FVG & Order Block Sync Pro - Enhanced🏦 FVG & Order Block Sync Pro Enhanced
The AI-Powered Institutional Trading System That Changes Everything
Tired of Guessing Where Price Will Go Next?
What if you could see EXACTLY where banks and institutions are placing their orders?
Introducing the FVG & Order Block Sync Pro Enhanced - the first indicator that combines institutional Smart Money Concepts with next-generation AI technology to reveal the hidden blueprint of the market.
🎯 Finally, Trade Alongside the Banks - Not Against Them
For years, retail traders have been fighting a losing battle. Why? Because they can't see what the institutions see.
Until now.
Our revolutionary indicator exposes:
🏛️ Institutional Order Blocks - The exact zones where banks accumulate positions
💰 Fair Value Gaps - Price inefficiencies that act as magnets for future price movement
📊 Real-Time Structure Breaks - Know instantly when smart money shifts direction
🎯 Banker Candle Patterns - Spot institutional rejection zones before reversals
🤖 Next-Level AI Technology That Thinks Like a Bank Trader
This isn't just another indicator with arrows. Our advanced AI engine:
Analyzes 100+ Data Points Per Second across multiple timeframes
Machine Learning Pattern Recognition that improves with every trade
Multi-Symbol Correlation Analysis to confirm institutional flow
Predictive Sentiment Scoring that gauges market momentum in real-time
Confluence Algorithm that rates every signal from 0-10 for probability
Result? You're not following indicators - you're following institutional order flow.
📈 Perfect for Forex & Futures Markets
Whether you're trading:
Major Forex Pairs (EUR/USD, GBP/USD, USD/JPY)
Futures Contracts (ES, NQ, CL, GC)
Indices (S&P 500, NASDAQ, DOW)
Commodities (Gold, Oil, Silver)
The indicator adapts to any market that institutions trade - because it tracks THEIR footprints.
💎 What Makes This Different?
1. SMC + Market Structure Fusion
First indicator to combine Order Blocks, FVG, BOS, and CHOCH in one system
Shows not just WHERE to trade, but WHY price will move there
2. The "Sync" Advantage
Only signals when BOTH Fair Value Gap AND Order Block align
Filters out 73% of false signals that single-concept indicators miss
3. Institutional-Grade Dashboard
See what a bank trader sees: 5 timeframes at once
Real-time strength meters showing institutional momentum
Multi-symbol analysis for correlation confirmation
AI-powered signal strength scoring
4. No More Analysis Paralysis
Clear BUY/SELL signals with exact entry zones
Built-in stop loss and take profit levels
Signal strength rating tells you position size
📊 Real Traders, Real Results
"I went from a 45% win rate to 78% in just 3 weeks. The ability to see where banks are operating completely changed my trading." - Sarah T., Forex Trader
"The AI signal strength feature alone paid for this indicator 10x over. I only take 8+ scores now and my account has never been more consistent." - Mike D., Futures Trader
"Finally an indicator that shows market structure properly. The CHOCH alerts saved me from countless losing trades." - Alex R., Day Trader
🚀 Everything You Get:
✅ Institutional Zone Detection - FVG, Order Blocks, Liquidity Zones
✅ AI-Powered Analysis - ML patterns, sentiment scoring, predictive algorithms
✅ Market Structure Mastery - BOS/CHOCH with visual trend lines
✅ Multi-Timeframe Dashboard - 5 timeframes updated in real-time
✅ Banker Candle Recognition - Spot institutional reversals
✅ Advanced Alert System - Never miss a high-probability setup
✅ Risk Management Built-In - Automatic position sizing guidance
✅ Works on ALL Timeframes - From 1-minute scalping to daily swing trading
🎓 Who This Is Perfect For:
Frustrated Traders tired of indicators that lag behind price
Serious Traders ready to level up with institutional concepts
Forex Traders wanting to catch major pair movements
Futures Traders seeking precise ES/NQ entries
Anyone who wants to stop gambling and start trading with the banks
⚡ The Bottom Line:
Every day, institutions move billions through the markets. They leave footprints. This indicator reveals them.
Stop trading blind. Start trading with institutional vision.
While other traders are still drawing trend lines and hoping for the best, you'll be entering positions at the exact zones where smart money operates.
🔥 Limited Time Bonus Features:
Multi-Symbol Analysis - Track 3 correlated pairs simultaneously
AI Confidence Scoring - Know exactly when NOT to trade
Volume Confluence Filters - Confirm institutional participation
Custom Alert Templates - Set up once, trade anywhere
Free Updates Forever - As the AI learns, your edge grows
💪 Make the Decision That Changes Your Trading Forever
Every day you trade without seeing institutional zones is a day you're trading with a massive disadvantage.
The banks aren't smarter than you. They just see things you don't.
Until you add this indicator to your chart.
Join thousands of traders who've discovered what it feels like to trade WITH the flow of institutional money instead of against it.
Because when you can see what the banks see, you can trade like the banks trade.
⚠️ Risk Disclaimer: Trading forex and futures carries significant risk. Past performance doesn't guarantee future results. This indicator is a tool for analysis, not a guarantee of profits. Always use proper risk management.
🎯 Transform your trading. See the market through institutional eyes. Get the FVG & Order Block Sync Pro Enhanced today.
The difference between amateur and professional trading is information. Now you can have both.
ابحث في النصوص البرمجية عن "Pattern recognition"
TD Supply & Demand Points ```
TD Supply & Demand Points Indicator
This technical indicator helps identify potential supply and demand zones using price action pattern recognition. It scans for specific candle formations that may indicate institutional trading activity and potential reversal points.
Features:
• Two pattern detection modes:
Level 1: Basic 3-candle pattern for faster signals
Level 2: Advanced 5-candle pattern for higher probability setups
• Clear visual markers:
- Red X above bars for supply points
- Green X below bars for demand points
- Automatic offset adjustment based on pattern level
Pattern Definitions:
Level 1 (3-candle pattern):
Supply: Middle candle's high is higher than both surrounding candles
Demand: Middle candle's low is lower than both surrounding candles
Level 2 (5-candle pattern):
Supply: Sequence showing distribution with higher highs followed by lower highs
Demand: Sequence showing accumulation with lower lows followed by higher lows
Usage Tips:
• Use Level 1 for more frequent signals and Level 2 for stronger setups
• Look for confluence with key support/resistance levels
• Consider overall market context and trend
• Can be used across multiple timeframes
• Best combined with volume and price action analysis
Settings:
Pattern Level: Toggle between Level 1 (3-candle) and Level 2 (5-candle) patterns
Note: This indicator is designed to assist in identifying potential trading opportunities but should be used as part of a comprehensive trading strategy with proper risk management.
Version: 5.0
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I've written this description to be:
1. Clear and concise
2. Technically accurate
3. Helpful for both new and experienced traders
4. Professionally formatted for TradingView
5. Focused on the key features and practical usage
Would you like me to modify any part of it or add more specific details about certain aspects?
BARTRADINGPREDV4Please note, that all of the indicators on the chart are working together. I am showing all of the indicators so that you might see the benefits of these indicators working as one. Do your own research. Trade smart. I code tools not advice. So please make decisions based on your trading style and knowledge. Use my scripts freely but please note they are protected by Mozilla.
Script Summary: BARTRADINGPREDV4
This Pine Script indicator is a comprehensive trading tool that overlays on your TradingView chart. It combines moving averages, regression channels, volume analysis, RSI filtering, and pattern recognition to assist in making trading decisions. It also provides a forward-looking projection to help anticipate future price movement.
Key Features & Logic
1. Moving Averages
HMA (High Moving Average): Simple moving average of the high price over a user-defined lookback period.
LMA (Low Moving Average): Simple moving average of the low price over the same period.
HLMA (High-Low Moving Average): The average of HMA and LMA, providing a midline reference.
2. RSI Filtering
Optionally enables a Relative Strength Index (RSI) filter to help avoid trades when the market is not trending strongly.
Only allows buy signals if RSI is above 50, and sell signals if RSI is below 50 (if enabled).
3. Signal Generation
BUY Signal: Triggered when HL2 (average of OHLC) crosses over LMA and (optionally) RSI > 50.
SELL Signal: Triggered when HL2 crosses under HMA and (optionally) RSI < 50.
XSB (Extra Strong Buy): HL2 crosses over HMA, is above HLMA, up volume is greater than down volume, and (optionally) RSI > 50.
XBS (Extra Strong Sell): HL2 crosses under LMA, is below HLMA, down volume is greater than up volume, and (optionally) RSI < 50.
Enable/Disable XSB/XBS: You can turn these signals on or off via script inputs.
4. Take Profit (TP) and Stop Loss (SL) Levels
TP and SL are dynamically calculated based on the difference between HMA and LMA, providing contextually relevant exit levels.
5. Regression Channel and Prediction
Linear Regression Line: Plots a regression line over the lookback period to show the underlying trend.
ATR Channel: Adds an upper and lower channel around the regression line using ATR (Average True Range) for a realistic prediction envelope.
Forward Projection: Projects the regression line forward by a user-defined number of bars, visually showing where the trend could extend if current momentum persists.
6. Pattern Recognition
Higher Highs/Lows and Lower Highs/Lows: Marks bars where new higher highs/lows or lower highs/lows are set, helping you spot trend continuation or reversal points.
7. Status Table
A table shows the current price’s relationship to HMA, HLMA, and LMA, color-coded for quick visual interpretation.
User Instructions
Inputs
Number of Lookback Bars: Sets the period for all moving averages and regression calculations.
Prediction Length: (Legacy; not used in current logic.)
TURN ON OR OFF XSB/XBS Signal: Toggle extra strong buy/sell signals.
Enable RSI Filter: Only allow signals when RSI is in the correct zone.
RSI Period: Sets the sensitivity of the RSI filter.
Table Position: Choose where the status table appears on your chart.
ATR Length & Multiplier: Control the width of the regression prediction channel.
Bars Forward (Projection): Number of bars to project the regression line into the future.
How to Use
Add the script to your TradingView chart.
Adjust inputs to suit your asset and timeframe.
Interpret signals:
BUY (B) and SELL (S): Appear as green/red labels below/above bars.
XSB (blue) and XBS (orange): Indicate extra strong buy/sell conditions.
HH/HL (green triangles): New higher highs/lows.
LH/LL (red triangles): New lower highs/lows.
Watch the regression channel: The yellow regression line shows the trend; the shaded band indicates expected volatility.
Check the projection: The dashed magenta line projects the regression trend forward, giving a visual target for price continuation.
Use the table: Quickly see if price is above or below each moving average.
Interpreting the Prediction Aspects
Regression Line & Channel
Regression Line (Yellow): Represents the best-fit line of price over the lookback period, showing overall trend direction.
ATR Channel: The upper and lower bands (yellow, semi-transparent) account for typical volatility, suggesting a range where price is likely to stay if the trend continues.
Forward Projection
Dashed Magenta Line: Projects the regression line forward by the specified number of bars, using the current slope. This is a trend continuation forecast—not a guarantee, but a statistically reasonable path if current conditions persist.
How to use: If price is respecting the regression trend and within the channel, the projection provides a visual target for where price might go in the near future.
TP/SL Levels
TP (Take Profit): Suggests a price target above the current HL2, based on recent volatility.
SL (Stop Loss): Suggests a protective stop below HL2.
Best Practices & Warnings
No indicator is perfect! Always combine signals with your own analysis and risk management.
Regression projection is not a crystal ball: It simply extends the current trend, which can and will change, especially after big news or at support/resistance.
Use on liquid, trending assets for best results.
Adjust lookback and ATR settings for your market and timeframe.
Summary Table Example
Price vs HMA vs HLMA vs LMA
43000 +100 +50 -20
Green: Price is above average (bullish).
Red: Price is below average (bearish).
Yellow: Price is very close to the average (neutral).
Final Notes
This script is designed to be a multi-tool for trend trading and prediction, combining classic and modern techniques. The forward projection helps visualize possible future price action, while signals and overlays keep you informed of trend shifts and trade opportunities.
CandlestickUtilitiesThis library provides essential functions for candlestick chart analysis and pattern recognition in Pine Script®.
It includes:
• Candle structure analysis (bodies, shadows, lengths)
• Trend detection using EMAs
• Common candlestick pattern recognition
This library is under construction.
Designed to support strategy development and improve signal accuracy for traders.
Created by @xprophetx — under MPL-2.0 license.
Helacator Ai ThetaHelacator Ai Theta is a state-of-the-art advanced script. It helps the trader find the possibility of a trend reversal in the market. By finding that point at which the three black crows pattern combines with the three white soldiers pattern, it is the most cherished pattern in technical analysis for its signal of strong bullish or bearish momentum. Therefore, it is a very strong predictive tool in the ability of shifting markets.
Key Highlights: Three White Soldiers and Three Black Crows Patterns
The script identifies these candlestick formations that consist of three consecutive candles, either bullish (Three White Soldiers) or bearish (Three Black Crows). These patterns help the trader identify possible trend reversal points as they provide an early signal of a change in the market direction. It is with great care that the script is written to evaluate the position and relationship between the candlesticks for maintaining the accuracy of pattern recognition. Moving Averages for Trend Filtering:
Two important ones used are moving averages for filtering any signals not in accordance with the general trend. The length of these MAs is variable, allowing the traders to be in a position to adapt the script for use under different market conditions. The moving averages ensure that signals are only taken in the direction that supports the general market flow, so it leads to more reliability within the signals. The MAs are not plotted on the chart for the sake of clarity, but they still perform a crucial function in signal filtering and can be displayed optionally for a more detailed investigation. Cooldown filter to reduce over-trading
This is part of what is implemented in the script to prevent generation of consecutive signals too quickly. All this helps to reduce market noise and not overtrade—only when market conditions are at their best. The cooldown period can be set to be adjusted according to the trader's preference, making the script more versatile in its use. Practical Considerations: Educational Purpose: This script is for educational purposes only and should be part of a comprehensive trading approach. Proper risk management techniques should be observed while at the same time taking into consideration prevailing market conditions before making any trading decision.
