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A new Bayesian approach to quantile autoregressive time series model estimation and forecasting

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  • Yuzhi Cai
  • Julian Stander
  • Neville Davies

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  • Yuzhi Cai & Julian Stander & Neville Davies, 2012. "A new Bayesian approach to quantile autoregressive time series model estimation and forecasting," Journal of Time Series Analysis, Wiley Blackwell, vol. 33(4), pages 684-698, July.
    • Handle: RePEc:bla:jtsera:v:33:y:2012:i:4:p:684-698
    DOI: j.1467-9892.2012.00800.x
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    File URL: http://hdl.handle.net/10.1111/j.1467-9892.2012.00800.x
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    Cited by:

    1. Yuzhi Cai & Julian Stander, 2020. "The Threshold GARCH Model: Estimation and Density Forecasting for Financial Returns," Journal of Financial Econometrics, Oxford University Press, vol. 18(2), pages 395-424.
    2. Gideon Boako & Maurice Omane-Adjepong & Joseph Magnus Frimpong, 2016. "Stock Returns and Exchange Rate Nexus in Ghana: A Bayesian Quantile Regression Approach," South African Journal of Economics, Economic Society of South Africa, vol. 84(1), pages 149-179, March.
    3. Guodong Li & Yang Li & Chih-Ling Tsai, 2015. "Quantile Correlations and Quantile Autoregressive Modeling," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 246-261, March.
    4. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2014. "A new quantile regression forecasting model," Journal of Business Research, Elsevier, vol. 67(5), pages 779-784.
    5. Kai Yang & Luan Zhao & Qian Hu & Wenshan Wang, 2024. "Bayesian Quantile Regression Analysis for Bivariate Vector Autoregressive Models with an Application to Financial Time Series," Computational Economics, Springer;Society for Computational Economics, vol. 64(4), pages 1939-1963, October.
    6. Huarng, Kun-Huang & Yu, Tiffany Hui-Kuang, 2015. "Forecasting ICT development through quantile confidence intervals," Journal of Business Research, Elsevier, vol. 68(11), pages 2295-2298.
    7. Griffin, Jim E. & Mitrodima, Gelly, 2020. "A Bayesian quantile time series model for asset returns," LSE Research Online Documents on Economics 105610, London School of Economics and Political Science, LSE Library.

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