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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...

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Published in: Biometrika
ISSN: 0006-3444
Published: Oxford University Press 2010
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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.
Keywords: Monte Carlo method, Forecasting method, Predictive density function, Quantile forecast.
College: School of Management
Issue: 1
Start Page: 199
End Page: 208