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From Discrete to Continuous: Modeling Volatility of the Istanbul Stock Exchange Market with GARCH and COGARCH

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  • Yildirim, Yavuz
  • Unal, Gazanfer
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    Abstract

    The objective of this paper is to model the volatility of Istanbul Stock Exchange market, ISE100 Index by ARMA and GARCH models and then take a step further into the analysis from discrete modeling to continuous modeling. Through applying unit root and stationary tests on the log return of the index, we found that log return of ISE100 data is stationary. Best candidate model chosen was found to be AR(1)~GARCH(1,1) by AIC and BIC criteria. Then using the parameters from the discrete model, COGARCH(1,1) was applied as a continuous model.

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    File URL: http://mpra.ub.uni-muenchen.de/27946/
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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 27946.

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    Date of creation: 15 Nov 2010
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    Handle: RePEc:pra:mprapa:27946

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    Keywords: ISE100; IMKB100; GARCH Modeling; COGARCH Modeling; discrete modeling; continuous modeling;

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    1. Ross A. Maller & Gernot M\"uller & Alex Szimayer, 2008. "GARCH modelling in continuous time for irregularly spaced time series data," Papers 0805.2096, arXiv.org.
    2. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    3. 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.
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