ISR Special Seminar: Xianming Sun, "Quantifying Model Uncertainty in Financial Markets"

Wednesday, February 1, 2017
10:00 a.m.
2224 A.V. Williams Bldg.
Michael Fu
mfu@umd.edu

Quantifying Model Uncertainty in Financial Markets

Prof. Xianming Sun
Zhongnan University of Economics and Law
China

Host: Michael Fu

Abstract
Parametric models are extensively used in financial markets. However, model uncertainty arises from the complexity or limited capability of parametric models. In this talk, I will present three numerical methods for quantifying model uncertainty in financial markets. First, a backward stochastic differential equation approach is proposed to prove the convergence of locally-risk minimizing strategy when different models can be used to approximate the infinite jump part for underlying asset price process. Second, an efficient Monte Carlo-based method is proposed to calculate uncertainty measures in the setting of derivative pricing. And lastly, an interpolation-based method is proposed to calculate distorted expectations.

Biography
Xianming Sun received his PhD in Mathematics in 2016 from Central South University (China) and Ghent University (Belgium). Afterwards he joined the School of Finance, Zhongnan University of Economics and Law (China) as an assistant professor. His thesis involves numerical methods for quantifying model uncertainty embedded in financial derivatives and risk measures. His research interests include financial derivatives, sequential decision making, and simulation optimization.

Audience: Graduate  Undergraduate  Faculty  Post-Docs 

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