Research & Analysis
In-depth articles on Hidden Markov Model regime detection, Bitcoin and altcoin market structure, and quantitative approaches to crypto risk management. Data-driven, jargon-optional.
How Bitcoin's Hidden Markov Model Detects Regime Changes
A deep-dive into the math and mechanics behind BTCMonitors — from the Baum-Welch training algorithm to how the Forward Algorithm produces real-time confidence scores on the dashboard.
The 4 Bitcoin Market Regimes — Duration, Returns & What They Mean
A detailed breakdown of each HMM state: what Low Vol Bull, Low Vol Bear, High Vol Bear, and Transition look like in practice, how long they typically persist, and what distinguishes each from the others.
Using HMM Regime Signals in Your Crypto Trading Strategy
Practical frameworks for regime-aware position sizing, confidence threshold selection, entry and exit timing, and risk rules — translating the model's output into actionable trading discipline.
Altcoin Regime Analysis: How ETH, SOL & Others Behave Across Market Cycles
How 29 tracked altcoins correlate with, lag behind, or diverge from Bitcoin's regime — volatility multipliers by asset category, regime leaders vs. laggards, and how to read multi-asset divergences.
Bitcoin Halving Cycles & Market Regimes: A Quantitative Framework
How Bitcoin's four-year halving cycle maps to HMM regime sequences — which regimes dominate each phase, typical durations, and a data-driven framework for cycle-aware positioning.