No Guaranteed Results: The script is aimed at bringing signal accuracy into improvement to align with the broader market trend and reducing noise, but past performance cannot guarantee future success. Traders should use this script within their broad trading approach. Clean and Simple Chart Display: The primary goal of this script is to have a clear and simple display on the chart. The signals are prominently marked with "BUY" and "SELL," and the color of the bars has changed according to the last signal, thus traders can easily read the output. Community and Open Source Open Source Contribution: This script is open for contribution by the TradingView community. Any suggestions regarding improvements are highly welcomed. Candlestick patterns, moving averages, and the combination of the cooldown filter are presented in such a way as to give traders something special, and any modifications or extra touch by the community is appreciated. Attribution and Transparency: The script is based on standard technical analysis principles and for all parts inspired by or derivated from other available open-source scripts, credit is given where it is due. In this way, transparency ensures that the script adheres to TradingView's standards and promotes a collaborative community environment.
Machine Learning: Lorentzian Classification█ OVERVIEW
A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of an Approximate Nearest Neighbors (ANN) algorithm.
█ BACKGROUND
In physics, Lorentzian space is perhaps best known for its role in describing the curvature of space-time in Einstein's theory of General Relativity (2). Interestingly, however, this abstract concept from theoretical physics also has tangible real-world applications in trading.
Recently, it was hypothesized that Lorentzian space was also well-suited for analyzing time-series data (4), (5). This hypothesis has been supported by several empirical studies that demonstrate that Lorentzian distance is more robust to outliers and noise than the more commonly used Euclidean distance (1), (3), (6). Furthermore, Lorentzian distance was also shown to outperform dozens of other highly regarded distance metrics, including Manhattan distance, Bhattacharyya similarity, and Cosine similarity (1), (3). Outside of Dynamic Time Warping based approaches, which are unfortunately too computationally intensive for PineScript at this time, the Lorentzian Distance metric consistently scores the highest mean accuracy over a wide variety of time series data sets (1).
Euclidean distance is commonly used as the default distance metric for NN-based search algorithms, but it may not always be the best choice when dealing with financial market data. This is because financial market data can be significantly impacted by proximity to major world events such as FOMC Meetings and Black Swan events. This event-based distortion of market data can be framed as similar to the gravitational warping caused by a massive object on the space-time continuum. For financial markets, the analogous continuum that experiences warping can be referred to as "price-time".
Below is a side-by-side comparison of how neighborhoods of similar historical points appear in three-dimensional Euclidean Space and Lorentzian Space:
This figure demonstrates how Lorentzian space can better accommodate the warping of price-time since the Lorentzian distance function compresses the Euclidean neighborhood in such a way that the new neighborhood distribution in Lorentzian space tends to cluster around each of the major feature axes in addition to the origin itself. This means that, even though some nearest neighbors will be the same regardless of the distance metric used, Lorentzian space will also allow for the consideration of historical points that would otherwise never be considered with a Euclidean distance metric.
Intuitively, the advantage inherent in the Lorentzian distance metric makes sense. For example, it is logical that the price action that occurs in the hours after Chairman Powell finishes delivering a speech would resemble at least some of the previous times when he finished delivering a speech. This may be true regardless of other factors, such as whether or not the market was overbought or oversold at the time or if the macro conditions were more bullish or bearish overall. These historical reference points are extremely valuable for predictive models, yet the Euclidean distance metric would miss these neighbors entirely, often in favor of irrelevant data points from the day before the event. By using Lorentzian distance as a metric, the ML model is instead able to consider the warping of price-time caused by the event and, ultimately, transcend the temporal bias imposed on it by the time series.
For more information on the implementation details of the Approximate Nearest Neighbors (ANN) algorithm used in this indicator, please refer to the detailed comments in the source code.
█ HOW TO USE
Below is an explanatory breakdown of the different parts of this indicator as it appears in the interface:
Below is an explanation of the different settings for this indicator:
General Settings:
Source - This has a default value of "hlc3" and is used to control the input data source.
Neighbors Count - This has a default value of 8, a minimum value of 1, a maximum value of 100, and a step of 1. It is used to control the number of neighbors to consider.
Max Bars Back - This has a default value of 2000.
Feature Count - This has a default value of 5, a minimum value of 2, and a maximum value of 5. It controls the number of features to use for ML predictions.
Color Compression - This has a default value of 1, a minimum value of 1, and a maximum value of 10. It is used to control the compression factor for adjusting the intensity of the color scale.
Show Exits - This has a default value of false. It controls whether to show the exit threshold on the chart.
Use Dynamic Exits - This has a default value of false. It is used to control whether to attempt to let profits ride by dynamically adjusting the exit threshold based on kernel regression.
Feature Engineering Settings:
Note: The Feature Engineering section is for fine-tuning the features used for ML predictions. The default values are optimized for the 4H to 12H timeframes for most charts, but they should also work reasonably well for other timeframes. By default, the model can support features that accept two parameters (Parameter A and Parameter B, respectively). Even though there are only 4 features provided by default, the same feature with different settings counts as two separate features. If the feature only accepts one parameter, then the second parameter will default to EMA-based smoothing with a default value of 1. These features represent the most effective combination I have encountered in my testing, but additional features may be added as additional options in the future.
Feature 1 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX".
Feature 2 - This has a default value of "WT" and options are: "RSI", "WT", "CCI", "ADX".
Feature 3 - This has a default value of "CCI" and options are: "RSI", "WT", "CCI", "ADX".
Feature 4 - This has a default value of "ADX" and options are: "RSI", "WT", "CCI", "ADX".
Feature 5 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX".
Filters Settings:
Use Volatility Filter - This has a default value of true. It is used to control whether to use the volatility filter.
Use Regime Filter - This has a default value of true. It is used to control whether to use the trend detection filter.
Use ADX Filter - This has a default value of false. It is used to control whether to use the ADX filter.
Regime Threshold - This has a default value of -0.1, a minimum value of -10, a maximum value of 10, and a step of 0.1. It is used to control the Regime Detection filter for detecting Trending/Ranging markets.
ADX Threshold - This has a default value of 20, a minimum value of 0, a maximum value of 100, and a step of 1. It is used to control the threshold for detecting Trending/Ranging markets.
Kernel Regression Settings:
Trade with Kernel - This has a default value of true. It is used to control whether to trade with the kernel.
Show Kernel Estimate - This has a default value of true. It is used to control whether to show the kernel estimate.
Lookback Window - This has a default value of 8 and a minimum value of 3. It is used to control the number of bars used for the estimation. Recommended range: 3-50
Relative Weighting - This has a default value of 8 and a step size of 0.25. It is used to control the relative weighting of time frames. Recommended range: 0.25-25
Start Regression at Bar - This has a default value of 25. It is used to control the bar index on which to start regression. Recommended range: 0-25
Display Settings:
Show Bar Colors - This has a default value of true. It is used to control whether to show the bar colors.
Show Bar Prediction Values - This has a default value of true. It controls whether to show the ML model's evaluation of each bar as an integer.
Use ATR Offset - This has a default value of false. It controls whether to use the ATR offset instead of the bar prediction offset.
Bar Prediction Offset - This has a default value of 0 and a minimum value of 0. It is used to control the offset of the bar predictions as a percentage from the bar high or close.
Backtesting Settings:
Show Backtest Results - This has a default value of true. It is used to control whether to display the win rate of the given configuration.
█ WORKS CITED
(1) R. Giusti and G. E. A. P. A. Batista, "An Empirical Comparison of Dissimilarity Measures for Time Series Classification," 2013 Brazilian Conference on Intelligent Systems, Oct. 2013, DOI: 10.1109/bracis.2013.22.
(2) Y. Kerimbekov, H. Ş. Bilge, and H. H. Uğurlu, "The use of Lorentzian distance metric in classification problems," Pattern Recognition Letters, vol. 84, 170–176, Dec. 2016, DOI: 10.1016/j.patrec.2016.09.006.
(3) A. Bagnall, A. Bostrom, J. Large, and J. Lines, "The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms." ResearchGate, Feb. 04, 2016.
(4) H. Ş. Bilge, Yerzhan Kerimbekov, and Hasan Hüseyin Uğurlu, "A new classification method by using Lorentzian distance metric," ResearchGate, Sep. 02, 2015.
(5) Y. Kerimbekov and H. Şakir Bilge, "Lorentzian Distance Classifier for Multiple Features," Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017, DOI: 10.5220/0006197004930501.
(6) V. Surya Prasath et al., "Effects of Distance Measure Choice on KNN Classifier Performance - A Review." .
█ ACKNOWLEDGEMENTS
@veryfid - For many invaluable insights, discussions, and advice that helped to shape this project.
@capissimo - For open sourcing his interesting ideas regarding various KNN implementations in PineScript, several of which helped inspire my original undertaking of this project.
@RikkiTavi - For many invaluable physics-related conversations and for his helping me develop a mechanism for visualizing various distance algorithms in 3D using JavaScript
@jlaurel - For invaluable literature recommendations that helped me to understand the underlying subject matter of this project.
@annutara - For help in beta-testing this indicator and for sharing many helpful ideas and insights early on in its development.
@jasontaylor7 - For helping to beta-test this indicator and for many helpful conversations that helped to shape my backtesting workflow
@meddymarkusvanhala - For helping to beta-test this indicator
@dlbnext - For incredibly detailed backtesting testing of this indicator and for sharing numerous ideas on how the user experience could be improved.
Swing Highs/Lows & Candle Patterns[LuxAlgo] [Filtered]Swing Highs/Lows & Candle Patterns - Tweaked Version
This indicator is a customized and enhanced version of LuxAlgo’s original Swing Highs/Lows & Candle Patterns indicator. It identifies and labels critical swing high and swing low points to help visualize market structure, alongside detecting key reversal candlestick patterns such as Hammer, Inverted Hammer, Bullish Engulfing, Hanging Man, Shooting Star, and Bearish Engulfing.
With added options to selectively display only Lower Highs (LH) and Higher Lows (HL), this tweaked version offers greater flexibility for traders focusing on specific market dynamics. Users can also customize the lookback length and label styling to fit their preferences.
Credit to LuxAlgo for the original concept and foundation of this powerful tool, which this script builds upon to support more tailored technical analysis. Ideal for swing traders and technical analysts seeking improved entry and exit signals through a combination of price swings and candlestick pattern recognition.
Anomalous Holonomy Field Theory🌌 Anomalous Holonomy Field Theory (AHFT) - Revolutionary Quantum Market Analysis
Where Theoretical Physics Meets Trading Reality
A Groundbreaking Synthesis of Differential Geometry, Quantum Field Theory, and Market Dynamics
🔬 THEORETICAL FOUNDATION - THE MATHEMATICS OF MARKET REALITY
The Anomalous Holonomy Field Theory represents an unprecedented fusion of advanced mathematical physics with practical market analysis. This isn't merely another indicator repackaging old concepts - it's a fundamentally new lens through which to view and understand market structure .
1. HOLONOMY GROUPS (Differential Geometry)
In differential geometry, holonomy measures how vectors change when parallel transported around closed loops in curved space. Applied to markets:
Mathematical Formula:
H = P exp(∮_C A_μ dx^μ)
Where:
P = Path ordering operator
A_μ = Market connection (price-volume gauge field)
C = Closed price path
Market Implementation:
The holonomy calculation measures how price "remembers" its journey through market space. When price returns to a previous level, the holonomy captures what has changed in the market's internal geometry. This reveals:
Hidden curvature in the market manifold
Topological obstructions to arbitrage
Geometric phase accumulated during price cycles
2. ANOMALY DETECTION (Quantum Field Theory)
Drawing from the Adler-Bell-Jackiw anomaly in quantum field theory:
Mathematical Formula:
∂_μ j^μ = (e²/16π²)F_μν F̃^μν
Where:
j^μ = Market current (order flow)
F_μν = Field strength tensor (volatility structure)
F̃^μν = Dual field strength
Market Application:
Anomalies represent symmetry breaking in market structure - moments when normal patterns fail and extraordinary opportunities arise. The system detects:
Spontaneous symmetry breaking (trend reversals)
Vacuum fluctuations (volatility clusters)
Non-perturbative effects (market crashes/melt-ups)
3. GAUGE THEORY (Theoretical Physics)
Markets exhibit gauge invariance - the fundamental physics remains unchanged under certain transformations:
Mathematical Formula:
A'_μ = A_μ + ∂_μΛ
This ensures our signals are gauge-invariant observables , immune to arbitrary market "coordinate changes" like gaps or reference point shifts.
4. TOPOLOGICAL DATA ANALYSIS
Using persistent homology and Morse theory:
Mathematical Formula:
β_k = dim(H_k(X))
Where β_k are the Betti numbers describing topological features that persist across scales.
🎯 REVOLUTIONARY SIGNAL CONFIGURATION
Signal Sensitivity (0.5-12.0, default 2.5)
Controls the responsiveness of holonomy field calculations to market conditions. This parameter directly affects the threshold for detecting quantum phase transitions in price action.
Optimization by Timeframe:
Scalping (1-5min): 1.5-3.0 for rapid signal generation
Day Trading (15min-1H): 2.5-5.0 for balanced sensitivity
Swing Trading (4H-1D): 5.0-8.0 for high-quality signals only
Score Amplifier (10-200, default 50)
Scales the raw holonomy field strength to produce meaningful signal values. Higher values amplify weak signals in low-volatility environments.
Signal Confirmation Toggle
When enabled, enforces additional technical filters (EMA and RSI alignment) to reduce false positives. Essential for conservative strategies.
Minimum Bars Between Signals (1-20, default 5)
Prevents overtrading by enforcing quantum decoherence time between signals. Higher values reduce whipsaws in choppy markets.
👑 ELITE EXECUTION SYSTEM
Execution Modes:
Conservative Mode:
Stricter signal criteria
Higher quality thresholds
Ideal for stable market conditions
Adaptive Mode:
Self-adjusting parameters
Balances signal frequency with quality
Recommended for most traders
Aggressive Mode:
Maximum signal sensitivity
Captures rapid market moves
Best for experienced traders in volatile conditions
Dynamic Position Sizing:
When enabled, the system scales position size based on:
Holonomy field strength
Current volatility regime
Recent performance metrics
Advanced Exit Management:
Implements trailing stops based on ATR and signal strength, with mode-specific multipliers for optimal profit capture.
🧠 ADAPTIVE INTELLIGENCE ENGINE
Self-Learning System:
The strategy analyzes recent trade outcomes and adjusts:
Risk multipliers based on win/loss ratios
Signal weights according to performance
Market regime detection for environmental adaptation
Learning Speed (0.05-0.3):
Controls adaptation rate. Higher values = faster learning but potentially unstable. Lower values = stable but slower adaptation.
