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Abstract Details
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Activity Number:
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354
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Type:
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Contributed
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Date/Time:
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Tuesday, July 31, 2012 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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| Abstract - #305285 |
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Title:
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Monte Carlo Methods for Jump-Diffusion Processes
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Author(s):
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Anton Kliewer*+
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Companies:
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Texas Tech University
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Address:
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2830 65th St, Lubbock, TX, 79413, United States
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Keywords:
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stochastic differential equations ;
exit time ;
jump process ;
poisson process ;
Monte Carlo
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Abstract:
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Exit times for stochastic differential equations are used in many finance and economics problems. Since solutions are often impossible to find analytically efficient computational methods are sought. Kou and Wang have found solutions for a jump-diffusion process where the jump sizes have a double exponential solution while Atiya and Metwally have found efficient numerical methods for finding probability solutions. This work attempts to find straightforward ways of determining small samples that represent the probability distribution of exit times via statistical analysis and Monte Carlo. This is shown to work for several numerical examples for jump-diffusion processes.
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