Uncertain Portfolio Optimization

Authors: Zhongfeng Qin



Presents a comprehensive and up-to-date guide to uncertain portfolio optimization

Can serve as a valuable reference source for academics, researchers and practitioners

Provides an efficient approach to handling risk constraints in general optimization problems

This book provides a new modeling approach for portfolio optimization problems involving a lack of sufficient historical data. The content mainly reflects the author’s extensive work on uncertainty portfolio optimization in recent years. Considering security returns as different variables, the book presents a series of portfolio optimization models in the framework of credibility theory, uncertainty theory and chance theory, respectively. As such, it offers readers a comprehensive and up-to-date guide to uncertain portfolio optimization models.

Table of contents (10 chapters)

Preliminaries

Credibilistic Mean-Variance-Skewness Model

Credibilistic Mean-Absolute Deviation Model

Credibilistic Cross-Entropy Minimization Model

Uncertain Mean-Semiabsolute Deviation Model

Uncertain Mean-LPMs Model

Interval Mean-Semiabsolute Deviation Model

Uncertain Random Mean-Variance Model

Fuzzy Random Mean-Variance Adjusting Model

Random Fuzzy Mean-Risk Model