Dynamic Fuzzy Asset Management for Worst Scenarios with Average Value-at-Risks

A dynamic portfolio allocation is discussed in asset management with fuzziness. By perception-based extension for fuzzy random variables, a dynamic portfolio model for average value-at-risks of fuzzy random variables is introduced. By dynamic programming and mathematical programming, this paper derives analytical solutions of the optimization problem for dynamic worst scenarios. A few numerical examples are given to discuss the results. We find the average value-at-risk is a more reasonable criterion than value-at-risk.

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