Revisiting fast profit investor sentiment and stock returns during Ramadan

Osamah Al-Khazali

International Review of Financial Analysis, 2014, vol. 33, issue C, 158-170

Abstract: Using stochastic dominance (SD) approach, this paper revisits the Ramadan effect in the stock returns of 15 Muslim countries and altogether as a portfolio. Our study is motivated by the preferred statistical attributes of SD analysis. Specifically, SD requires no normal distribution of returns assumption and it imposes few restrictions on investors' risk-return tradeoff preference. Our results indicate that the Ramadan effect exists in most of Muslim countries used in the study during the sub-periods 1996–2000 and 2001–2006 and in the portfolio during the sub-period 1995–2007. However, its magnitude diminishes during the global financial crisis period (2007–2012). The findings of this paper indicate that previous results are not an artifact deriving from violations of distributional assumptions. We conclude that risk-averse investors would benefit from increased utility by switching from non-Ramadan to Ramadan.

Keywords: Ramadan effect; Stochastic dominance; Calendar anomaly; Market efficiency (search for similar items in EconPapers)
JEL-codes: G12 G14 G15 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (25)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S105752191400026X
Full text for ScienceDirect subscribers only

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:eee:finana:v:33:y:2014:i:c:p:158-170

DOI: 10.1016/j.irfa.2014.02.003

Access Statistics for this article

International Review of Financial Analysis is currently edited by B.M. Lucey

More articles in International Review of Financial Analysis from Elsevier
Bibliographic data for series maintained by Catherine Liu ().