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equations with state-dependent noise
Error estimates of the $\theta$-scheme for backward stochastic differential
equations
In this paper, we study the error estimate of the $\theta$-scheme
for the backward stochastic differential equation
$y_t=\varphi(W_T)+\int_t^Tf(s,y_s)ds-\int_t^Tz_sdW_s$. We show that
this scheme is of first-order convergence in $y$ for general
$\theta$. In particular, for the case of $\theta=\frac{1}{2}$ (i.e.,
the Crank-Nicolson scheme), we prove that this scheme is of
second-order convergence in $y$ and first-order in $z$. Some
numerical examples are also given to validate our theoretical
results.