A Multi-level Monte Carlo Simulation for Invariant Distribution of Markovian Switching Lévy-Driven SDEs with Super-Linearly Growth Coefficients

Hoang-Viet Nguyen (), Trung-Thuy Kieu (), Duc-Trong Luong (), Hoang-Long Ngo () and Ngoc Khue Tran ()
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Hoang-Viet Nguyen: Hanoi National University of Education
Trung-Thuy Kieu: Hanoi National University of Education
Duc-Trong Luong: Hanoi National University of Education
Hoang-Long Ngo: Hanoi National University of Education
Ngoc Khue Tran: Hanoi University of Science and Technology

Methodology and Computing in Applied Probability, 2025, vol. 27, issue 4, 1-25

Abstract: Abstract This paper concerns the numerical approximation for the invariant distribution of Markovian switching Lévy-driven stochastic differential equations. By combining the tamed-adaptive Euler-Maruyama scheme with the Multi-level Monte Carlo method, we propose an approximation scheme that can be applied to stochastic differential equations with super-linear growth drift and diffusion coefficients.

Keywords: Invariant measure; Markovian switching; Multi-level Monte-Carlo; Super-linearly growth coefficient; Tamed-adaptive Euler-Maruyama scheme; 60H10; 65C30 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s11009-025-10205-2

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