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- W4206264839 abstract "Stochastic differential equations (SDEs) are used to model various phenomena such as stock prices or physical systems subject to thermal fluctuations. This chapter presents an overview of numerical approximation methods for SDEs. The theory of differential equations (DEs) is the origin of classical calculus and motivated the creation of differential and integral calculus. The chapter presents some necessary steps in order to find an analytic solution for a class of SDEs that arise in population models. It presents two examples: modeling asset prices, and modeling magnitude of earthquake series. If a finite number of SDEs are given in a model, then the multidimensional case should be considered. The chapter discusses the simulation of SDEs focusing mainly on the Euler –Maruyama method Maruyama and Euler–Milstein scheme Milstein for approximating the sample path of SDEs. The Euler–Maruyama method is a technique used to approximate the numerical solution of a SDE." @default.
- W4206264839 created "2022-01-26" @default.
- W4206264839 date "2021-09-24" @default.
- W4206264839 modified "2023-10-16" @default.
- W4206264839 title "Stochastic Differential Equations" @default.
- W4206264839 doi "https://doi.org/10.1002/9781119674757.ch22" @default.
- W4206264839 hasPublicationYear "2021" @default.
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