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    A Linear Belief Function Approach to Portfolio Evaluation

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    UAI03b.pdf (1.647Mb)
    Issue Date
    2003-08
    Author
    Liu, Liping
    Shenoy, Catherine
    Shenoy, Prakash P.
    Publisher
    Morgan Kaufmann Publishers
    Format
    1727612 bytes
    Type
    Book chapter
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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.
    URI
    http://hdl.handle.net/1808/154
    ISBN
    0-127-05664-5
    Collections
    • School of Business Scholarly Works [212]
    • Center for East Asian Studies Scholarly Works [354]
    • Distinguished Professors Scholarly Works [918]
    Citation
    U. Kjærulff and C. Meek (eds.), Uncertainty in Artificial Intelligence, 2003, pp. 370--377, Morgan Kaufmann, San Francisco, CA

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    KU Libraries
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    KU Libraries
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    Lawrence, KS 66045
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    Contact KU ScholarWorks
    785-864-8983
    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    785-864-8983

    KU Libraries
    1425 Jayhawk Blvd
    Lawrence, KS 66045
    Image Credits
     

     

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