Simulation
Market State Monte Carlo
Probabilistic simulation of future market states from conditional historical transitions.
Status experimental · Version 0.4 · Sep 2026
P(Xₜ₊₁ | Xₜ)
Illustrative distribution, not a live forecast.
Bull 34%
Neutral 41%
Bear 25%
Overview
Market State Monte Carlo models the evolution of a market as a stochastic state process rather than simulating price on its own. The state is the joint observation; the model estimates P(Xₜ₊₁ | Xₜ).
Figures on this page are model output examples. They are estimated distributions, not a statement of where the market will trade.
How it works
- 01 Current market state
- 02 Similar historical states
- 03 Conditional transition distribution
- 04 Monte Carlo sampling
- 05 Future market states
- 06 Probability distribution
Inputs
| Asset | BTCUSDT |
| Horizon | 24h |
| Resolution | 5m |
| Paths | 10,000 |
| Data source | ArcDelta |
| State variables | Price, volume, OI, CVD, volatility |
| Historical window | 180 days |
Outputs
- Return distribution
- Market states
- Risk distribution
- Scenario paths
Model statistics
Published as quality of the estimate. Directional accuracy is not the headline for a probabilistic model.
- Evaluated period
- 2024-01 → 2026-09
- Assets
- BTC / ETH / SOL
- Samples
- 124,812
- Brier score
- 0.182
- Calibration error
- 0.041
- 95% coverage
- 93.7%
Validation
- Out-of-sample
- Bootstrap
- Calibration
Data sources
ArcDelta: trades, order book, open interest, funding, OHLCV.
Access
From $49 / month. Included runs, path limits, and API access follow the Labs tier on the TreVmS account. Individual metrics are not sold separately.
Experimental. This is an active research project. Interface, methodology, and outputs may change.