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Please use this identifier to cite or link to this item: http://hdl.handle.net/1808/988
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Title: Knowledge representation and integration for portfolio evaluation using linear belief functions
Authors: Liu, Liping
Shenoy, Catherine
Shenoy, Prakash P.
Keywords: Dempster-Shafer belief functions
knowledge-based systems
linear belief functions
Gaussian belief functions
multivariate normal distribution
portfolio evaluation
Issue Date: Jul-2006
Publisher: The Institute of Electrical and Electronic Engineers, Inc.
Extent: 5439358 bytes
Type: Article
Citation: Liu, L., C. Shenoy, and P. P. Shenoy, "Knowledge representation and integration for portfolio evaluation using linear belief functions," IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans, Vol. 36, No. 4, July 2006, pp. 774--785.
Abstract: In this paper, we propose a linear belief function approach to evaluating portfolio performance. By drawing on the notion of linear belief functions, we propose an elementary approach to knowledge representation for expert systems using linear belief functions. We show how to use basic matrices to represent market information and financial knowledge, including complete ignorance, statistical observations, subjective speculations, distributional assumptions, linear relations, and empirical asset pricing models. We then appeal to Dempster’s rule of combination to integrate the knowledge for assessing the overall belief of portfolio performance, and updating the belief by incorporating additional information. We use an example of three gold stocks to illustrate the approach.
URI: http://hdl.handle.net/1808/988
Appears in Collections:School of Business Articles

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