Crypto Market Regime Analysis
Hidden Markov Model-based regime classification across all tracked assets. Identifies whether the market is in a risk-on, risk-off, or transitional state.
Current Regime Classifications
BTC
Trending
Confidence: +91.2%
Vol 24h: 47.5% · high · Funding: balanced
ETH
Trending
Confidence: +93.4%
Vol 24h: 56.4% · high · Funding: balanced
SOL
Trending
Confidence: +74.1%
Vol 24h: 61.2% · high · Funding: balanced
HYPE
Trending
Confidence: +95.0%
Vol 24h: 74.0% · high · Funding: balanced
Model Parameters
Model Type
random_forest_onnx
Regime Floor
high
Evaluation Interval
5.0s
What Is Market Regime Analysis?
Market regime analysis uses statistical models to classify the current market environment into distinct states. In crypto markets, regimes typically include:
- Risk-On / Accumulation: Markets trending up with strong momentum and increasing volume
- Risk-Off / Distribution: Declining prices, rising fear, capital outflows
- Transitional / Mean-Reverting: Markets between regimes, often choppy and range-bound
Algo Tick uses a Hidden Markov Model (HMM) trained on funding rates, open interest changes, price momentum, and on-chain metrics to classify the regime in real-time. The model evaluates new data every 5.0 seconds.