Optimal Time Interval Selection in Long-Run Correlation Estimation

Pedro Albuquerque

Econometrics from University Library of Munich, Germany

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.

Keywords: Long-Run Correlation; Bartlett; Lag Selection; Time Interval; Alignment; Newey-West (search for similar items in EconPapers)
JEL-codes: C14 (search for similar items in EconPapers)
Pages: 23 pages
Date: 2005-11-23, Revised 2005-11-27
New Economics Papers: this item is included in nep-ecm and nep-ets
Note: Type of Document - pdf; pages: 23
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Citations: View citations in EconPapers (4)

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Related works:
Journal Article: Optimal Time Interval Selection in Long-Run Correlation Estimation (2020)
Working Paper: Optimal Time Interval Selection in Long-Run Correlation Estimation (2020)
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Persistent link: https://EconPapers.repec.org/RePEc:wpa:wuwpem:0511017

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