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Fractional Cointegration

In: Handbook of Financial Time Series

Author

Listed:
  • Willa W. Chen

    (Texas A&M University, Department of Statistics)

  • Clifford M. Hurvich

    (New York University)

Abstract

We describe a variety of seimparametric models and estimators for fractional cointegration. All of the estimators we consider are based on the discrete Fourier transform of the data. This includes the ordinary least squares estimator as a special case.We make a distinction between Type I and Type II models, which differ from each other in terms of assumptions about initialization, and which lead to different functional limit laws for the partial sum processes. We compare the estimators in terms of rate of convergence. We briefly discuss the problems of testing for cointegration and determining the cointegrating rank. We also discuss relevant modeling issues, such as the local parametrization of the phase function.

Suggested Citation

  • Willa W. Chen & Clifford M. Hurvich, 2009. "Fractional Cointegration," Springer Books, in: Thomas Mikosch & Jens-Peter Kreiß & Richard A. Davis & Torben Gustav Andersen (ed.), Handbook of Financial Time Series, chapter 31, pages 709-726, Springer.
    • Handle: RePEc:spr:sprchp:978-3-540-71297-8_31
    DOI: 10.1007/978-3-540-71297-8_31
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