Pathwise convergence of a novel numerical scheme based on semi-implicit method for stochastic differential-algebraic equations with non-global Lipschitz coefficients
Guy Tsafack, Antoine Tambue

TL;DR
This paper introduces a semi-implicit numerical scheme for stochastic differential-algebraic equations with non-global Lipschitz coefficients, proving pathwise convergence and demonstrating efficiency through numerical simulations.
Contribution
A novel semi-implicit scheme for SDAEs with non-global Lipschitz coefficients that handles singular matrices and proves pathwise convergence with rate 1/2 - epsilon.
Findings
Scheme converges pathwise with rate 1/2 - epsilon.
Numerical simulations confirm theoretical convergence and efficiency.
Method effectively handles high-dimensional SDAEs with singular matrices.
Abstract
This paper delves into the well-posedness and the numerical approximation of non-autonomous stochastic differential algebraic equations (SDAEs) with nonlinear local Lipschitz coefficients that satisfy the more general monotonicity condition called Khasminskii condition. The key challenge is the presence of a singular matrix which makes the numerical integration hard and heavy. To address this challenge, we propose a novel numerical scheme based on semi-implicit method for the drift component of the SDAEs. More precisely we split the drift term as the sum of a linear term and a nonlinear term. The linear part is approximated implicitly, while the nonlinear part is approximated explicitly. The linear component's role is to handle the singularity issues during the numerical integration without the resolution of nonlinear algebraic equations in the constraint equations. This novel scheme is…
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Taxonomy
TopicsStochastic processes and financial applications
