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Alternative Estimators for Factor GARCH Models--A Monte Carlo Comparison

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  • Lin, Wen-Ling

Abstract

This paper proposes four estimators for factor GARCH models: two-stage univariate GARCH (2SUE), two-stage quasi-maximum likelihood (2SML), quasi-maximum likelihood with known factor weights (RMLE), quasi-maximum likelihood with unknown factor weights (MLE). A Monte-Carlo study is designed for bivariate one-factor GARCH models to examine the finite sample properties. Results are presented for biases, ratios of standard errors to standard deviations, ratios of variances, coverage of confidence intervals, effects of misspecified factor weights, and finite sample properties of the 2SUE for factor GARCH-in-mean models. Copyright 1992 by John Wiley & Sons, Ltd.

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  • Lin, Wen-Ling, 1992. "Alternative Estimators for Factor GARCH Models--A Monte Carlo Comparison," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 7(3), pages 259-279, July-Sept.
  • Handle: RePEc:jae:japmet:v:7:y:1992:i:3:p:259-79
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    Cited by:

    1. Audrone Virbickaite & M. Concepción Ausín & Pedro Galeano, 2015. "Bayesian Inference Methods For Univariate And Multivariate Garch Models: A Survey," Journal of Economic Surveys, Wiley Blackwell, vol. 29(1), pages 76-96, February.
    2. Sentana, Enrique & Fiorentini, Gabriele, 2001. "Identification, estimation and testing of conditionally heteroskedastic factor models," Journal of Econometrics, Elsevier, vol. 102(2), pages 143-164, June.
    3. Hecq Alain & Palm Franz C. & Laurent Sébastien, 2016. "On the Univariate Representation of BEKK Models with Common Factors," Journal of Time Series Econometrics, De Gruyter, vol. 8(2), pages 91-113, July.
    4. Font, Begoña, 1998. "Modelización de series temporales financieras. Una recopilación," DES - Documentos de Trabajo. Estadística y Econometría. DS 3664, Universidad Carlos III de Madrid. Departamento de Estadística.
    5. Bollerslev, Tim & Engle, Robert F. & Nelson, Daniel B., 1986. "Arch models," Handbook of Econometrics,in: R. F. Engle & D. McFadden (ed.), Handbook of Econometrics, edition 1, volume 4, chapter 49, pages 2959-3038 Elsevier.
    6. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521770415, May.
    7. Sébastien Laurent & Luc Bauwens & Jeroen V. K. Rombouts, 2006. "Multivariate GARCH models: a survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 21(1), pages 79-109.
    8. LeBaron, Blake, 2003. "Non-Linear Time Series Models in Empirical Finance,: Philip Hans Franses and Dick van Dijk, Cambridge University Press, Cambridge, 2000, 296 pp., Paperback, ISBN 0-521-77965-0, $33, [UK pound]22.95, [," International Journal of Forecasting, Elsevier, vol. 19(4), pages 751-752.
    9. Kaiser, Thomas, 1996. "One-factor-Garch models for German stocks: Estimation and forecasting," Tübinger Diskussionsbeiträge 87, University of Tübingen, School of Business and Economics.
    10. Ng, Victor K. & Pirrong, Stephen Craig, 1996. "Price dynamics in refined petroleum spot and futures markets," Journal of Empirical Finance, Elsevier, vol. 2(4), pages 359-388, February.
    11. Klaassen, F.J.G.M., 1999. "Have Exchange Rates Become More Closely Tied? Evidence from a New Multivariate GARCH Model," Discussion Paper 1999-10, Tilburg University, Center for Economic Research.

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