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QUANTIFYING THE IMPACT OF PARTIAL INFORMATION ON SHARPE RATIO OPTIMIZATION

Published online by Cambridge University Press:  28 March 2013

Lihong Zhang and
Lin Zhao
Lihong Zhang
Affiliation:
School of Economics and Management, Tsinghua University, Beijing 100084, PRC E-mail: zhanglh2@sem.tsinghua.edu.cn
Lin Zhao
Affiliation:
Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, PRC E-mail: zhaolin@iss.ac.cn
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Abstract

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Motivated by the fact that many investors have limited ability to update the expectation regarding future stock returns with the arrival of new information instantly, this paper provides a continuous-time model to study the performance of passive trading strategies. We derive the true Sharp ratio of the passive strategies in terms of the mean and variance of an explicit stochastic process. Based on this expression, we quantify the impact of partial information by performing a thorough comparative static analysis. Such an analysis provides a rationale for why investors with inaccurate information about stock return behave better in the mean-reverting environment than in the i.i.d. environment and why pessimistic investors can achieve better performance than optimistic ones. As a by-product, we propose an analytical approach to compute the “implied” parameters in stock return predictor for both i.i.d. and mean-reverting dynamics, which seems interesting for future research.

Information

Type
Research Article
Information
Probability in the Engineering and Informational Sciences , Volume 27 , Issue 3 , July 2013, pp. 375 - 402
Copyright
Copyright © Cambridge University Press 2013 

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