Journal article 458 views
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...
Published in: | Journal of Time Series Econometrics |
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ISSN: | 1941-1928 |
Published: |
2009
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Online Access: |
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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. |
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Keywords: |
Bayesian method, quantile function, non-Gaussian time series, simulation, parametric and semi-parametric approaches |
College: |
School of Management |
Issue: |
2 |