High order weak approximation schemes for L\'evy-driven SDEs

TL;DR

This paper introduces new jump-adapted weak approximation schemes for Le9vy-driven SDEs, improving convergence rates and ease of implementation by matching moments of the driving process.

Contribution

The authors develop a novel scheme that replaces the Le9vy process with a finite intensity process matching moments, applicable to all Le9vy measures and with high convergence rates for stable-like jumps.

Findings

Scheme matches 3 moments, works for all Le9vy measures.

Achieves superior convergence rates compared to existing methods.

Allows arbitrarily high convergence rates for stable-like small jumps.

Abstract

We propose new jump-adapted weak approximation schemes for stochastic differential equations driven by pure-jump L\'evy processes. The idea is to replace the driving L\'evy process $Z$ with a finite intensity process which has the same L\'evy measure outside a neighborhood of zero and matches a given number of moments of $Z$. By matching 3 moments we construct a scheme which works for all L\'evy measures and is superior to the existing approaches both in terms of convergence rates and easiness of implementation. In the case of L\'evy processes with stable-like behavior of small jumps, we construct schemes with arbitrarily high rates of convergence by matching a sufficiently large number of moments.