Threshold estimation for jump-diffusions under small noise asymptotics
arXiv:2207.09852 · doi:10.1007/s11203-023-09286-y
Abstract
We consider parameter estimation of stochastic differential equations driven by a Wiener process and a compound Poisson process as small noises. The goal is to give a threshold-type quasi-likelihood estimator and show its consistency and asymptotic normality under new asymptotics. One of the novelties of the paper is that we give a new localization argument, which enables us to avoid truncation in the contrast function that has been used in earlier works and to deal with a wider class of jumps in threshold estimation than ever before.
arXiv comment38 pages