What is a good Sharpe ratio?

Sharpe ratio interpretation by range: Below 0 = negative risk-adjusted return (worse than risk-free); 0 to 0.5 = poor; 0.5 to 0.75 = acceptable; 0.75 to 1.0 = good; 1.0 to 1.25 = very good; above 1.25 = excellent (rare over long periods). For context, the S&P 500 has produced a Sharpe ratio of approximately 0.35-0.40 over long periods. The Balanced ETF portfolio studied by BrixNation (QQQ 50%/XLU 20%/XLE 20%/Gold 10%) produced a Sharpe ratio of 1.079 over 15 years.

What is the difference between Sharpe ratio and CAGR?

CAGR (Compound Annual Growth Rate) measures how much your investment grew annually on average, expressed as a percentage. It tells you where you ended up. The Sharpe ratio measures how much return you earned per unit of risk (volatility) taken. A portfolio with a 16% CAGR and high volatility may have a lower Sharpe ratio than a portfolio with a 14% CAGR and lower volatility. Sharpe ratio is particularly useful when comparing portfolios that have different return AND different risk levels.

How is the Sharpe ratio calculated?

Step 1: Calculate the portfolio's annualized return (CAGR). Step 2: Subtract the risk-free rate (commonly approximated using the 3-month Treasury bill yield or a fixed proxy such as 2.5%). Step 3: Calculate the annualized standard deviation of the portfolio's periodic returns. Step 4: Divide the result of Step 2 by the result of Step 3. Example: QQQ CAGR = 10.62%, risk-free rate = 2.5%, annualized standard deviation = 27.8%. Sharpe = (10.62 - 2.5) / 27.8 = 0.292.

Why does a higher Sharpe ratio matter for investors?

A higher Sharpe ratio matters primarily because of investor behavior. Empirical research consistently shows that investors do not earn their portfolio's stated CAGR in practice — they earn less because they sell during drawdowns and buy back after recoveries. A portfolio with a high Sharpe ratio experiences smaller drawdowns, which makes investors more likely to stay invested through difficult periods and actually capture the full compounding benefit. The Balanced ETF portfolio's -3.2% worst year (vs QQQ's -32.6%) is an example of how a higher Sharpe ratio translates to a more behaviorally sustainable investment experience.

// BrixNation Financial Education

What Is a Sharpe Ratio?

Q: What is a Sharpe ratio?

The Sharpe ratio is a measure of risk-adjusted return developed by Nobel Prize-winning economist William F. Sharpe. It is calculated by subtracting the risk-free rate from the portfolio's return, then dividing by the annualized standard deviation of returns. The formula is: Sharpe Ratio = (Portfolio Return - Risk-Free Rate) / Standard Deviation. A higher Sharpe ratio indicates more return earned per unit of risk taken.

Definition · Formula · Interpretation Scale · Real ETF Examples

Developed by: William F. Sharpe (1966) Nobel Prize in Economics: 1990 Measures: Risk-Adjusted Return Unit: Return per unit of standard deviation

Definition

The Sharpe ratio is a quantitative measure of risk-adjusted return developed by economist William F. Sharpe, published in the Journal of Portfolio Management in 1966 and for which he was awarded the Nobel Memorial Prize in Economic Sciences in 1990. It answers a specific analytical question: how much excess return (above the risk-free rate) does an investment produce per unit of risk (standard deviation) taken to generate that return? A higher Sharpe ratio indicates superior risk-adjusted performance — more return earned for each unit of volatility accepted.

The ratio is widely used in portfolio analytics, hedge fund evaluation, ETF comparison, and asset allocation research. It is the primary optimization criterion in the BrixNation ETF Portfolio Study.