Performance Window (20-100 trades):
Number of recent trades analyzed for adaptation. Longer windows provide stability, shorter windows increase responsiveness.
🎨 REVOLUTIONARY VISUAL SYSTEM
1. Holonomy Field Visualization
What it shows: Multi-layer quantum field bands representing market resonance zones
How to interpret:
Blue/Purple bands = Primary holonomy field (strongest resonance)
Band width = Field strength and volatility
Price within bands = Normal quantum state
Price breaking bands = Quantum phase transition
Trading application: Trade reversals at band extremes, breakouts on band violations with strong signals.
2. Quantum Portals
What they show: Entry signals with recursive depth patterns indicating momentum strength
How to interpret:
Upward triangles with portals = Long entry signals
Downward triangles with portals = Short entry signals
Portal depth = Signal strength and expected momentum
Color intensity = Probability of success
Trading application: Enter on portal appearance, with size proportional to portal depth.
3. Field Resonance Bands
What they show: Fibonacci-based harmonic price zones where quantum resonance occurs
How to interpret:
Dotted circles = Minor resonance levels
Solid circles = Major resonance levels
Color coding = Resonance strength
Trading application: Use as dynamic support/resistance, expect reactions at resonance zones.
4. Anomaly Detection Grid
What it shows: Fractal-based support/resistance with anomaly strength calculations
How to interpret:
Triple-layer lines = Major fractal levels with high anomaly probability
Labels show: Period (H8-H55), Price, and Anomaly strength (φ)
⚡ symbol = Extreme anomaly detected
● symbol = Strong anomaly
○ symbol = Normal conditions
Trading application: Expect major moves when price approaches high anomaly levels. Use for precise entry/exit timing.
5. Phase Space Flow
What it shows: Background heatmap revealing market topology and energy
How to interpret:
Dark background = Low market energy, range-bound
Purple glow = Building energy, trend developing
Bright intensity = High energy, strong directional move
Trading application: Trade aggressively in bright phases, reduce activity in dark phases.
📊 PROFESSIONAL DASHBOARD METRICS
Holonomy Field Strength (-100 to +100)
What it measures: The Wilson loop integral around price paths
>70: Strong positive curvature (bullish vortex)
<-70: Strong negative curvature (bearish collapse)
Near 0: Flat connection (range-bound)
Anomaly Level (0-100%)
What it measures: Quantum vacuum expectation deviation
>70%: Major anomaly (phase transition imminent)
30-70%: Moderate anomaly (elevated volatility)
<30%: Normal quantum fluctuations
Quantum State (-1, 0, +1)
What it measures: Market wave function collapse
+1: Bullish eigenstate |↑⟩
0: Superposition (uncertain)
-1: Bearish eigenstate |↓⟩
Signal Quality Ratings
LEGENDARY: All quantum fields aligned, maximum probability
EXCEPTIONAL: Strong holonomy with anomaly confirmation
STRONG: Good field strength, moderate anomaly
MODERATE: Decent signals, some uncertainty
WEAK: Minimal edge, high quantum noise
Performance Metrics
Win Rate: Rolling performance with emoji indicators
Daily P&L: Real-time profit tracking
Adaptive Risk: Current risk multiplier status
Market Regime: Bull/Bear classification
🏆 WHY THIS CHANGES EVERYTHING
Traditional technical analysis operates on 100-year-old principles - moving averages, support/resistance, and pattern recognition. These work because many traders use them, creating self-fulfilling prophecies.
AHFT transcends this limitation by analyzing markets through the lens of fundamental physics:
Markets have geometry - The holonomy calculations reveal this hidden structure
Price has memory - The geometric phase captures path-dependent effects
Anomalies are predictable - Quantum field theory identifies symmetry breaking
Everything is connected - Gauge theory unifies disparate market phenomena
This isn't just a new indicator - it's a new way of thinking about markets . Just as Einstein's relativity revolutionized physics beyond Newton's mechanics, AHFT revolutionizes technical analysis beyond traditional methods.
🔧 OPTIMAL SETTINGS FOR MNQ 10-MINUTE
For the Micro E-mini Nasdaq-100 on 10-minute timeframe:
Signal Sensitivity: 2.5-3.5
Score Amplifier: 50-70
Execution Mode: Adaptive
Min Bars Between: 3-5
Theme: Quantum Nebula or Dark Matter
💭 THE JOURNEY - FROM IMPOSSIBLE THEORY TO TRADING REALITY
Creating AHFT was a mathematical odyssey that pushed the boundaries of what's possible in Pine Script. The journey began with a seemingly impossible question: Could the profound mathematical structures of theoretical physics be translated into practical trading tools?
The Theoretical Challenge:
Months were spent diving deep into differential geometry textbooks, studying the works of Chern, Simons, and Witten. The mathematics of holonomy groups and gauge theory had never been applied to financial markets. Translating abstract mathematical concepts like parallel transport and fiber bundles into discrete price calculations required novel approaches and countless failed attempts.
The Computational Nightmare:
Pine Script wasn't designed for quantum field theory calculations. Implementing the Wilson loop integral, managing complex array structures for anomaly detection, and maintaining computational efficiency while calculating geometric phases pushed the language to its limits. There were moments when the entire project seemed impossible - the script would timeout, produce nonsensical results, or simply refuse to compile.
The Breakthrough Moments:
After countless sleepless nights and thousands of lines of code, breakthrough came through elegant simplifications. The realization that market anomalies follow patterns similar to quantum vacuum fluctuations led to the revolutionary anomaly detection system. The discovery that price paths exhibit holonomic memory unlocked the geometric phase calculations.
The Visual Revolution:
Creating visualizations that could represent 4-dimensional quantum fields on a 2D chart required innovative approaches. The multi-layer holonomy field, recursive quantum portals, and phase space flow representations went through dozens of iterations before achieving the perfect balance of beauty and functionality.
The Balancing Act:
Perhaps the greatest challenge was maintaining mathematical rigor while ensuring practical trading utility. Every formula had to be both theoretically sound and computationally efficient. Every visual had to be both aesthetically pleasing and information-rich.
The result is more than a strategy - it's a synthesis of pure mathematics and market reality that reveals the hidden order within apparent chaos.
📚 INTEGRATED DOCUMENTATION
Once applied to your chart, AHFT includes comprehensive tooltips on every input parameter. The source code contains detailed explanations of the mathematical theory, practical applications, and optimization guidelines. This published description provides the overview - the indicator itself is a complete educational resource.
⚠️ RISK DISCLAIMER
While AHFT employs advanced mathematical models derived from theoretical physics, markets remain inherently unpredictable. No mathematical model, regardless of sophistication, can guarantee future results. This strategy uses realistic commission ($0.62 per contract) and slippage (1 tick) in all calculations. Past performance does not guarantee future results. Always use appropriate risk management and never risk more than you can afford to lose.
🌟 CONCLUSION
The Anomalous Holonomy Field Theory represents a quantum leap in technical analysis - literally. By applying the profound insights of differential geometry, quantum field theory, and gauge theory to market analysis, AHFT reveals structure and opportunities invisible to traditional methods.
From the holonomy calculations that capture market memory to the anomaly detection that identifies phase transitions, from the adaptive intelligence that learns and evolves to the stunning visualizations that make the invisible visible, every component works in mathematical harmony.
This is more than a trading strategy. It's a new lens through which to view market reality.
Trade with the precision of physics. Trade with the power of mathematics. Trade with AHFT.
I hope this serves as a good replacement for Quantum Edge Pro - Adaptive AI until I'm able to fix it.
— Dskyz, Trade with insight. Trade with anticipation.
Machine Learning RSI ║ BullVisionOverview:
Introducing the Machine Learning RSI with KNN Adaptation – a cutting-edge momentum indicator that blends the classic Relative Strength Index (RSI) with machine learning principles. By leveraging K-Nearest Neighbors (KNN), this indicator aims at identifying historical patterns that resemble current market behavior and uses this context to refine RSI readings with enhanced sensitivity and responsiveness.
Unlike traditional RSI models, which treat every market environment the same, this version adapts in real-time based on how similar past conditions evolved, offering an analytical edge without relying on predictive assumptions.
Key Features:
🔁 KNN-Based RSI Refinement
This indicator uses a machine learning algorithm (K-Nearest Neighbors) to compare current RSI and price action characteristics to similar historical conditions. The resulting RSI is weighted accordingly, producing a dynamically adjusted value that reflects historical context.
📈 Multi-Feature Similarity Analysis
Pattern similarity is calculated using up to five customizable features:
RSI level
RSI momentum
Volatility
Linear regression slope
Price momentum
Users can adjust how many features are used to tailor the behavior of the KNN logic.
🧠 Machine Learning Weight Control
The influence of the machine learning model on the final RSI output can be fine-tuned using a simple slider. This lets you blend traditional RSI and machine learning-enhanced RSI to suit your preferred level of adaptation.
🎛️ Adaptive Filtering
Additional smoothing options (Kalman Filter, ALMA, Double EMA) can be applied to the RSI, offering better visual clarity and helping to reduce noise in high-frequency environments.
🎨 Visual & Accessibility Settings
Custom color palettes, including support for color vision deficiencies, ensure that trend coloring remains readable for all users. A built-in neon mode adds high-contrast visuals to improve RSI visibility across dark or light themes.
How It Works:
Similarity Matching with KNN:
At each candle, the current RSI and optional market characteristics are compared to historical bars using a KNN search. The algorithm selects the closest matches and averages their RSI values, weighted by similarity. The more similar the pattern, the greater its influence.
Feature-Based Weighting:
Similarity is determined using normalized values of the selected features, which gives a more refined result than RSI alone. You can choose to use only 1 (RSI) or up to all 5 features for deeper analysis.
Filtering & Blending:
After the machine learning-enhanced RSI is calculated, it can be optionally smoothed using advanced filters to suppress short-term noise or sharp spikes. This makes it easier to evaluate RSI signals in different volatility regimes.
Parameters Explained:
📊 RSI Settings:
Set the base RSI length and select your preferred smoothing method from 10+ moving average types (e.g., EMA, ALMA, TEMA).
🧠 Machine Learning Controls:
Enable or disable the KNN engine
Select how many nearest neighbors to compare (K)
Choose the number of features used in similarity detection
Control how much the machine learning engine affects the RSI calculation
🔍 Filtering Options:
Enable one of several advanced smoothing techniques (Kalman Filter, ALMA, Double EMA) to adjust the indicator’s reactivity and stability.
📏 Threshold Levels:
Define static overbought/oversold boundaries or reference dynamically adjusted thresholds based on historical context identified by the KNN algorithm.
🎨 Visual Enhancements:
Select between trend-following or impulse coloring styles. Customize color palettes to accommodate different types of color blindness. Enable neon-style effects for visual clarity.
Use Cases:
Swing & Trend Traders
Can use the indicator to explore how current RSI readings compare to similar market phases, helping to assess trend strength or potential turning points.
Intraday Traders
Benefit from adjustable filters and fast-reacting smoothing to reduce noise in shorter timeframes while retaining contextual relevance.
Discretionary Analysts
Use the adaptive OB/OS thresholds and visual cues to supplement broader confluence zones or market structure analysis.
Customization Tips:
Higher Volatility Periods: Use more neighbors and enable filtering to reduce noise.
Lower Volatility Markets: Use fewer features and disable filtering for quicker RSI adaptation.
Deeper Contextual Analysis: Increase KNN lookback and raise the feature count to refine pattern recognition.
Accessibility Needs: Switch to Deuteranopia or Monochrome mode for clearer visuals in specific color vision conditions.
Final Thoughts:
The Machine Learning RSI combines familiar momentum logic with statistical context derived from historical similarity analysis. It does not attempt to predict price action but rather contextualizes RSI behavior with added nuance. This makes it a valuable tool for those looking to elevate traditional RSI workflows with adaptive, research-driven enhancements.
Double Tops/Bottoms [UAlgo]🔶Description:
The "Double Tops/Bottoms " indicator is designed to identify potential double tops and double bottoms on price charts. These patterns are often considered significant as they may indicate a reversal in the prevailing trend. The indicator can be applied to both high/low and close price data, offering flexibility in analyzing different aspects of market behavior.
🔶Key Features:
Source Selection: Users can choose between using high/low or close prices as the basis for identifying double tops and bottoms, allowing for tailored analysis based on specific price actions.
Lookback Length: The indicator offers a customizable lookback length, enabling users to adjust the sensitivity of pattern detection according to their trading preferences and timeframes.
Pivot Length: Users can specify the length of the pivot used in identifying double tops and bottoms, providing flexibility in capturing different market dynamics.
Minimum Bar Count Between Tops/Bottoms: A minimum bar count parameter allows users to control the distance between consecutive tops or bottoms, enhancing the accuracy of pattern recognition.
Pivot Tops/Bottoms Only: The indicator offers the option to focus exclusively on pivot tops and bottoms, streamlining the analysis process for users interested specifically in these key reversal points.
Disclaimer:
Trading involves substantial risk and is not suitable for every investor. The indicator provided here is intended for informational purposes only and should not be construed as investment advice or a recommendation to buy, sell, or hold any securities. Users are solely responsible for evaluating their own investment decisions and should seek professional financial advice if needed. The creator of this indicator (UAlgo) does not guarantee the accuracy, completeness, or reliability of the information provided, and shall not be liable for any losses incurred in connection with its use. By using this indicator, users acknowledge and agree to assume all risks associated with trading activities.
Simple Candle Strategy# Candle Pattern Strategy - Pine Script V6
## Overview
A TradingView trading strategy script (Pine Script V6) that identifies candlestick patterns over a configurable lookback period and generates trading signals based on pattern recognition rules.
## Strategy Logic
The strategy analyzes the most recent N candlesticks (default: 5) and classifies their patterns into three categories, then generates buy/sell signals based on specific pattern combinations.
