SPEAKER: 朱书尚 教授，中山大学

TIME/DATE: 2024年9月20日上午 10:00

CLASSROOM: 同济大厦A楼 403教室

ABSTRACT

In the financial system, the bailout strategy is crucial to cushion the massive loss caused by systemic risk. There is no closed-form formulation of the optimal bailout problem, making solving it difficult. In this paper, we consider the issue of the optimal bailout (capital injection) as a black-box optimization problem, where the black box is characterized as a fixed-point system that adheres to the E-N framework for measuring the systemic risk of the financial system. We propose the so-called “Prediction-Gradient-Optimization”(PGO) framework to address this problem. In this framework, the “Prediction” refers to approximating and predicting the objective function without a closed-form using a neural network, the “Gradient” is calculated based on the previous approximation, and the “Optimization” procedure is further implemented within a gradient projection algorithm to solve the problem. Comprehensive numerical simulations demonstrate that the proposed approach is promising for systemic risk management.

GUEST BIO

朱书尚，湖南人，本科（1997）和硕士（2000）毕业于湘潭大学， 2003年毕业于中国科学院系统科学研究所，获管理学博士学位。2003年7月到2012年1月于复旦大学管理学院任教，现任中山大学管理学院财务与投资系教授、博士生导师。多次到香港中文大学、京都大学做访问交流。研究领域包括金融工程、风险管理和运筹学等。当前研究兴趣主要包括投资组合优化、Forward-Looking收益预测、风险值优化、系统性风险传染机制与测度、随机规划等。在国内外专业学术期刊上发表论文70余篇，其中包括在Operations Research, INFORMS Journal on Computing, Mathematical Finance, IEEE Transactions on Automatic Control, IISE Transactions, Journal of Economic Dynamics and Control, Journal of Banking and Finance, Journal of Financial Stability, Quantitative Finance, Journal of Computational Finance,《管理科学学报》和《金融研究》等期刊上发表的多篇论文。兼任中国运筹学会金融工程与金融风险管理分会副理事长、广东经济学会副会长等职。