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The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence

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  • Sethuraman, S.
  • Basawa, I. V.

Abstract

A vector time series model with long-memory dependence is introduced. It is assumed that, at each time point, the observations are equi-correlated. The model is based on a fractionally differenced autoregressive process (long-memory) adjoined to a Gaussian sequence with constant autocorrelation. The maximum likelihood estimators for the parameters in the model are derived and their asymptotic distributions are obtained.

Suggested Citation

  • Sethuraman, S. & Basawa, I. V., 1997. "The asymptotic distribution of the maximum likelihood estimator for a vector time series model with long memory dependence," Statistics & Probability Letters, Elsevier, vol. 31(4), pages 285-293, February.
    • Handle: RePEc:eee:stapro:v:31:y:1997:i:4:p:285-293
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    References listed on IDEAS

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    1. Greene, Myron T. & Fielitz, Bruce D., 1977. "Long-term dependence in common stock returns," Journal of Financial Economics, Elsevier, vol. 4(3), pages 339-349, May.
    2. Myron T. Greene & Bruce D. Fielitz, 1979. "The Effect of Long Term Dependence on Risk-Return Models of Common Stocks," Operations Research, INFORMS, vol. 27(5), pages 944-951, October.
    3. C. W. J. Granger & Roselyne Joyeux, 1980. "An Introduction To Long‐Memory Time Series Models And Fractional Differencing," Journal of Time Series Analysis, Wiley Blackwell, vol. 1(1), pages 15-29, January.
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    Cited by:

    1. Ravishanker, Nalini & Ray, Bonnie K., 2002. "Bayesian prediction for vector ARFIMA processes," International Journal of Forecasting, Elsevier, vol. 18(2), pages 207-214.

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