Formula

Sharpe Ratio = ( Rₚ − Rῒ ) ÷ σ

Where: Rₚ = Portfolio Return | Rῒ = Risk-Free Rate | σ = Standard Deviation of Returns

Component	Description	In This Research
Rₚ (Portfolio Return)	The annualized compound growth rate (CAGR) of the investment over the measurement period	Annual total return including dividends, compounded
Rῒ (Risk-Free Rate)	The theoretical return of an investment with zero risk, typically approximated by short-term government bond yield	2.5% fixed proxy used throughout the study
σ (Standard Deviation)	The annualized standard deviation of periodic returns, measuring the volatility or variability of the return series	Standard deviation of annual returns over the back-test period

Interpretation Scale

Sharpe ratio thresholds are conventions rather than absolute rules, but the following ranges are widely used in institutional portfolio analytics and academic finance research:

< 0

Negative

Return below risk-free rate. Uncompensated risk.

0 – 0.5

Poor

Inadequate compensation for volatility accepted.

0.5 – 0.75

Acceptable

Reasonable risk-return tradeoff. Below institutional standard.

0.75 – 1.0

Good

Well-compensated risk. Typical of disciplined equity strategies.

1.0 – 1.25

Very Good

Strong risk-adjusted return. Uncommon over multi-decade periods.

> 1.25

Excellent

Rare over long periods. May reflect favorable back-test conditions.

For context: S&P 500 long-run Sharpe ratio is approximately 0.35-0.40. Warren Buffett's Berkshire Hathaway has historically produced a Sharpe ratio of approximately 0.65-0.76 over multi-decade periods.

Worked Examples — Real ETF Data

The following examples use actual annual return data from the BrixNation research studies. All calculations use a 2.5% risk-free rate proxy and annualized standard deviation of annual returns over the stated back-test period.

Example 1 — QQQ (25-Year, 2001-2025)

CAGR = 10.62% | Std Dev = 27.8% | Risk-Free = 2.5%
Sharpe = (10.62% − 2.5%) ÷ 27.8% = 8.12% ÷ 27.8% = 0.292
Interpretation: Acceptable to good. High volatility (27.8%) reduces the score despite solid CAGR.

Example 2 — XLK (25-Year, 2001-2025)

CAGR = 10.58% | Std Dev = 26.4% | Risk-Free = 2.5%
Sharpe = (10.58% − 2.5%) ÷ 26.4% = 8.08% ÷ 26.4% = 0.306
Interpretation: Marginally higher than QQQ due to lower standard deviation, not higher return.

Example 3 — XLU Utilities (15-Year, 2011-2025)

CAGR = 10.6% | Std Dev = 11.4% | Risk-Free = 2.5%
Sharpe = (10.6% − 2.5%) ÷ 11.4% = 8.1% ÷ 11.4% = 0.711
Interpretation: Good. Lower CAGR than QQQ but dramatically lower volatility produces a superior Sharpe ratio.

Example 4 — Balanced Portfolio (15-Year, 2011-2025)

QQQ 50% / XLU 20% / XLE 20% / Gold 10% | CAGR = 14.4% | Std Dev = 11.0% | Risk-Free = 2.5%
Sharpe = (14.4% − 2.5%) ÷ 11.0% = 11.9% ÷ 11.0% = 1.079
Interpretation: Very good. The near-zero QQQ-XLU correlation reduces portfolio standard deviation well below any single constituent, enabling a high Sharpe even at modest overall volatility.

Sharpe Ratio Comparison — Individual Assets & Model Portfolios

Green reference line at 1.0 = "Very Good" threshold. Individual asset Sharpe ratios computed over 15-year period (2011-2025). Portfolio Sharpe ratios from grid-search optimization study.

CAGR vs Sharpe Ratio — Understanding the Tradeoff

The chart below plots CAGR against Sharpe ratio for all assets and model portfolios studied. The upper-right quadrant (high CAGR, high Sharpe) represents the most efficient investments. Note that the model portfolios cluster in the upper-right while individual assets are dispersed — this is the mathematical benefit of combining low-correlation assets.

15-year data (2011-2025). Bubble size not scaled to any metric. QQQ individual stat uses 15-year window for consistency with portfolios.

Why Sharpe Ratio Matters More Than CAGR Alone

The behavioral finance argument

Empirical research in behavioral finance consistently shows that investors do not earn their portfolio's stated CAGR. The gap between stated fund returns and actual investor returns — known as the behavior gap — is driven primarily by ill-timed entries and exits during periods of high volatility. Investors sell during large drawdowns and re-enter after recoveries, systematically buying high and selling low.

