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Backtesting & statistics

Sharpe Ratio (net / gross)

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Definition

Excess return per unit of return volatility: (annualized return minus risk-free rate) divided by annualized standard deviation of returns. 'Gross' is before trading costs; 'net' is after commissions, fees, borrow, and slippage.

How to read it

Higher is better, but only compare Sharpes measured over the same horizon, frequency, and cost basis. Annualize by scaling: Sharpe_annual = Sharpe_period x sqrt(periods per year) (e.g. x sqrt(252) for daily). The gap between gross and net Sharpe is the single most honest diagnostic of a strategy's fragility: a large gross-to-net decay means the edge lives inside the cost model. Sharpe assumes returns are roughly i.i.d. and near-Gaussian; it rewards steady grinders and understates the danger of strategies with negative skew (e.g. short-vol) whose worst days are far larger than their standard deviation implies.

How practitioners use it

Used as context among multiple indicators — never as a standalone signal to act.

Less common professional uses

The naive sqrt-time annualization is only valid under zero autocorrelation. Positively autocorrelated returns (trend, illiquidity smoothing, stale marks) inflate the annualized Sharpe; use Lo's autocorrelation-adjusted scaling factor instead of sqrt(T). Sharpe ignores higher moments. Two strategies with identical Sharpe can have opposite skew/kurtosis; prefer the Probabilistic Sharpe Ratio (PSR) or a skew/kurtosis-adjusted Sharpe when returns are non-Gaussian. When many strategy variants are screened, the maximum observed Sharpe is upward-biased by selection. The correct guard is the Deflated Sharpe Ratio, which discounts for the number of trials and the non-normality of returns.

Sources & provenance

Sharpe (1994), 'The Sharpe Ratio', Journal of Portfolio Management; Lo (2002), 'The Statistics of Sharpe Ratios', Financial Analysts Journal

This page is educational content published by Pachira Aquatica Global LLC. It is not investment advice and not a recommendation.

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