本文研究了由一维Lévy过程驱动的倒向随机微分方程(BSDE)的反比较定理.利用一般g-期望下BSDE的反比较定理的证明方法,推导出了一般f-期望下BSDE的反比较定理,并给出了一般f-期望下Jensen不等式成立的充分必要条件.
In this paper, we are devoted to the converse comparison theorem for backward stochastic differential equations (BSDEs, for short) driven by 1-dimensional Levy processes. With the similar method of the converse comparison theorem under g-expectation, we prove the converse comparison theorem under f-expectation. Moreover, we provide a necessary and sufficient condition for the Jensen's inequality to hold under the f-expectation, the nonlinear expectation defined by BSDEs driven by Levy processes.