A multi-period fuzzy mean-minimax risk portfolio model with investor's risk attitude

This paper deals with a multi-period portfolio selection problem considering investor's risk attitude in fuzzy environment. We regard the return rate of each risky asset as a fuzzy number and use the expected value and semi-absolute deviation to measure its return and risk, respectively. We adopt an l(infinity) downside risk function to measure the portfolio's risk, which is represented by the maximum individual risk. Moreover, we formulate a reasonable diversification constraint for the portfolio involving risk-free asset. Then, we propose a multi-period portfolio selection model with the objectives of maximizing the final expected wealth and minimizing the final cumulative risk. Furthermore, we design a multiple particle swarm optimization to solve it. Finally, we illustrate the effectiveness of the model and algorithm by using a real case.

Automated summary

This paper discusses a multi-period portfolio selection problem considering investor's risk attitude in a fuzzy environment, using fuzzy numbers to represent the return rates of risky assets and an l(infinity) downside risk function to measure the portfolio's risk. The proposed model aims to maximize expected wealth and minimize cumulative risk, with a diversification constraint for risk-free assets, and is solved using a multiple particle swarm optimization method, demonstrating its effectiveness with a real case example.