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

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  • Lin, Wen-Ling
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    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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    Bibliographic Info

    Article provided by John Wiley & Sons, Ltd. in its journal Journal of Applied Econometrics.

    Volume (Year): 7 (1992)
    Issue (Month): 3 (July-Sept.)
    Pages: 259-79

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    Handle: RePEc:jae:japmet:v:7:y:1992:i:3:p:259-79

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    Cited by:
    1. Sentana, E. & Fiorentini, G., 1997. "Identification, Estimation and Testing of Conditionally Heteroskedastic Factor Model," Papers 9709, Centro de Estudios Monetarios Y Financieros-.
    2. 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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