ElinaAalipour/statistical-range-detection

# Statistical Range Detection ## Objective This project aims to statistically define ranging market conditions using quantitative volatility-based features. ## Research Question How can ranging markets be statistically defined using measurable volatility compression signals? ## Market EURUSD (H1 Timeframe) ## Methodology The project follows a feature-driven research approach: 1. Define volatility-based hypotheses 2. Construct statistical features 3. Validate features visually and statistically 4. Combine multiple weak signals into a regime score ## Feature Set (v1) ### 1. ATR Compression Measures volatility contraction relative to historical baseline. - atr_rel_16 - atr_rel_48 ## Visual Validation ### Price Behavior  ### ATR Compression Behavior  ## Key Insight Volatility compression is not absolute; it is relative to historical context. ATR features show clear separation between: - ranging regimes (low relative ATR) - trending regimes (high relative ATR) ## Project Status Feature 1 (ATR Compression): Completed & Validated Next: Rolling Standard Deviation Feature