kratu/wess_hmm
Hybrid Wasserstein + HMM Regime Detection
This system helps quantitative traders and analysts understand current market behavior by classifying it into clear categories like 'Trending,' 'Range,' 'Choppy,' or 'Transitional.' It takes raw price, volatility, and momentum data as input and outputs a real-time label for the market's state, along with visual overlays and segment breakdowns. You would use this if you build or manage automated trading strategies and need to adapt to different market conditions.
Use this if you need to detect market regimes in real-time, gain insights into market structure, and integrate this understanding into your trading or analytical workflows.
Not ideal if you require extremely low computational overhead or are working with data that deviates significantly from typical financial market characteristics.
Stars
7
Forks
1
Language
Python
License
Apache-2.0
Category
Last pushed
Feb 26, 2026
Commits (30d)
0
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