时 间：2025年4月18日（周五） 09：00 – 10：00
地 点：普陀校区理科大楼A1414室
报告人：金卓 Macquarie 大学教授
主持人：危佳钦 华东师范大学教授
摘 要：
This paper addresses portfolio optimization for retired investors managing risk-free assets, risky assets, and variable annuities with GMDBs under mortality and surrender risks. Using the Lee-Carter model, it analyzes Australian demographic data, predicts mortality risk, and simulates surrender risk for fair GMDB pricing. A deep reinforcement learning (DRL) algorithm optimizes high-dimensional asset allocation, leveraging neural networks to adapt dynamically to market changes. The algorithm's global convergence is proven, ensuring robustness. Numerical experiments validate its effectiveness in managing complex portfolios, highlighting its stability and advantages in integrating mortality, surrender, and financial risks for retirement planning.
报告人简介：
Zhuo Jin is a full professor at Macquarie University. Before joining MQ, he worked as a lecturer, senior lecturer, and associate professor at The University of Melbourne for ten years. His research interests include stochastic optimal control, actuarial science, and mathematical finance. He is an Associate in the Society of Actuaries(ASA).