What Is the Sharpe Ratio?
The Sharpe ratio is a strategy's return above the risk-free rate divided by the standard deviation of its returns. It answers how much return was earned per unit of volatility, and it treats gains and losses as equally risky — which is both its usefulness and its main flaw.
What is the formula?
Sharpe = (return − risk-free rate) ÷ standard deviation of returns, computed on a consistent period and then annualised by multiplying by the square root of the number of periods in a year.[1]
Worked example. Daily returns average 0.05% with a standard deviation of 0.80%. The daily Sharpe is 0.05 ÷ 0.80 = 0.0625. Annualising: 0.0625 × sqrt(252) = 0.0625 × 15.87 = 0.99.
Monthly data annualises by sqrt(12) = 3.46. A 1.5% monthly mean with a 4% monthly standard deviation is 0.375 monthly, or 1.30 annualised.
What counts as good?
Context decides. A long-only equity index has historically sat well under 1 over long periods. A ratio above 1 is respectable for a directional strategy, above 2 is strong, and anything advertised above 3 deserves the four questions below before anything else.
How does a Sharpe ratio get flattered?
1. Short samples. A great quarter annualises into a spectacular number. Ask how many periods went into the calculation; 12 monthly observations is not a measurement of a strategy.
2. Infrequent marking. Illiquid or self-marked positions have artificially low measured volatility. Volatility is the denominator, so understating it inflates the ratio directly without anything about the strategy having improved.
3. Negative skew. Selling options produces a stream of small gains with rare large losses. Before the loss arrives, the Sharpe is excellent and describes nothing about the risk actually being carried.
4. Annualising the wrong thing. Multiplying a daily Sharpe by 252 instead of sqrt(252) inflates it 15.9x. This happens more often than it should.
Sharpe or Sortino?
Sharpe penalises volatility in both directions; Sortino counts only the downside. For a strategy whose returns are roughly symmetric they tell a similar story. For anything with a long tail in either direction they diverge sharply, and the pair together is more informative than either alone.
How does this connect to a track record?
Lo showed that a Sharpe ratio is itself a statistical estimate with a standard error, and that annualising a monthly figure by multiplying by the square root of 12 is only valid when returns are independent — serial correlation can overstate an annualised Sharpe substantially.[2] And after decades of testing, Harvey, Liu and Zhu argued that a newly claimed result in finance should clear a t-statistic above 3.0 rather than 2.0.[3] A Sharpe quoted without a sample size is not yet a claim.
A metric is a summary of a record, so it inherits every weakness of that record. Computed from trades selected after the fact, it is a number about the selection. kappi commits each trade before it resolves and publishes it on a Merkle-anchored log, so PnL, RME, correlation to SPX, mean R:R and trade count over 30, 100 and 200-day windows are computed over everything that was committed, losses included. $15/month to keep a record; reading one is free.
Sources
- Sharpe, 'The Sharpe Ratio', Journal of Portfolio Management 21(1), 1994, 49–58 read 2026-08-16
- Lo, 'The Statistics of Sharpe Ratios', Financial Analysts Journal 58(4), 2002, 36–52 read 2026-08-16
- Harvey, Liu & Zhu, '… and the Cross-Section of Expected Returns', Review of Financial Studies 29(1), 2016, 5–68 — argues a newly claimed factor should clear a t-statistic above 3.0 read 2026-08-16
Frequently asked questions
How do you annualise a Sharpe ratio?
Multiply the per-period Sharpe by the square root of the number of periods in a year: sqrt(252) = 15.87 for daily data, sqrt(12) = 3.46 for monthly. Multiplying by 252 instead is a common and very large error.
What is a good Sharpe ratio?
Above 1 is respectable for a directional strategy and above 2 is strong. Long-only equity indices have historically sat well below 1 over long periods, so claims above 3 warrant scrutiny.
Why can the Sharpe ratio be misleading?
It treats upside and downside volatility identically, it is easily inflated by short samples or illiquid marking, and strategies with rare large losses look excellent until the loss arrives.
Should I use Sharpe or Sortino?
Both. They agree when returns are roughly symmetric and diverge when there is a long tail, and the divergence itself tells you about the shape of the strategy's risk.