Approximations of Euler-Maruyama type for stochastic differential equations with Markovian switching, under non-Lipschitz conditions
By Xuerong Mao, Chenggui Yuan, George Yin. 2007
63 citations recorded by the source corpus.
We develop the Euler-Maruyama scheme for a class of stochastic differential equations with Markovian switching (SDEwMSs) under non-Lipschitz conditions. Both L^1 and L^2-convergence are discussed under different non-Lipschitz conditions. To overcome the mathematical difficulties arisen from the Markovian switching as well as the non-Lipschitz coefficients, several new analytical techniques have been developed in this paper which should prove to be very useful in the numerical analysis of stochastic systems.
Subfields: Demography, Finance
View Paper: https://www.semanticscholar.org/paper/27173b87484114cb4374e827d82c572206755434
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In Demography
In Finance
- Xuerong Mao
- Lukasz Szpruch
- Sotirios Sabanis
- George Yin
- Xiaoyue Li
- Aurélien Alfonsi
- Ke Wang
- Arnulf Jentzen
Citations in the corpus
- Strong convergence rates for backward Euler–Maruyama method for non-linear dissipative-type stochastic differential equations with super-linear diffusion coefficients (2013, background): “The majority of existing results about strong convergence for numerical schemes only cover SDEs where the diffusion part is of the form s x, with r [ 1⁄20:5;1 , [6,14,21,27].”