Bayesian Applications to the Investment Management Process

Biliana Bagasheva, Svetlozar Zari Rachev, John Hsu and Frank Fabozzi
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Biliana Bagasheva: University of California
Svetlozar Zari Rachev: University of Karlsruhe
John Hsu: University of California
Frank Fabozzi: Yale School of Management

Chapter 24 in Handbook on Information Technology in Finance, 2008, pp 587-611 from Springer

Abstract: Abstract There are several tasks in the investment management process. These include setting the investment objectives, establishing an investment policy, selecting a portfolio strategy, asset allocation, and measuring and evaluating performance. Bayesian methods have been either used or proposed as a tool for improving the implementation of several of these tasks. There are principal reasons for using Bayesian methods in the investment management process. First, they allow the investor to account for the uncertainty about the parameters of the return-generating process and the distributions of returns for asset classes and to incorporate prior beliefs in the decision- making process. Second, they address a deficiency of the standard statistical measures in conveying the economic significance of the information contained in the observed sample of data. Finally, they provide an analytically and computationally manageable framework in models where a large number of variables and parameters makes classical formulations a formidable challenge.

Keywords: Stock Return; Portfolio Selection; Asset Allocation; Capital Asset Price Model; Bayesian Model Average (search for similar items in EconPapers)
Date: 2008
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ihichp:978-3-540-49487-4_24

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DOI: 10.1007/978-3-540-49487-4_24

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