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TL;DR

The risk-adjusted return: \( SR = \frac{E[R] - R_f}{\sigma_R} \), measuring excess return per unit of total risk. A Sharpe ratio of 1.0 means 1% excess return per 1% of volatility.

By Valenke Exam Prep Team·Last updated 2026-06-03

Sharpe Ratio

The risk-adjusted return: \( SR = \frac{E[R] - R_f}{\sigma_R} \), measuring excess return per unit of total risk. A Sharpe ratio of 1.0 means 1% excess return per 1% of volatility.

Why it matters for interviews

The standard metric for evaluating trading strategies. Understanding its limitations (assumes normality, time-aggregation, estimation uncertainty) and alternatives (Sortino, Calmar) is essential for quantitative portfolio management.

Definition and Mathematical Foundation

The risk-adjusted return: \( SR = \frac{E[R] - R_f}{\sigma_R} \), measuring excess return per unit of total risk. A Sharpe ratio of 1.0 means 1% excess return per 1% of volatility.

Application in Quantitative Finance

The standard metric for evaluating trading strategies. Understanding its limitations (assumes normality, time-aggregation, estimation uncertainty) and alternatives (Sortino, Calmar) is essential for quantitative portfolio management.

Related Terms

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Frequently Asked Questions

How does the Sharpe ratio scale with time?▼
Under iid returns, the annualized Sharpe scales as \( SR_{annual} = SR_{period} \times \sqrt{n} \) where n is the number of periods per year. This assumes returns are independent -- serial correlation breaks this relationship.
What is a good Sharpe ratio?▼
For a long-only equity portfolio, SR > 0.5 is decent. For a hedge fund strategy, SR > 1.0 is good, > 2.0 is excellent. However, reported Sharpes are often inflated by survivorship bias, overfitting, and illiquidity smoothing.
What are the limitations of the Sharpe ratio?▼
It penalizes upside volatility equally with downside (Sortino ratio fixes this). It assumes normal returns (misleading for skewed/fat-tailed strategies). It is not comparable across different time horizons without adjustment.