  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.
