Abstract
In the paper we present a dynamic portfolio selection system. The system combines recent results from the domains of time series analysis, portfolio theory and multiperiod linear programming under uncertainty. The performance of the decision support system is tested empirically against a dynamic super criterion defined in the study. We demonstrate that suitable combination of ex ante and ex post information with initial balances for the planning horizon yields better portfolio efficiency through time than a strategy relying purely on ex ante information. The system was programmed on Åbo Academy's vax 8800 computer, mainly in fortran, with access to the imsl library and ifps/optimum.
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