fuzzy variables

After closing, the multi-period portfolio can be corrected and revised at regular intervals. The philosophy behind using multi-period portfolio models is that investors often have a multi-period view of future changes in assets, which can be the result of technical and fundamental analysis or statistical model analysis. In conventional multi-period portfolio models, it is assumed that the forecast and correction time horizons are the same for all assets. However, one asset may be forecasted over a one-month horizon while another may be forecasted over a two-month horizon, and both may be revised in the future. The purpose of this study is to present a multi-period portfolio model in which assets have different time horizons for corrections or an asset may not be traded for the first few periods and then enter the correction stage. In this model, fuzzy variables defined in a credibility space are used to describe the return, and the credibility measure controls the risk. The model's objective function is to maximize the portfolio's ultimate wealth, and a constraint is used to control portfolio risk, in which the validity of the portfolio's ultimate wealth below a certain threshold is controlled at a certain level of confidence. A combination of particle swarm optimization and simulation is used to find the best solution. Finally, using a numerical example, the model is implemented on a portfolio with 6 assets and 4 monthly time steps on the Tehran Stock Exchange.