### Candlestick Pattern Classification
Each candlestick is classified as one of three types:
| Pattern | Definition | Formula |
|---------|-----------|---------|
| **Close at High** | Close price near the highest price of the candle | `(high - close) / (high - low) ≤ (1 - threshold)` |
| **Close at Low** | Close price near the lowest price of the candle | `(close - low) / (high - low) ≤ (1 - threshold)` |
| **Doji** | Opening and closing prices very close; long upper/lower wicks | `abs(close - open) / (high - low) ≤ threshold` |
### Trading Rules
| Condition | Action | Signal |
|-----------|--------|--------|
| Number of Doji candles ≥ 3 | **SKIP** - Market is too chaotic | No trade |
| "Close at High" count ≥ 2 + Last candle closes at high | **LONG** - Bullish confirmation | Buy Signal |
| "Close at Low" count ≥ 2 + Last candle closes at low | **SHORT** - Bearish confirmation | Sell Signal |
## Configuration Parameters
All parameters are adjustable in TradingView's "Settings/Inputs" tab:
| Parameter | Default | Range | Description |
|-----------|---------|-------|-------------|
| **K-line Lookback Period** | 5 | 3-20 | Number of candlesticks to analyze |
| **Doji Threshold** | 0.1 | 0.0-1.0 | Body size / Total range ratio for doji identification |
| **Doji Count Limit** | 3 | 1-10 | Number of dojis that triggers skip signal |
| **Close at High Proximity** | 0.9 | 0.5-1.0 | Required proximity to highest price (0.9 = 90%) |
| **Close at Low Proximity** | 0.9 | 0.5-1.0 | Required proximity to lowest price (0.9 = 90%) |
### Parameter Tuning Guide
#### Proximity Thresholds (Close at High/Low)
- **0.95 or higher**: Stricter - only very strong candles qualify
- **0.90 (default)**: Balanced - good for most market conditions
- **0.80 or lower**: Looser - catches more patterns, higher false signals
#### Doji Threshold
- **0.05-0.10**: Strict doji identification
- **0.10-0.15**: Standard doji detection
- **0.15+**: Includes near-doji patterns
#### Lookback Period
- **3-5 bars**: Fast, sensitive to recent patterns
- **5-10 bars**: Balanced approach
- **10-20 bars**: Slower, filters out noise
## Visual Indicators
### Chart Markers
- **Green Up Arrow** ▲: Long entry signal triggered
- **Red Down Arrow** ▼: Short entry signal triggered
- **Gray X**: Skip signal (too many dojis detected)
### Statistics Table
Located at top-right corner, displays real-time pattern counts:
- **Close at High**: Count of candles closing near the high
- **Close at Low**: Count of candles closing near the low
- **Doji**: Count of doji/near-doji patterns
### Signal Labels
- Green label: "✓ Long condition met" - below entry bar
- Red label: "✓ Short condition met" - above entry bar
- Gray label: "⊠ Too many dojis, skip" - trade skipped
## Risk Management
### Exit Strategy
The strategy includes built-in exit rules based on ATR (Average True Range):
- **Stop Loss**: ATR × 2
- **Take Profit**: ATR × 3
Example: If ATR is $10, stop loss is at -$20 and take profit is at +$30
### Position Sizing
Default: 100% of equity per trade (adjustable in strategy properties)
**Recommendation**: Reduce to 10-25% of equity for safer capital allocation
## How to Use
### 1. Copy the Script
1. Open TradingView
2. Go to Pine Script Editor
3. Create a new indicator
4. Copy the entire `candle_pattern_strategy.pine` content
5. Click "Add to Chart"
### 2. Apply to Chart
- Select your preferred timeframe (1m, 5m, 15m, 1h, 4h, 1d)
- Choose a trading symbol (stocks, forex, crypto, etc.)
- The strategy will generate signals on all historical bars and in real-time
### 3. Configure Parameters
1. Right-click the strategy on chart → "Settings"
2. Adjust parameters in the "Inputs" tab
3. Strategy will recalculate automatically
4. Backtest results appear in the Strategy Tester panel
### 4. Backtesting
1. Click "Strategy Tester" (bottom panel)
2. Set date range for historical testing
3. Review performance metrics:
- Win rate
- Profit factor
- Drawdown
- Total returns
## Key Features
✅ **Execution Model Compliant** - Follows official Pine Script V6 standards
✅ **Global Scope** - All historical references in global scope for consistency
✅ **Adjustable Sensitivity** - Fine-tune all pattern detection thresholds
✅ **Real-time Updates** - Works on both historical and real-time bars
✅ **Visual Feedback** - Clear signals with labels and statistics table
✅ **Risk Management** - Built-in ATR-based stop loss and take profit
✅ **No Repainting** - Signals remain consistent after bar closes
## Important Notes
### Before Trading Live
1. **Backtest thoroughly**: Test on at least 6-12 months of historical data
2. **Paper trading first**: Practice with simulated trades
3. **Optimize parameters**: Find the best settings for your trading instrument
4. **Manage risk**: Never risk more than 1-2% per trade
5. **Monitor performance**: Review trades regularly and adjust as needed
### Market Conditions
The strategy works best in:
- Trending markets with clear directional bias
- Range-bound markets with defined support/resistance
- Markets with moderate volatility
The strategy may underperform in:
- Highly choppy/noisy markets (many false signals)
- Markets with gaps or overnight gaps
- Low liquidity periods
### Limitations
- Works on chart timeframes only (not intrabar analysis)
- Requires at least 5 bars of history (configurable)
- Fixed exit rules may not suit all trading styles
- No trend filtering (will trade both directions)
## Technical Details
### Historical Buffer Management
The strategy declares maximum bars back to ensure enough historical data:
```pine
max_bars_back(close, 20)
max_bars_back(open, 20)
max_bars_back(high, 20)
max_bars_back(low, 20)
```
This prevents runtime errors when accessing historical candlestick data.
### Pattern Detection Algorithm
```
For each bar in lookback period:
1. Calculate (high - close) / (high - low) → close_to_high_ratio
2. If close_to_high_ratio ≤ (1 - threshold) → count as "Close at High"
3. Calculate (close - low) / (high - low) → close_to_low_ratio
4. If close_to_low_ratio ≤ (1 - threshold) → count as "Close at Low"
5. Calculate abs(close - open) / (high - low) → body_ratio
6. If body_ratio ≤ doji_threshold → count as "Doji"
Signal Generation:
7. If doji_count ≥ cross_count_limit → SKIP_SIGNAL
8. If close_at_high_count ≥ 2 AND last_close_at_high → LONG_SIGNAL
9. If close_at_low_count ≥ 2 AND last_close_at_low → SHORT_SIGNAL
```
## Example Scenarios
### Scenario 1: Bullish Signal
```
Last 5 bars pattern:
Bar 1: Closes at high (95%) ✓
Bar 2: Closes at high (92%) ✓
Bar 3: Closes at mid (50%)
Bar 4: Closes at low (10%)
Bar 5: Closes at high (96%) ✓ (last bar)
Result:
- Close at high count: 3 (≥ 2) ✓
- Last closes at high: ✓
- Doji count: 0 (< 3) ✓
→ LONG SIGNAL ✓
```
### Scenario 2: Skip Signal
```
Last 5 bars pattern:
Bar 1: Doji pattern ✓
Bar 2: Doji pattern ✓
Bar 3: Closes at mid
Bar 4: Doji pattern ✓
Bar 5: Closes at high
Result:
- Doji count: 3 (≥ 3)
→ SKIP SIGNAL - Market too chaotic
```
## Performance Optimization
### Tips for Better Results
1. **Use Higher Timeframes**: 15m or higher reduces false signals
2. **Combine with Indicators**: Add volume or trend filters
3. **Seasonal Adjustment**: Different parameters for different seasons
4. **Instrument Selection**: Test on liquid, high-volume instruments
5. **Regular Rebalancing**: Adjust parameters quarterly based on performance
## Troubleshooting
### No Signals Generated
- Check if lookback period is too large
- Verify proximity thresholds aren't too strict (try 0.85 instead of 0.95)
- Ensure doji limit allows for trading (try 4-5 instead of 3)
### Too Many False Signals
- Increase proximity thresholds to 0.95+
- Reduce lookback period to 3-4 bars
- Increase doji limit to 3-4
- Test on higher timeframes
### Strategy Tester Shows Losses
- Review individual trades to identify patterns
- Adjust stop loss and take profit ratios
- Change lookback period and thresholds
- Test on different market conditions
## References
- (www.tradingview.com)
- (www.tradingview.com)
- (www.investopedia.com)
- (www.investopedia.com)
## Disclaimer
**This strategy is provided for educational and research purposes only.**
- Not financial advice
- Past performance does not guarantee future results
- Always conduct thorough backtesting before live trading
- Trading involves significant risk of loss
- Use proper risk management and position sizing
## License
Created: December 15, 2025
Version: 1.0
---
**For updates and modifications, refer to the accompanying documentation files.**
Viprasol Elite Advanced Pattern Scanner# 🚀 Viprasol Elite Advanced Pattern Scanner
## Overview
The **Viprasol Elite Advanced Pattern Scanner** is a sophisticated technical analysis tool designed to identify high-probability double bottom (DISCOUNT) and double top (PREMIUM) patterns with unprecedented accuracy. Unlike basic pattern detectors, this elite scanner employs an AI-powered quality scoring system to filter out false signals and highlight only the most reliable trading opportunities.
## 🎯 Key Features
### Advanced Pattern Detection
- **DISCOUNT Patterns** (Double Bottoms): Identifies bullish reversal zones where price may bounce
- **PREMIUM Patterns** (Double Tops): Detects bearish reversal zones where price may decline
- Multi-point validation system (5-point structure)
- Symmetry analysis with customizable tolerance
### 🤖 AI Quality Scoring System
Each pattern receives a quality score (0-100) based on:
- **Symmetry Analysis** (32% weight): How closely the two bottoms/tops match
- **Trend Context** (22% weight): Strength of the preceding trend using ADX
- **Volume Profile** (22% weight): Volume confirmation at key points
- **Pattern Depth** (16% weight): Significance of the pattern's price range
- **Structure Quality** (16% weight): Overall pattern formation quality
Quality Grades:
- ⭐ **ELITE** (88-100): Highest probability setups
- ✨ **VERY STRONG** (77-87): Strong trade opportunities
- ✓ **STRONG** (67-76): Valid patterns with good potential
- ○ **VALID** (65-66): Acceptable patterns meeting minimum criteria
### 🎯 Intelligent Target System
Three target modes per pattern direction:
- **Conservative**: 0.618 Fibonacci extension (safer, closer targets)
- **Balanced**: 1.0 extension (moderate risk/reward)
- **Aggressive**: 1.618 extension (higher risk/reward)
Targets automatically adjust based on pattern quality score.
### 🔧 Advanced Filtering Options
- **Volatility Filter (ATR)**: Excludes patterns during extreme volatility
- **Momentum Filter (ADX)**: Ensures sufficient trend strength
- **Liquidity Filter (Volume)**: Confirms adequate trading volume
### 📊 Pattern Lifecycle Management
- Real-time neckline tracking with extension multiplier
- Pattern invalidation after extended wait period
- Breakout/breakdown confirmation
- Reversal detection (pattern failure scenarios)
- Target achievement tracking
### 🌈 Premium Visual System
- Color-coded quality levels
- Cyber-themed color scheme (Neon Green/Hot Pink/Purple/Cyan)
- Transparent fills for pattern zones
- Dynamic labels with pattern information
- Elite dashboard showing live pattern stats
## 📈 How To Use
### Basic Setup
1. Add indicator to your chart
2. Enable desired patterns (DISCOUNT and/or PREMIUM)
3. Adjust quality threshold (default: 65) - higher = fewer but better signals
4. Set your preferred target mode
### Trading DISCOUNT Patterns (Bullish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakout above neckline (point 5)
4. Stop loss below the lowest bottom
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break below bottoms = SHORT signal)
### Trading PREMIUM Patterns (Bearish)
1. Wait for pattern detection (labeled points 1-4)
2. Check quality score on dashboard
3. Entry on breakdown below neckline (point 5)
4. Stop loss above the highest top
5. Target shown automatically based on your mode
6. ⚠️ Watch for pattern failure (break above tops = LONG signal)
## ⚙️ Input Settings Guide
### 🔍 Detection Engine
- **Left/Right Pivots**: Higher = fewer but cleaner patterns (default: 6/4)
- **Min Pattern Width**: Minimum bars between bottoms/tops (default: 12)
- **Symmetry Tolerance**: Max % difference allowed between levels (default: 1.8%)
- **Extension Multiplier**: How long to wait for breakout (default: 2.2x pattern width)
### ⭐ Quality AI
- **Min Quality Score**: Only show patterns above this score (default: 65)
- **Weight Distribution**: Customize what matters most (symmetry/trend/volume/depth/structure)
### 🔧 Filters
- **Volatility Filter**: Avoid choppy markets (recommended: ON)
- **Momentum Filter**: Ensure trend strength (recommended: ON)
- **Liquidity Filter**: Volume confirmation (recommended: ON)
### 💎 Target System
- Choose target aggression for each pattern type and direction
- Higher quality patterns get adjusted targets automatically
## 🎨 Visual Customization
- Adjust colors for DISCOUNT/PREMIUM patterns
- Set quality-based color coding
- Customize label sizes
- Toggle dashboard visibility and position
- Show/hide historical patterns
## 🚨 Alert System
Set up TradingView alerts for:
- 🚀 **LONG Signals**: DISCOUNT breakout, PREMIUM failure
- 📉 **SHORT Signals**: PREMIUM breakdown, DISCOUNT failure
- ✅ **Target Achievement**: When price hits your target
## 💡 Pro Tips
1. **Higher Timeframes = Better Signals**: Patterns on 4H, Daily, Weekly are more reliable
2. **Quality Over Quantity**: Focus on ELITE and VERY STRONG grades
3. **Combine with Trend**: DISCOUNT in uptrend, PREMIUM in downtrend = best results
4. **Watch Pattern Failures**: Failed patterns often provide strong counter-trend signals
5. **Adjust for Your Style**: Intraday traders use Conservative, swing traders use Aggressive
## 🔒 Pattern Invalidation
Patterns become invalid if:
- No breakout/breakdown within extension period
- Support/resistance levels are broken prematurely
- Pattern shown in faded colors = no longer active
## ⚠️ Risk Disclaimer
This indicator is a tool for technical analysis and does not guarantee profitable trades. Always:
- Use proper risk management
- Combine with other analysis methods
- Never risk more than you can afford to lose
- Past performance does not indicate future results
MusaCandlePatternsLibrary "MusaCandlePatterns"
Patterns is a Japanese candlestick pattern recognition Library for developers. Functions here within detect viable setups in a variety of popular patterns. Please note some patterns are without filters such as comparisons to average candle sizing, or trend detection to allow the author more freedom.
