Asymptotic Theory for M-Estimates in Unstable AR(p) Processes with Infinite Variance Innovations
Applications
2016-12-13 v2 Statistics Theory
Statistics Theory
Abstract
In this paper, we present the asymptotic distribution of M-estimators for parameters in non-stationary AR(p) processes. The innovations are assumed to be in the domain of attraction of a stable law with index . In particular, when the model involves repeated unit roots or conjugate complex unit roots, M-estimators have a higher asymptotic rate of convergence compared to the least square estimators and the asymptotic results can be written as It\^{o} stochastic integrals.
Keywords
Cite
@article{arxiv.1506.05830,
title = {Asymptotic Theory for M-Estimates in Unstable AR(p) Processes with Infinite Variance Innovations},
author = {Maryam Sohrabi and Mahmoud Zarepour},
journal= {arXiv preprint arXiv:1506.05830},
year = {2016}
}