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.

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

Autorentext
Zhongfeng Qin received his BS degree from Nankai University, Tianjin, China and his PhD degree in Operations Research and Cybernetics from Tsinghua University, Beijing, China. He is currently an associate professor at the School of Economics and Management at Beihang University, Beijing, China. His current research interests include uncertain modeling and optimization, portfolio optimization and risk modeling. He was awarded New Century Excellent Talents in University of the Ministry of Education in 2012. Also, he was honored with the 7th Jiaqing Zhong Prize on Operations Research and the 9th Outstanding New Scholar on Operations Research award.

Inhalt
Preface.- 1 Preliminaries.- 2 Credibilistic Mean-Variance-Skewness Model.- 3 Credibilistic Mean-Absolute Deviation Model.- 4 Minimization Model.- 5 Uncertain Mean-Semiabsolude Deviation Model.- 6 Uncertain Mean-LPMs Model.- 7 Interval Mean-Semiabsolute Deviation Model.- 8 Uncertain Random Mean-Variance Model.- 9 Fuzzy Random Mean-Variance Adjusting Model.- 10 Random Fuzzy Mean-Risk Model.- Bibliography.- List of Frequently Used Symbols.