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ARCH-Prozesse und ihre Erweiterungen - Eine empirische Untersuchung für Finanzmarktzeitreihen -

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  • Jacobi, Frank
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    Abstract

    Das in Finanzmarktdaten zu beobachtende volatility-clustering impliziert, daß große Renditeschocks bei der Preisbildung die Wahrscheinlichkeit einer hohen zukünftigen Volatilität steigern. Ausgehend von den von Engle (1982) vorgeschlagenen ARCH-Modellen hat sich eine ganze Reihe von Modellvarianten zur Modellierung und Prognose bedingter Varianzen entwickelt. In dieser Analyse werden ARCH-Modelle und ausgewählte Erweiterungen hinsichtlich ihrer Eignung zur Modellierung und Prognose bedingter Varianzen im DAX miteinander verglichen. -- The volatility clustering observed in financial market data implies that large net yield shocks increase the probability of a higher future volatility during the price formation. Starting from the ARCH models which were suggested by Engle (1982), a range of models for conditional variances have been developed. In this analysis ARCH models and selected extensions are compared with each other regarding their suitability for the modelling and prognosis of conditional variances in the DAX-index.

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    Bibliographic Info

    Paper provided by Johannes Gutenberg-Universität Mainz, Institut für Statistik und Ökonometrie in its series Arbeitspapiere des Instituts für Statistik und Ökonometrie with number 31.

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    Date of creation: 2005
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    Handle: RePEc:zbw:maista:31

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    Postal: Haus Recht und Wirtschaft I, Jakob-Welder-Weg 9, D-55128 Mainz
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    1. HARDLE, Wolfgang & HAFNER, Christian M., . "Discrete time option pricing with flexible volatility estimation," CORE Discussion Papers RP -1439, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. Robert Engle, 2002. "New frontiers for arch models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 17(5), pages 425-446.
    4. Robert F. Engle & Victor K. Ng, 1991. "Measuring and Testing the Impact of News on Volatility," NBER Working Papers 3681, National Bureau of Economic Research, Inc.
    5. Bera, Anil K & Higgins, Matthew L, 1993. " ARCH Models: Properties, Estimation and Testing," Journal of Economic Surveys, Wiley Blackwell, vol. 7(4), pages 305-66, December.
    6. Nelson, Daniel B & Foster, Dean P, 1994. "Asymptotic Filtering Theory for Univariate ARCH Models," Econometrica, Econometric Society, vol. 62(1), pages 1-41, January.
    7. Schoffer, Olaf, 2000. "Ist die Hebelwirkung der Grund für Asymmetrie in ARCH- und GARCH-Modellen?," Technical Reports 2000,51, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    8. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
    9. Nelson, Daniel B & Cao, Charles Q, 1992. "Inequality Constraints in the Univariate GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 10(2), pages 229-35, April.
    10. Daniel B. Nelson, 1994. "Asymptotically Optimal Smoothing with ARCH Models," NBER Technical Working Papers 0161, National Bureau of Economic Research, Inc.
    11. Robert F. Engle & Joshua Rosenberg, 1994. "Hedging Options in a GARCH Environment: Testing the Term Structure of Stochastic Volatility Models," NBER Working Papers 4958, National Bureau of Economic Research, Inc.
    12. repec:wop:humbsf:1997-56 is not listed on IDEAS
    13. Lamoureux, Christopher G & Lastrapes, William D, 1990. "Persistence in Variance, Structural Change, and the GARCH Model," Journal of Business & Economic Statistics, American Statistical Association, vol. 8(2), pages 225-34, April.
    14. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    15. E.K. Berndt & B.H. Hall & R.E. Hall, 1974. "Estimation and Inference in Nonlinear Structural Models," NBER Chapters, in: Annals of Economic and Social Measurement, Volume 3, number 4, pages 103-116 National Bureau of Economic Research, Inc.
    16. Daniel B. Nelson, 1994. "Asymptotic Filtering Theory for Multivariate ARCH Models," NBER Technical Working Papers 0162, National Bureau of Economic Research, Inc.
    17. 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.
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