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A Smooth Transition GARCH-M Model

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  • Tsatsura, Oleg

    ()
    (Plekhanov Russian University of Economics)

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    Abstract

    Generalized autoregressive conditional heteroscedasticity in-mean model allows accounting for both time-varying variance and risk premium in financial time series data. This paper introduces an extension of this particular model with more flexible parameterization of the way variance enters the conditional mean equation, which allows for more complex dynamics in the time-varying risk premium. Paper presents model specification, criteria for hypothesis testing and develops an application for several stock exchange indexes. Results suggest evidence that proposed model may be more preferable to standard GARCH-in-mean model.

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    File URL: http://pe.cemi.rssi.ru/pe_2010_1_45-61.pdf
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    Bibliographic Info

    Article provided by Publishing House "SINERGIA PRESS" in its journal Applied Econometrics.

    Volume (Year): 17 (2010)
    Issue (Month): 1 ()
    Pages: 45-61

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    Handle: RePEc:ris:apltrx:0085

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    Web page: http://appliedeconometrics.cemi.rssi.ru/

    Related research

    Keywords: Nonlinear GARCH; volatility; risk premium; varying parameters;

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    1. Lawrence R. Glosten & Ravi Jagannathan & David E. Runkle, 1993. "On the relation between the expected value and the volatility of the nominal excess return on stocks," Staff Report 157, Federal Reserve Bank of Minneapolis.
    2. Lundbergh, Stefan & Terasvirta, Timo, 2002. "Evaluating GARCH models," Journal of Econometrics, Elsevier, vol. 110(2), pages 417-435, October.
    3. Fiorentini, Gabriele & Calzolari, Giorgio & Panattoni, Lorenzo, 1996. "Analytic Derivatives and the Computation of GARCH Estimates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(4), pages 399-417, July-Aug..
    4. Menelaos Karanasos & J. Kim, . "Alternative GARCH in Mean Models: An Application to the Korean Stock Market," Discussion Papers 00/25, Department of Economics, University of York.
    5. Engle, Robert F & Lilien, David M & Robins, Russell P, 1987. "Estimating Time Varying Risk Premia in the Term Structure: The Arch-M Model," Econometrica, Econometric Society, vol. 55(2), pages 391-407, March.
    6. Felix Chan & Michael McAleer, 2001. "Estimating Smooth Transition Autoregressive Models with GARCH Errors in the Presence of Extreme Observations and Outliers," ISER Discussion Paper 0539, Institute of Social and Economic Research, Osaka University.
    7. Nelson, Daniel B, 1991. "Conditional Heteroskedasticity in Asset Returns: A New Approach," Econometrica, Econometric Society, vol. 59(2), pages 347-70, March.
    8. Silvennoinen, Annastiina & Teräsvirta, Timo, 2007. "Multivariate GARCH models," Working Paper Series in Economics and Finance 669, Stockholm School of Economics, revised 18 Jan 2008.
    9. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    10. Tim Bollerslev, 2008. "Glossary to ARCH (GARCH)," CREATES Research Papers 2008-49, School of Economics and Management, University of Aarhus.
    11. Godfrey,L. G., 1991. "Misspecification Tests in Econometrics," Cambridge Books, Cambridge University Press, number 9780521424592, April.
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