Transform onchain, derivatives, stablecoin, liquidity, and portfolio data into forward-looking probabilities, expected ranges, confidence scores, and risk estimates.
Crypto teams already have dashboards, onchain data, DEX data, funding data, stablecoin data, and portfolio data. The challenge is turning that data into forward-looking probabilities and risk estimates.
Signals live across separate providers, chains, venues, and dashboards — with no shared forward-looking layer to unify them.
Existing analytics describe the past in detail but rarely express what may happen next as calibrated probabilities and expected ranges.
Professional teams require confidence scoring, calibration tracking, and an auditable record of every forecast against realized outcomes.
Each module transforms an existing data domain into forward-looking, confidence-scored forecast objects — delivered through the same API and console.
Forward-looking probabilities, expected return ranges, volatility forecasts, confidence scores, and regime labels across major assets, alts, meme tokens, and long-tail tokens.
Forecast funding regimes, volatility expansion, liquidation cascade probability, basis changes, and derivatives market regimes.
Estimate depeg probability, repeg probability, expected peg deviation, liquidity fragmentation, route risk, and collateral stress.
Translate asset-level forecasts into portfolio-level drawdown probability, volatility forecasts, concentration risk, correlation stress, and transaction risk estimates.
Access forecast objects through APIs, webhooks, dashboards, and forecast archives with confidence scores, calibration metrics, data freshness, and historical performance tracking.
Amonhen complements your data platforms — including providers like Dune — rather than replacing them.
Every forecast is a typed object with an input category, an output type, a forecast horizon, and a confidence score — consistent across modules.
| Forecast object | Input category | Output type | Horizon | Example user |
|---|---|---|---|---|
| Directional probability | Market & onchain | probability | 1h – 7d | Funds & desks |
| Expected return range | Market data | range | 24h – 30d | Funds & desks |
| Realized volatility forecast | Market & derivatives | estimate | 24h – 7d | Market makers |
| Funding regime forecast | Derivatives data | regime | 8h – 3d | Trading desks |
| Liquidation cascade probability | Derivatives data | probability | 1h – 24h | Exchanges |
| Depeg probability | Stablecoin data | probability | 24h – 30d | Treasury teams |
| Repeg probability | Stablecoin data | probability | 24h – 14d | Stablecoin teams |
| Route-risk forecast | Liquidity & routing | estimate | real-time | Wallets & fintech |
| Portfolio drawdown probability | Portfolio data | probability | 7d – 90d | Risk teams |
| Forecast confidence score | Model meta | score | per forecast | All users |
Embed forecasted risk and confidence scores into token pages, pre-trade views, and client risk experiences.
Surface stablecoin route risk, token risk estimates, and transaction risk previews without becoming an advisory product.
Use forecast distributions, volatility estimates, funding regime forecasts, and liquidation-risk probabilities as decision-support inputs.
Monitor depeg probability, liquidity fragmentation, balance migration, and route-level stress.
Use collateral stress probability, stablecoin risk forecasts, and liquidity risk estimates to inform risk monitoring workflows.
Amonhen delivers informational, model-generated estimates. Your teams decide what to do with them — Amonhen never recommends transactions.
Every forecast carries a calibrated confidence level.
Predicted probabilities are measured against realized frequencies.
A durable record of every forecast ever issued.
Forecasts expose the recency of their input data.
Estimates are withheld where data coverage is insufficient.
Each output is traceable to the drivers behind it.
Documented model behavior, horizons, and limitations.
Confidence, coverage, and outcomes in one record.
Amonhen tracks every forecast against realized outcomes, helping teams understand model calibration, confidence, coverage, and historical performance.
Retrieve typed forecast objects over REST, subscribe to updates via webhooks, and run scenario requests — all with neutral, informational output.
{ "asset": "ETH", "horizon": "24h", "probability_positive_move": 0.61, "expected_return_range": { "lower": -0.015, "upper": 0.034 }, "confidence": "medium", "regime": "trend_continuation", "disclaimer": "model_generated_informational_estimate" }
Amonhen turns existing crypto data into probabilistic forecasts, confidence scores, and risk estimates for institutional workflows.