Study Of The Modeling Of Fuzzy Dynamic Portfolio Selection

Stochastic and fuzzy are two main aspects of the uncertainty in the financial market. The uncertainty of securities' return rate is the case. The financial market is characterized by fuzziness because of an investor's subjective judgment. Therefore, the models of portfolio selection with fuzzy criterion are investigated, their hybrid intelligent algorithms are also designed. The concrete contents are as follows:Generally speaking, risk preference is not fixed but depends on the context of choice. This paper assumes that the investor survives only if the wealth is large enough to meet the consumption requirement in every time period over the finite horizon. The criterion function is the sum of the credibility that the current wealth is not lower than the given consumption level. So the model of fuzzy dynamic portfolio selection for survial is put forward.After analysing the characters of the VaR value, VaR value is used to measure the investor's risk preference. The investor may have the different VaR value in different time period, which indicates that the investor's risk preference is changing. The criterion function is the sum of the credibility that the return rate of portfolio is not lower than a given expected one. So the fuzzy dynamic portfolio selection model based on the VaR value is put forward.In order to solve the two models proposed above, a hybrid intelligent algorithm that the fuzzy simulation based genetic algorithm and artificial neural network are integrated with the dynamic programming is given to solve it. Illustrative cases are given respectively to demonstrate the efficiency of the proposed method.