Academic Report of School of Mathematical Sciences [2025] No. 151

(Series Report for High-Level University Construction No. 1252)

Title：Deep Operator Network Expressivity for European Option Pricing under Exponential Levy Models

Speaker：Assistant Professor Gongqiu Zhang（The Chinese University of Hong Kong，Shenzhen）

Time：14:30-15:30, Dec.9, 2025

Location：Huixing Building 514, Yuehai Campus, Shenzhen University

Abstract：In this paper, we obtain the expression rates of the deep operator network (DeepONet) for learning the pricing operator that maps from the space of coefficient functions to that of pricing functions for European options under exponential time-inhomogeneous L´evy models. Under some structural assumptions on the payoff function, we show that DeepONet overcomes the curse of dimensionality for this problem, i.e., it can achieve an arbitrary uniform error of ε > 0 with the network size growing polynomially in the number of underlying assets (d) and 1/ε. With another set of assumptions on the payoff, we show that the error of DeepONet can decay exponentially in its size, albeit with the implied constant possibly growing exponentially in d. This work is joint with Lingfei Li, Yeda Cui and Wenyong Zhang.

Speaker Profile：Gongqiu Zhang is an Assistant Professor and PhD supervisor at The Chinese University of Hong Kong, Shenzhen, and a Research Scientist at the Shenzhen Big Data Institute. His research focuses on financial mathematics, fintech, and computational finance. His work has been published in journals including Operations Research, Mathematical Finance, Finance and Stochastics, Journal of Economic Dynamics and Control, SIAM Journal on Financial Mathematics, and SIAM Journal on Scientific Computing. He has led multiple projects funded by the National Natural Science Foundation of China and the Shenzhen Science and Technology Innovation Commission.

Faculty and students are welcome to attend!

Invited by:  Jingchao Li

School of Mathematical Sciences

December 8, 2025