Multi-stage stochastic model in portfolio selection problem

Shokoofeh Banihashemi, Ali Moayedi Azarpour, Marzeih Kaveh


In this paper, a multi objective model is presented for portfolio selection problem, characterized on the basis of four parameters: the expected return, downside beta  coefficient, semivariance and Conditional value at risk (CVaR) at a specified confidence level. Also, multi- period models can be defined as stochastic. At the first variance was considered as a risk measure. However, both theories and practices indicate that variance is not a good measure of risk and has some disadvantage. Therefore, downside risk measures, such as semivariance, downside beta coefficient, Value-at-Risk (VaR), or Conditional Value-at-Risk (CVaR) should be replaced with variance. In order to solve the proposed model, genetic algorithm is used. Finally, numerical example are given to illustrate the effectiveness of the proposed algorithm.  

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