Fractional Integration and Cointegration in US Financial Time Series Data
Guglielmo Maria Caporale
London South Bank University; Brunel University - Brunel Business School; CESifo (Center for Economic Studies and Ifo Institute for Economic Research)
Luis A. Gil-Alana
University of Navarra - Department of Economics
DIW Berlin Discussion Paper No. 1116
This paper examines several US monthly financial time series data using fractional integration and cointegration techniques. The univariate analysis based on fractional integration aims to determine whether the series are I(1) (in which case markets might be efficient) or alternatively I(d) with d < 1, which implies mean reversion. The multivariate framework exploiting recent developments in fractional cointegration allows to investigate in greater depth the relationships between financial series. We show that there exist many (fractionally) cointegrated bivariate relationships among the variables examined.
Number of Pages in PDF File: 45
Keywords: Fractional integration, long-range dependence, fractional cointegration, financial data
JEL Classification: C22, G10working papers series
Date posted: April 22, 2011
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