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Autoregression with Non-Gaussian Innovations / Yuzhi Cai

Journal of Time Series Econometrics, Volume: 1, Issue: 2

Swansea University Author: Yuzhi, Cai

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DOI (Published version): 10.2202/1941-1928.1016

Abstract

Most economics and finance time series are non-Gaussian. In this paper, we propose aBayesian approach to non-Gaussian autoregressive time series models via quantile functions.This approach is parametric, so we also compare the proposed parametric approach with a semiparametricapproach. Simulation st...

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Published in: Journal of Time Series Econometrics
ISSN: 1941-1928
Published: 2009
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URI: https://cronfa.swan.ac.uk/Record/cronfa11977
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Abstract: Most economics and finance time series are non-Gaussian. In this paper, we propose aBayesian approach to non-Gaussian autoregressive time series models via quantile functions.This approach is parametric, so we also compare the proposed parametric approach with a semiparametricapproach. Simulation studies and applications to real time series show that this methodworks very well.
Keywords: Bayesian method, quantile function, non-Gaussian time series, simulation, parametric and semi-parametric approaches
College: School of Management
Issue: 2