Regime Scope | mad_tiger_slayer

RegimeScope by mad_tiger_slayer

Adapt to the Market’s Mood. Trade in Sync with Regime Scope.

Overview
Regime Scope is an advanced multi-factor market regime identifier meticulously engineered to determine whether an asset is exhibiting trending behavior (Markup/Markdown phases) or mean-reverting dynamics (Sideways - Accumulation/Distribution). By integrating and synthesizing outputs from nine rigorously chosen statistical and volatility-based models, this tool offers a unified framework for assessing regime conditions with precision.

This indicator is best used in conjunction with other tools in your trading arsenal—serving not as a standalone signal generator, but as a high-value filter for confluence and strategic alignment. Whether you're trading breakouts, reversals, or mean-reversion setups, Regime Scope can elevate your system’s contextual awareness and execution timing.

How It Works – Part 1
Regime Scope calculates a composite "regime score" by normalizing and averaging a range of volatility and statistical measures. This score, which ranges between -1 and +1, indicates the likelihood of the market being in a trending versus mean-reverting state.

• Values near +1 suggest a strong trending environment.
  
• Values near -1 suggest strong mean-reversion (sideways, volatile) conditions.
  
• Values between -0.30 and +0.30 are considered neutral and indicate choppy or range-bound market behavior.
  
• When the average regime score crosses above the upper threshold, the asset likely enters a trending state.
  
• When it crosses below the lower threshold, the market likely shifts to a volatile, mean-reverting state.
  
• The histogram and dynamic background color provide an intuitive visual guide to the current regime.
  

How It Works – Part 2: Components
Each of the following sub-models has been carefully selected for its contribution to understanding price behavior. All components are normalized to create a consistent, unified score:

• Phillips-Perron Test: Detects the presence of a unit root to infer stationarity and mean-reverting characteristics.
  
• Hurst Exponent: Measures long-term memory in a time series to identify persistence or anti-persistence.
  
• KPSS Test: Tests for level stationarity to contrast against unit-root behavior and validate trending assumptions.
  
• GARCH Volatility: Captures volatility clustering and regime shifts in conditional variance.
  
• Wavelet Transform: Decomposes price action into time-frequency space to extract non-linear and localized dynamics.
  
• Half-Life of Mean Reversion: Estimates the speed at which price returns to its mean, enhancing the timing of reversion plays.
  
• Augmented Dickey-Fuller (ADF) Test: Statistically verifies whether a series exhibits mean-reverting tendencies.
  
• Garman-Klass-Yang-Zhang Volatility: A robust historical volatility measure using open-high-low-close data.
  
• ADX (Average Directional Index): A classic technical tool for quantifying the strength of trend directionality.
  

How It Works – Part 3: Output Interpretation
All sub-models are normalized and synthesized into a single histogram plot shown in the lower chart panel.

• +1.0 to +0.30: Indicates high probability of a directional, trending market.
  
• -1.0 to -0.30: Indicates high probability of a sideways, mean-reverting regime.
  
• -0.30 to +0.30: Suggests a neutral, uncertain market condition.
  
• Transitions above or below these thresholds signal regime shifts.
  
• Background shading adapts in real-time to visually reflect regime classification.
  

Features

• Customizable thresholds to fine-tune sensitivity for regime classification.
  
• Visual overlay positioning (choose from top-left, bottom-right, etc.).
  
• Toggleable reference lines for regime thresholds.
  
• Cross-timeframe consistency through dynamic normalization.
  
• Each sub-model includes adjustable settings for personalized optimization.
  

Use Cases

• Dynamically switch between trend-following and mean-reversion strategies.
  
• Filter out choppy, low-probability zones by avoiding neutral regime periods.
  
• Use regime score as confluence with entry/exit signals from other indicators.
  
• Adapt strategies across timeframes—works well from scalping to swing trading.
  
• Best used on timeframes ≥12H for macro regime context, but scalpers can benefit by using it on shorter windows with tuned parameters.
  

Scalping Use Case

Overlay the regime score on low timeframes (e.g., 1m–15m) and use it to avoid high chop zones or confirm breakout volume spikes during trending periods.

Long-Term Use Case

On 1D–1W charts, Regime Scope can filter false breakouts and confirm macro trend alignment for position trades or swing setups.

Tip

• Combine Regime Scope with traditional technical tools like RSI, MACD, Bollinger Bands, or moving average crossovers to enhance strategic coherence.
  
• For example, only act on breakout or trend-following signals when the regime score exceeds the upper threshold, confirming a high-trend environment.
  
• Conversely, mean-reversion strategies like fading RSI extremes or trading Bollinger Band bounces work best when the regime score is in the lower range.
  
• Aligning your tactical entries with the broader regime can significantly reduce false signals, enhance trade probability, and improve overall system robustness.