The Sharpe Ratio

Statistics and Applications

Steven E. Pav

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English

Chapman & Hall/CRC
23 September 2021

Econometrics; Economic statistics; Business strategy; Applied mathematics

The Sharpe ratio is the most widely used metric for comparing the performance of financial assets. The Markowitz portfolio is the portfolio with the highest Sharpe ratio. The Sharpe Ratio: Statistics and Applications

examines the statistical propertiesof the Sharpe ratio and Markowitz portfolio,

both under the simplifying assumption of Gaussian returns and asymptotically.

Connections are drawn between the financial measures and classical statistics including Student's t, Hotelling's T^2, and the Hotelling-Lawley trace.

The robustness of these statistics to heteroskedasticity, autocorrelation, fat tails, and skew of returns are considered. The construction of portfolios to maximize the Sharpe is expanded from the usual static unconditional model to include

subspace constraints, heding out assets, and the use of conditioning information on

both expected returns and risk. {book title} is the most comprehensive treatment of the statistical properties of the Sharpe ratio and Markowitz portfolio ever published.

Features:
* Material on single asset problems, market timing,

unconditional and conditional portfolio problems, hedged portfolios.
* Inference via both Frequentist and Bayesian paradigms.
*A comprehensive treatment of overoptimism and overfitting of trading

strategies.
*Advice on backtesting strategies.
*Dozens of examples and hundreds of exercises for self study.

This book is an essential reference for

the practicing quant strategist and the researcher alike,

and an invaluable textbook for the student.

Steven E. Pav holds a PhD in mathematics from Carnegie Mellon University, and degrees in mathematics and ceramic engineering science from Indiana University, Bloomington and Alfred University. He was formerly a quantitative strategist at Convexus Advisors and Cerebellum Capital, and a quantitative analyst at Bank of America. He is the author of a dozen R packages, including those for analyzing the

significance of the Sharpe ratio and Markowitz portfolio. He writes about the Sharpe ratio at https://protect-us.mimecast.com/s/BUveCPNMYvt0vnwX8Cj689u?domain=sharperat.io .

By: Steven E. Pav
Imprint: Chapman & Hall/CRC
Country of Publication: United Kingdom
Dimensions: Height: 234mm, Width: 156mm,
Weight: 807g
ISBN: 9781032019307
ISBN 10: 1032019301
Pages: 470
Publication Date: 23 September 2021
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

I The Sharpe Ratio 1. The Sharpe Ratio and the Signal-Noise Ratio 2. The Sharpe Ratio for Gaussian Returns 3. The Sharpe Ratio for Other Returns 4. Overoptimism II Maximizing the Signal-Noise Ratio 5. Maximizing the Sharpe Ratio 6. Portfolio Inference for Gaussian Returns 7. Portfolio Inference for Other Returns 8. Overoptimism and Overfitting 9. Market Timing 10. Backtesting Appendix A Prerequisites

Steven E. Pav holds a PhD in mathematics from Carnegie Mellon University, and degrees in mathematics and ceramic engineering science from Indiana University, Bloomington and Alfred University. He was formerly a quantitative strategist at Convexus Advisors and Cerebellum Capital. He is the author of a dozen R packages, including those for analyzing the significance of the Sharpe ratio and Markowitz portfolio. He writes about the Sharpe ratio at http://www.sharperat.io/ .