Scoring — Indicadores y estrategias

Chaos Theory - Butterfly Effect Strategy The Chaos Theory - Butterfly Effect Strategy applies advanced principles from chaos theory and non-linear dynamics to financial market analysis. This strategy recognizes that markets, like chaotic systems, are highly sensitive to initial conditions where small price movements can cascade into significant trends—the "butterfly effect." Core Concept: Markets exhibit deterministic chaos: while governed by underlying rules, they remain unpredictable over long timeframes. This strategy identifies "strange attractors" (equilibrium states) and capitalizes on transitional phases when markets shift between chaotic regimes. Key Components: Butterfly Effect Detector - Measures price acceleration and volatility sensitivity to identify amplification of small changes Chaos Deviation Oscillator - Tracks normalized distance between fast/slow EMAs, detecting departures from equilibrium Fractal Complexity Index - Approximates self-similar patterns across multiple timeframes Strange Attractor Signals - Identifies crossovers indicating system phase transitions Momentum Confirmation - RSI filter prevents false signals during ranging markets Trend Alignment Filter - Optional longer-term trend filter for directional bias Entry Logic: Long: Chaos deviation crosses above signal line, exceeds positive threshold, with bullish momentum (and uptrend if filter enabled) Short: Chaos deviation crosses below signal line, exceeds negative threshold, with bearish momentum (and downtrend if filter enabled) Risk Management: Adjustable stop loss and take profit percentages Optional trailing stop for trend-following exits Emergency reversal exit on opposite chaos signal Volatility filter prevents trading during low-movement periods Position sizing based on equity percentage Best Markets: Volatile assets (crypto, forex majors, indices) where non-linear behavior is pronounced This strategy combines mathematical chaos theory with practical technical analysis to find exploitable patterns within market randomness, making it suitable for traders seeking systematic approaches to complex market dynamics.

Volume Conviction Index v1.0 Volume Conviction Index (VCI) v1.0 This indicator helps answer a simple question: Does this price move have real strength behind it, or is the volume too weak to trust??? It measures "conviction" through how many participants are in the marketplace by looking at volume in a smart, reliable way: - Spots unusual volume surges (buying or selling pressure) that stand out from normal (median line plotted) levels. - visually helps with discretionary calls and allows the median avg of participation not just volume to be 'seen' - Blends recent volume changes with how volume compares to its typical range. How to read the chart (super straightforward): - Teal columns above the zero line: Strong buying conviction — volume supporting the up move (good sign for breakouts or holds). - Orange columns below zero: Strong selling conviction — heavy participation on the downside (watch for reversals or weakness on rallies). - Flat/small bars near zero: Low conviction — price might be moving on fumes (often leads to fakeouts or quick fades). - Optional white dashed line (the "median conviction"): A smoothed version over the last few bars. If it crosses zero or diverges from price, it can signal shifting momentum. index works the same for both bears and bulls. teal bars in the positive are above participation or conviction in both bearish and bullish participation. also allows identifying exhaustion in both bearish and bullish scenarios. works well equally on lower TFs and higher TFs Why use it: It uses robust statistics (rolling median volume + Median Absolute Deviation for a "z-like" score) instead of plain averages — much better at handling noisy or outlier-heavy markets like crypto, forex, or stocks during news events. Then it adds a weighted mix of short-term volume acceleration and relative volume for better context. Great for: - Beginners: Start with defaults — the colors and zero line make it easy to see at a glance. - Day/swing traders: Filter entries/exits with real participation (e.g., teal spike on support bounce = higher odds). - Anyone learning volume: Shows clearly when moves have "muscle" vs. when they're suspect. Quick usage tips: - Best on 5m to 4h charts with good volume data. - Combine with price action, levels, or your favorite tools — use VCI to confirm conviction. - Toggle the median line in settings if your timeframe is noisy. Defaults work well across most assets — adjust "Volume Window" for longer/shorter lookback, or "Recent Weight" to emphasize sudden changes more/less. I personally like using it on 1min / 5min / 30min charts. Has a microscope / high-rez feel about it when I'm on quicker TFs. Open-source under © RU55IANROUL3TT3 — feel free to study, fork, or build on it! Feedback welcomed — what markets/timeframes does it help you with?

