Vector forecasting and dynamic portfolio selection: Empirical efficiency of recursive multiperiod strategies
作者： Ralf Östermark
DOI: 10.1016/0377-2217(91)90190-7
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摘要: Abstract In the paper we present a dynamic portfolio selection system. The system combines recent results from domains of time series analysis, theory and multiperiod linear programming under uncertainty. performance decision support is tested empirically against super criterion defined in study. We demonstrate that suitable combination ex ante post information with initial balances for planning horizon yields better efficiency through than strategy relying purely on information. was programmed Abo Academy's vax 8800 computer, mainly fortran , access to imsl library ifps/optimum .
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