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A note on the estimated GARCH coefficients from the S&P1500 universe

Author

Listed:
  • Georgios Bampinas

    () (Department of Economics, University of Macedonia, Greece)

  • Konstantinos Ladopoulos

    () (Citrix Systems Research & Development Ltd, UK)

  • Theodore Panagiotidis

    () (Department of Economics, University of Macedonia, Greece; The Rimini Centre for Economic Analysis, Italy)

Abstract

We employ 1440 stocks listed in the S&P Composite 1500 Index of the NYSE. Three benchmark GARCH models are estimated for the returns of each individual stock under three alternative distributions (Normal, t and GED). We provide summary statistics for all the GARCH coefficients derived from 11520 regressions. The EGARCH model with GED errors emerges as the preferred choice for the individual stocks in the S&P 1500 universe when non-negativity and stationarity constraints in the conditional variance are imposed. 57% of the constraint’s violations are taking place in the S&P small cap stocks.

Suggested Citation

  • Georgios Bampinas & Konstantinos Ladopoulos & Theodore Panagiotidis, 2017. "A note on the estimated GARCH coefficients from the S&P1500 universe," Working Paper series 17-09, Rimini Centre for Economic Analysis.
  • Handle: RePEc:rim:rimwps:17-09
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    References listed on IDEAS

    as
    1. He, Changli & Ter svirta, Timo & Malmsten, Hans, 2002. "Moment Structure Of A Family Of First-Order Exponential Garch Models," Econometric Theory, Cambridge University Press, vol. 18(04), pages 868-885, August.
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    3. Glosten, Lawrence R & Jagannathan, Ravi & Runkle, David E, 1993. " On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks," Journal of Finance, American Finance Association, vol. 48(5), pages 1779-1801, December.
    4. R. F. Engle & A. J. Patton, 2001. "What good is a volatility model?," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 237-245.
    5. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    6. 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 229-235, April.
    7. Changli He & Timo Terasvirta & Hans Malmsten, 1999. "Fourth Moment Structure of a Family of First-Order Exponential GARCH Models," Research Paper Series 29, Quantitative Finance Research Centre, University of Technology, Sydney.
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    Blog mentions

    As found by EconAcademics.org, the blog aggregator for Economics research:
    1. Here's What I've Been Reading
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2017-05-05 18:37:00

    More about this item

    Keywords

    GARCH; GJR-GARCH; EGARCH; alternative distributions; volatility; time-series;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes

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