The Euler scheme for stochastic differential equations: error analysis with Malliavin calculus

1995 ◽  
Vol 38 (1-3) ◽  
pp. 35-41 ◽  
Author(s):  
Vlad Bally ◽  
Denis Talay
2019 ◽  
Vol 25 (4) ◽  
pp. 341-361
Author(s):  
Riu Naito ◽  
Toshihiro Yamada

Abstract The paper proposes a new second-order discretization method for forward-backward stochastic differential equations. The method is given by an algorithm with polynomials of Brownian motions where the local approximations using Malliavin calculus play a role. For the implementation, we introduce a new least squares Monte Carlo method for the scheme. A numerical example is illustrated to check the effectiveness.


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