arXiv · 2102.04131
Higher Strong Order Methods for It\^o SDEs on Matrix Lie Groups
Abstract
In this paper we present a general procedure for designing higher strong order methods for It\^o stochastic differential equations on matrix Lie groups and illustrate this strategy with two novel schemes that have a strong convergence order of 1.5. Based on the Runge-Kutta--Munthe-Kaas (RKMK) method for ordinary differential equations on Lie groups, we present a stochastic version of this scheme and derive a condition such that the stochastic RKMK has the same strong convergence order as the underlying stochastic Runge-Kutta method. Further, we show how our higher order schemes can be applied in a mechanical engineering as well as in a financial mathematics setting.
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Michelle Muniz, Matthias Ehrhardt, Michael Günther, Renate Winkler. 2021-02-08. Higher Strong Order Methods for It\^o SDEs on Matrix Lie Groups. https://arxiv.org/abs/2102.04131
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