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A suggestion for constructing a large time-varying conditional covariance matrix

Author

Listed:
  • Gibson, Heather D.
  • Hall, Stephen G.
  • Tavlas, George S.
Abstract
The construction of large conditional covariance matrices has posed a problem in the empirical literature because the direct extension of the univariate GARCH model to a multivariate setting produces large numbers of parameters to be estimated as the number of equations rises. A number of procedures have previously aimed to simplify the model and restrict the number of parameters, but these procedures typically involve either invalid or undesirable restrictions. This paper suggests an alternative way forward, based on the GARCH approach, which allows conditional covariance matrices of unlimited size to be constructed. The procedure is computationally straightforward to implement. At no point in the procedure is it necessary to estimate anything other than a univariate GARCH model.

Suggested Citation

  • Gibson, Heather D. & Hall, Stephen G. & Tavlas, George S., 2017. "A suggestion for constructing a large time-varying conditional covariance matrix," Economics Letters, Elsevier, vol. 156(C), pages 110-113.
    • Handle: RePEc:eee:ecolet:v:156:y:2017:i:c:p:110-113
    DOI: 10.1016/j.econlet.2017.04.020
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    References listed on IDEAS

    as
    1. Nijman, Theo & Sentana, Enrique, 1996. "Marginalization and contemporaneous aggregation in multivariate GARCH processes," Journal of Econometrics, Elsevier, vol. 71(1-2), pages 71-87.
    2. Heather D. Gibson & Stephen G. Hall & George S. Tavlas, 2016. "Measuring Systemic Stress in European Banking Systems," Discussion Papers in Economics 16/19, Division of Economics, School of Business, University of Leicester.
    3. Bollerslev, Tim, 1986. "Generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 31(3), pages 307-327, April.
    4. Weiss, Andrew A., 1986. "Asymptotic Theory for ARCH Models: Estimation and Testing," Econometric Theory, Cambridge University Press, vol. 2(1), pages 107-131, April.
    5. Komunjer, Ivana, 2001. "Consistent Estimation for Aggregated GARCH," University of California at San Diego, Economics Working Paper Series qt1fp2v3q7, Department of Economics, UC San Diego.
    6. 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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    Cited by:

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    4. Hussein Hassan & Minko Markovski & Alexander Mihailov, 2022. "COVID-19 Cases and Stock Prices by Sector in Major Economies: What Do We Learn from the Daily Data?," Economics Discussion Papers em-dp2022-04, Department of Economics, University of Reading.

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    More about this item

    Keywords

    Large conditional covariance matrix; GARCH; Multivariate GARCH;
    All these keywords.

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C30 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - General
    • C20 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - General

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