The Heston model is a popular stochastic volatility model used in financial mathematics to option pricing. This paper focuses on the stochastic Heston model (SHM) with one singular point. In this way, we first consider the existence, uniqueness and boundedness of the numerical solution under the global Lipschitz condition and the linear growth condition. In addition, the stochastic θ-scheme is developed to solve the equation numerically, and we obtain a convergence rate with min{2 − 2α, 1 − 2β} which depends on the kernel parameters. Moreover, Monte Carlo (M.C.) simulation is implemented to this kind of problem in the 95 percent confidence interval, which reveals that it verifies the stochastic θ-scheme results. Finally, a numerical example is given to show the validity and effectiveness of the theoretical results.
Shandal Hashim, A. , Najafi, E. , Ahmadian, D. and Farkhonde Rouz, O. (2025). Investigation of convergence analysis of stochastic Heston model with one singular point. Computational Methods for Differential Equations, (), -. doi: 10.22034/cmde.2025.64394.2921
MLA
Shandal Hashim, A. , , Najafi, E. , , Ahmadian, D. , and Farkhonde Rouz, O. . "Investigation of convergence analysis of stochastic Heston model with one singular point", Computational Methods for Differential Equations, , , 2025, -. doi: 10.22034/cmde.2025.64394.2921
HARVARD
Shandal Hashim, A., Najafi, E., Ahmadian, D., Farkhonde Rouz, O. (2025). 'Investigation of convergence analysis of stochastic Heston model with one singular point', Computational Methods for Differential Equations, (), pp. -. doi: 10.22034/cmde.2025.64394.2921
CHICAGO
A. Shandal Hashim , E. Najafi , D. Ahmadian and O. Farkhonde Rouz, "Investigation of convergence analysis of stochastic Heston model with one singular point," Computational Methods for Differential Equations, (2025): -, doi: 10.22034/cmde.2025.64394.2921
VANCOUVER
Shandal Hashim, A., Najafi, E., Ahmadian, D., Farkhonde Rouz, O. Investigation of convergence analysis of stochastic Heston model with one singular point. Computational Methods for Differential Equations, 2025; (): -. doi: 10.22034/cmde.2025.64394.2921
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