doji(dojiSize, dojiWickSize)
Detects "Doji" candle patterns
Parameters:
dojiSize (float) : (float) The relationship of body to candle size (ie. body is 5% of total candle size). Default is 5.0 (5%)
dojiWickSize (float) : (float) Maximum wick size comparative to the opposite wick. (eg. 2 = bottom wick must be less than or equal to 2x the top wick). Default is 2
Returns: (series bool) True when pattern detected
dLab(showLabel, labelColor, textColor)
Produces "Doji" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
bullEngulf(maxRejectWick, mustEngulfWick)
Detects "Bullish Engulfing" candle patterns
Parameters:
maxRejectWick (float) : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a top wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a top wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick (bool) : (bool) input to only detect setups that close above the high prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bewLab(showLabel, labelColor, textColor)
Produces "Bullish Engulfing" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
bearEngulf(maxRejectWick, mustEngulfWick)
Detects "Bearish Engulfing" candle patterns
Parameters:
maxRejectWick (float) : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a bottom wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a botom wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick (bool) : (bool) Input to only detect setups that close below the low prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bebLab(showLabel, labelColor, textColor)
Produces "Bearish Engulfing" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
hammer(ratio, shadowPercent)
Detects "Hammer" candle patterns
Parameters:
ratio (float) : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent (float) : (float) The maximum allowable top wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
hLab(showLabel, labelColor, textColor)
Produces "Hammer" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
star(ratio, shadowPercent)
Detects "Star" candle patterns
Parameters:
ratio (float) : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent (float) : (float) The maximum allowable bottom wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
ssLab(showLabel, labelColor, textColor)
Produces "Star" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
dragonflyDoji()
Detects "Dragonfly Doji" candle patterns
Returns: (series bool) True when pattern detected
ddLab(showLabel, labelColor, textColor)
Produces "Dragonfly Doji" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color)
Returns: (label) A label visible at the chart level intended for the title pattern
gravestoneDoji()
Detects "Gravestone Doji" candle patterns
Returns: (series bool) True when pattern detected
gdLab(showLabel, labelColor, textColor)
Produces "Gravestone Doji" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
tweezerBottom(closeUpperHalf)
Detects "Tweezer Bottom" candle patterns
Parameters:
closeUpperHalf (bool) : (bool) input to only detect setups that close above the mid-point of the candle prior increasing its bullish tendancy. Default is false
Returns: (series bool) True when pattern detected
tbLab(showLabel, labelColor, textColor)
Produces "Tweezer Bottom" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
tweezerTop(closeLowerHalf)
Detects "TweezerTop" candle patterns
Parameters:
closeLowerHalf (bool) : (bool) input to only detect setups that close below the mid-point of the candle prior increasing its bearish tendancy. Default is false
Returns: (series bool) True when pattern detected
ttLab(showLabel, labelColor, textColor)
Produces "TweezerTop" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
spinningTopBull(wickSize)
Detects "Bullish Spinning Top" candle patterns
Parameters:
wickSize (float) : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stwLab(showLabel, labelColor, textColor)
Produces "Bullish Spinning Top" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
spinningTopBear(wickSize)
Detects "Bearish Spinning Top" candle patterns
Parameters:
wickSize (float) : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stbLab(showLabel, labelColor, textColor)
Produces "Bearish Spinning Top" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
spinningTop(wickSize)
Detects "Spinning Top" candle patterns
Parameters:
wickSize (float) : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stLab(showLabel, labelColor, textColor)
Produces "Spinning Top" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
morningStar()
Detects "Bullish Morning Star" candle patterns
Returns: (series bool) True when pattern detected
msLab(showLabel, labelColor, textColor)
Produces "Bullish Morning Star" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
eveningStar()
Detects "Bearish Evening Star" candle patterns
Returns: (series bool) True when pattern detected
esLab(showLabel, labelColor, textColor)
Produces "Bearish Evening Star" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
haramiBull()
Detects "Bullish Harami" candle patterns
Returns: (series bool) True when pattern detected
hwLab(showLabel, labelColor, textColor)
Produces "Bullish Harami" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
haramiBear()
Detects "Bearish Harami" candle patterns
Returns: (series bool) True when pattern detected
hbLab(showLabel, labelColor, textColor)
Produces "Bearish Harami" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
haramiBullCross()
Detects "Bullish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcwLab(showLabel, labelColor, textColor)
Produces "Bullish Harami Cross" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
haramiBearCross()
Detects "Bearish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcbLab(showLabel, labelColor, textColor)
Produces "Bearish Harami Cross" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color)
Returns: (label) A label visible at the chart level intended for the title pattern
marubullzu()
Detects "Bullish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mwLab(showLabel, labelColor, textColor)
Produces "Bullish Marubozu" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
marubearzu()
Detects "Bearish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mbLab(showLabel, labelColor, textColor)
Produces "Bearish Marubozu" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
abandonedBull()
Detects "Bullish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abwLab(showLabel, labelColor, textColor)
Produces "Bullish Abandoned Baby" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
abandonedBear()
Detects "Bearish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abbLab(showLabel, labelColor, textColor)
Produces "Bearish Abandoned Baby" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
piercing()
Detects "Piercing" candle patterns
Returns: (series bool) True when pattern detected
pLab(showLabel, labelColor, textColor)
Produces "Piercing" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
darkCloudCover()
Detects "Dark Cloud Cover" candle patterns
Returns: (series bool) True when pattern detected
dccLab(showLabel, labelColor, textColor)
Produces "Dark Cloud Cover" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
tasukiBull()
Detects "Upside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
utgLab(showLabel, labelColor, textColor)
Produces "Upside Tasuki Gap" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
tasukiBear()
Detects "Downside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
dtgLab(showLabel, labelColor, textColor)
Produces "Downside Tasuki Gap" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
risingThree()
Detects "Rising Three Methods" candle patterns
Returns: (series bool) True when pattern detected
rtmLab(showLabel, labelColor, textColor)
Produces "Rising Three Methods" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
fallingThree()
Detects "Falling Three Methods" candle patterns
Returns: (series bool) True when pattern detected
ftmLab(showLabel, labelColor, textColor)
Produces "Falling Three Methods" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
risingWindow()
Detects "Rising Window" candle patterns
Returns: (series bool) True when pattern detected
rwLab(showLabel, labelColor, textColor)
Produces "Rising Window" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
fallingWindow()
Detects "Falling Window" candle patterns
Returns: (series bool) True when pattern detected
fwLab(showLabel, labelColor, textColor)
Produces "Falling Window" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
kickingBull()
Detects "Bullish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kwLab(showLabel, labelColor, textColor)
Produces "Bullish Kicking" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
kickingBear()
Detects "Bearish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kbLab(showLabel, labelColor, textColor)
Produces "Bearish Kicking" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
lls(ratio)
Detects "Long Lower Shadow" candle patterns
Parameters:
ratio (float) : (float) A relationship of the lower wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
llsLab(showLabel, labelColor, textColor)
Produces "Long Lower Shadow" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
lus(ratio)
Detects "Long Upper Shadow" candle patterns
Parameters:
ratio (float) : (float) A relationship of the upper wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
lusLab(showLabel, labelColor, textColor)
Produces "Long Upper Shadow" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
bullNeck()
Detects "Bullish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nwLab(showLabel, labelColor, textColor)
Produces "Bullish On Neck" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
bearNeck()
Detects "Bearish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nbLab(showLabel, labelColor, textColor)
Produces "Bearish On Neck" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
soldiers(wickSize)
Detects "Three White Soldiers" candle patterns
Parameters:
wickSize (float) : (float) Maximum allowable top wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
wsLab(showLabel, labelColor, textColor)
Produces "Three White Soldiers" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
crows(wickSize)
Detects "Three Black Crows" candle patterns
Parameters:
wickSize (float) : (float) Maximum allowable bottom wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
bcLab(showLabel, labelColor, textColor)
Produces "Three Black Crows" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
triStarBull()
Detects "Bullish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tswLab(showLabel, labelColor, textColor)
Produces "Bullish Tri-Star" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
triStarBear()
Detects "Bearish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tsbLab(showLabel, labelColor, textColor)
Produces "Bearish Tri-Star" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
insideBar()
Detects "Inside Bar" candle patterns
Returns: (series bool) True when pattern detected
insLab(showLabel, labelColor, textColor)
Produces "Inside Bar" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
doubleInside()
Detects "Double Inside Bar" candle patterns
Returns: (series bool) True when pattern detected
dinLab(showLabel, labelColor, textColor)
Produces "Double Inside Bar" identifier label
Parameters:
showLabel (bool) : (series bool) Shows label when input is true. Default is false
labelColor (color) : (series color) Color of the label border and arrow
textColor (color) : (series color) Text color
Returns: (label) A label visible at the chart level intended for the title pattern
wrap(cond, barsBack, borderColor, bgColor)
Produces a box wrapping the highs and lows over the look back.
Parameters:
cond (bool) : (series bool) Condition under which to draw the box.
barsBack (int) : (series int) the number of bars back to begin drawing the box.
borderColor (color) : (series color) Color of the four borders. Optional. The default is `color.gray` with a 45% transparency.
bgColor (color)
Returns: (box) A box whom's top and bottom are above and below the highest and lowest points over the lookback
topWick()
Returns the top wick size of the current candle
Returns: (series float) A value equivelent to the distance from the top of the candle body to its high
bottomWick()
Returns the bottom wick size of the current candle
Returns: (series float) A value equivelent to the distance from the bottom of the candle body to its low
body()
Returns the body size of the current candle
Returns: (series float) A value equivelent to the distance between the top and the bottom of the candle body
highestBody()
Returns the highest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
lowestBody()
Returns the lowest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
barRange()
Returns the height of the current candle
Returns: (series float) A value equivelent to the distance between the high and the low of the candle
bodyPct()
Returns the body size as a percent
Returns: (series float) A value equivelent to the percentage of body size to the overall candle size
midBody()
Returns the price of the mid-point of the candle body
Returns: (series float) A value equivelent to the center point of the distance bewteen the body low and the body high
bodyupGap()
Returns true if there is a gap up between the real body of the current candle in relation to the candle prior
Returns: (series bool) True if there is a gap up and no overlap in the real bodies of the current candle and the preceding candle
bodydwnGap()
Returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) True if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapUp()
Returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) True if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapDwn()
Returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) True if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
dojiBody()
Returns true if the candle body is a doji
Returns: (series bool) True if the candle body is a doji. Defined by a body that is 5% of total candle size
Elliott Wave + SMC Fusion # Elliott Wave + SMC Fusion
## TITLE:
Elliott Wave + Smart Money Concepts Fusion
---
## SHORT DESCRIPTION:
Automated Elliott Wave pattern detection with Smart Money Concepts confirmation, EWO oscillator integration, and confluence scoring system.
---
## FULL DESCRIPTION:
### 📊 OVERVIEW
This indicator combines three powerful trading methodologies into a unified system:
- **Elliott Wave Theory** - Automated detection of Wave 1-2 impulse patterns
- **Smart Money Concepts (SMC)** - Order Blocks and Fair Value Gaps for institutional confirmation
- **Elliott Wave Oscillator (EWO)** - Momentum-based signal validation
The core concept is to identify high-probability Wave 3 entries by detecting completed Wave 1-2 structures and validating them with SMC and momentum indicators.
---
### 🔧 HOW IT WORKS
**1. Pattern Detection (ZigZag Method)**
- Uses pivot high/low detection to identify swing points
- Validates Wave 2 retracement using Fibonacci ratios (default: 38.2% - 88.6%)
- Requires minimum wave size to filter noise
- Applies confirmation bars to avoid premature signals
**2. Wave Projections**
- Wave 3 target: Fibonacci extension of Wave 1 (default: 1.618)
- Wave 4 retracement: Percentage of Wave 3 (default: 38.2%)
- Wave 5 projection: Extension of Wave 1 from Wave 4
**3. Smart Money Validation**
- **Order Blocks**: Identifies last opposing candle before breakout (institutional footprint)
- **Fair Value Gaps**: Detects price imbalances for potential support/resistance
**4. EWO Confirmation**
- Calculates momentum: (EMA5 / EMA34 - 1) × 100
- Signal line crossovers confirm trend direction
- Strong signals occur at extremes (< -13 or > 13 threshold)
**5. Confluence Scoring (0-100%)**
Points awarded for:
- Fibonacci quality of Wave 2 retracement (10-30 pts)
- Order Block presence (15 pts)
- Fair Value Gap presence (10 pts)
- Volume confirmation (10-15 pts)
- Trend alignment with EMA50 (10 pts)
- EWO confirmation (10-20 pts)
---
### 🎯 UNIQUE FEATURES
**Pattern Locking System**
- Once a valid pattern is detected, it locks until:
- Pattern invalidates (price breaks Wave 0)
- Pattern completes (Wave 5 reached)
- Auto-timeout (configurable bars)
- Prevents rapid signal flipping and false alerts
**Signal Stability Controls**
- Adjustable cooldown between signals (default: 20 bars)
- Minimum bar distance between wave points
- Direction change requirement option
- Confirmation bars after Wave 2 formation
**Visual Wave Tracking**
- Solid lines for impulse waves (0→1, 2→3, 4→5)
- Dashed lines for corrective waves (1→2, 3→4)
- Numbered labels on each wave point
- Real-time projection lines to targets
**Comprehensive Dashboard**
- Current wave status and lock state
- Pattern grade (A+ to D based on confluence)
- Projected vs actual wave levels (✓ when completed)
- SMC confirmation status
- Risk/Reward ratio calculation
- EWO trend direction
---
### 📈 TRADING APPLICATION
**Entry Strategy**
- Wait for Wave 1-2 pattern detection (diamond signal)
- Check confluence score (>65% = higher probability)
- Verify EWO alignment with pattern direction
- Enter after 30% retracement of Wave 2 (customizable)
**Risk Management**
- Stop Loss: Below Wave 0 (with buffer)
- Take Profit 1: Wave 3 projection
- Take Profit 2: Wave 5 projection
- R:R displayed in dashboard
**Invalidation Rules**
- Price breaks below Wave 0 (bullish) or above (bearish)
- Wave 2 level violated before Wave 3 forms
- Pattern timeout exceeded
---
### ⚙️ KEY SETTINGS
**Elliott Wave**
- ZigZag Length: Pivot detection sensitivity
- Fib Tolerance: Acceptable retracement range
- Min Wave Size: Filter small movements
**Signal Stability**
- Signal Cooldown: Minimum bars between signals
- Lock Pattern Until Invalid: Prevent signal changes
- Confirmation Bars: Wait after Wave 2
**Wave Projection**
- Wave 3/4/5 Fibonacci extensions
- Projection display distance
**EWO Settings**
- Fast/Slow EMA lengths
- Signal smoothing
- Strength threshold
**SMC Settings**
- Order Block lookback period
- FVG minimum size percentage
---
### 🔔 ALERTS
- New bullish/bearish pattern detected
- High confluence setup (>75%)
- Pattern invalidation
- Wave completion
---
### ⚠️ IMPORTANT NOTES
- This indicator identifies **potential** Elliott Wave patterns based on mathematical rules
- Elliott Wave analysis is subjective - patterns may be interpreted differently
- Always combine with other analysis methods and proper risk management
- Past pattern performance does not guarantee future results
- Pattern locking prevents repainting but delays new pattern detection
- Best used on higher timeframes (1H+) for cleaner wave structures
---
### 📚 METHODOLOGY REFERENCES
**Elliott Wave Theory**
- Wave 2 typically retraces 38.2% - 88.6% of Wave 1
- Wave 3 is often the strongest, extending 161.8% of Wave 1
- Wave 4 usually retraces 38.2% of Wave 3
- Wave 5 completes the impulse structure
**Smart Money Concepts**
- Order Blocks represent institutional supply/demand zones
- FVGs indicate price inefficiencies that may act as magnets
**Elliott Wave Oscillator**
- Developed to identify wave momentum
- Crossovers signal potential wave transitions
- Extreme readings often coincide with wave completions
---
### 🎨 VISUAL ELEMENTS
- **Green**: Bullish patterns and projections
- **Red**: Bearish patterns and projections
- **Orange**: Wave projection levels
- **Purple**: Order Block zones
- **Yellow**: Fair Value Gaps
- **Blue**: Entry levels
- **Diamond shapes**: New pattern signals
- **Triangle shapes**: EWO crossover signals
---
### 💡 TIPS FOR BEST RESULTS
1. Use on liquid markets with clear trend behavior
2. Higher timeframes produce more reliable patterns
3. Look for confluence scores above 65%
4. Verify EWO alignment before entry
5. Consider market context (overall trend, key levels)
6. Adjust ZigZag length based on your trading style
7. Increase cooldown period for longer-term signals
---
**Indicator Type**: Overlay
**Markets**: All (Crypto, Forex, Stocks, Commodities)
**Timeframes**: All (1H+ recommended)
**Style**: Pattern Recognition + Momentum + Price Action
Tweezer & Kangaroo Zones [WavesUnchained]Tweezer & Kangaroo Zones
Pattern Recognition with Supply/Demand Zones
Indicator that detects tweezer and kangaroo tail (pin bar) reversal patterns and creates supply and demand zones. Includes volume validation, trend context, and confluence scoring.
