Approximation and error analysis of forward–backward SDEs driven by general Lévy processes using shot noise series representations

We consider the simulation of a system of decoupled forward–backward stochastic differential equations (FBSDEs) driven by a pure jump Lévy process L and an independent Brownian motion B . We allow the Lévy process L to have an infinite jump activity. Therefore, it is necessary for the simulation to...

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Veröffentlicht in:Probability and statistics 2023, Vol.27, p.694-722
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description We consider the simulation of a system of decoupled forward–backward stochastic differential equations (FBSDEs) driven by a pure jump Lévy process L and an independent Brownian motion B . We allow the Lévy process L to have an infinite jump activity. Therefore, it is necessary for the simulation to employ a finite approximation of its Lévy measure. We use the generalized shot noise series representation method by [26] to approximate the driving Lévy process L . We compute the L p error, p ≥ 2, between the true and the approximated FBSDEs which arises from the finite truncation of the shot noise series (given sufficient conditions for existence and uniqueness of the FBSDE). We also derive the L p error between the true solution and the discretization of the approximated FBSDE using an appropriate backward Euler scheme.
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