regime-allocation-strategy
Unverified ML strategy on Multi by I-am-Uchenna. BotFinder score 18 out of 100.
Systematic multi-asset allocation strategy using Hidden Markov Models to identify VIX volatility regimes and dynamically rotate between TLT, GLD, and SPY
Source: github
BotFinder analysis pending.
regime-allocation-strategy
Regime-Based Multi-Asset Allocation Strategy A quantitative trading strategy that leverages Hidden Markov Models to identify market volatility regimes and systematically allocate capital across US Treasuries (TLT), Gold (GLD), and Equities (SPY). Table of Contents - Overview - Key Features - Methodology - Installation - Quick Start - Implementation Details - Performance Metrics - Results - Limitations & Assumptions - Future Work - Contributing - License - Contact Overview This repository implements a systematic regime-switching allocation framework that adapts portfolio positioning based on VIX-derived volatility states. Using unsupervised machine learning, the strategy identifies distinct market environments and executes rule-based rotations designed to optimize risk-adjusted returns across varying market conditions. Key Features - Regime Detection: Gaussian Hidden Markov Models (HMM) for volatility state identification - Dynamic Allocation: Rule-based rotation among three liquid ETFs - Risk Management: Execution lag implementation to prevent lookahead bias - Comprehensive Analytics
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