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计算数学（英文版）
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2026年6期
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HIGH ORDER PROBABILISTIC NUMERICAL METHODS FOR FORWARD BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS
HIGH ORDER PROBABILISTIC NUMERICAL METHODS FOR FORWARD BACKWARD STOCHASTIC DIFFERENTIAL EQUATIONS
摘要
In this paper,we design novel high order probabilistic numerical algorithms for forward backward stochastic differential equations.Moreover,we derive the error estimates and prove the high order convergence rates of the proposed schemes.Because the proposed scheme involves conditional expectations,an estimator based on the multilevel Monte Carlo method is applied to approximate the conditional expectations.Furthermore,we theoretically demonstrate that the computational complexity of our numerical method is proportional to the square of prescribed accuracy.Numerical experiments are given to illustrate the theoretical results.
年，卷(期)：
2026, 44(6)
分类号：
60H35
60Y20
65C30
65C05
机标分类号：
TP31
P631.84
TS974
在线出版日期：
2026年9月15日
