What Is the Sharpe Ratio, and Why It Flatters Some Strategies

The Sharpe ratio measures return per unit of risk, where risk is defined as volatility. In its usual form it is the strategy's return above the risk-free rate, divided by the standard deviation of its returns. The intuition is clean and reasonable: two strategies that made the same return are not equally good if one delivered it smoothly and the other on a rollercoaster, and the Sharpe ratio rewards the smoother one. It is the most common single number used to compare performance, which is exactly why its blind spots are worth knowing.

Assumption one: returns are well-behaved

Standard deviation describes a bell-shaped distribution well and a fat-tailed one poorly. Many trading strategies are deeply fat-tailed: they produce a long run of small, steady gains punctuated by rare, severe losses. Selling options, shorting volatility, and various carry trades all share this shape. On the Sharpe ratio these look outstanding, because the steady small gains keep volatility low and the rare disaster has not yet entered the sample. The ratio reports a strategy as low-risk right up to the moment the tail it could not see arrives. A high Sharpe on a fat-tailed strategy is often a measure of how long you have gone without the bad event, not of how safe you are from it.

Assumption two: all volatility is bad

Standard deviation treats a large move up exactly like a large move down. A strategy that occasionally leaps in your favour is penalised for that leap as if it were a loss, which is backwards. Two strategies can share a Sharpe ratio while one gets its volatility from upside surprises and the other from drawdowns. The ratio cannot distinguish the good kind of surprise from the bad, so it can rate a genuinely convex, crash-resistant approach as no better than a fragile one.

Assumption three: the history is long enough to be honest

Volatility is measured over whatever window you feed it, and a calm window produces a low volatility and therefore a high Sharpe. A strategy that has only lived through one benign regime will show a flattering ratio that says more about the weather than the strategy. Annualising a Sharpe from a few months of quiet data compounds the illusion. A great ratio over a short, single-regime history is not evidence of a great strategy; it is evidence you have not yet seen the strategy tested.

Using it without being fooled

The Sharpe ratio is a fine starting point precisely because it rewards smoothness, but smoothness and safety are not the same thing, and the gap between them is where strategies blow up. The honest way to read a Sharpe is to ask what the volatility figure could be concealing: a tail that has not printed yet, upside being punished as if it were risk, or a history too short and too calm to mean anything. A single ratio cannot answer those, which is why the shape of the whole return distribution, not one summary of it, is what actually tells you how a strategy behaves. That is the reasoning behind how our case study evaluates results.