Springer Uncertain Portfolio Optimization (Uncertainty and Operations Research)

Product Description 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. From the Back Cover 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. About the Author 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.