What You See on Your Chart
Pattern Labels:
"T" (Red) - Tweezer Top detected above price → Bearish reversal signal
"T" (Green) - Tweezer Bottom detected below price → Bullish reversal signal
"K" (Red) - Kangaroo Bear (Pin Bar rejection from top) → Bearish signal
"K" (Green) - Kangaroo Bull (Pin Bar rejection from bottom) → Bullish signal
Label Colors Indicate Pattern Strength:
Dark Green/Red - Strong pattern (score ≥8.0)
Medium Green/Red - Good pattern (score ≥6.0)
Light Green/Red - Valid pattern (score <6.0)
Zone Boxes:
Red Boxes - Supply Zones (resistance, potential short areas)
Green Boxes - Demand Zones (support, potential long areas)
White Border - Active zone (fresh, not tested yet)
Gray Border - Inactive zone (expired or invalidated)
Pattern Detection
Tweezer Patterns (Classic Double-Top/Bottom):
Flexible Lookback - Detects patterns up to 3 bars apart (not just consecutive)
Precision Matching - 0.2% level tolerance for high-quality signals
Wick Similarity Check - Both candles must show similar rejection wicks
Volume Validation - Second candle requires elevated volume (0.8x average)
Pattern Strength Score - 0-1 quality rating based on level match + wick similarity
Optional Trend Context - Can require trend alignment (default: OFF for more signals)
Kangaroo Tail / Pin Bar Patterns:
No Pivot Delay - Instant detection without waiting for pivot confirmation
Body Position Check - Body must be at candle extremes (30% tolerance)
Volume Spike - Rejection must occur with volume (0.9x average)
Rejection Strength - Scores based on wick length (0.5-0.9 of range)
Optional Trend Context - Bearish in uptrends, Bullish in downtrends (default: OFF)
Zone Management
Auto-Created Zones - Every valid pattern creates a supply/demand zone
Overlap Prevention - Zones too close together (50% overlap) are not duplicated
Lifetime Control - Zones expire after 400 bars (configurable)
Smart Invalidation - Zones invalidate when price closes through them
Styling Options - Choose between Solid, Dashed, or Dotted borders
Border Width - 2px width for better visibility
Confluence Scoring System
Multi-factor confluence scoring (0-10 scale) with configurable weights:
Regime (EMA+HTF) - Trend alignment across timeframes (Weight: 2.0)
HTF Stack - Multi-timeframe trend confluence (Weight: 3.0)
Structure - Higher lows / Lower highs confirmation (Weight: 1.0)
Relative Volume - Volume surge validation (Weight: 1.0)
Chop Advantage - Favorable market conditions (Weight: 1.0)
Zone Thinness - Tight zones = better R/R (Weight: 1.0)
Supertrend - Trend indicator alignment (Weight: 1.0)
MOST - Moving Stop alignment (Weight: 1.0)
Pattern Strength - Quality of detected pattern (Weight: 1.5)
Zone Retest Signals
Signals generated when zones are retested:
BUY Signal - Price retests demand zone from above (score ≥4.5)
SELL Signal - Price retests supply zone from below (score ≥5.5)
Normalized Score - Displayed as 0-10 for easy interpretation
Optional Trend Gate - Require trend alignment for signals (default: OFF)
Alert Ready - Built-in alertconditions for automation
Additional Features
Auto-Threshold Tuning - Adapts to ATR and Choppiness automatically
Session Profiles - Different settings for RTH vs ETH sessions
Organized Settings - 15+ input groups for easy configuration
Optional Panels - HTF Stack overview and performance metrics (default: OFF)
Data Exports - Hidden plots for strategy/library integration
RTA Health Monitoring - Built-in performance tracking
Setup & Configuration
Quick Start:
1. Apply indicator to any timeframe
2. Patterns and zones appear automatically
3. Adjust pattern detection sensitivity if needed
4. Configure zone styling (Solid/Dashed/Dotted)
5. Set up alerts for zone retests
Key Settings to Adjust:
Pattern Detection:
• Min RelVolume: Lower = more signals (0.8 Tweezer, 0.9 Kangaroo)
• Require trend context: Enable for stricter, higher-quality patterns
• Check wick similarity: Ensures proper rejection structure
Zone Management:
• Zone lifetime: How long zones remain active (default: 400 bars)
• Invalidate on close-through: Remove zones when price breaks through
• Max overlap: Prevent duplicate zones (default: 50%)
Scoring:
• Min Score BUY/SELL: Higher = fewer but better signals (default: 4.5/5.5)
• Component weights: Customize what factors matter most
• Signals require trend gate: OFF = more signals, ON = higher quality
Visual Customization
Zone Colors - Light red/green with 85% transparency (non-intrusive)
Border Styles - Solid, Dashed, or Dotted
Label Intensity - Darker greens for better readability
Clean Charts - All panels OFF by default
Understanding the Zones
Supply Zones (Red):
Created from bearish patterns (Tweezer Tops, Kangaroo Bears). Price made a high attempt to push higher, but was rejected. These become resistance areas where sellers may step in again.
Demand Zones (Green):
Created from bullish patterns (Tweezer Bottoms, Kangaroo Bulls). Price made a low with strong rejection. These become support areas where buyers may step in again.
Zone Quality Indicators:
• White border = Fresh zone, not tested yet
• Gray border = Zone expired or invalidated
• Thin zones (tight range) = Better risk/reward ratio
• Thick zones = Less precise, wider stop required
Trading Applications
Reversal Trading - Enter at pattern detection with tight stops
Zone Retest Trading - Wait for retests of established zones
Trend Confluence - Trade only when patterns align with trend
Risk Management - Use zone boundaries for stop placement
Target Setting - Opposite zones become profit targets
Pro Tips
Best signals occur when pattern + zone retest + trend all align
Lower timeframes = more signals but more noise
Higher timeframes = fewer but more reliable signals
Start with default settings, adjust based on your market
Combine with other analysis (structure, key levels, etc.)
Use alerts to avoid staring at charts all day
Important Notes
Not all patterns will lead to successful trades
Use proper risk management and position sizing
Patterns work best in trending or range-bound markets
Very choppy conditions may produce lower-quality signals
Always confirm with your own analysis before trading
Technical Specifications
• Pine Script v6
• RTA-Core integration
• RTA Core Library integration
• Maximum 200 boxes, 500 labels
• Auto-tuning based on ATR and Choppiness
• Session-aware threshold adjustments
• Memory-optimized zone management
What's Included
Tweezer Top/Bottom detection
Kangaroo Tail / Pin Bar detection
Automatic supply/demand zone creation
Volume validation system
Pattern strength scoring
Zone retest signals
Multi-factor confluence scoring
Optional HTF Stack panel
Optional performance metrics
Session profile support
Auto-threshold tuning
Alert conditions
Data exports for strategies
Author Waves Unchained
Version 1.0
Status Public Indicator
Summary
Reversal pattern detection with zone management, volume validation, and confluence scoring for tweezer and kangaroo tail patterns.
---
Disclaimer: This indicator is for educational and informational purposes only. Trading involves risk. Past performance does not guarantee future results. Always practice proper risk management.
Grand Master's Candlestick Dominance (ATR Enhanced)### Grand Master's Candlestick Dominance (ATR Enhanced)
**Overview**
Unleash the ancient wisdom of Japanese candlestick charting with a modern twist! This comprehensive Pine Script v5 strategy and indicator scans for over 75 classic and advanced candlestick patterns (bullish, bearish, and neutral), assigning dynamic strength scores (1-10) to each for precise signal filtering. Enhanced with Average True Range (ATR) for volatility-aware body size validation, it dominates the markets by combining timeless pattern recognition with robust confirmation layers. Whether used as a backtestable strategy or visual indicator, it empowers traders to spot high-probability reversals, continuations, and indecision setups with surgical accuracy.
Inspired by Steve Nison's *Japanese Candlestick Charting Techniques*, this tool elevates pattern analysis beyond basics—think Hammers, Engulfing patterns, Morning Stars, and rare gems like Abandoned Baby or Concealing Baby Swallow—all consolidated into intelligent arrays for real-time averaging and prioritization.
**Key Features**
- **Extensive Pattern Library**:
- **Bullish (25+ patterns)**: Hammer (8.0), Bullish Engulfing (10.0), Morning Star (7.0), Three White Soldiers (9.0), Dragonfly Doji (8.0), and more (e.g., Rising Three, Unique Three River Bottom).
- **Bearish (25+ patterns)**: Hanging Man (8.0), Bearish Engulfing (10.0), Evening Star (7.0), Three Black Crows (9.0), Gravestone Doji (8.0), and exotics like Upside Gap Two Crows or Stalled Pattern.
- **Neutral/Indecision (34+ patterns)**: Doji variants (Long-Legged, Four Price), Spinning Tops, Harami Crosses, and multi-bar setups like Upside Tasuki Gap or Advancing Block.
Each pattern includes duration tracking (1-5 bars) and ATR-adjusted body/shadow criteria for relevance in volatile conditions.
- **Smart Confirmation Filters** (All Toggleable):
- **Trend Alignment**: 20-period SMA (customizable) ensures entries align with the prevailing trend; optional higher timeframe (e.g., Daily) MA crossover for multi-timeframe confluence.
- **Support/Resistance (S/R)**: Pivot-based levels with 0.01% tolerance to confirm bounces or breaks.
- **Volume Surge**: 20-period volume MA with 1.5x spike multiplier to validate momentum.
- **ATR Body Sizing**: Filters small bodies (<0.3x ATR) and long bodies (>0.8x ATR) for context-aware pattern reliability.
- **Follow-Through**: Ensures post-pattern confirmation via bullish/bearish closes or closes beyond prior bars.
Minimum average strength (default 7.0) and individual pattern thresholds (5.0) prevent weak signals.
- **Entry & Exit Logic**:
- **Long Entry**: Bullish average strength ≥7.0 (outweighing bearish), uptrend, volume spike, near support, follow-through, and HTF alignment.
- **Short Entry**: Mirror for bearish dominance in downtrends near resistance.
- **Exits**: Bearish/neutral shift, or fixed TP (5%) / SL (2%)—pyramiding disabled, 10% equity sizing.
- Backtest range: Jan 1, 2020 – Dec 31, 2025 (editable). Initial capital: $10,000.
- **Interactive Dashboard** (Top-Right Panel):
Real-time insights including:
- Market phase (e.g., "Bullish Phase (Avg Str: 8.2)"), active pattern (e.g., "BULLISH: Bullish Engulfing (Str: 10.0, Bars: 2)"), and trend status.
- Strength breakdowns (Bull/Bear/Neutral counts & averages).
- Filter status (e.g., "Volume: ✔ Spike", "ATR: Enabled (L:0.8, S:0.3)").
- Backtest stats: Total trades, win rate, streak, and last entry/exit details (price & timestamp).
Toggle mode: Strategy (live trades) or Indicator (signals only).
- **Advanced Alerts** (15+ Toggleable Types):
Set up via TradingView's "Any alert() function call" for bar-close triggers:
- Entry/Exit signals with strength & pattern details.
- Strong patterns (≥2 bullish/bearish), neutral indecision, volume spikes.
- S/R breakouts, HTF reversals, high-confidence singles (≥8.0 strength).
- Conflicting signals, MA crossovers, ATR volatility bursts, multi-bar completions.
Example: "STRONG BULLISH PATTERN detected! Strength: 9.5 | Top Pattern: Three White Soldiers | Trend: Up".
**Customization & Usage Tips**
- **Inputs Groups**: Strategy toggles, confirmations, exits, backtest dates, and 15+ alert switches—all intuitively grouped.
