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Forecasting Volatility of Turkish Markets: A Comparison of Thin and Thick Models

Author

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  • Ekrem Kilic

    (Marmara University)

Abstract

Volatility of financial markets is an important topic for academics, policy makers and market participants. In this study first I summarized several specifications for the conditional variance and also define some methods for combination of these specifications. Then assuming that the squared returns are the benchmark estimate for actual volatility of the day, I compare all of the models with respect to how much efficient they are to mimic the realized volatility. At the same time I used a VaR approach to compare these forecasts. With the help of these analyses I examine if combination of the forecast could outperform the single models.

Suggested Citation

  • Ekrem Kilic, 2005. "Forecasting Volatility of Turkish Markets: A Comparison of Thin and Thick Models," Econometrics 0510007, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpem:0510007
    Note: Type of Document - pdf; pages: 52
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    References listed on IDEAS

    as
    1. Stock, James H. & Watson, Mark W., 1999. "Forecasting inflation," Journal of Monetary Economics, Elsevier, vol. 44(2), pages 293-335, October.
    2. Francis X. Diebold & Peter Pauly, 1987. "Structural change and the combination of forecasts," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 6(1), pages 21-40.
    3. Diebold, Francis X, 1988. "Serial Correlation and the Combination of Forecasts," Journal of Business & Economic Statistics, American Statistical Association, vol. 6(1), pages 105-111, January.
    4. Francis X. Diebold & Jose A. Lopez, 1995. "Forecast evaluation and combination," Research Paper 9525, Federal Reserve Bank of New York.
    5. Francis X. Diebold & Peter Pauly, 1986. "Structural change and the combination of forecasts," Special Studies Papers 201, Board of Governors of the Federal Reserve System (U.S.).
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    Cited by:

    1. Kilic, Ekrem, 2006. "Violation duration as a better way of VaR model evaluation : evidence from Turkish market portfolio," MPRA Paper 5610, University Library of Munich, Germany.

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    More about this item

    Keywords

    volatility; arch; garch; combination; VaR;
    All these keywords.

    JEL classification:

    • C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
    • C2 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables
    • C3 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables
    • C4 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics
    • C5 - Mathematical and Quantitative Methods - - Econometric Modeling
    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs

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