University of Oxford
Christoph Reisinger is Professor of Applied Mathematics at the University of Oxford, a member of the Mathematical and Computational Finance and Data Science research groups at Oxford, the Oxford-Man Institute of Quantitative Finance, the Oxford-Nie Financial Big Data Lab, and a Fellow of St Catherine’s College.
He is now editor-in-chief of The Journal of Computational Finance. Previously, he directed the professional MSc in Mathematical Finance at Oxford and was editor-in-dhief for Applied Mathematical Finance, where he remains an associate editor. He has active research collaborations with financial institutions, including recently Bank of America Merrill Lynch, BNP Paribas, and the Chicago Mercantile Exchange.
His scientific contributions cover a broad spectrum of areas such as stochastic control and PDE methods for asset allocation, the calibration of local-stochastic and path-dependent volatility models for derivatives markets, and the simulation of interacting particle systems and filtering equations for credit risk computations.
Calibration of local-stochastic and path-dependent volatility models to vanilla and no-touch options
In this paper, the authors consider a large class of continuous semi-martingale models and propose a generic framework for their simultaneous calibration to vanilla and no-touch options.
A mixed Monte Carlo and partial differential equation variance reduction method for foreign exchange options under the Heston–Cox–Ingersoll–Ross model
The paper concerns a hybrid pricing method build upon a combination of Monte Carlo and PDE approach for FX options under the four-factor Heston-CIR model.
Numerical valuation of derivatives in high-dimensional settings via partial differential equation expansions
This paper presents a new numerical approach to solving high-dimensional partial differential equations that arise in the valuation of exotic derivative securities. The resulting numerical solutions are carefully compared in terms of accuracy and run…