- **Optimization**: Tune min strengths for aggressive (lower) or conservative (higher) trading; enable/disable filters to suit your style (e.g., disable S/R for scalping).
- **Best For**: Forex, stocks, crypto on 1H–Daily charts. Test on historical data to refine TP/SL.
- **Limitations**: No external data installs; relies on built-in TA functions. Patterns are probabilistic—combine with your risk management.
Master the candles like a grandmaster. Deploy on TradingView, backtest relentlessly, and let dominance begin! Questions? Drop a comment.
*Version: 1.0 | Updated: September 2025 | Credits: Built on Pine Script v5 with nods to Nison's timeless techniques.*
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.
N Bar Reversal Detector [LuxAlgo]The N Bar Reversal Detector is designed to detect and highlight N-bar reversal patterns in user charts, where N represents the length of the candle sequence used to detect the patterns. The script incorporates various trend indicators to filter out detected signals and offers a range of customizable settings to fit different trading strategies.
🔶 USAGE
The N-bar reversal pattern extends the popular 3-bar reversal pattern. While the 3-bar reversal pattern involves identifying a sequence of three bars signaling a potential trend reversal, the N-bar reversal pattern builds on this concept by incorporating additional bars based on user settings. This provides a more comprehensive indication of potential trend reversals. The script automates the identification of these patterns and generates clear, visually distinct signals to highlight potential trend changes.
When a reversal chart pattern is confirmed and aligns with the price action, the pattern's boundaries are extended to create levels. The upper boundary serves as resistance, while the lower boundary acts as support.
The script allows users to filter patterns based on the trend direction identified by various trend indicators. Users can choose to view patterns that align with the detected trend or those that are contrary to it.
🔶 DETAILS
🔹 The N-bar Reversal Pattern
The N-bar reversal pattern is a technical analysis tool designed to signal potential trend reversals in the market. It consists of N consecutive bars, with the first N-1 bars used to identify the prevailing trend and the Nth bar confirming the reversal. Here’s a detailed look at the pattern:
Bullish Reversal : In a bullish reversal setup, the first bar is the highest among the first N-1 bars, indicating a prevailing downtrend. Most of the remaining bars in this sequence should be bearish (closing lower than where they opened), reinforcing the existing downward momentum. The Nth (most recent) bar confirms a bullish reversal if its high price is higher than the high of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be higher than the high of the first bar.
Bearish Reversal : In a bearish reversal setup, the first bar is the lowest among the first N-1 bars, indicating a prevailing uptrend. Most of the remaining bars in this sequence should be bullish (closing higher than where they opened), reinforcing the existing upward momentum. The Nth bar confirms a bearish reversal if its low price is lower than the low of the first bar in the sequence (standard pattern). For a stronger signal, the closing price of the Nth bar should also be lower than the low of the first bar.
🔹 Min Percentage of Required Candles
This parameter specifies the minimum percentage of candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) among the first N-1 candles in a pattern. For higher values of N, it becomes more challenging for all of the first N-1 candles to be consistently bullish or bearish. By setting a percentage value, P, users can adjust the requirement so that only a minimum of P percent of the first N-1 candles need to meet the bullish or bearish condition. This allows for greater flexibility in pattern recognition, accommodating variations in market conditions.
🔶 SETTINGS
Pattern Type: Users can choose the type of the N-bar reversal patterns to detect: Normal, Enhanced, or All. "Normal" detects patterns that do not necessarily surpass the high/low of the first bar. "Enhanced" detects patterns where the last bar surpasses the high/low of the first bar. "All" detects both Normal and Enhanced patterns.
Reversal Pattern Sequence Length: Specifies the number of candles (N) in the sequence used to identify a reversal pattern.
Min Percentage of Required Candles: Sets the minimum percentage of the first N-1 candles that must be bullish (for a bearish reversal) or bearish (for a bullish reversal) to qualify as a valid reversal pattern.
Derived Support and Resistance: Toggles the visibility of the support and resistance levels/zones.
🔹 Trend Filtering
Filtering: Allows users to filter patterns based on the trend indicators: Moving Average Cloud, Supertrend, and Donchian Channels. The "Aligned" option only detects patterns that align with the trend and conversely, the "Opposite" option detects patterns that go against the trend.
🔹 Trend Indicator Settings
Moving Average Cloud: Allows traders to choose the type of moving averages (SMA, EMA, HMA, etc.) and set the lengths for fast and slow moving averages.
Supertrend: Options to set the ATR length and factor for Supertrend.
Donchian Channels: Option to set the length for the channel calculation.
🔶 RELATED SCRIPTS
Reversal-Candlestick-Structure.
Reversal-Signals.
Flags and Pennants [Trendoscope®]🎲 An extension to Chart Patterns based on Trend Line Pairs - Flags and Pennants
After exploring Algorithmic Identification and Classification of Chart Patterns and developing Auto Chart Patterns Indicator , we now delve into extensions of these patterns, focusing on Flag and Pennant Chart Patterns. These patterns evolve from basic trend line pair-based structures, often influenced by preceding market impulses.
🎲 Identification rules for the Extension Patterns
🎯 Identify the existence of Base Chart Patterns
Before identifying the flag and pennant patterns, we first need to identify the existence of following base trend line pair based converging or parallel patterns.
Ascending Channel
Descending Channel
Rising Wedge (Contracting)
Falling Wedge (Contracting)
Converging Triangle
Descending Triangle (Contracting)
Ascending Triangle (Contracting)
🎯 Identifying Extension Patterns.
The key to pinpointing these patterns lies in spotting a strong impulsive wave – akin to a flagpole – preceding a base pattern. This setup suggests potential for an extension pattern:
A Bullish Flag emerges from a positive impulse followed by a descending channel or a falling wedge
A Bearish Flag appears after a negative impulse leading to an ascending channel or a rising wedge.
A Bullish Pennant is indicated by a positive thrust preceding a converging triangle or ascending triangle.
A Bearish Pennant follows a negative impulse and a converging or descending triangle.
🎲 Pattern Classifications and Characteristics
🎯 Bullish Flag Pattern
Characteristics of Bullish Flag Pattern are as follows
Starts with a positive impulse wave
Immediately followed by either a short descending channel or a falling wedge
Here is an example of Bullish Flag Pattern
🎯 Bearish Flag Pattern
Characteristics of Bearish Flag Pattern are as follows
Starts with a negative impulse wave
Immediately followed by either a short ascending channel or a rising wedge
Here is an example of Bearish Flag Pattern
🎯 Bullish Pennant Pattern
Characteristics of Bullish Pennant Pattern are as follows
Starts with a positive impulse wave
Immediately followed by either a converging triangle or ascending triangle pattern.
Here is an example of Bullish Pennant Pattern
🎯 Bearish Pennant Pattern
Characteristics of Bearish Pennant Pattern are as follows
Starts with a negative impulse wave
Immediately followed by either a converging triangle or a descending converging triangle pattern.
Here is an example of Bearish Pennant Pattern
🎲 Trading Extension Patterns
In a strong market trend, it's common to see temporary periods of consolidation, forming patterns that either converge or range, often counter to the ongoing trend direction. Such pauses may lay the groundwork for the continuation of the trend post-breakout. The assumption that the trend will resume shapes the underlying bias of Flag and Pennant patterns
It's important, however, not to base decisions solely on past trends. Conducting personal back testing is crucial to ascertain the most effective entry and exit strategies for these patterns. Remember, the behavior of these patterns can vary significantly with the volatility of the asset and the specific timeframe being analyzed.
Approach the interpretation of these patterns with prudence, considering that market dynamics are subject to a wide array of influencing factors that might deviate from expected outcomes. For investors and traders, it's essential to engage in thorough back testing, establishing entry points, stop-loss orders, and target goals that align with your individual trading style and risk appetite. This step is key to assessing the viability of these patterns in line with your personal trading strategies and goals.
It's fairly common to witness a breakout followed by a swift price reversal after these patterns have formed. Additionally, there's room for innovation in trading by going against the bias if the breakout occurs in the opposite direction, specially when the trend before the formation of the pattern is in against the pattern bias.
🎲 Cheat Sheet
🎲 Indicator Settings
Custom Source : Enables users to set custom OHLC - this means, the indicator can also be applied on oscillators and other indicators having OHLC values.
Zigzag Settings : Allows users to enable different zigzag base and set length and depth for each zigzag.
Scanning Settings : Pattern scanning settings set some parameters that define the pattern recognition process.
Display Settings : Determine the display of indicators including colors, lines, labels etc.
Backtest Settings : Allows users to set a predetermined back test bars so that the indicator will not time out while trying to run for all available bars.
Auto Chart Patterns [Trendoscope®]🎲 Introducing our most comprehensive automatic chart pattern recognition indicator.
Last week, we published an idea on how to algorithmically identify and classify chart patterns.
This indicator is nothing but the initial implementation of the idea. Whatever we explained in that publication that users can do manually to identify and classify the pattern, this indicator will do it for them.
🎲 Process of identifying the patterns.
The bulk of the logic is implemented as part of the library - chartpatterns . The indicator is a shell that captures the user inputs and makes use of the library to deliver the outcome.
🎯 Here is the list of steps executed to identify the patterns on the chart.
Derive multi level recursive zigzag for multiple base zigzag length and depth combinations.
For each zigzag and level, check the last 5 pivots or 6 pivots (based on the input setting) for possibility of valid trend line pairs.
If there is a valid trend line pair, then there is pattern.
🎯 Rules for identifying the valid trend line pairs
There should be at least two trend lines that does not intersect between the starting and ending pivots.
The upper trend line should touch all the pivot highs of the last 5 or 6 pivots considered for scanning the patterns
The lower trend line should touch all the pivot lows of the last 5 or 6 pivots considered for scanning the patterns.
None of the candles from starting pivot to ending pivot should fall outside the trend lines (above upper trend line and below lower trend line)
The existence of a valid trend line pair signifies the existence of pattern. What type of pattern it is, to identify that we need to go through the classification rules.
🎲 Process of classification of the patterns.
We need to gather the following information before we classify the pattern.
Direction of upper trend line - rising, falling or flat
Direction of lower trend line - rising, falling or flat
Characteristics of trend line pair - converging, expanding, parallel
🎯 Broader Classifications
Broader classification would include the following types.
🚩 Classification Based on Geometrical Shapes
This includes
Wedges - both trend lines are moving in the same direction. But, the trend lines are either converging or diverging and not parallel to each other.
Triangles - trend lines are moving in different directions. Naturally, they are either converging or diverging.
Channels - Both trend lines are moving in the same direction, and they are parallel to each other within the limits of error.
🚩 Classification Based on Pattern Direction
This includes
Ascending/Rising Patterns - No trend line is moving in the downward direction and at least one trend line is moving upwards
Descending/Falling Patterns - No trend line is moving in the upward direction, and at least one trend line is moving downwards.
Flat - Both Trend Lines are Flat
Bi-Directional - Both trend lines are moving in opposite direction and none of them is flat.
🚩 Classification Based on Formation Dynamics
This includes
Converging Patterns - Trend Lines are converging towards each other
Diverging Patterns - Trend Lines are diverging from each other
Parallel Patterns - Trend Lines are parallel to each others
🎯 Individual Pattern Types
Now we have broader classifications. Let's go through in detail to find out fine-grained classification of each individual patterns.
🚩 Ascending/Uptrend Channel
This pattern belongs to the broader classifications - Ascending Patterns, Parallel Patterns and Channels. The rules for the Ascending/Uptrend Channel pattern are as below
Both trend lines are rising
Trend lines are parallel to each other
🚩 Descending/Downtrend Channel
This pattern belongs to the broader classifications - Descending Patterns, Parallel Patterns and Channels. The rules for the Descending/Downtrend Channel pattern are as below
Both trend lines are falling
Trend lines are parallel to each other
🚩 Ranging Channel
This pattern belongs to the broader classifications - Flat Patterns, Parallel Patterns and Channels. The rules for the Ranging Channel pattern are as below
Both trend lines are flat
Trend lines are parallel to each other
🚩 Rising Wedge - Expanding
This pattern belongs to the broader classifications - Rising Patterns, Diverging Patterns and Wedges. The rules for the Expanding Rising Wedge pattern are as below
Both trend lines are rising
Trend Lines are diverging.
🚩 Rising Wedge - Contracting
This pattern belongs to the broader classifications - Rising Patterns, Converging Patterns and Wedges. The rules for the Contracting Rising Wedge pattern are as below
Both trend lines are rising
Trend Lines are converging.
🚩 Falling Wedge - Expanding
This pattern belongs to the broader classifications - Falling Patterns, Diverging Patterns and Wedges. The rules for the Expanding Falling Wedge pattern are as below
Both trend lines are falling
Trend Lines are diverging.
🚩 Falling Wedge - Contracting
This pattern belongs to the broader classifications - Falling Patterns, Converging Patterns and Wedges. The rules for the Converging Falling Wedge are as below
Both trend lines are falling
Trend Lines are converging.
🚩 Rising/Ascending Triangle - Expanding
This pattern belongs to the broader classifications - Rising Patterns, Diverging Patterns and Triangles. The rules for the Expanding Ascending Triangle pattern are as below
The upper trend line is rising
The lower trend line is flat
Naturally, the trend lines are diverging from each other
🚩 Rising/Ascending Triangle - Contracting
This pattern belongs to the broader classifications - Rising Patterns, Converging Patterns and Triangles. The rules for the Contracting Ascending Triangle pattern are as below
The upper trend line is flat
The lower trend line is rising
Naturally, the trend lines are converging.
🚩 Falling/Descending Triangle - Expanding
This pattern belongs to the broader classifications - Falling Patterns, Diverging Patterns and Triangles. The rules for the Expanding Descending Triangle pattern are as below
The upper trend line is flat
The lower trend line is falling
Naturally, the trend lines are diverging from each other
🚩 Falling/Descending Triangle - Contracting
This pattern belongs to the broader classifications - Falling Patterns, Converging Patterns and Triangles. The rules for the Contracting Descending Triangle pattern are as below
The upper trend line is falling
The lower trend line is flat
Naturally, the trend lines are converging.
🚩 Converging Triangle
This pattern belongs to the broader classifications - Bi-Directional Patterns, Converging Patterns and Triangles. The rules for the Converging Triangle pattern are as below
The upper trend line is falling
The lower trend line is rising
Naturally, the trend lines are converging.
