Uncertainty in Artificial Intelligence
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A Linear Belief Function Approach to Portfolio Evaluation
Liping Liu, Catherine Shenoy, Prakash Shenoy
By elaborating on the notion of linear belief functions (Dempster 1990; Liu 1996), 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 an 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.
Keywords: continuous belief functions, multivariate normal, portfolio management
Pages: 370-377
PS Link:
PDF Link: /papers/03/p370-liu.pdf
AUTHOR = "Liping Liu and Catherine Shenoy and Prakash Shenoy",
TITLE = "A Linear Belief Function Approach to Portfolio Evaluation",
BOOKTITLE = "Proceedings of the Nineteenth Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-03)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Francisco, CA",
YEAR = "2003",
PAGES = "370--377"

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