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Optimal Time Interval Selection in Long-Run Correlation Estimation

Author

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  • Pedro H. Albuquerque

    (Texas A&M International University)

Abstract

This paper presents an asymptotically optimal time interval selection criterion for the long-run correlation block estimator (Bartlett kernel estimator) based on the Newey-West and Andrews-Monahan approaches. An alignment criterion that enhances finite-sample performance is also proposed. The procedure offers an optimal yet unobtrusive alternative to the common practice in finance and economics of arbitrarily choosing time intervals or lags in correlation studies. A Monte Carlo experiment using parameters derived from Dow Jones returns data confirms that the procedures are MSE-superior to typical alternatives such as aggregation over arbitrary time intervals, parametric VAR estimation, and Newey-West covariance matrix estimation with automatic lag selection.

Suggested Citation

  • Pedro H. Albuquerque, 2005. "Optimal Time Interval Selection in Long-Run Correlation Estimation," Econometrics 0511017, University Library of Munich, Germany, revised 27 Nov 2005.
  • Handle: RePEc:wpa:wuwpem:0511017
    Note: Type of Document - pdf; pages: 23
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    More about this item

    Keywords

    Long-Run Correlation; Bartlett; Lag Selection; Time Interval; Alignment; Newey-West;
    All these keywords.

    JEL classification:

    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General

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