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A Linear Belief Function Approach to Portfolio Evaluation
Liu, Liping Shenoy, Catherine Shenoy, Prakash P.
Liu, Liping
Shenoy, Catherine
Shenoy, Prakash P.
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Abstract
We show how to use linear belief functions to represent market information and financial knowledge, including complete ignorance, statistical observations, subjective speculations, dis-tributional assumptions, linear relations, and em-pirical asset pricing models. We then appeal to Dempster’s rule of combination to integrate the knowledge for assessing an overall belief on portfolio performance, and to update this belief by incorporating additional information.
Description
This paper is a condensed 8-pp version of a longer paper titled "Knowledge Representation and Integration for Portfolio Evaluation Using Linear Belief Functions," School of Business Working Paper, December 2003, that has been conditionally accepted in Nov. 2004 for publication in IEEE Transactions on Systems, Man & Cybernetics, Part A.
Date
2003-08
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Morgan Kaufmann Publishers
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Keywords
Normal belief functions, Multivariate normal distribution, Dempster-Shafer belief function theory, Portfolio theory
Citation
U. Kjærulff and C. Meek (eds.), Uncertainty in Artificial Intelligence, 2003, pp. 370--377, Morgan Kaufmann, San Francisco, CA