Robust investment policies with bound forecasts
AbstractWe present a continuous minimax model for robust portfolio optimization based on worst-case analysis. The classical Markowitz framework is extended to continuous minimax with upper and lower bounds on the return scenarios and a discrete number of rival risk scenarios. The model integrates benchmark relative computations in view of scalable (not fixed) transaction costs. It evaluates worst-case optimal strategies in view of upper and lower bounds on forecast return and a discrete set of risk scenarios. Robustness arises from the non-inferiority of the min-max strategy. The robust optimal policies are obtained simultaneously with the worst-case scenario. We apply the model to a selection of investment problem and evaluate the ex-ante performance of the strategy using historical data.
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Bibliographic InfoPaper provided by Society for Computational Economics in its series Computing in Economics and Finance 2004 with number 68.
Date of creation: 11 Aug 2004
Date of revision:
Continuous minimax; rival scenarios; portfolio optimization;
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- G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
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