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Statistical Inference for Sharpe Ratio

In: Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds

Author

Listed:
  • Friedrich Schmid
  • Rafael Schmidt

Abstract

Sharpe ratios (Sharpe 1966) are the most popular risk-adjusted performance measure for investment portfolios and investment funds. Given a riskless security as a benchmark, its Sharpe ratio is defined by S R = μ − z σ 2 $$SR = \frac{{\mu - z}}{{\sqrt {{\sigma ^2}} }}$$ where μ and σ2 denote the portfolio’s mean return and return volatility, respectively, and z represents the riskless return of the benchmark security. From an investor’s point of view, a Sharpe ratio describes how well the return of an investment portfolio compensates the investor for the risk he takes. Financial information systems, for example, publish lists where investment funds are ranked by their Sharpe ratios. Investors are then advised to invest into funds with a high Sharpe ratio. The rationale behind this is that, if the historical returns of two funds are compared to the same benchmark, the fund with the higher Sharpe ratio yields a higher return for the same amount of risk. Though (ex post) Sharpe ratios are computed using historical returns, it is assumed that they have a predictive ability (ex ante). We refer to Sharpe (1994) for related discussions and further references.

Suggested Citation

  • Friedrich Schmid & Rafael Schmidt, 2010. "Statistical Inference for Sharpe Ratio," Palgrave Macmillan Books, in: Arjan B. Berkelaar & Joachim Coche & Ken Nyholm (ed.), Interest Rate Models, Asset Allocation and Quantitative Techniques for Central Banks and Sovereign Wealth Funds, chapter 17, pages 337-357, Palgrave Macmillan.
  • Handle: RePEc:pal:palchp:978-0-230-25129-8_17
    DOI: 10.1057/9780230251298_17
    as

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