Dynamic portfolio allocation for financial markets: A perspective of competitive-cum-compensatory strategy

Abstract

Portfolio allocation is an important research branch in the realm of financial management and financial engineering. In this paper, a dynamic portfolio allocation problem considering the competitive-cum- compensatory relationship among decision objectives is discussed. Interval type-2 fuzzy numbers that provide more flexibility for processing uncertainty are innovatively utilized to characterize asset returns. To capture the behavioral characteristics of investors’ bounded rationality, prospect theory with dynamic updating of loss aversion rate and reference wealth is introduced. The expected semi-absolute deviation and the entropy function based on the Minkowski measure are adopted to describe the risk and diversification degree of portfolio allocation, respectively. With this description, a dynamic multi-objective portfolio allocation model is formulated. Regarding the multi-dimensional characteristics of the problem, competitive-cum-compensatory strategy-based fuzzy goal programming is embedded in the whole optimization process; thus, the model is transformed into a single-objective form for the solution. Several interesting conclusions are drawn from empirical studies in two financial markets. The robustness and superiority of the proposed model are verified by multi-angle comparison and sensitivity analysis. This research not only enriches and extends the field of dynamic portfolio allocation in the fuzzy context, but also offers an effective means for the optimization of multi-objective portfolio models.