The Sharpe Ratio Rewards Smoothness, Which Is Not the Same as Safety
Dividing excess return by volatility produces the most cited number in fund evaluation. It also systematically flatters strategies that hide their risk rather than avoid it.
The Calculation
The Sharpe ratio is the return above the risk free rate, divided by the standard deviation of returns.
A fund returning 12 percent when cash pays 3 percent, with 9 percent volatility, has a Sharpe ratio of one. It earned one unit of excess return per unit of volatility.
The purpose is comparability. A strategy returning 20 percent with enormous swings and one returning 8 percent with small ones cannot be compared on return alone. The ratio puts them on a common footing.
Why It Became the Standard
It answers the right question. Return without reference to risk is meaningless, since any return can be manufactured with enough leverage. Doubling leverage roughly doubles return and roughly doubles volatility, leaving the Sharpe ratio unchanged, which is exactly the property you want in a measure of skill.
Leverage changes return and does not change the Sharpe ratio. That is the whole reason it works as a comparison across strategies.
The First Problem: Symmetry
Standard deviation treats upside and downside deviation identically. A fund that occasionally returns 15 percent in a month is penalised exactly as much as one that occasionally loses 15 percent.
No investor experiences those as equivalent. The measure is treating good surprises as risk.
The Sortino ratio addresses this by using only downside deviation in the denominator. It is a genuine improvement and is far less widely quoted, mostly through convention.
The Second Problem: The Distribution
Standard deviation fully describes risk only for a normal distribution. Financial returns are not normally distributed, and the deviations matter.
| Property | What Sharpe assumes | Reality |
|---|---|---|
| Distribution shape | Normal | Fat tails, extreme moves more common |
| Skew | Symmetric | Often negatively skewed |
| Independence | Returns uncorrelated over time | Autocorrelation is common |
A strategy with many small gains and rare large losses has low measured volatility and a high Sharpe ratio, right up until the large loss. The ratio describes the calm period accurately and says nothing about the shape of the eventual failure.
The Third Problem: It Can Be Manufactured
This is the serious one. Certain strategies produce high Sharpe ratios by construction rather than by skill.
Selling options collects steady premium and reports low volatility until a large move arrives. Illiquid assets are marked infrequently, and infrequent marking mechanically reduces measured volatility, since a price that does not update cannot deviate. Any strategy whose losses arrive rarely and severely will look excellent on this measure during the interval between failures.
The pattern is consistent: strategies that sell insurance report high Sharpe ratios, because premium income is steady and claims are occasional. The ratio is measuring the frequency of the payout, not the magnitude of the exposure.
The Autocorrelation Tell
One practical diagnostic is checking whether monthly returns are correlated with the previous month. Genuinely marked liquid returns show little relationship. Smoothed or stale valuations show substantial positive autocorrelation, because a stale mark propagates.
High autocorrelation is a signal that reported volatility understates true volatility, and therefore that the Sharpe ratio is overstated. It is one of the more useful checks available from return series alone.
Using It Properly
Compare within a strategy category rather than across categories, since different strategies have structurally different return distributions. Look at the ratio over a long period including at least one stress event. Check skew and kurtosis alongside it. And treat any Sharpe ratio well above the range typical for the strategy as a question rather than an achievement.
The Bottom Line
The Sharpe ratio measures excess return per unit of volatility and is genuinely useful because it is unaffected by leverage. Its weaknesses are that it treats upside as risk, assumes a distribution returns do not follow, and rewards strategies whose losses are rare and large. A very high figure over a calm period is frequently a description of a risk that has not yet been realised.