Zhan Pang , 普渡大学副教授:累积前景理论中的风险规避与风险追逐

【主讲】Zhan Pang , 普渡大学副教授

【主题】累积前景理论中的风险规避与风险追逐

【时间】20181221日(周五) 10:00-12:00

【地点】清华经管学院 伟伦楼453

【语言】英语

【主办】管理科学与工程系

【简历】Zhan Pang老师的简历

Professor Pang is an associate professor in supply chain and operations management at Krannert School of Management of Purdue University. Prior to Purdue, he was a faculty member of City University of Hong Kong and Lancaster University and also held an adjunct position at Norweigian School of Economics (NHH).  

His research interests include supply chain and service operations, risk modeling and management, pricing and revenue management, healthcare management, and decision making under risk and uncertainty. He is coordinating the Purdue Blockchain Lab based in Krannert Center. His publications have appeared in Operations Research, Production and Operations Management, Manufacturing and Service Operations Management, IEEE Transactions on Automatic Control, Applied Energy, etc. He is a senior editor of Production and Operations Management.

He has rich industrial experience. He has consulted extensively for various companies across the world, including Astra Zeneca, Shop Direct Group (UK), Pentland and HNA Qianhai Supply Chain, etc. He was also an entrepreneur and managment consultant.  He is on the board of directors of China Titans Energy Technology (HKEx 2188).

 

SpeakerZhan Pang, associate professorPurdue University

TopicRisk Aversion and Risk Seeking in Cumulative Prospect Theory: A Stochastic Dominance Approach

TimeFriday, Dec. 21, 2018, 10:00-12:00

VenueRoom 453, Weilun Building, Tsinghua SEM

LanguageEnglish

OrganizerDepartment of Management Science and Engineering

Abstract The emergence of the cumulative prospect theory (CPT) provides a prominent alternative paradigm to expected utility theory (EUT). Inspired by the  notions of increase in risk and strong risk aversion introduced by Rothschild and Stiglitz (1970) in the EUT paradigm, we employ a stochastic dominance (SD) approach to provide a choice-theoretic characterization for risk aversion and risk seeking preferences in the CPT paradigm where the risk preferences are jointly represented by a reference-dependent value function and a pair of probability weighting functions (PWFs). We first identify an SD condition, namely, mean-preserving prospect stochastic dominance (M-PSD), to measure the increase in risk in CPT, which implies strong risk aversion and strong risk seeking in gains and losses respectively (defined as CPT strong risk aversion), and show that such that the preference agreeing with such an order must be represented by an S-shaped value function and a pair of convex PWFs. To account for the inverse-S-shaped PWFs that overweight small probabilities that favor risk aversion in the lower tail of gains and risk seeking in the upper tail of gain, we further generalize the SD conditions and reveal that the corresponding value function must be inverse-S-shaped as well in losses and gains with the same inflection points as that of the PWFs.  We also show that increase in risk aversion in CPT can be characterized by increased absolute values of the Arrow-Pratt absolute risk aversion measures in losses and gains, respectively, and convex cumulative probability transformations. As applications, we discuss the implications our results on risk preference elicitation in experimental studies and optimal decision problems (e.g., portfolio choice) in CPT. We also extend the analysis to account for general reference points and inverse S-shaped value functions.