Multi-period portfolio selection under the coherent fuzzy environment with dynamic risk-tolerance and expected-return levels（一致模糊环境下具有动态风险容忍和期望收益水平的多周期投资组合研究）
Published in: Applied Soft Computing（JCR一区，IF: 6.725）
We discuss the portfolio selection problems in which the uncertainty of future returns and the heterogeneity of investor attitudes towards the stock market (optimistic–pessimistic–neutral) are captured by coherent fuzzy numbers. Two coherent fuzzy multi-period portfolio selection models are developed from the perspectives of wealth maximization and risk minimization. Given that the constraint levels regarding risk and return of the current period tend to be influenced by the outcome of the previous period, the dynamic risk-tolerance and expected-return levels are integrated into the portfolio modeling. Practical constraints and transaction costs are also taken into account, which enables the models more effective and lifelike in simulating the real-world trading of the stock market. The empirical studies based on two large data sets are presented to illustrate the applicability of the proposed models. To survey the models’ performance, several portfolio evaluation criteria are used to conduct out-of-sample analysis. The results show outstanding performance of the presented models with dynamic strategies over conventional ways (static risk-tolerance and expected-return levels) on most of the indicators. This research offers references for investors with different attitudes to make long-term investment decisions, and is an effective supplement to behavioral portfolio selection research based on bounded rationality under uncertainty.