Long range dependence in daily stock returns
Guglielmo Maria Caporale and
Luis Gil-Alana
Applied Financial Economics, 2004, vol. 14, issue 6, 375-383
Abstract:
The tests of Robinson (Journal of the American Statistical Association, 89, 1420-37, 1994a) are used to analyse the degree of dependence in the intertemporal structure of daily stock returns (defined as the first difference of the logarithm of stock prices, where the series being considered is the S&P500 index). These tests have several distinguishing features compared with other procedures for testing for unit (or fractional) roots. In particular, they have a standard null limit distribution and they are the most efficient ones when carried out against the appropriate alternatives. In addition, they allow the incorporation of the Bloomfield (Biometrika, 60, 217-226, 1973) exponential spectral model for the underlying I(0) disturbances. The full sample, which comprises 17 000 observations, is first divided in 10 subsamples of 1700 observations each. These are then grouped two by two, and five by five; finally, the whole sample is considered. The results indicate that the degree of dependence remains relatively constant over time, with the order of integration of stock returns fluctuating slightly above or below zero. On the whole, there is very little evidence of fractional integration, despite the length of the series. Therefore, it appears that the standard practice of taking first differences when modelling stock returns might be adequate.
Date: 2004
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100410001673603 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:apfiec:v:14:y:2004:i:6:p:375-383
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20
DOI: 10.1080/09603100410001673603
Access Statistics for this article
Applied Financial Economics is currently edited by Anita Phillips
More articles in Applied Financial Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().