Key Takeaways
- • Investopedia's guide outlines a quantitative framework for evaluating hedge funds, centered on absolute returns, relative returns, risk metrics, and benchmark ratios.
- • Absolute (total) return measures the gain or loss of a fund, while relative return compares performance against peers, mutual funds, or indexes over one-, three-, and five-year annualized periods.
- • The article cautions that standard deviation understates the risk of asymmetric hedge fund returns and that Value at Risk (VaR) can underestimate losses under normal-distribution assumptions, so skewness and kurtosis should also be analyzed.
- • The Sharpe ratio is presented as a key risk-adjusted return measure, with a ratio above 1 generally considered good, and its attractiveness varies with interest-rate conditions.
- • Beta, correlation, and alpha are identified as benchmark measures; most hedge funds calculate beta against the S&P 500, according to the article.
Summary
The Investopedia guide, authored by Arturo Neto and updated January 19, 2026, sets out how investors can apply quantitative analysis to hedge fund performance and risk. It argues that hedge funds should be evaluated on both absolute and relative returns. Absolute return, also called total return, measures the gain or loss generated by a fund and helps position it relative to traditional investments. Relative return assesses attractiveness against peers, including other hedge funds, mutual funds, or indexes, and the article recommends measuring it across several time periods, such as one-, three- and five-year annualized returns, and adjusting for risk. A strong fund should rank in the top quartiles across these periods to demonstrate alpha-generating ability.
On risk, the guide states that outsized returns generally require risk-taking, so risk must be incorporated into any performance assessment. Standard deviation is described as easy to calculate but weak for hedge funds, because their returns are often asymmetric and the metric can mask a higher probability of large losses. VaR, which estimates the highest likely loss at a five percent probability, is considered useful but can underestimate both loss size and likelihood when returns are assumed to be normally distributed. The article therefore recommends examining skewness, which measures return asymmetry, and kurtosis, which measures the weight of distribution tails. A negatively skewed distribution carries the risk of very negative outcomes even when their probability is low.
For risk-adjusted performance, the article highlights the Sharpe ratio, which measures additional return per unit of risk. It notes that a ratio above 1 is good, while lower ratios should be judged against the asset class or strategy. Because the calculation depends on the risk-free rate, Sharpe ratios may look more attractive in low-rate environments. Benchmark ratios complete the framework: beta measures sensitivity to an index (a beta of 1.5 implies roughly 1.5 percent fund movement per 1 percent market move), and most hedge funds measure beta against the S&P 500, according to the article. Correlation measures how closely fund returns move together, which informs diversification decisions.
On risk, the guide states that outsized returns generally require risk-taking, so risk must be incorporated into any performance assessment. Standard deviation is described as easy to calculate but weak for hedge funds, because their returns are often asymmetric and the metric can mask a higher probability of large losses. VaR, which estimates the highest likely loss at a five percent probability, is considered useful but can underestimate both loss size and likelihood when returns are assumed to be normally distributed. The article therefore recommends examining skewness, which measures return asymmetry, and kurtosis, which measures the weight of distribution tails. A negatively skewed distribution carries the risk of very negative outcomes even when their probability is low.
For risk-adjusted performance, the article highlights the Sharpe ratio, which measures additional return per unit of risk. It notes that a ratio above 1 is good, while lower ratios should be judged against the asset class or strategy. Because the calculation depends on the risk-free rate, Sharpe ratios may look more attractive in low-rate environments. Benchmark ratios complete the framework: beta measures sensitivity to an index (a beta of 1.5 implies roughly 1.5 percent fund movement per 1 percent market move), and most hedge funds measure beta against the S&P 500, according to the article. Correlation measures how closely fund returns move together, which informs diversification decisions.
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