LONG MEMORY IN FINANCIAL TIME SERIES DATA WITH NON-GAUSSIAN DISTURBANCES

Luis Gil-Alana

International Journal of Theoretical and Applied Finance (IJTAF), 2003, vol. 06, issue 02, 119-134

Abstract: In this article we propose the use of a version of the tests of Robinson [32] for testing unit and fractional roots in financial time series data. The tests have a standard null limit distribution and they are the most efficient ones in the context of Gaussian disturbances. We compute finite sample critical values based on non-Gaussian disturbances and the power properties of the tests are compared when using both, the asymptotic and the finite-sample (Gaussian and non-Gaussian) critical values. The tests are applied to the monthly structure of several stock market indexes and the results show that the if the underlyingI(0)disturbances are white noise, the confidence intervals include the unit root; however, if they are autocorrelated, the unit root is rejected in favour of smaller degrees of integration. Usingt-distributed critical values, the confidence intervals for the non-rejection values are generally narrower than with the asymptotic or than with the Gaussian finite-sample ones, suggesting that they may better describe the time series behaviour of the data examined.

Keywords: Fractional integration; long memory; Monte Carlo simulations; stock market (search for similar items in EconPapers)
Date: 2003
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219024903001827
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:wsi:ijtafx:v:06:y:2003:i:02:n:s0219024903001827

Ordering information: This journal article can be ordered from

DOI: 10.1142/S0219024903001827

Access Statistics for this article

International Journal of Theoretical and Applied Finance (IJTAF) is currently edited by L P Hughston

More articles in International Journal of Theoretical and Applied Finance (IJTAF) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().