Posted: 21 Apr 2005 Last revised: 5 Feb 2017
Date Written: October 1, 2006
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, Andrews-Monahan
JEL Classification: C14
Suggested Citation: Suggested Citation
Albuquerque, Pedro H., Optimal Time Interval Selection in Long-Run Correlation Estimation (October 1, 2006). Available at SSRN: https://ssrn.com/abstract=702650 or http://dx.doi.org/10.2139/ssrn.702650