Risk-adjusted return measure.

The measure that separates good luck from good investing

Any investment that goes up is considered a win. The Sharpe ratio asks a harder question: did the investment's return compensate adequately for the risk taken? It's the return per unit of volatility — specifically, (investment return - low-risk rate) / standard deviation of returns. A Sharpe ratio of 1.0 means each unit of volatility produced one unit of excess return above low-risk. Higher Sharpe means more return for the risk. Two investments with identical returns but different Sharpe ratios are not equally good — the higher-Sharpe one took less risk to get there.

The formula in plain terms

Sharpe = (R_p - R_f) / σ_p

Where R_p is portfolio return, R_f is the low-risk rate government bond yields currently around 4.5%), and σ_p is the standard deviation of the portfolio's returns. The numerator is "excess return" — what you earned above doing nothing in government bonds. The denominator is the price paid in volatility. The ratio expresses the efficiency of that trade-off.

What Sharpe values actually mean

Rule-of-thumb benchmarks for annual Sharpe ratios:

Below 0: Underperformed the low-risk rate. Took risk for no reward.

0 to 1: Positive excess return but relatively risky for what was gained. Most actively-managed funds sit here.

1 to 2: Good risk-adjusted performance. Well-constructed portfolios and skilled active managers fall in this range.

2 to 3: Very good. Rare in retail investing; usually limited to specific strategies or short periods.

Above 3: Exceptional, often suspicious. Long-term Sharpe above 3 in retail-accessible products is unusual enough to warrant scrutiny.

For comparison, the S&P 500 long-term Sharpe is roughly 0.5-0.7. Equity index funds sit similar. Adding bonds to a portfolio typically raises Sharpe by reducing volatility more than it reduces return.

Why Sharpe matters more than raw return

Consider two investments over 10 years:

Investment A: 12% annual return with 25% annual standard deviation.
Investment B: 9% annual return with 12% annual standard deviation.

Raw return favours A. Sharpe (assuming 4% low-risk rate) favours B:

A: (12-4)/25 = 0.32
B: (9-4)/12 = 0.42

B generated more return per unit of risk despite lower absolute return. This matters because real investors face volatility drag — large drawdowns emotionally force selling, compounding mathematical losses with behavioural ones. A Sharpe-optimised portfolio is more likely to be actually held through market cycles. A raw-return-optimised portfolio often isn't.

The low-risk rate assumption

Sharpe ratio's quality depends on using the right low-risk rate. For investors:

Short-term analysis: 3-month Treasury bill yield (currently ~4.5%).
Long-term analysis: 10-year gilt yield (currently ~4.5%).
Historical comparisons: average gilt yield over the period being analysed.

Using the wrong rate distorts Sharpe significantly. Calculating Sharpe for 2005-2015 using 2024's 4.5% rate is nonsense — during most of that period, low-risk rates were under 1%. Sharpe comparisons across time periods require appropriate low-risk rates for each period.

The Sharpe limitations investors miss

Assumes normal distribution. Sharpe uses standard deviation, which assumes returns are normally distributed. They usually aren't — investment returns have fatter tails (more extreme events) than normal distributions suggest. This means Sharpe often underestimates tail risk and overstates the appeal of strategies that look stable but occasionally blow up.

Treats upside and downside symmetrically. A strategy with 20% upside volatility and 0% downside volatility has the same Sharpe as one with 10% upside and 10% downside. Most investors don't care about upside volatility — only downside. Sortino ratio (using only downside deviation) addresses this.

Period-sensitive. Annualised Sharpe can vary substantially by period used. Bull market periods produce high Sharpe; bear market periods crater it. Short windows (1-3 years) are noisy; 10+ year Sharpe is more meaningful but requires patience to wait.

Survivorship bias. Funds with bad Sharpe often close. Looking at current fund Sharpe ratios naturally over-samples survivors. True average Sharpe including closed funds is lower than reported averages.

Using Sharpe for portfolio construction

The mathematical result behind modern portfolio theory: combining assets that aren't perfectly correlated produces a portfolio with lower volatility than either asset alone. If the combined portfolio has better return per unit of risk than either individual asset, Sharpe has improved. Adding 20% bonds to an equity portfolio typically reduces annual return by 1-1.5% but reduces volatility by 3-4% — Sharpe improves despite lower absolute return. This is the mathematical argument for diversification beyond risk reduction alone.

Sharpe vs alpha

Both measure fund manager skill, differently:

Sharpe: Total return per unit of total risk. Doesn't care about benchmark.

Alpha: Return above benchmark per unit of benchmark-relative risk. Cares specifically about benchmark comparison.

A fund with 10% return, 15% volatility vs benchmark return 8% and volatility 12%: Sharpe calculation = (10-4)/15 = 0.40 vs benchmark (8-4)/12 = 0.33 — fund Sharpe-beats benchmark. Alpha calculation depends on beta (how fund moves relative to benchmark). If beta is 1.2 (fund 20% more volatile than benchmark), expected return was 4% + 1.2 × (8-4) = 8.8%. Actual 10% - expected 8.8% = 1.2% positive alpha. Both measures agree fund added value; neither is strictly right.

The retail investor's Sharpe reality

For most retail portfolios, the Sharpe comparison that matters is: my actively-managed portfolio vs simple 60/40 index portfolio. The 60/40 passive portfolio typically delivers Sharpe of 0.6-0.8 over long periods. Retail active portfolios with individual stocks, active managers, and market timing frequently deliver Sharpe below 0.5 — lower return for more risk than the passive alternative. This is Sharpe-based evidence for the index investing argument: the passive portfolio is Sharpe-efficient, and most active efforts don't improve on it after fees and taxes.

Sharpe as behaviour insurance

High-Sharpe portfolios are easier to hold through adverse markets because drawdowns are smaller. This matters because the single largest cause of retail investor underperformance is selling at market bottoms. A portfolio with 1.0 Sharpe that loses 20% in a downturn is easier to hold than a portfolio with 0.4 Sharpe that loses 40% in the same downturn — even if both have similar long-term expected returns. Sharpe optimisation is partly psychological engineering — building portfolios you'll actually stay invested.

What this calculator shows

The tool computes Sharpe ratio from portfolio return, low-risk rate, and standard deviation. It doesn't automatically gather your return history, calculate standard deviation from monthly data, or compare against benchmark alternatives. For a specific Sharpe calculation, input your portfolio's actual returns and appropriate low-risk rate; for portfolio improvement, compare your Sharpe against a simple diversified benchmark.