POC Migration Velocity (POC-MV) [PhenLabs]📊POC Migration Velocity (POC-MV) Version: PineScript™v6 📌Description The POC Migration Velocity indicator revolutionizes market structure analysis by tracking the movement, speed, and acceleration of Point of Control (POC) levels in real-time. This tool combines sophisticated volume distribution estimation with velocity calculations to reveal hidden market dynamics that conventional indicators miss. POC-MV provides traders with unprecedented insight into volume-based price movement patterns, enabling the early identification of continuation and exhaustion signals before they become apparent to the broader market. By measuring how quickly and consistently the POC migrates across price levels, traders gain early warning signals for significant market shifts and can position themselves advantageously. The indicator employs advanced algorithms to estimate intra-bar volume distribution without requiring lower timeframe data, making it accessible across all chart timeframes while maintaining sophisticated analytical capabilities. 🚀Points of Innovation Micro-POC calculation using advanced OHLC-based volume distribution estimation Real-time velocity and acceleration tracking normalized by ATR for cross-market consistency Persistence scoring system that quantifies directional consistency over multiple periods Multi-signal detection combining continuation patterns, exhaustion signals, and gap alerts Dynamic color-coded visualization system with intensity-based feedback Comprehensive customization options for resolution, periods, and thresholds 🔧Core Components POC Calculation Engine: Estimates volume distribution within each bar using configurable price bands and sophisticated weighting algorithms Velocity Measurement System: Tracks the rate of POC movement over customizable lookback periods with ATR normalization Acceleration Calculator: Measures the rate of change of velocity to identify momentum shifts in POC migration Persistence Analyzer: Quantifies how consistently POC moves in the same direction using exponential weighting Signal Detection Framework: Combines trend analysis, velocity thresholds, and persistence requirements for signal generation Visual Rendering System: Provides dynamic color-coded lines and heat ribbons based on velocity and price-POC relationships 🔥Key Features Real-time POC calculation with 10-100 configurable price bands for optimal precision Velocity tracking with customizable lookback periods from 5 to 50 bars Acceleration measurement for detecting momentum changes in POC movement Persistence scoring to validate signal strength and filter false signals Dynamic visual feedback with blue/orange color scheme indicating bullish/bearish conditions Comprehensive alert system for continuation patterns, exhaustion signals, and POC gaps Adjustable information table displaying real-time metrics and current signals Heat ribbon visualization showing price-POC relationship intensity Multiple threshold settings for customizing signal sensitivity Export capability for use with separate panel indicators 🎨Visualization POC Connecting Lines: Color-coded lines showing POC levels with intensity based on velocity magnitude Heat Ribbon: Dynamic colored ribbon around price showing POC-price basis intensity Signal Markers: Clear exhaustion top/bottom signals with labeled shapes Information Table: Real-time display of POC value, velocity, acceleration, basis, persistence, and current signal status Color Gradients: Blue gradients for bullish conditions, orange gradients for bearish conditions 📖Usage Guidelines POC Calculation Settings POC Resolution (Price Bands): Default 20, Range 10-100. Controls the number of price bands used to estimate volume distribution within each bar Volume Weight Factor: Default 0.7, Range 0.1-1.0. Adjusts the influence of volume in POC calculation POC Smoothing: Default 3, Range 1-10. EMA smoothing period applied to the calculated POC to reduce noise Velocity Settings Velocity Lookback Period: Default 14, Range 5-50. Number of bars used to calculate POC velocity Acceleration Period: Default 7, Range 3-20. Period for calculating POC acceleration Velocity Significance Threshold: Default 0.5, Range 0.1-2.0. Minimum normalized velocity for continuation signals Persistence Settings Persistence Lookback: Default 5, Range 3-20. Number of bars examined for persistence score calculation Persistence Threshold: Default 0.7, Range 0.5-1.0. Minimum persistence score required for continuation signals Visual Settings Show POC Connecting Lines: Toggle display of colored lines connecting POC levels Show Heat Ribbon: Toggle display of colored ribbon showing POC-price relationship Ribbon Transparency: Default 70, Range 0-100. Controls transparency level of heat ribbon Alert Settings Enable Continuation Alerts: Toggle alerts for continuation pattern detection Enable Exhaustion Alerts: Toggle alerts for exhaustion pattern detection Enable POC Gap Alerts: Toggle alerts for significant POC gaps Gap Threshold: Default 2.0 ATR, Range 0.5-5.0. Minimum gap size to trigger alerts ✅Best Use Cases Identifying trend continuation opportunities when POC velocity aligns with price direction Spotting potential reversal points through exhaustion pattern detection Confirming breakout validity by monitoring POC gap behavior Adding volume-based context to traditional technical analysis Managing position sizing based on POC-price basis strength ⚠️Limitations POC calculations are estimations based on OHLC data, not true tick-by-tick volume distribution Effectiveness may vary in low-volume or highly volatile market conditions Requires complementary analysis tools for complete trading decisions Signal frequency may be lower in ranging markets compared to trending conditions Performance optimization needed for very short timeframes below 1-minute 💡What Makes This Unique Advanced Estimation Algorithm: Sophisticated method for calculating POC without requiring lower timeframe data Velocity-Based Analysis: Focus on POC movement dynamics rather than static levels Comprehensive Signal Framework: Integration of continuation, exhaustion, and gap detection in one indicator Dynamic Visual Feedback: Intensity-based color coding that adapts to market conditions Persistence Validation: Unique scoring system to filter signals based on directional consistency 🔬How It Works Volume Distribution Estimation: Divides each bar into configurable price bands for volume analysis Applies sophisticated weighting based on OHLC relationships and proximity to close Identifies the price level with maximum estimated volume as the POC Velocity and Acceleration Calculation: Measures POC rate of change over specified lookback periods Normalizes values using ATR for consistent cross-market performance Calculates acceleration as the rate of change of velocity Signal Generation Process: Combines trend direction analysis using EMA crossovers Applies velocity and persistence thresholds to filter signals Generates continuation, exhaustion, and gap alerts based on specific criteria 💡Note: This indicator provides estimated POC calculations based on available OHLC data and should be used in conjunction with other analysis methods. The velocity-based approach offers unique insights into market structure dynamics but requires proper risk management and complementary analysis for optimal trading decisions.

Scoring Development Sample [BigBitsIO]This script shows a sample of how to do confidence weighted scoring indicators and for loops with Pine. This indicator may or may not be found useful, it's intent is to provide a sample on how to create such an indicator and use certain Pine features. Features: - Defined points based on the confidence of RSI and Stochastic indicator - Defined points based on candle color and sma trend direction - For loops used to calculate bonus points for "extended periods" of confidence. *** DISCLAIMER: For educational and entertainment purposes only. Nothing in this content should be interpreted as financial advice or a recommendation to buy or sell any sort of security or investment including all types of crypto. DYOR, TYOB. ***