A similarity‐based approach to time‐varying coefficient non‐stationary autoregression
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- Hamid, Alain & Heiden, Moritz, 2015. "Forecasting volatility with empirical similarity and Google Trends," Journal of Economic Behavior & Organization, Elsevier, vol. 117(C), pages 62-81.
- Lieberman, Offer & Phillips, Peter C.B., 2017.
"A multivariate stochastic unit root model with an application to derivative pricing,"
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- Offer Lieberman & Peter C.B. Phillips, 2014. "A Multivariate Stochastic Unit Root Model with an Application to Derivative Pricing," Cowles Foundation Discussion Papers 1964, Cowles Foundation for Research in Economics, Yale University.
- Kinjo Keita & Sugawara Shinya, 2016. "Predicting Empirical Patterns in Viewing Japanese TV Dramas Using Case-Based Decision Theory," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 16(2), pages 679-709, June.
- Golosnoy, Vasyl & Hamid, Alain & Okhrin, Yarema, 2014. "The empirical similarity approach for volatility prediction," Journal of Banking & Finance, Elsevier, vol. 40(C), pages 321-329.
- Kapetanios, George & Mitchell, James & Shin, Yongcheol, 2014.
"A nonlinear panel data model of cross-sectional dependence,"
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- James Mitchell & George Kapetanios & Yongcheol Shin, 2012. "A Nonlinear Panel Data Model of Cross-Sectional Dependence," Discussion Papers in Economics 12/01, Department of Economics, University of Leicester.
- Kapetanios, George & James Mitchell & Yongcheol Shin, 2013. "A Nonlinear Panel Data Model of Cross-Sectional Dependence," EMF Research Papers 03, Economic Modelling and Forecasting Group.
- Offer Lieberman & Peter C. B. Phillips, 2014.
"Norming Rates And Limit Theory For Some Time-Varying Coefficient Autoregressions,"
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Wiley Blackwell, vol. 35(6), pages 592-623, November.
- Offer Lieberman & Peter C.B. Phillips, 2013. "Norming Rates and Limit Theory for Some Time-Varying Coefficient Autoregressions," Cowles Foundation Discussion Papers 1916, Cowles Foundation for Research in Economics, Yale University.
- Teitelbaum, Joshua C., 2013. "Asymmetric empirical similarity," Mathematical Social Sciences, Elsevier, vol. 66(3), pages 346-351.
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