Marcus Stochastic Differential Equations: Representation of Probability Density

Fang Yang, Chen Fang and Xu Sun ()
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Fang Yang: Basic Department, Information Engineering University, Zhengzhou 450001, China
Chen Fang: Department of Cryptogram Engineering, Information Engineering University, Zhengzhou 450001, China
Xu Sun: School of Mathematics and Statistics, Huazhong University of Science and Technology, Wuhan 430074, China

Mathematics, 2024, vol. 12, issue 19, 1-15

Abstract: Marcus stochastic delay differential equations are often used to model stochastic dynamical systems with memory in science and engineering. It is challenging to study the existence, uniqueness, and probability density of Marcus stochastic delay differential equations, due to the fact that the delays cause very complicated correction terms. In this paper, we identify Marcus stochastic delay differential equations with some Marcus stochastic differential equations without delays but subject to extra constraints. This helps us to obtain the following two main results: (i) we establish a sufficient condition for the existence and uniqueness of the solution to the Marcus delay differential equations; and (ii) we establish a representation formula for the probability density of the Marcus stochastic delay differential equations. In the representation formula, the probability density for Marcus stochastic differential equations with memory is analytically expressed in terms of probability density for the corresponding Marcus stochastic differential equations without memory.

Keywords: stochastic differential equation; stochastic dynamical systems; delay; Lévy process; probability density (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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