A multivariate test for stock market efficiency: the case of ASE
Manolis Kavussanos () and
Everton Dockery
Applied Financial Economics, 2001, vol. 11, issue 5, 573-579
Abstract:
Market efficiency tests in developing markets display mixed evidence, in contrast to evidence on developed markets where the null hypothesis seems to be supported. Specifically, previous tests for market efficiency on the index and on samples of stocks traded in the Athens Stock Exchange (ASE) are broadly not supportive of the efficient market hypothesis. This paper introduces multivariate generalizations of the univariate Dickey-Fuller likelihood ratio tests to the class of Seemingly Unrelated Regressions, to investigate empirically the stock price efficiency of ASE. The method takes into account the contemporaneous correlation between stocks in the ASE, and avoids the sample biases which may result by considering only subsets of stocks listed in the exchange. Conclusively, the results confirm that the ASE is informationally inefficient, implying that past stock prices contain some information as to future price movements which investors may act on.
Date: 2001
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (17)
Downloads: (external link)
http://www.tandfonline.com/doi/abs/10.1080/09603100010013006 (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:11:y:2001:i:5:p:573-579
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAFE20
DOI: 10.1080/09603100010013006
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 ().