Journal article 1446 views
Forecasting for quantile self-exciting threshold autoregressive time series models
Y Cai,
Yuzhi Cai 
Biometrika, Volume: 97, Issue: 1, Pages: 199 - 208
Swansea University Author:
Yuzhi Cai
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DOI (Published version): 10.1093/biomet/asp070
Abstract
Self-exciting threshold autoregressive time series models have been used extensively and the conditional mean obtained from these models can be used to predict the future value of a random variable. In this paper we consider quantile forecasts of a time series based on the quantile self-exciting thr...
| Published in: | Biometrika |
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| ISSN: | 0006-3444 |
| Published: |
Oxford University Press
2010
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| Online Access: |
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| URI: | https://cronfa.swan.ac.uk/Record/cronfa6996 |
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| Abstract: |
Self-exciting threshold autoregressive time series models have been used extensively and the conditional mean obtained from these models can be used to predict the future value of a random variable. In this paper we consider quantile forecasts of a time series based on the quantile self-exciting threshold autoregressive time series models proposed by Cai and Stander (2008) and present a new forecasting method for these quantile models. Simulation studies and application to real time series show that the method works very well. |
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| Keywords: |
Monte Carlo method, Forecasting method, Predictive density function, Quantile forecast. |
| College: |
Faculty of Humanities and Social Sciences |
| Issue: |
1 |
| Start Page: |
199 |
| End Page: |
208 |