The 45th Frontier Forum for Digital Technology and Finance

Abstract：

Deep Reinforcement Learning (DRL) has emerged as a transformative methodology for solving sequential decision-making problems, particularly in environments characterized by uncertainty, high dimensional state spaces, and dynamic feedback. This survey provides a comprehensive overview of DRL algorithms and their applications in finance and actuarial science. We begin by reviewing foundational concepts and notable DRL algorithms, including value-based, policy-based, and actor-critic methods. We then explore their deployment in key financial domains, such as portfolio optimization, algorithmic trading, and risk management, as well as in actuarial tasks like dynamic pricing and claims reserving. The article concludes with a discussion of current challenges, research opportunities, and future directions for DRL in these domains.

Speaker Introduction：

Lai Yongzeng, Full Professor in the Department of Mathematics at Wilfrid Laurier University, Canada, obtained his Bachelor's degree in 1983 and Master's degree in 1988 from the Department of Mathematics at Sun Yat-sen University. He received his Ph.D. in January 2000 from Claremont Graduate University in California, USA. From May 2000 to June 2002, he was a Postdoctoral Fellow at the Centre for Advanced Studies in Finance and the Department of Statistics and Actuarial Science at the University of Waterloo, Canada. His main research areas include Financial Mathematics (pricing and risk management of derivatives, financial computation, portfolio optimization, applications of stochastic analysis in finance and insurance), applications of differential equations in finance and economics, Monte Carlo and quasi-Monte Carlo simulation methods and applications; machine learning and its applications, particularly in economics and finance. He has published over 70 papers in international journals such as Automatica, Computers & Operations Research, Economic Modeling, Expert Systems with Applications, Energy Economics, Finance Research Letters, Insurance: Mathematics and Economics, and Journal of Computational Finance. He has secured multiple grants from the Natural Sciences and Engineering Research Council of Canada (NSERC) and serves as a member of the NSERC Mathematics and Statistics Grant Selection Committee.