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QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500

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  • Szabolcs Blazsek
  • Vicente Mendoza

Abstract

Statistical performance and out-of-sample forecast precision of ARMA-GARCH and QARMA-Beta- t -EGARCH are compared. We study daily returns on the Standard and Poor’s 500 (S&P 500) index and a random sample of 50 stocks from the S&P 500 for period May 2006 to July 2010. Competing models are estimated for periods before and during the US financial crisis of 2008. Out-of-sample point and density forecasts are performed for periods during and after the US financial crisis. The results provide evidence of the superior in-sample statistical and out-of-sample predictive performance of QARMA-Beta- t -EGARCH.

Suggested Citation

  • Szabolcs Blazsek & Vicente Mendoza, 2016. "QARMA-Beta- t -EGARCH versus ARMA-GARCH: an application to S&P 500," Applied Economics, Taylor & Francis Journals, vol. 48(12), pages 1119-1129, March.
    • Handle: RePEc:taf:applec:v:48:y:2016:i:12:p:1119-1129
    DOI: 10.1080/00036846.2015.1093086
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    Cited by:

    1. Astrid Ayala & Szabolcs Blazsek, 2019. "Score-driven currency exchange rate seasonality as applied to the Guatemalan Quetzal/US Dollar," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 10(1), pages 65-92, March.
    2. Blazsek, Szabolcs & Escribano, Álvaro & Licht, Adrian, 2018. "Seasonality Detection in Small Samples using Score-Driven Nonlinear Multivariate Dynamic Location Models," UC3M Working papers. Economics 27483, Universidad Carlos III de Madrid. Departamento de Economía.

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