The Month-of-the-Year Effect in the European, American, Australian and Asian Markets

Gualter Couto, Pedro Pimentel, Catarina Barbosa and Rui Alexandre Castanho
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Gualter Couto: School of Business and Economics and CEEAplA, University of the Azores, 9500-321 Ponta Delgada, Portugal
Pedro Pimentel: School of Business and Economics and CEEAplA, University of the Azores, 9500-321 Ponta Delgada, Portugal
Catarina Barbosa: School of Business and Economics, University of the Azores, 9500-321 Ponta Delgada, Portugal
Rui Alexandre Castanho: Faculty of Applied Sciences, WSB University, 41-300 Dąbrowa Górnicza, Poland

Economies, 2021, vol. 9, issue 4, 1-14

Abstract: This paper examines the existence of the month-of-the-year effects in four different continents, namely Europe, Asia, America, and Oceania. Nine indexes were analyzed in order to verify differences between monthly returns from January 1990 to December 2013, followed by an examination of the January effect, Halloween effect, and the October effect, testing for statistical significance using an OLS linear regression in order to verify whether those effects offer consistent opportunities for investors. Investors with globally diversified portfolios benefit from the Halloween effect, with a 1.2% average monthly excess return in winter and spring, while the pre-dotcom-bubble period had a better performance than the post-dotcom-bubble period. In the global post-dotcom-bubble period, there is statistical evidence for 1.60% and 1% lower average monthly returns in January (the January effect) and in months other than October (the October effect), respectively, contradicting the literature. The dotcom bubble seems to be responsible for the January effect differing from what might otherwise have been expected in the later period. There is no consistent and clear impact on continental incidence. The Halloween effect is revealed to be a fruitful strategy in the FTSE, DAX, Dow Jones, BOVESPA, and N225 indexes taken one-by-one. The January effect excess average return was only statistically significative for the pre-dotcom-bubble period for globally diversified portfolios. This paper contributes to a wider global and comparable view upon month-of-the-year effect.

Keywords: bubble; dotcom; Halloween effect; month-of-the-year effect (search for similar items in EconPapers)
JEL-codes: E F I J O Q (search for similar items in EconPapers)
Date: 2021
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