Bandwidth selection by cross-validation for forecasting long memory financial time series

Richard T. Baillie, George Kapetanios and Fotis Papailias

Journal of Empirical Finance, 2014, vol. 29, issue C, 129-143

Abstract: The paper addresses the issue of choice of bandwidth in the application of semiparametric estimation of the long memory parameter in a univariate time series process. The focus is on the properties of forecasts from the long memory model. A variety of cross-validation methods based on out of sample forecasting properties are proposed. These procedures are used for the choice of bandwidth and subsequent model selection. Simulation evidence is presented that demonstrates the advantage of the proposed new methodology.

Keywords: Long memory; Fractional integration; Filtering; Cross-validation; Forecasting (search for similar items in EconPapers)
JEL-codes: C22 C53 (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:empfin:v:29:y:2014:i:c:p:129-143

DOI: 10.1016/j.jempfin.2014.04.002

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Journal of Empirical Finance is currently edited by R. T. Baillie, F. C. Palm, Th. J. Vermaelen and C. C. P. Wolff

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