Strong convergence of Monte Carlo simulations of the mean-reverting square root process with jump

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摘要

More and more empirical evidence shows that the jump-diffusion process is more appropriate to model an asset price, the interest rate and stochastic volatility. This paper considers the numerical methods of the mean-reverting square root process with jump. We concentrate on the Euler–Maruyama (EM) method and derive explicitly computable error bounds over finite time intervals. These error bounds imply strong convergence as the timestep tends to zero. We also prove strong convergence of error bounds under stochastic volatility with correlated jumps (SVCJ). Finally, we apply these convergence to examine some option prices and a bond.

论文关键词:CIR model,Compensated Poisson process,Euler–Maruyama,SV model,SVCJ model

论文评审过程:Available online 4 October 2008.

论文官网地址:https://doi.org/10.1016/j.amc.2008.09.040