Normal Inverse Gaussian Autoregressive Model Using EM Algorithm
Methodology
2021-07-16 v2
Abstract
In this article, normal inverse Gaussian (NIG) autoregressive model is introduced. The parameters of the model are estimated using Expectation Maximization (EM) algorithm. The efficacy of the EM algorithm is shown using simulated and real world financial data. It is shown that NIG autoregressive model fit very well the considered financial data and hence could be useful in modeling of various real life time-series data.
Cite
@article{arxiv.2105.14502,
title = {Normal Inverse Gaussian Autoregressive Model Using EM Algorithm},
author = {Monika Singh Dhull and Arun Kumar},
journal= {arXiv preprint arXiv:2105.14502},
year = {2021}
}
Comments
15 pages, 5 figures