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AgentsTools Quant Risk Metrics
x402
AgentsTools Quant Risk Metrics is a paid API for AI agents from api.agentstools.dev, paid per call via x402, $0.003/call, status unknown (last checked 2026-10-11).
Computes a full suite of portfolio risk metrics—VaR, CVaR, Sharpe, Sortino, max drawdown, Calmar, volatility, and more—from an array of periodic returns.
Price / call$0.003
Success—
StatusUnknown
How this service works
Portfolio risk metrics over an array of periodic returns: value-at-risk, conditional VaR, Sharpe, Sortino, max drawdown, Calmar, volatility, and more. Pure computation over your inputs.
Output
A JSON object containing the requested risk metrics computed from the provided returns array. Possible fields include mean, std, volatility (annualized), var_historical, var_parametric, cvar, downside_deviation, sharpe, sortino, max_drawdown, and calmar—each as a numeric value. If no metrics are specified, all are returned.
Example use cases
Hedge fund strategy risk audit
“I have a list of 500 daily returns for my long-short equity strategy—can you compute the full suite of risk metrics including VaR, CVaR, Sharpe, Sortino, max drawdown, and Calmar using a 2% annual risk-free rate at 95% confidence with 252 periods per year?”
Crypto portfolio volatility check
“Run risk metrics on these 365 daily returns for my crypto portfolio using 365 periods per year and a 0% risk-free rate—I specifically want volatility, max drawdown, Sharpe, and conditional VaR at 99% confidence.”
Backtesting strategy comparison
“I'm comparing two trading strategies—here are 252 daily return observations for strategy A: [...]. Give me all available risk metrics with a 5% annual risk-free rate so I can benchmark it properly.”
Technical details
Endpoint
POSThttps://api.agentstools.dev/quant/risk?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need pure, stateless computation of standard quantitative risk metrics from a series of periodic returns—no data fetching, no storage, no external market data required. Ideal when you already have return series from your own data pipeline and want fast, reproducible risk analytics including VaR, CVaR, Sharpe, Sortino, max drawdown, and Calmar without standing up your own quant library.
Side effects
- Missing or empty 'returns' array returns a validation error
- Returns array exceeding 10,000 entries is rejected
- Invalid metric name in the 'metrics' array causes a validation error
- Non-numeric values in returns array cause a parsing error
- Confidence value outside (0,1) range may produce unexpected results
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| metrics | array | Which metrics to compute; omit for all |
| returns | array | Periodic returns as decimals, at most 10000 entries |
| risk_free | number | Annual risk-free rate as a decimal, default 0 |
| confidence | number | Confidence for VaR and CVaR, default 0.95 |
| periods_per_year | number | Annualization factor, default 252 |
Tags
x402
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