A portfolio with a Sharpe ratio of 1.079 and a worst year of -3.2% (Balanced portfolio) is fundamentally more behaviorally sustainable than QQQ alone with a Sharpe of 0.589 and a worst year of -32.6%. Most investors will hold through a -3.2% year without intervention; far fewer will hold through -32.6% without making a portfolio change that locks in losses.

The compounding asymmetry

Large drawdowns create a mathematical asymmetry: a -32.6% loss requires a subsequent +48.4% gain just to break even. A -3.2% loss requires only a +3.3% gain to recover. This asymmetry means that high-volatility portfolios must work harder in recovery years to deliver the same long-run CAGR as lower-volatility alternatives. The Sharpe ratio captures this efficiency directly.

Limitations of the Sharpe Ratio

The Sharpe ratio has several known limitations that practitioners should consider in their analysis:

Limitation 1 — Normal Distribution Assumption

Standard deviation assumes returns are normally distributed. Asset returns often exhibit fat tails (leptokurtosis) — extreme events occur more frequently than a normal distribution predicts. Strategies that appear to have high Sharpe ratios by collecting small premiums while bearing hidden tail risk (such as short-volatility strategies) can look excellent until the tail event occurs.

Limitation 2 — In-Sample Bias

All Sharpe ratios computed in this research are in-sample back-test statistics. The observed correlation structure, standard deviations, and return means in the 2011–2025 sample period may not persist in future market regimes. The low QQQ-XLU correlation of 0.028 is an empirical observation, not a structural guarantee.

Limitation 3 — Risk-Free Rate Sensitivity

The Sharpe ratio changes with the assumed risk-free rate. A 2.5% risk-free proxy was used throughout this research. If the actual risk-free rate were 5% (as in 2023-2024), all computed Sharpe ratios would decrease. The relative ranking of portfolios is less sensitive to this choice than the absolute values.

Who invented the Sharpe ratio?

The Sharpe ratio was introduced by William F. Sharpe, an economist at Stanford University, in a 1966 paper titled "Mutual Fund Performance" published in the Journal of Business. Sharpe originally called it the "reward-to-variability ratio." It was later renamed the Sharpe ratio in his honor. Sharpe was awarded the Nobel Memorial Prize in Economic Sciences in 1990 for his contributions to the theory of financial economics, including the Capital Asset Pricing Model (CAPM).

Is a Sharpe ratio of 1 good?

Yes. A Sharpe ratio of 1.0 is considered very good and is difficult to achieve consistently over long periods. For context, the S&P 500 has historically produced a Sharpe ratio of approximately 0.35-0.40 over multi-decade periods. Most actively managed mutual funds fail to achieve a Sharpe ratio above 0.5 over 10+ year periods. The Balanced ETF portfolio in the BrixNation study achieved a Sharpe ratio of 1.079 over 15 years, which falls in the "very good" range — though this is an in-sample back-test result.

What is the difference between Sharpe ratio and Sortino ratio?

The Sortino ratio is a variant of the Sharpe ratio that replaces the standard deviation of all returns with the standard deviation of only negative returns (downside deviation). This makes the Sortino ratio more forgiving of upward volatility — it only penalizes downside risk. For assets or strategies where positive volatility (large gains) is desirable, the Sortino ratio may be a more appropriate metric. The Sharpe ratio treats all volatility equally, whether the return was unexpectedly high or unexpectedly low.

Can the Sharpe ratio be negative?

Yes. A negative Sharpe ratio occurs when the portfolio's return is less than the risk-free rate, meaning the investor would have been better off holding cash or short-term treasuries and taking no market risk. For example, in 2022 QQQ returned -32.6% while the risk-free rate was approximately 4%. QQQ's single-year Sharpe for 2022 was deeply negative. Multi-year Sharpe ratios for extended bear markets (such as the 2001-2010 QQQ period, CAGR approximately -1.1%) can also be negative.

References

This page is for financial education purposes. It does not constitute investment advice. All Sharpe ratio examples use in-sample back-test data from publicly available sources.