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Hidden Markov Model (HMM)

A statistical model where the system being modeled is assumed to follow a Markov process with unobserved (hidden) states. In finance, HMMs are used to classify market regimes — the 'hidden' state (regime) produces 'observed' market data (returns, volume, etc.). Transitions between regimes follow probabilistic rules.

Definition

A statistical model where the system being modeled is assumed to follow a Markov process with unobserved (hidden) states. In finance, HMMs are used to classify market regimes — the 'hidden' state (regime) produces 'observed' market data (returns, volume, etc.). Transitions between regimes follow probabilistic rules.

Live Data Example </> API
# Hidden Markov Model (HMM) live data
$ curl command:
curl https://algotick.dev/v3/signals/regime?coin=BTC
Endpoint: /v3/signals/regime?coin=BTC
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Current Hidden Markov Model (HMM) data from the Algo Tick API:

{
  "evaluation_interval_sec": 5,
  "model_type": "random_forest_onnx",
  "regime_floor": "high",
  "regimes": [
    {
      "coin": "BTC",
      "confidence_score": 0.5,
      "features_used": 38,
      "funding_regime": "balanced",
      "persistence_probability": 0.4,
      "regime_label": "Mean-Reverting",
      "risk_warnings": null,
      "vol_24h": 46.67,
      "vol_regime": "high"
    }
  ],
  "timestamp": "2026-06-17T08:08:00.090Z"
}
# Fetch this yourself:
curl https://algotick.dev/v3/signals/regime?coin=BTC

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