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  1. Trust Score
  2. Methodology
Versioned model guide

How Forvest calculates crypto market and news risk

Trust Score is a positive-facing view of observed risk. The model combines asset-relative market behavior with attributed news signals when both are available, then exposes contributors, warnings and version information alongside the score.

Compare assetsReview model inputs

Observed risk

A 0–100 asset-relative historical percentile. Zero means low observed risk relative to that asset's history; 100 means high.

Trust Score

Trust Score equals 100 minus overall observed risk. It is not a safety grade, investment quality rating or probability of loss.

Data availability

Timestamps, missing inputs and warnings identify the evidence available for each snapshot. Missing values remain unavailable.

Default component model

Technical signals plus attributed news context

When both components are available, the default configuration is 65% technical risk and 35% news risk. Production pages show the model version and configuration identifier used for each snapshot.

Technical risk

Default weight: 65%

Volatility

Annualized log-return volatility across configured windows.

Drawdown

Rolling maximum drawdown relative to the asset's own history.

Price instability

Return shocks and the frequency of recent extreme moves.

Activity anomaly

Unusual volume or trade-count activity; high activity is not automatically negative.

Trend instability

Directional inefficiency or choppiness, not bullish or bearish quality.

News risk

Default weight: 35%

Sentiment risk

Risk-oriented sentiment derived from attributed coverage.

Negative-news ratio

The share of attributed coverage classified as negative in the model window.

News frequency

Coverage frequency over configured short and medium windows.

Sentiment momentum

Observed change in sentiment, not price momentum.

Recency pressure

The relative weight of recent attributed coverage.

Missing-data behavior

If attributed news coverage is insufficient, news risk is null, the model falls back to available technical inputs and the snapshot carries a warning. A missing value is never treated as zero.

Timestamp

When the snapshot was calculated

Timeframe

The observation window

Warnings

Material gaps or fallback states

Version + hash

The model and configuration used

Known limitations

Asset-relative percentiles support directional comparison but are not identical probabilities of loss. News outputs depend on coverage, sentiment and asset attribution. The current model does not include on-chain data, funding, open interest, liquidations, order books, macro regimes or social data.

Apply the method

Open an asset risk page

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No investment advice. The methodology explains a descriptive risk model. It does not determine whether an asset is suitable for a person, portfolio or investment objective.