Risk

Pricing high-dimensional Bermudan options using deep learning and higher-order weak approximation

This paper proposes a new deep-learning-based algorithm for high-dimensional Bermudan option pricing. To the best of our knowledge, this is the first study of the arbitrary-order discretization scheme ...
Nature

Statistical Approximation Theory and Operators

Statistical Approximation Theory and Operators is a vibrant area within applied mathematics that investigates how diverse families of operators can be utilised to ...
Risk

Stability and convergence of Galerkin schemes for parabolic equations with application to Kolmogorov pricing equations in time-inhomogeneous Lévy models

Two essential quantities for the analysis of approximation schemes of evolution equations are stability and convergence. We derive stability and convergence of fully discrete approximation schemes of ...