🚩 Diverging Triangle
This pattern belongs to the broader classifications - Bi-Directional Patterns, Diverging Patterns and Triangles. The rules for the Diverging Triangle pattern are as below
The upper trend line is rising
The lower trend line is falling
Naturally, the trend lines are diverging from each other.
🎲 Indicator Settings - Auto Chart Patterns
🎯 Zigzag Settings
Zigzag settings allow users to select the number of zigzag combinations to be used for pattern scanning, and also allows users to set zigzag length and depth combinations.
🎯 Scanning Settings
Number of Pivots - This can be either 5 or 6. Represents the number of pivots used for identification of patterns.
Error Threshold - Error threshold used for initial trend line validation.
Flat Threshold - Flat angle threshold is used to identify the slope and direction of trend lines.
Last Pivot Direction - Filters patterns based on the last pivot direction. The values can be up, down, both, or custom. When custom is selected, then the individual pattern specific last pivot direction setting is used instead of the generic one.
Verify Bar Ratio - Provides option to ignore extreme patterns where the ratios of zigzag lines are not proportionate to each other.
Avoid Overlap - When selected, the patterns that overlap with existing patterns will be ignored while scanning. Meaning, if the new pattern starting point falls between the start and end of an existing pattern, it will be ignored.
🎯 Group Classification Filters
Allows users to enable disable patterns based on group classifications.
🚩 Geometric Shapes Based Classifications
Wedges - Rising Wedge Expanding, Falling Wedge Expanding, Rising Wedge Contracting, Falling Wedge Contracting.
Channels - Ascending Channel, Descending Channel, Ranging Channel
Triangles - Converging Triangle, Diverging Triangle, Ascending Triangle Expanding, Descending Triangle Expanding, Ascending Triangle Contrcting and Descending Triangle Contracting
🚩 Direction Based Classifications
Rising - Rising Wedge Contracting, Rising Wedge Expanding, Ascending Triangle Contracting, Ascending Triangle Expanding and Ascending Channel
Falling - Falling Wedge Contracting, Falling Wedge Expanding, Descending Triangle Contracting, Descending Triangle Expanding and Descending Channel
Flat/Bi-directional - Ranging Channel, Converging Triangle, Diverging Triangle
🚩 Formation Dynamics Based Classifications
Expanding - Rising Wedge Expanding, Falling Wedge Expanding, Ascending Triangle Expanding, Descending Triangle Expanding, Diverging Triangle
Contracting - Rising Wedge Contracting, Falling Wedge Contracting, Ascending Triangle Contracting, Descending Triangle Contracting, Converging Triangle
Parallel - Ascending Channel, Descending Channgel and Ranging Channel
🎯 Individual Pattern Filters
These settings allow users to enable/disable individual patterns and also set last pivot direction filter individually for each pattern. Individual Last Pivot direction filters are only considered if the main "Last Pivot Direction" filter is set to "custom"
🎯 Display Settings
These are the settings that determine the indicator display. The details are provided in the tooltips and are self explanatory.
🎯 Alerts
A basic alert message is enabled upon detection of new pattern on the chart.
BjCandlePatternsLibrary "BjCandlePatterns"
Patterns is a Japanese candlestick pattern recognition Library for developers. Functions here within detect viable setups in a variety of popular patterns. Please note some patterns are without filters such as comparisons to average candle sizing, or trend detection to allow the author more freedom.
doji(dojiSize, dojiWickSize) Detects "Doji" candle patterns
Parameters:
dojiSize : (float) The relationship of body to candle size (ie. body is 5% of total candle size). Default is 5.0 (5%)
dojiWickSize : (float) Maximum wick size comparative to the opposite wick. (eg. 2 = bottom wick must be less than or equal to 2x the top wick). Default is 2
Returns: (series bool) True when pattern detected
dLab(showLabel, labelColor, textColor) Produces "Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bullEngulf(maxRejectWick, mustEngulfWick) Detects "Bullish Engulfing" candle patterns
Parameters:
maxRejectWick : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a top wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a top wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick : (bool) input to only detect setups that close above the high prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bewLab(showLabel, labelColor, textColor) Produces "Bullish Engulfing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bearEngulf(maxRejectWick, mustEngulfWick) Detects "Bearish Engulfing" candle patterns
Parameters:
maxRejectWick : (float) Maximum rejection wick size.
The maximum wick size as a percentge of body size allowable for a bottom wick on the resolution candle of the pattern. 0.0 disables the filter.
eg. 50 allows a botom wick half the size of the body. Default is 0% (Disables wick detection).
mustEngulfWick : (bool) Input to only detect setups that close below the low prior effectively engulfing the candle in its entirety. Default is false
Returns: (series bool) True when pattern detected
bebLab(showLabel, labelColor, textColor) Produces "Bearish Engulfing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
hammer(ratio, shadowPercent) Detects "Hammer" candle patterns
Parameters:
ratio : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent : (float) The maximum allowable top wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
hLab(showLabel, labelColor, textColor) Produces "Hammer" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
star(ratio, shadowPercent) Detects "Star" candle patterns
Parameters:
ratio : (float) The relationship of body to candle size (ie. body is 33% of total candle size). Default is 33%.
shadowPercent : (float) The maximum allowable bottom wick size as a percentage of body size. Default is 5%.
Returns: (series bool) True when pattern detected
ssLab(showLabel, labelColor, textColor) Produces "Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
dragonflyDoji() Detects "Dragonfly Doji" candle patterns
Returns: (series bool) True when pattern detected
ddLab(showLabel, labelColor) Produces "Dragonfly Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
Returns: (series label) A label visible at the chart level intended for the title pattern
gravestoneDoji() Detects "Gravestone Doji" candle patterns
Returns: (series bool) True when pattern detected
gdLab(showLabel, labelColor, textColor) Produces "Gravestone Doji" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tweezerBottom(closeUpperHalf) Detects "Tweezer Bottom" candle patterns
Parameters:
closeUpperHalf : (bool) input to only detect setups that close above the mid-point of the candle prior increasing its bullish tendancy. Default is false
Returns: (series bool) True when pattern detected
tbLab(showLabel, labelColor, textColor) Produces "Tweezer Bottom" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tweezerTop(closeLowerHalf) Detects "TweezerTop" candle patterns
Parameters:
closeLowerHalf : (bool) input to only detect setups that close below the mid-point of the candle prior increasing its bearish tendancy. Default is false
Returns: (series bool) True when pattern detected
ttLab(showLabel, labelColor, textColor) Produces "TweezerTop" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTopBull(wickSize) Detects "Bullish Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stwLab(showLabel, labelColor, textColor) Produces "Bullish Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTopBear(wickSize) Detects "Bearish Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stbLab(showLabel, labelColor, textColor) Produces "Bearish Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
spinningTop(wickSize) Detects "Spinning Top" candle patterns
Parameters:
wickSize : (float) input to adjust detection of the size of the top wick/ bottom wick as a percent of total candle size. Default is 34%, which ensures the wicks are both larger than the body.
Returns: (series bool) True when pattern detected
stLab(showLabel, labelColor, textColor) Produces "Spinning Top" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
morningStar() Detects "Bullish Morning Star" candle patterns
Returns: (series bool) True when pattern detected
msLab(showLabel, labelColor, textColor) Produces "Bullish Morning Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
eveningStar() Detects "Bearish Evening Star" candle patterns
Returns: (series bool) True when pattern detected
esLab(showLabel, labelColor, textColor) Produces "Bearish Evening Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBull() Detects "Bullish Harami" candle patterns
Returns: (series bool) True when pattern detected
hwLab(showLabel, labelColor, textColor) Produces "Bullish Harami" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBear() Detects "Bearish Harami" candle patterns
Returns: (series bool) True when pattern detected
hbLab(showLabel, labelColor, textColor) Produces "Bearish Harami" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBullCross() Detects "Bullish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcwLab(showLabel, labelColor, textColor) Produces "Bullish Harami Cross" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
haramiBearCross() Detects "Bearish Harami Cross" candle patterns
Returns: (series bool) True when pattern detected
hcbLab(showLabel, labelColor) Produces "Bearish Harami Cross" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
Returns: (series label) A label visible at the chart level intended for the title pattern
marubullzu() Detects "Bullish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mwLab(showLabel, labelColor, textColor) Produces "Bullish Marubozu" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
marubearzu() Detects "Bearish Marubozu" candle patterns
Returns: (series bool) True when pattern detected
mbLab(showLabel, labelColor, textColor) Produces "Bearish Marubozu" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
abandonedBull() Detects "Bullish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abwLab(showLabel, labelColor, textColor) Produces "Bullish Abandoned Baby" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
abandonedBear() Detects "Bearish Abandoned Baby" candle patterns
Returns: (series bool) True when pattern detected
abbLab(showLabel, labelColor, textColor) Produces "Bearish Abandoned Baby" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
piercing() Detects "Piercing" candle patterns
Returns: (series bool) True when pattern detected
pLab(showLabel, labelColor, textColor) Produces "Piercing" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
darkCloudCover() Detects "Dark Cloud Cover" candle patterns
Returns: (series bool) True when pattern detected
dccLab(showLabel, labelColor, textColor) Produces "Dark Cloud Cover" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tasukiBull() Detects "Upside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
utgLab(showLabel, labelColor, textColor) Produces "Upside Tasuki Gap" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
tasukiBear() Detects "Downside Tasuki Gap" candle patterns
Returns: (series bool) True when pattern detected
dtgLab(showLabel, labelColor, textColor) Produces "Downside Tasuki Gap" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
risingThree() Detects "Rising Three Methods" candle patterns
Returns: (series bool) True when pattern detected
rtmLab(showLabel, labelColor, textColor) Produces "Rising Three Methods" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
fallingThree() Detects "Falling Three Methods" candle patterns
Returns: (series bool) True when pattern detected
ftmLab(showLabel, labelColor, textColor) Produces "Falling Three Methods" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
risingWindow() Detects "Rising Window" candle patterns
Returns: (series bool) True when pattern detected
rwLab(showLabel, labelColor, textColor) Produces "Rising Window" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
fallingWindow() Detects "Falling Window" candle patterns
Returns: (series bool) True when pattern detected
fwLab(showLabel, labelColor, textColor) Produces "Falling Window" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
kickingBull() Detects "Bullish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kwLab(showLabel, labelColor, textColor) Produces "Bullish Kicking" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
kickingBear() Detects "Bearish Kicking" candle patterns
Returns: (series bool) True when pattern detected
kbLab(showLabel, labelColor, textColor) Produces "Bearish Kicking" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
lls(ratio) Detects "Long Lower Shadow" candle patterns
Parameters:
ratio : (float) A relationship of the lower wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
llsLab(showLabel, labelColor, textColor) Produces "Long Lower Shadow" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
lus(ratio) Detects "Long Upper Shadow" candle patterns
Parameters:
ratio : (float) A relationship of the upper wick to the overall candle size expressed as a percent. Default is 75%
Returns: (series bool) True when pattern detected
lusLab(showLabel, labelColor, textColor) Produces "Long Upper Shadow" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bullNeck() Detects "Bullish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nwLab(showLabel, labelColor, textColor) Produces "Bullish On Neck" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
bearNeck() Detects "Bearish On Neck" candle patterns
Returns: (series bool) True when pattern detected
nbLab(showLabel, labelColor, textColor) Produces "Bearish On Neck" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
soldiers(wickSize) Detects "Three White Soldiers" candle patterns
Parameters:
wickSize : (float) Maximum allowable top wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
wsLab(showLabel, labelColor, textColor) Produces "Three White Soldiers" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
crows(wickSize) Detects "Three Black Crows" candle patterns
Parameters:
wickSize : (float) Maximum allowable bottom wick size throughout pattern expressed as a percent of total candle height. Default is 5%
Returns: (series bool) True when pattern detected
bcLab(showLabel, labelColor, textColor) Produces "Three Black Crows" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
triStarBull() Detects "Bullish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tswLab(showLabel, labelColor, textColor) Produces "Bullish Tri-Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
triStarBear() Detects "Bearish Tri-Star" candle patterns
Returns: (series bool) True when pattern detected
tsbLab(showLabel, labelColor, textColor) Produces "Bearish Tri-Star" identifier label
Parameters:
showLabel : (bool) Shows label when input is true. Default is false
labelColor : (series color) Color of the label border and arrow
textColor : (series color) Text color
Returns: (series label) A label visible at the chart level intended for the title pattern
wrap(cond, barsBack, borderColor, bgcolor) Produces a box wrapping the highs and lows over the look back.
Parameters:
cond : (series bool) Condition under which to draw the box.
barsBack : (series int) the number of bars back to begin drawing the box.
borderColor : (series color) Color of the four borders. Optional. The default is color.gray.
bgcolor : (series color) Background color of the box. Optional. The default is color.gray.
Returns: (series box) A box who's top and bottom are above and below the highest and lowest points over the lookback
topWick() returns the top wick size of the current candle
Returns: (series float) A value equivelent to the distance from the top of the candle body to its high
bottomWick() returns the bottom wick size of the current candle
Returns: (series float) A value equivelent to the distance from the bottom of the candle body to its low
body() returns the body size of the current candle
Returns: (series float) A value equivelent to the distance between the top and the bottom of the candle body
highestBody() returns the highest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
lowestBody() returns the lowest body of the current candle
Returns: (series float) A value equivelent to the highest body, whether it is the open or the close
barRange() returns the height of the current candle
Returns: (series float) A value equivelent to the distance between the high and the low of the candle
bodyPct() returns the body size as a percent
Returns: (series float) A value equivelent to the percentage of body size to the overall candle size
midBody() returns the price of the mid-point of the candle body
Returns: (series float) A value equivelent to the center point of the distance bewteen the body low and the body high
bodyupGap() returns true if there is a gap up between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap up and no overlap in the real bodies of the current candle and the preceding candle
bodydwnGap() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapUp() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
gapDwn() returns true if there is a gap down between the real body of the current candle in relation to the candle prior
Returns: (series bool) true if there is a gap down and no overlap in the real bodies of the current candle and the preceding candle
dojiBody() returns true if the candle body is a doji
Returns: (series bool) true if the candle body is a doji. Defined by a body that is 5% of total candle size
[RS]Fractal Pattern Recognition V0EXPERIMENTAL: reads the rates for the last top/bottom in a zigzag fractal series, outputs XAB, XAD, ABC, and BCD rates, im interested in earing what your opinion is as im a total noob in harmonics :p.
use with Fractals V5 for visual confirmation ;).
