The Sharpe ratio is the most widely used measure of investment performance. Virtually every fund fact sheet, performance attribution report, and investment manager pitch includes it. It is also one of the most frequently misused and misunderstood statistics in finance — a metric that is straightforward to calculate but easy to game, and that fails to capture precisely the kinds of risk that matter most. Understanding the Sharpe ratio means understanding both why it is useful and why it is insufficient.
What the Sharpe ratio measures — and what it assumes
The Sharpe ratio uses standard deviation as its measure of risk. This is meaningful only if returns are approximately normally distributed — symmetrically distributed around their mean, with the probability of extreme outcomes fully captured by the standard deviation. Many real investment strategies — particularly those involving options, credit, or illiquid assets — have return distributions that are decidedly non-normal: they have fat tails (more frequent extreme outcomes than a normal distribution predicts) or are skewed (with a large number of small gains and a small number of very large losses).
The short volatility problem
Strategies that systematically sell options — collecting premium regularly and absorbing rare large losses — produce return distributions with high Sharpe ratios during normal markets and catastrophic outcomes during tail events. A portfolio that earns 1% per month consistently for two years and then loses 40% in a month has a historical Sharpe ratio that looks attractive (low volatility over the sample period) but has embedded enormous tail risk that the Sharpe ratio fails to capture. The 2018 collapse of the XIV ETF (short VIX) is a case study: it had a multi-year Sharpe ratio above 2.0 before losing 90% of its value in a single session.
Gaming the Sharpe ratio
Sophisticated investors should be aware that Sharpe ratios can be deliberately inflated through several techniques. Smoothed valuations — using stale or appraisal-based pricing for illiquid assets — artificially suppress measured volatility, inflating the Sharpe denominator downward. Survivorship bias inflates Sharpe ratios in databases of hedge fund returns: funds that close due to poor performance are removed, leaving only the survivors. Return manipulation strategies — selling deep out-of-the-money puts to collect premium that boosts monthly returns at the cost of tail risk — can produce impressive Sharpe ratios until the puts land in the money. A Sharpe ratio should always be read alongside skewness, kurtosis, maximum drawdown, and a critical examination of the strategy's liquidity assumptions.