Regime Detection HMM
CommunityBayesian regime tracking for smarter trading.
Data & Analytics#backtesting#bayesian#regime-detection#hmm#market-regimes#online-filter#parameter-blending
Authortrudumb
Version1.0.0
Installs0
System Documentation
What problem does it solve?
Bayesian belief tracking over market regimes using Hidden Markov Models replaces crude proxies with principled state estimation, enabling smoother parameter blending and uncertainty-aware decisions.
Core Features & Use Cases
- Online forward-filtering to infer regime probabilities in real time.
- Regime-specific parameter blending to adapt trading logic and risk controls.
- Baum-Welch style offline learning to retune emissions and transitions from historical data.
- Seamless integration with a quote engine for regime-aware quoting and deployment.
Quick Start
Initialize the HMM, feed market observations to start tracking regimes, and blend parameters for regime-aware decisions.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: Regime Detection HMM Download link: https://github.com/trudumb/hyper_make/archive/main.zip#regime-detection-hmm Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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