学术报告报告题目: Green Nested Simulation with Application in Portfolio Risk Measurement
报 告人: 刘光梧教授
报告时间: 2022年5月26日（星期四）下午3:00-4:00
报告地点: 四号楼4131会议室
邀 请人: 何志坚教授
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数学学院
2022年5月24日
报告摘要：Nested simulation is a natural approach to tackle nested estimation problems in operations research and financial engineering. The outer-level simulation generates scenarios and the inner-level simulations are ran in each outer scenario to estimate the corresponding conditional expectation. The resulting sample of conditional expectations is then used to estimate different risk measures of interest. Despite its flexibility, nested simulation is notorious for its heavy computational burden.
We introduce a novel simulation procedure that reuses inner simulation outputs to improve the efficiency and accuracy in solving nested estimation problems. We analyze the convergence rates of the bias, variance, and MSE of the resulting estimator. In addition, central limit theorems and variance estimators are presented, which lead to asymptotically valid confidence intervals for the nested risk measure of interest. Numerical studies on two financial risk measurement problems show consistent results with the asymptotic analysis and show that the proposed approach outperforms the standard nested simulation and a state-of-art regression approach for nested estimation problems.
报告人简介：Dr. Guangwu Liu is currently a professor in Department of Management Sciences, College of Business at City University of Hong Kong. His research interests include stochastic simulation and machine learning, with applications in financial engineering and risk management. He has published in journals including INFORMS Journal on Computing, Management Science, Operations Research, and Production and Operations Management. He currently serves as an associate editor for Naval Research Logistics and Operations Research.