YAO YAO

About me

I studied Financial Mathematics at Zhejiang University in China, and then came to University of Calgary for postgraduate studies in Statistics. Now, I am working on the algo model risk quantification and I am passionate about quantitative finance and machine learning.

Outputs

Pricing options under rough volatility with backward SPDEs

In this paper, we study the option pricing problems for rough volatility models. As the framework is non-Markovian, the value function for a European option is not deterministic; rather, it is random and satisfies a backward stochastic partial differential equation (BSPDE). The existence and uniqueness of a weak solution is proved for general nonlinear BSPDEs with unbounded random leading coefficients whose connections with certain forward-backward stochastic differential equations are derived as well. These BSPDEs are then used to approximate American option prices. A deep leaning-based method is also investigated for the numerical approximations to such BSPDEs and associated non-Markovian pricing problems. Finally, the examples of rough Bergomi type are numerically computed for both European and American options.