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Convergence of Numerical Approximation for Jump Models Involving Delay and Mean-Reverting Square Root Process
The mean-reverting square root process with jump has been widely used as a model on the financial market. Since the diffusion coefficient in the model does not satisfy the linear growth condition and local Lipschitz condition, we can not examine its properties by traditional techniques. To overcome...
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Published in: | Stochastic analysis and applications 2011-03, Vol.29 (2), p.216-236 |
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creator | Jiang, Feng Shen, Yi Wu, Fuke |
description | The mean-reverting square root process with jump has been widely used as a model on the financial market. Since the diffusion coefficient in the model does not satisfy the linear growth condition and local Lipschitz condition, we can not examine its properties by traditional techniques. To overcome the difficulties, we develop several new techniques to examine the numerical method of jump models involving delay and mean-reverting square root. We show that the numerical approximate solutions converge to the true solutions. Finally, we apply the convergence to examine a path-dependent option price and a bond in the financial pricing. |
doi_str_mv | 10.1080/07362994.2011.532043 |
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subjects | Applications Approximation Bonding Compensated Poisson process Convergence Delay Euler-Maruyama method Exact sciences and technology Insurance, economics, finance Lipschitz condition Markov processes Mathematical analysis Mathematical models Mathematics Mean-reverting square root process Probability and statistics Probability theory and stochastic processes Roots Sciences and techniques of general use Statistics Stochastic analysis Stochastic processes Strong convergence |
title | Convergence of Numerical Approximation for Jump Models Involving Delay and Mean-Reverting Square Root Process |
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