Journal article 1328 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 |
| 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: |
Faculty of Humanities and Social Sciences |
| Issue: |
2 |