报告题目：An Efficient and Provable Sequential Quadratic Programming Method for American Pricing

报告人：沈金叶 副教授 西南财经大学

报告时间：2025年8月11日 13:00-14:00

报告地点：正新楼105

报告摘要：

A sequential quadratic programming numerical method is proposed for American option pricing based on the variational inequality formulation. The variational inequality is discretized using the $\theta$-method and BDF2 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,negative option are studied. Numerical examples are presented to confirm the effectiveness of the method.

报告人简介：沈金叶,副教授，西南财经大学禁漫天堂 硕士生导师。研究兴趣：分数阶模型的数值算法,金融期权定价模型的数值算法，Bernoulli 自由边界问题的自适应算法，非线性发展方程的差分方法。主持国家自然科学基金青年基金项目1项，四川省自然科学基金1项。近5年在国际主流计算数学，金融数学杂志上发表学术论文20余篇。长期从事《数值分析》、《偏微分方程数值解》等课程的教学工作。