒 Core Features
• Live Session Boxes :
Highlight active ranges during Asia, Europe, and US sessions with dynamic high/low updates.
• Session Start/End Labels :
Know exactly when each session begins and ends plotted clearly on your chart with context.
• Session Behavior Analysis :
At the end of each session, the indicator classifies the price action as:
- Trend Up
- Trend Down
- Consolidation
- Manipulation
• Liquidity Grab Detection: Automatically detects possible stop hunts (fake breakouts) and marks them on the chart with precision filters (volume, ATR, reversal).
• Session Countdown Table: A live dashboard showing:
- Current active session
- Time left in session
- Upcoming session and how many minutes until it starts
- Utility time converter (e.g. 90 min = 01:30)
• Vertical Session Lines: Visualize past and upcoming session boundaries with customizable history and future range.
• Multi-Day Support: Draw session ranges for previous, current, and future days for better backtesting and forecasting.
⚙️ Settings Panel
Customize everything to fit your trading style and schedule:
• Session Time Settings:
Set the opening and closing time for each session manually using UTC-based minute inputs.
→ For example, enter Asia Start: 0, Asia End: 480 for 00:00–08:00 UTC.
This gives full flexibility to adjust session hours to match your preferred market behavior.
• Enable or Disable Elements:
Toggle the visibility of each session (Asia, Europe, US), as well as:
- Session Boxes
- Countdown Table
- Session Lines
- Liquidity Grab Labels
• Timezone Selection:
Choose between using UTC or your chart’s local timezone for session calculations.
• Customization Options:
Select number of past and future days to draw session data
Adjust vertical line transparency
Fine-tune label offset and spacing for clean layout
📊 Smart Session Boxes
Each session box tracks high, low, open, and close in real time, providing visual clarity on market structure. Once a session ends, the box closes, and the behavior type is saved and labeled ideal for spotting patterns across sessions.
• Asia: Green Box
• Europe: Orange Box
• US: Blue Box
💡 Why Use This Tool?
• Perfect Timing: Don’t get chopped in low-liquidity hours. Focus on sessions where volume and volatility align.
• Pattern Recognition: Study how price behaves session-to-session to build better strategies.
• Trap Detection: Spot manipulation moves (liquidity grabs) early and avoid common retail pitfalls.
• Macro Session Mapping: Use as a foundational layer to align trades with market structure and news cycles.
🔍 Example Use Case
You're watching BTC at 12:45 UTC. The indicator tells you:
The Asia session just ended (label shows “Asia Session End: Trend Up”)
Europe session starts in 15 minutes
A liquidity grab just triggered at the previous high—label confirmed
Now you know who’s active, what the market just did, and what’s about to start—all in one glance.
✅ Why Traders Trust It
• Visual & Intuitive: Fully chart-based, no clutter, no guessing
• Crypto-Focused: Designed specifically for 24/7 crypto markets (not outdated forex models)
• Non-Repainting: All labels and boxes stay as printed—no tricks
• Reliable: Tested across multiple exchanges, pairs, and timeframes
🧩 Built by Trade City Pro (TCP)
The TCP Market Session Indicator is part of a suite of professional tools used by over 150,000 traders. It’s coded in Pine Script v6 for full compatibility with TradingView’s latest capabilities.
🔗 Resources
• Tutorial: Learn how to analyze sessions like a pro in our TradingView guide:
"TradeCityPro Academy: Session Mapping & Liquidity Traps"
• More Tools: Explore our full library of indicators on
3-1-3 PatternThis Pine Script indicator analyzes and visualizes a specific candlestick pattern called the "3-1-3 Pattern" across multiple timeframes. Here's what it does:
Core Functionality
Pattern Detection: The script looks for a 7-bar candlestick pattern:
Bearish 3-1-3: 3 red candles + 1 green candle + 3 red candles
Bullish 3-1-3: 3 green candles + 1 red candle + 3 green candles
Visual Output
When a 3-1-3 pattern is detected, the script:
Creates a colored box around the middle bar (bar 3) of the pattern
Adds a small label showing the pattern type ("Bear 1H" or "Bull 4H", etc.)
Extends the box forward until the price breaks above the pattern's high or below its low
Pattern Management
The script actively manages the patterns by:
Tracking active patterns for each timeframe separately
Removing expired patterns when price breaks the pattern's high/low levels
Extending boxes to the current time to keep them visible
Practical Use
This indicator helps traders:
Spot reversal patterns across multiple timeframes simultaneously
See confluence when patterns align on different timeframes
Track pattern validity (boxes disappear when invalidated by price action)
Essentially, it's a multi-timeframe pattern recognition tool that automatically identifies and tracks these specific 7-bar reversal patterns on your chart.
