Glossary · Backtesting & Analytics
Sharpe Ratio
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The Sharpe ratio is a measure of risk-adjusted return: the excess return a strategy earns above the risk-free rate, divided by the volatility (standard deviation) of its returns. It answers “how much return per unit of bumpiness?” — so two strategies with identical returns can have very different Sharpe ratios if one’s equity curve is far smoother.
Formula
Sharpe ratio = (Rp − Rf) ÷ σp
where Rp is the strategy’s annualized return, Rf the risk-free rate (Indian traders typically use a short-term government yield), and σp the annualized standard deviation of returns.
Hypothetical example: a NIFTY options strategy returns 19% annualized with 14% volatility, while the risk-free rate is 6.5%.
Sharpe = (19 − 6.5) ÷ 14 = 0.89
A second strategy returning 24% with 28% volatility scores (24 − 6.5) ÷ 28 = 0.63 — higher return, worse risk-adjusted result. As rough intuition, sustained live Sharpe ratios above 1 are considered good and above 2 excellent, while backtested Sharpes far above that often signal overfitting rather than genius.
Why it matters
Systematic traders compare strategies — and decide leverage — on risk-adjusted terms, not raw returns. A smooth 15% can safely be run at larger size than a violent 25%. The Sharpe ratio’s known blind spots matter too: it penalizes upside volatility the same as downside and says nothing about tail risk, which is why it is read alongside max drawdown rather than instead of it.
In INDfolio AI, Sharpe ratio is computed for every backtest alongside drawdown and expectancy — see Backtesting.