JANUARY EFFECT ANOMALY AND MARKET EFFICIENCY IN THE WESTERN BALKANS ECONOMIES

Faculty of Economics Pale, University of East Sarajevo, Republic of Srpska, BiH
Bosnia and Herzegovina


Abstract

The issue of the existence of calendar anomalies in financial markets has not lost its relevance for years; on the contrary, it remains a subject of ongoing debate and investigation among numerous economists. Most studies place particular emphasis on examining the efficiency of small and insufficiently developed financial markets, as well as on the possibility of generating above-average returns within them. This paper focuses on the analysis of the January effect in the context of the efficiency of financial markets in Bosnia and Herzegovina, Serbia, Montenegro, Croatia, and North Macedonia over the period from January 2019 to December 2023. The analysis is based on daily values of the stock market indices BIRS, SASX10, BELEX15, MONEX, CROBEX, and MBI10. The starting hypothesis of the study posits that the January effect anomaly is not statistically significant in the financial markets of the Western Balkans, that is, these markets exhibit efficiency in this respect. The research employs panel data as a unified dataset, along with the t-test as the primary analytical method. The results obtained confirm the null hypothesis, indicating that within the given sample and applied methodological framework, the January effect was not observed in the analyzed markets during the specified period. The paper also outlines the limitations of the conducted test, as well as the specific characteristics of the selected time interval, which should be taken into account when interpreting the results. A descriptive examination of the panel data reveals certain simultaneous increases or decreases in returns across all observed financial markets, which may be interpreted as a form of pattern or seasonal anomaly. However, given that this observation has not been statistically validated, future research should be directed toward examining other seasonal monthly anomalies, as well as the day-of-the-week effect.

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