毓菁秀华 | 我院弓晓敏老师合作论文已在国际一流期刊 “J INT FINANC MARK” 上发表

Journal of International Financial Markets Institutions & Money

《货币经济学杂志》（Journal  of International Financial Markets Institutions &  Money）是经济学领域的核心期刊之一，每年出版十次，文章涵盖了对广泛现代宏观经济主题的重要研究贡献，包括经验、方法和理论方面的研究成果，该期刊最近五年影响因子为4.755。

弓晓敏

Portfolio  allocation is one of the core issues in financial engineering, as it  focuses on identifying the optimal asset allocation strategy to  guarantee that investors’ investment goals are met. This paper studies  the dynamic portfolio allocation problem in financial markets under the  IT2F environment. Three objectives are simultaneously considered in the  proposed model, including portfolio prospect theory value, risk, and  diversification degree. Given that investors’ behaviors and decisions in  each period are susceptible to the results that have been realized in  the previous period, the loss aversion rate and reference wealth in the  prospect value function are dynamically updated in the modeling of this  study. Regarding the multi-dimensional characteristics of the research  problem, a fuzzy goal programming model under the  competitive-cum-compensatory decision strategy is considered. In this  model, the “Min” operator based competitive strategy is fused with the  “Arithmetic average” operator based compensatory strategy.

Empirical  studies are carried out with data sets from two financial markets to  test the proposed model. Research findings show that the compensatory  parameter significantly impacts asset allocation in each period. A  targeted comparison of multiple portfolio models formed from a  three-tier perspective is conducted. The results of the comparison  suggest that IT2FSs are more accurate than classical fuzzy sets in  describing the uncertainty of asset information. The main reason is that  the membership functions of IT2FSs are represented by fuzzy rather than  precise values. The results also show that considering investors’ loss  aversion can effectively improve portfolio performance in the TI2F  environment. The presented model under the competitive-cum-compensatory  decision strategy is superior to the model under the fully competitive  or fully compensatory strategy in terms of return criteria and  return-risk criteria. Comparison between models incorporating dynamic  and static prospect value functions shows that portfolios under the  dynamic condition can bring better investment results. This indicates  that the investor’s loss aversion and reference dependence are closely  related to previous outputs. Finally, the sensitivity analysis shows  that the portfolio corresponding to high loss aversion rate is  accompanied by low-return and low-risk performance, but this does not  necessarily mean that a low loss aversion rate will obtain a high  portfolio return. This research contributes theoretically to the  existing literature by developing a new framework that can deal with the  multi-objective portfolio selection problem, and it can be treated as  the first research of dynamic multi-period portfolio allocation in the  IT2F context.