High-dimensional partial differential equations (PDEs) appear in a number of models from
the financial industry, such as in derivative pricing models, credit valuation adjustment …

This is a thoroughly updated edition of Dynamic Asset Pricing Theory, the standard text for
doctoral students and researchers on the theory of asset pricing and portfolio selection in …

In this paper, we introduce a numerical method for nonlinear parabolic partial differential
equations (PDEs) that combines operator splitting with deep learning. It divides the PDE …

In financial and actuarial modeling and other areas of application, stochastic differential
equations with jumps have been employed to describe the dynamics of various state …

During the seven years that elapsed between the first and second editions of the present
book, considerable progress was achieved in the area of financial modelling and pricing of …

This book is a substantially revised and expanded edition reflecting major developments in
stochastic numerics since the 1st edition [314] was published in 2004. The new topics …

We suggest a discrete-time approximation for decoupled forward–backward stochastic
differential equations. The Lp norm of the error is shown to be of the order of the time step …

In this paper we propose a numerical scheme for a class of backward stochastic differential
equations (BSDEs) with possible path-dependent terminal values. We prove that our …

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This paper aims to give an overview and summary of numerical methods for the solution of
stochastic differential equations. It covers discrete time strong and weak approximation …