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Moments of the ARMA-EGARCH Model

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  • Menelaos Karanasos
  • J. Kim

Abstract

This paper considers the moment structure of the ARMA(r,s)-EGARCH(p,q) model. In particular, we provide the autocorrelation function and any arbitrary moment of the conditional variance/squared errors. In addition, we derive the cross correlations between the process and the conditional variance/squared errors. We also explain our general results using the MA(1)-EGARCH(3,3)\ and the MA(1)-EGARCH(1,4) models as examples. Finally, the practical implications of the results are illustrated empirically using daily data on four East Asia Stock Indices.

Suggested Citation

  • Menelaos Karanasos & J. Kim, "undated". "Moments of the ARMA-EGARCH Model," Discussion Papers 00/29, Department of Economics, University of York.
  • Handle: RePEc:yor:yorken:00/29
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    Cited by:

    1. Liudas Giraitis, 2004. "LARCH, Leverage, and Long Memory," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 177-210.
    2. Vanderlei Kleinschmidt & Roberto Meurer, 2008. "Interdependence in conditional variances between Latin American stock markets," Anais do XXXVI Encontro Nacional de Economia [Proceedings of the 36th Brazilian Economics Meeting] 200807211543080, ANPEC - Associação Nacional dos Centros de Pós-Graduação em Economia [Brazilian Association of Graduate Programs in Economics].
    3. Denise R. Osborn & Christos S. Savva & Len Gill, 2008. "Periodic Dynamic Conditional Correlations between Stock Markets in Europe and the US," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 6(3), pages 307-325, Summer.
    4. Timo Terasvirta & Zhenfang Zhao, 2011. "Stylized facts of return series, robust estimates and three popular models of volatility," Applied Financial Economics, Taylor & Francis Journals, vol. 21(1-2), pages 67-94.
    5. Antonis Demos, 2002. "Moments and dynamic structure of a time-varying parameter stochastic volatility in mean model," Econometrics Journal, Royal Economic Society, vol. 5(2), pages 345-357, June.
    6. Lama, A. & Jha, G.K. & Paul, R.K. & Gurung, B., 2015. "Modelling and Forecasting of Price Volatility: An Application of GARCH and EGARCH Models," Agricultural Economics Research Review, Agricultural Economics Research Association (India), vol. 28(1).
    7. Malmsten, Hans & Teräsvirta, Timo, 2004. "Stylized Facts of Financial Time Series and Three Popular Models of Volatility," SSE/EFI Working Paper Series in Economics and Finance 563, Stockholm School of Economics, revised 03 Sep 2004.
    8. Jérôme Vandenbussche & Stanley B Watt & Szabolcs Blazsek, 2009. "The Liquidity and Liquidity Distribution Effects in Emerging Markets; The Case of Jordan," IMF Working Papers 09/228, International Monetary Fund.
    9. Giraitis, Liudas & Leipus, Remigijus & Robinson, Peter M. & Surgailis, Donatas, 2003. "LARCH, leverage and long memory," LSE Research Online Documents on Economics 2020, London School of Economics and Political Science, LSE Library.
    10. María José Rodríguez & Esther Ruiz, 2012. "Revisiting Several Popular GARCH Models with Leverage Effect: Differences and Similarities," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 10(4), pages 637-668, September.

    More about this item

    Keywords

    Autocorrelations; Exponential GARCH; Stock Returns.;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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