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Risk & Portfolio Ratios

Risk-adjusted performance metrics for single securities and portfolios.

Note

All functions accept a list of periodic returns (e.g. monthly or daily). Pass None or an empty list and the function returns None.

Return Metrics

sharpe_ratio

sharpe_ratio(returns, risk_free_rate=0.0) -> float | None

Formula: (Avg Return − Rf) / Std Dev. Returns None when standard deviation is zero.

sortino_ratio

sortino_ratio(returns, risk_free_rate=0.0, target=0.0) -> float | None

Like Sharpe but uses downside deviation only. Better for asymmetric return distributions.

calmar_ratio

calmar_ratio(returns) -> float | None

Formula: Annualised Return / Max Drawdown. Higher = better risk/reward for drawdown-averse investors.

omega_ratio

omega_ratio(returns, threshold=0.0) -> float | None

Probability-weighted ratio of gains to losses above/below a threshold.

Risk Metrics

beta

beta(asset_returns, market_returns) -> float | None

Market sensitivity. beta = 1 moves with market; < 1 less volatile; > 1 more volatile.

alpha

alpha(asset_returns, market_returns, risk_free_rate=0.0) -> float | None

Jensen's alpha — excess return above what CAPM predicts.

maximum_drawdown

maximum_drawdown(prices) -> float | None

Returns a positive decimal (e.g. 0.34 for a 34% peak-to-trough decline). Pass a list of prices, not returns.

historical_var

historical_var(returns, confidence=0.95) -> float | None

Value at Risk at given confidence level. Returns a positive loss value (e.g. 0.03 means 3% loss at the threshold).

conditional_var — CVaR / Expected Shortfall

conditional_var(returns, confidence=0.95) -> float | None

Expected loss beyond VaR threshold. Always ≥ historical_var.

ulcer_index

ulcer_index(prices) -> float | None

Measures drawdown depth and duration. Lower = smoother equity curve.

TypeScript

import { sharpeRatio, maximumDrawdown, historicalVaR } from 'fin-ratios'

// Monthly returns
const returns = [0.02, -0.01, 0.03, -0.005, 0.015, ...]

sharpeRatio({ returns, riskFreeRate: 0.0 })     // Sharpe ratio
maximumDrawdown({ prices: [100, 110, 95, 105] }) // 0.136 (positive)
historicalVaR({ returns, confidence: 0.95 })     // positive loss value