The Month-of-the-year Effect: Evidence from GARCH models in Fifty Five Stock Markets
Eleftherios Giovanis ()
MPRA Paper from University Library of Munich, Germany
Abstract:
This paper studies the month of the year effect, where January effect presents positive and the highest returns of the other months of the year. In order to investigate the specific calendar effect in global level, fifty five stock market indices from fifty one countries are examined. Symmetric GARCH models are applied and based on asymmetries tests asymmetric GARCH models are estimated. The main findings of this study is that a December effect is found on twenty stock markets, with higher returns on the specific month, while February effect is presented in nine stock markets, followed by January and April effects in seven and six stock markets respectively. These patterns provide positive and highest returns on the mentioned months, while a pattern where a specific month gives a persistence signal of negative returns couldn’t be found.
Keywords: seasonality; stock returns; calendar effects; month of the year effect; asymmetric GARCH models; asymmetry tests; January effect (search for similar items in EconPapers)
JEL-codes: G11 G14 G15 (search for similar items in EconPapers)
Date: 2009
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)
Downloads: (external link)
https://mpra.ub.uni-muenchen.de/22328/1/MPRA_paper_22328.pdf original version (application/pdf)
https://mpra.ub.uni-muenchen.de/77633/1/MPRA_paper_22328.pdf revised version (application/pdf)
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:pra:mprapa:22328
Access Statistics for this paper
More papers in MPRA Paper from University Library of Munich, Germany Ludwigstraße 33, D-80539 Munich, Germany. Contact information at EDIRC.
Bibliographic data for series maintained by Joachim Winter ().