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Multidimensional Analysis of Monthly Stock Market Returns

Multidimensional Analysis of Monthly Stock Market Returns This study examines the monthly returns in Turkish and American stock market indices to investigate whether these markets experience abnormal returns during some months of the calendar year. The data used in this research includes 212 observations between January 1996 and August 2014. I apply statistical summary analysis, decomposition technique, dummy variable estimation, and binary logistic regression to check for the monthly market anomalies. The multidimensional methods used in this article suggest weak evidence against the efficient market hypothesis on monthly returns. While some months tend to show abnormal returns, there is no absolute unanimity in the applied approaches. Nevertheless, there is a strikingly negative May effect on the Turkish stocks following a positive return in April. Stocks tend to be bullish in December in both markets, yet we do not observe anya significant January effect is not observed. Keywords: stock markets, calendar effect, decomposition, dummy variable, logistic regression JEL classification: G14, G17 1. INTRODUCTION The stock markets are among the most efficient ones where thousands, if not millions, of buyers and sellers act almost instantly to any new information. As such, one would expect that any abnormal opportunity to disappear as soon as it is discovered by investors, http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Annals of the Alexandru Ioan Cuza University - Economics de Gruyter

Multidimensional Analysis of Monthly Stock Market Returns

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Publisher
de Gruyter
Copyright
Sciendo is a De Gruyter company © 2018. ALL RIGHTS RESERVED Powered by PubFactory
ISSN
2068-8717
DOI
10.2478/aicue-2014-0013
Publisher site
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Abstract

This study examines the monthly returns in Turkish and American stock market indices to investigate whether these markets experience abnormal returns during some months of the calendar year. The data used in this research includes 212 observations between January 1996 and August 2014. I apply statistical summary analysis, decomposition technique, dummy variable estimation, and binary logistic regression to check for the monthly market anomalies. The multidimensional methods used in this article suggest weak evidence against the efficient market hypothesis on monthly returns. While some months tend to show abnormal returns, there is no absolute unanimity in the applied approaches. Nevertheless, there is a strikingly negative May effect on the Turkish stocks following a positive return in April. Stocks tend to be bullish in December in both markets, yet we do not observe anya significant January effect is not observed. Keywords: stock markets, calendar effect, decomposition, dummy variable, logistic regression JEL classification: G14, G17 1. INTRODUCTION The stock markets are among the most efficient ones where thousands, if not millions, of buyers and sellers act almost instantly to any new information. As such, one would expect that any abnormal opportunity to disappear as soon as it is discovered by investors,

Journal

Annals of the Alexandru Ioan Cuza University - Economics – de Gruyter

Published: Dec 1, 2014

Keywords: Business and Economics; Political Economics; Political Economics, other

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