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Calculator

Risk-Adjusted Returns Calculator

Returns CSV → Sharpe, Sortino, Calmar, Omega, alpha, beta, tracking error, information ratio, max drawdown, tail moments. Runs in your browser. Free.

Inputs
Form inputs / CSV
Runtime
Instant
Privacy
Client-side · no upload
API key
Not required
Methodology
Open →

Education · Not investment advice. BaFin/EU framework. Past performance does not indicate future results. Editorial standards Sponsor disclosure Corrections

1 · Upload a returns CSV

Long format: date,strategy,benchmark (benchmark optional). Returns interpreted as simple daily returns. Annualization uses √252. Computation is entirely client-side; nothing is uploaded.

Risk-free (annual)%

What this tool computes

Standard risk-adjusted performance metrics for a daily returns series. Load the synthetic demo for a walk-through or upload your own strategy + optional benchmark columns. Everything runs in your browser; nothing is uploaded.

How to use

Step-by-step

Full calculator guide →
  1. 1

    Upload your strategy's return series and (optionally) a benchmark return series for IR computation.

  2. 2

    Read all five metrics: Sharpe, Sortino, Calmar, Information Ratio, Treynor.

  3. 3

    Sortino > Sharpe materially → strategy has positive skew (upside-volatile, not symmetric).

  4. 4

    Information Ratio with mismatched benchmark is meaningless — pick a benchmark you'd hold without the strategy.

  5. 5

    Pair with the Returns Distribution Analyzer or VaR Backtest for tail-risk validation. Risk-adjusted returns alone can hide tail risk.

For agents

Use in an agent

Same math, same result shape as the UI above — as a static ES module. No HTTP request, no auth, no rate limit.

import { compute } from "https://aifinhub.io/engines/risk-adjusted-returns.js";

Contract: /contracts/risk-adjusted-returns.json Full agent guide →

Glossary references

Terms used by this tool

All glossary →

Questions people ask next

FAQ

Which risk-adjusted metrics does the tool compute?

Five from the methodology page: Sharpe (return per total volatility), Sortino (return per downside volatility), Calmar (return per max drawdown), Information Ratio (excess return per tracking-error vs. benchmark), and Treynor (return per beta). All annualized.

When is Sortino better than Sharpe?

When the strategy has asymmetric returns. Sortino penalizes downside volatility only; Sharpe penalizes both up and down volatility equally. For long-only equity, Sharpe and Sortino track closely. For strategies with positive skew (trend-following, options buying), Sortino is more representative.

What benchmark should I use for Information Ratio?

Whatever benchmark you'd hold if you didn't have the strategy. For US equity strategies, SPY is typical. For multi-asset, a 60/40 stock/bond mix. For style-specific (small-cap value), a style-matched index (IWM, VTV). Information Ratio against a mismatched benchmark is meaningless.

How long a sample do I need?

At least 36 monthly observations for Sharpe to be statistically meaningful (2 sigma SE). For Calmar, you need at least one full drawdown-recovery cycle (typically 3-7 years). Below those thresholds, the metrics are descriptive but not robust. The tool flags low-N estimates.

Can risk-adjusted returns be misleading?

Yes. A strategy with rare large losses (option selling, short-vol) can show high Sharpe in calm regimes and catastrophic Sharpe when the regime breaks. The methodology page warns about this and recommends pairing risk-adjusted metrics with explicit tail-risk measures (VaR, CVaR, drawdown duration).

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Planning estimates only — not financial, tax, or investment advice.