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Exact Simulation of the First-Passage Time of Diffusions
by
Zucca, C.
, Herrmann, S.
in
Algorithms
/ Approximation
/ Brownian motion
/ Computational Mathematics and Numerical Analysis
/ Diffusion
/ Mathematical and Computational Engineering
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Methods
/ Neurosciences
/ Random variables
/ Simulation
/ Theoretical
2019
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Exact Simulation of the First-Passage Time of Diffusions
by
Zucca, C.
, Herrmann, S.
in
Algorithms
/ Approximation
/ Brownian motion
/ Computational Mathematics and Numerical Analysis
/ Diffusion
/ Mathematical and Computational Engineering
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Methods
/ Neurosciences
/ Random variables
/ Simulation
/ Theoretical
2019
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Do you wish to request the book?
Exact Simulation of the First-Passage Time of Diffusions
by
Zucca, C.
, Herrmann, S.
in
Algorithms
/ Approximation
/ Brownian motion
/ Computational Mathematics and Numerical Analysis
/ Diffusion
/ Mathematical and Computational Engineering
/ Mathematical and Computational Physics
/ Mathematics
/ Mathematics and Statistics
/ Methods
/ Neurosciences
/ Random variables
/ Simulation
/ Theoretical
2019
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Journal Article
Exact Simulation of the First-Passage Time of Diffusions
2019
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Overview
Since diffusion processes arise in so many different fields, efficient technics for the simulation of sample paths, like discretization schemes, represent crucial tools in applied probability. Such methods permit to obtain approximations of the first-passage times as a by-product. For efficiency reasons, it is particularly challenging to simulate directly this hitting time by avoiding to construct the whole paths. In the Brownian case, the distribution of the first-passage time is explicitly known and can be easily used for simulation purposes. The authors introduce a new rejection sampling algorithm which permits to perform an exact simulation of the first-passage time for general one-dimensional diffusion processes. The efficiency of the method, which is essentially based on Girsanov’s transformation, is described through theoretical results and numerical examples.
Publisher
Springer US,Springer Nature B.V,Springer Verlag
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