A variance reduction technique for use with the extrapolated Euler method for numerical solution of stochastic differential equations

1994 ◽  
Vol 12 (1) ◽  
pp. 131-140 ◽  
Author(s):  
S.T. Goodlett ◽  
E.J. Allen
2016 ◽  
Vol 16 (1) ◽  
pp. 105-132 ◽  
Author(s):  
Nikolaos Halidias ◽  
Ioannis S. Stamatiou

AbstractWe are interested in the numerical solution of stochastic differential equations with non-negative solutions. Our goal is to construct explicit numerical schemes that preserve positivity, even for super-linear stochastic differential equations. It is well known that the usual Euler scheme diverges on super-linear problems and the tamed Euler method does not preserve positivity. In that direction, we use the semi-discrete method that the first author has proposed in two previous papers. We propose a new numerical scheme for a class of stochastic differential equations which are super-linear with non-negative solution. The Heston 3/2-model appearing in financial mathematics belongs to this class of stochastic differential equations. For this model we prove, through numerical experiments, the “optimal” order of strong convergence at least 1/2 of the semi-discrete method.


2017 ◽  
Vol 324 ◽  
pp. 18-26 ◽  
Author(s):  
Tao Shi ◽  
Jimin Ma ◽  
Hongwen Huang ◽  
Youheng Qiu ◽  
Zhenghong Li ◽  
...  

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