报告题目：An efficient sequential quadratic programming methods with finite element for American and swing option pricing
报告人：马敬堂
报告时间：2023年11月18日10:00-11:00
报告地点：数学与统计学院四楼会议室
报告摘要：In this talk, we present the recent work on the sequential quadratic programming method (SQPM) for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the theta method in time and the finite element method in space. The resulting system of algebraic inequalities at each time step is solved through a sequence of box-constrained quadratic programming problems, with the latter being solved by a globally and quadratically convergent, large-scale suitable reflective Newton method. It is proved that the sequence of quadratic programming problems converges with a constant rate under a mild condition on the time step size. The method is general in solving the variational inequalities for the option pricing with many styles of optimal stopping and complex underlying asset models. In particular, swing options and stochastic volatility and jump diffusion models are studied. Numerical examples are presented to confirm the effectiveness of the method. (This is joint work with Weizhang Huang and Jinye Shen.)
报告人简介：马敬堂，西南财经大学数学学院、光华英才杰出学者特聘教授、博士生导师、院长，教育部新世纪优秀人才。现任四川省数学会副理事长，中国运筹学会金融工程与金融风险管理分会副理事长，SCI期刊East Asian Journal on Applied Mathematics编委。主要研究方向为：计算数学与金融数学（期权定价模型、最优投资算法、随机控制计算、HJB方程数值解）。在SIAM Journal on Control and Optimization, European Journal of Operational Research, Insurance: Mathematics and Economics，Journal of Computational Physics等金融数学及计算数学领域期刊发表论文70余篇。