Parameter Estimation for Partially Observed Affine and Polynomial Processes
Statistics Theory
2025-07-11 v2 Statistics Theory
Abstract
This paper is devoted to parameter estimation for partially observed polynomial state space models. This class includes discretely observed affine or more generally polynomial Markov processes. The polynomial structure allows for the explicit computation of a Gaussian quasi-likelihood estimator and its asymptotic covariance matrix. We show consistency and asymptotic normality of the estimating sequence and provide explicitly computable expressions for the corresponding asymptotic covariance matrix.
Cite
@article{arxiv.2503.05590,
title = {Parameter Estimation for Partially Observed Affine and Polynomial Processes},
author = {Jan Kallsen and Ivo Richert},
journal= {arXiv preprint arXiv:2503.05590},
year = {2025}
}