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Cointegration models with non Gaussian GARCH innovations

Author

Listed:
  • Nimitha John

    (Cochin University of Science and Technology)

  • Balakrishna Narayana

    (Cochin University of Science and Technology)

Abstract

This paper presents the estimation procedures for a bivariate cointegration model when the errors are generated by a constant conditional correlation model. In particular, the method of maximum likelihood is discussed when the errors follow Generalised Autoregressive Conditional Hetroskedastic (GARCH) models with Gaussian and some non Gaussian innovations. The method of estimation is illustrated using simulated observations. Data analysis is provided to highlight the applications of the proposed models.

Suggested Citation

  • Nimitha John & Balakrishna Narayana, 2018. "Cointegration models with non Gaussian GARCH innovations," METRON, Springer;Sapienza Università di Roma, vol. 76(1), pages 83-98, April.
    • Handle: RePEc:spr:metron:v:76:y:2018:i:1:d:10.1007_s40300-017-0133-z
    DOI: 10.1007/s40300-017-0133-z
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    References listed on IDEAS

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    3. Bollerslev, Tim, 1990. "Modelling the Coherence in Short-run Nominal Exchange Rates: A Multivariate Generalized ARCH Model," The Review of Economics and Statistics, MIT Press, vol. 72(3), pages 498-505, August.
    4. Mak, T. K. & Wong, H. & Li, W. K., 1997. "Estimation of nonlinear time series with conditional heteroscedastic variances by iteratively weighted least squares," Computational Statistics & Data Analysis, Elsevier, vol. 24(2), pages 169-178, April.
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    6. Lee, Tae-Hwy & Tse, Yiuman, 1996. "Cointegration tests with conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 73(2), pages 401-410, August.
    7. Engle, Robert, 2002. "Dynamic Conditional Correlation: A Simple Class of Multivariate Generalized Autoregressive Conditional Heteroskedasticity Models," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(3), pages 339-350, July.
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    Cited by:

    1. Massimiliano Giacalone, 2022. "Optimal forecasting accuracy using Lp-norm combination," METRON, Springer;Sapienza Università di Roma, vol. 80(2), pages 187-230, August.

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