Uncertain portfolio adjusting model using semiabsolute deviation
SOFT COMPUTING
DOI:
10.1007/s00500-014-1535-y
出版年:
FEB 2016
摘要
Since the financial markets are complex, sometimes the future security returns are represented mainly based on experts' judgments. This paper discusses a portfolio adjusting problem with risky assets in which security returns are given subject to experts' estimations. Here, we propose uncertain mean-semiabsolute deviation adjusting models for portfolio optimization problem in the trade-off between risk and return on investment. Various uncertainty distributions of the security returns based on experts' evaluations are used to convert the proposed models into equivalent deterministic forms. Finally, numerical examples with synthetic uncertain returns are illustrated to demonstrate the effectiveness of the proposed models and the influence of transaction cost in portfolio selection.