报告题目：Stochastic Path-Dependent Volatility Models for Price-Storage Dynamics in Natural Gas Markets and Discrete-Time Swing Option Pricing

报告人：Yang Yang （Humboldt University of Berlin, Germany）

报告时间： 2025年11月17日14：00-15：00

报告地点：zoom Meeting ID: 886 248 2666 Passcode: 4J727K

校内联系人：张赫 [email protected]

报告摘要: This talk is devoted to the price-storage dynamics in natural gas markets. A novel stochastic path-dependent volatility model is introduced with path-dependence in both price volatility and storage increments. Model calibrations are conducted for both the price and storage dynamics. Further, we discuss the pricing problem of discrete-time swing options using the dynamic programming principle, and a deep learning-based method is proposed for this non-Markovian setting. A numerical algorithm is provided, followed by a convergence analysis result for the deep-learning approach.

报告人简介：Dr. Yang Yang is a postdoctoral researcher at Humboldt Universität zu Berlin under DFG CRC/TRR 388 “Rough Analysis, Stochastic Dynamics and Related Fields", Project B02. His research focuses on stochastic optimal control, path-dependent dynamics, and volatility modeling. He finished his PhD in the Department of Mathematics & Statistics in University of Calgary under the supervision of Dr. Jinniao Qiu and Dr. Antony Ware.