On the afternoon of June 21, 2019, at the invitation of Professor Wu Desheng, Vice Dean, Pang Zhan, Associate Professor of Crant School of Management, Purdue University and Yang Qiulin, Assistant Professor of South University of science and technology gave a wonderful academic report entitled "Risk measures in Cumulative Prospect Theory: A Stochastic Dominion Approach" to the faculty and students of the school of economics and management of the Chinese Academy of Sciences.
First of all, from the perspective of the most classical Expected Utility Theory in the field of behavioral finance, Professor Pang Zhan, by explaining the paradox in Experimental Studies in Kahneman and Tversky (1979), pointed out the shortcomings of Expected Utility Theory, which naturally led to the topic of the report -- Risk Measures in Cumulative Prospect Theory. In addition, Professor Pang Zhan, from the macro level, introduced some classical and frontier theories in the field of stochastic dominance and risk measurement, such as value at risk (VaR) and conditional value-at- risk (CVaR), cumulative prospect theory (CPT), etc. Next, Associate Professor Pang Zhan elaborated how to link risk measurement, risk selection and risk preference based on CPT. Associate Professor Pang Zhan introduced in detail how to use range value at risk (RVAR) to describe the risk preference under CPT framework through the method of stochastic dominance.
After that, Dr. Yang, based on both Associate Professor Pang Zhan’s report and probability weight function, explained VaR, CVaR and RVAR risk measurement methods in theory. Dr. Yang and Associate Professor Pang Zhan's research linked risk measure, risk change and choice and CPT with each other through random dominant method, and then people's risk preference can be deduced by observing people's risk choice.
At last, Associate Professor Pang Zhan and Dr. Yang Qiulin also had a warm exchange with the faculty and students from our school. Associate Professor Pang Zhan also proposed a research proposal to apply the cumulative-prospect-theory-based risk measurement model and the robust optimization method in the field of intelligent medical treatment, which greatly expanded the research vision of teachers and students.