Enhanced Sigma by Cryptorhythms [CR]

14 февр. 2021 г.

Enhanced Sigma by Cryptorhythms

Sigma is basically the deviation of returns compared to past returns. The higher / lower the value, shows you how deviated from the average this current bars returns are.

While perhaps not usable as a complete strategy for entering and exiting, its still quite useful and informative. It can give interesting signals as to potential turning points in price action. This behavior extends to all timeframes both long term and short term.

There are 2 overbought and oversold zones here inthe indicator. One is adaptive and will change to suit the shorter term giving your extra potential signals. The fixed line shows a general level for highly deviated values.

Expect a number of further totally unique and exclusive sigma based indicators from CR in the near future. We are nowhere near done extracting the alpha from this concept!

How to get access

This indicator is available for standalone purchase or as part of our subscription options. Please see my signature or profile for more information or contact me directly.

15 нояб.

Информация о релизе

Enhanced Sigma - Advanced Volatility-Normalized Returns Analysis

The Enhanced Sigma indicator measures volatility-adjusted price returns to identify statistical extremes, regime changes, and mean reversion opportunities. By normalizing returns against their standard deviation, the indicator reveals when markets are experiencing unusual moves relative to recent volatility—highlighting potential exhaustion points, capitulation events, and statistical anomalies.


█ OVERVIEW

Sigma (σ) represents how many standard deviations current returns deviate from normal behavior. Readings beyond ±2.0 indicate statistically unusual moves, while extreme readings beyond ±3.0 occur less than 1% of the time under normal distribution. This version adds multi-layered analysis including regime detection, multi-timeframe confirmation, and adaptive thresholds.

█ KEY FEATURES

Return Calculation Methods
The indicator supports multiple return calculation approaches:
- Simple Returns — Standard percentage change calculation
- Log Returns — Logarithmic returns for better statistical properties
- Geometric Returns — Square root based calculation
- Percentage Returns — Scaled percentage format

Volume Weighting
Optional volume weighting emphasizes high-volume moves while dampening low-volume noise. When enabled, returns are weighted by normalized volume to give more significance to moves occurring on institutional participation.

Threshold Methods
Two threshold calculation approaches:
- Fixed Thresholds — Manual static levels
- Percentile-Based — Adaptive thresholds calculated from historical distribution
Percentile-based thresholds automatically adjust to changing volatility regimes over configurable lookback periods.

Statistical Significance Testing
Built-in t-test functionality determines whether current sigma readings are statistically significant or merely random noise. Configurable confidence levels (80-99.9%) filter out insignificant moves. Non-significant readings are visually dimmed.

Multi-Timeframe Analysis
Analyzes sigma across multiple timeframes simultaneously. Confluence signals trigger when all timeframes (current, 3x, 5x) align at extremes—indicating stronger conviction and reduced false signals. MTF sigma values are plotted as reference lines.

Regime Detection
Automatically classifies current volatility environment into four regimes:
- Low Volatility — Market in compression
- Normal — Standard volatility conditions
- High Volatility — Elevated movement
- Extreme — Unusual volatility expansion
Regime classification uses percentile ranking and statistical deviation analysis.

Adaptive Threshold System
Three methods for automatic threshold adjustment:
- ATR-Based — Adjusts based on Average True Range ratio
- Volatility Regime — Tightens in low volatility, widens in high volatility
- Range Expansion — Responds to recent sigma range changes
When enabled, thresholds dynamically scale with market conditions to maintain consistent sensitivity.

Cluster Analysis
Detects and scores clusters of threshold breaches within rolling windows. High cluster scores can indicate capitulation or exhaustion phases. Visual labels "C" show active clusters.

Mean Reversion Signals
Generates entry and exit signals based on extreme sigma readings returning to mean:
- Long Entry — Triggered on oversold extremes
- Short Entry — Triggered on overbought extremes
- Exit Signals — When sigma normalizes or time-based exit reached (marked as gray "X")
Optional statistical significance filter ensures only high-probability setups generate signals. Position tracking displays unrealized P&L.

Distribution Histogram
Displays sigma value distribution as a horizontal histogram showing Point of Control (POC)—the most frequently occurring sigma level. Configurable bin size and lookback period.

Statistics Dashboard
Real-time table displaying:
- Current sigma value and percentile rank
- Statistical measures (mean, std dev, skewness, kurtosis)
- Volatility regime classification
- Extreme event frequency
- Bars since last extreme
- Position status and P&L (when mean reversion enabled)

█ VISUAL ELEMENTS

Threshold Lines
- Aqua/Cyan lines — Positive (high) thresholds
- Fuchsia/Magenta lines — Negative (low) thresholds
- Solid lines — Short-term dynamic thresholds
- Circles — Long-term dynamic thresholds
- Crosses — Percentile-based static thresholds (when enabled)

Sigma Histogram
Primary histogram uses momentum-based coloring:
- Purple shades — Negative sigma (declining)
- Cyan shades — Positive sigma (advancing)
- Darker shades indicate weakening momentum
- Brighter shades indicate strengthening momentum
Statistically significant threshold breaches are highlighted with intensified colors.

Shape Markers
- Small triangles — Statistically significant threshold breaches
- Diamonds — Multi-timeframe confluence signals
- Large triangles with text — Mean reversion entry signals (LONG/SHORT)
- X markers — Mean reversion exit signals
- Labels — Cluster detection alerts

█ ALERTS

The indicator includes comprehensive alert conditions. Use confirm on bar close if repainting is enabled.

█ HOW TO USE

Identifying Extremes
Sigma readings beyond ±2.0 indicate unusual moves. Look for:
- Threshold breaches with statistical significance markers (triangles)
- Multi-timeframe confluence (diamonds) for stronger signals
- Cluster formation indicating potential exhaustion

Regime-Aware Trading
Use regime detection to adjust expectations:
- In Low Volatility regimes, smaller sigma moves may be significant
- In Extreme regimes, higher thresholds prevent overtrading

Mean Reversion Strategy
Enable mean reversion signals for systematic entries:
- LONG signals appear after statistically significant oversold extremes
- SHORT signals appear after statistically significant overbought extremes
- Exit signals trigger on return to mean or time-based stops

Distribution Analysis
Use the histogram to identify:
- POC level — Where sigma spends most time (equilibrium)
- Current position relative to distribution

16 нояб.

Информация о релизе

Fixed bug on histogram's old boundary not deleting when creating a new histogram