Built a realtime BTC market regime classifier using HMM — happy to discuss the approach
I built a REST API that classifies the current BTC-USDT market regime every
15 minutes using a Hidden Markov Model trained on Binance kline data.
The model has three states:
- Trend: persistent directional move
- Range: mean-reverting, low volatility
- Chaotic: high volatility, no clear direction
The HMM uses a 720-hourly-bar rolling window refitted daily at UTC 00:00.
Forward filtering only intraday — no lookahead. Diagonal covariance to avoid
ill-conditioning. Confirmation filter (2 consecutive bars) before switching
regime label to reduce whipsawing.
Live demo: flowregime.nippotica.com
API waitlist: api.flowregime.nippotica.com
Curious whether anyone here has experimented with regime detection for
crypto — particularly interested in whether HMM outperforms simpler
volatility-based approaches in practice.