The week-of-the-month effect in stock returns: The evidence from the S&amp;P Composite Index

Kohli, Raj K.; Kohers, Theodor

doi:10.1007/bf02920113

Cited by 10 publications

(6 citation statements)

References 26 publications

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“…This finding is supported by Jaffe and Westerfield (1989) in Australia, Arsad and Coutts (1997) in the UK, and Bildik (2004) in Istanbul. Similarly, using daily returns of the US composite index from 1962-1990, Kohli and Kohers (1992) find that the first week in the month possesses higher average returns than other weeks. Moreover, Lukas (2012) investigates seasonality in the US stock market across six (6) major industrial sectors with the use of descriptive statistics, the GARCH (1,1) model, and Wald Chi-squared test.…”

Section: Literature Reviewmentioning

confidence: 96%

Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets

Obalade¹,

Muzindutsi²

2019

CEMJ

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Section: Literature Reviewmentioning

confidence: 96%

Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets

Obalade¹,

Muzindutsi²

2019

CEMJ

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“…There are several empirical studies which find and report time-related anomalies. For example, holiday effect (Ariel, 1990;Liano and White, 1994;Vergin and McGinnis, 1999), monthly effect (Kim and Park, 1994;Floros, 2008), weekend effect (Lakonishok and Levi, 1982;Jaffe and Westerfield, 1985;Kohli and Kohers, 1992), January effect (Haug and Hirschey, 2006;Rendon and Ziemba, 2007;Agnani and Aray, 2011), turn-of-month effect (Ogden, 1990) and day-of-the-week effect[1] (Chang and Kim, 1988;Dubois and Louvet, 1996;Keef and Roush, 2005;Berument and Dogan, 2012) in equity market returns. Moller and Zilca (2008) show that at the end of December and first few days of January, stock returns are found to be high.…”

Section: Introductionmentioning

confidence: 99%

Turn-of-month effect in the Indian currency market

Kumar

2015

International Journal of Managerial Finance

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Purpose – The purpose of this paper is to examine the presence of the turn-of-month effect in the Indian currency market for selected currency pairs: USD-INR, EUR-INR, GBP-INR and JPY-INR, from January 1999 to April 2014. Design/methodology/approach – Ordinary least square regression analysis is used to examine the presence of the turn-of-month effect and to test the efficiency of the Indian currency market. The characteristics of the returns during the turn-of-month days are compared with that of the non-turn-of-month trading days. The sample period is later divided into two sub-periods, that is, pre- and post-2008 to capture the behavior of returns before and after the 2008 financial crisis. Findings – The results indicate the existence of pricing patterns which are unique to individual currencies. For the entire sample period, USD and JPY exhibit turn-of-month effect and the returns in turn-of-month trading days are significantly lower than the returns during non-turn-of-month trading days. For the sub-period before 2008, all the currencies exhibit significant turn-of-month effects and the returns in the turn-of-month trading days are significantly lower than those in the non-turn-of-month trading days. However, post-2008; this effect vanishes for all the currencies except for USD. Practical implications – The results have important implications for both traders and investors. The findings suggest that the investors might not be able to earn excess profits by timing their positions in some particular currencies taking the advantage of turn-of-month effect which in turn indicates that the currency markets have become more efficient with time. The results are in conformity with those reported for the developed markets. Originality/value – To the best of the author’s knowledge, no study has yet examined these calendar anomalies in the currency markets using data which covers two important periods, pre-2008 and post-2008. Therefore, we provide a pioneer study in which we analyze the calendar anomalies in an emerging currency market (India) by segregating the data before and after 2008 financial crisis.

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“…This finding is supported by Jaffe and Westerfield [108] in Australia, Arsad and Coutts [109] in the UK and Bildik, [110] in Istanbul. Similarly, Kohli and Kohers [111] found that first week in the month possesses average returns that are higher than other weeks using daily returns of the US composite index from 1962 to 1990. In addition, Lukas [112] investigated seasonality in the US stock exchange across six [6] major industrial sectors using descriptive statistics, GARCH(1,1) model and Wald-chi squared test.…”

Section: Calendar Anomaly From Developed and Emerging Marketsmentioning

confidence: 90%

Are African Stock Markets Inefficient or Adaptive? Empirical Literature

Obalade¹,

Muzindutsi²

2021

Emerging Markets

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This chapter reviews empirical studies on weak form of efficiency with the aim of establishing whether the African market is inefficient or adaptive. The reviewed studies are categorised based on their methodological approaches to compare the power of linear and non-linear models in testing for weak-form efficiency. The studies on calendar anomalies, an indication of weak-form inefficiency, are reviewed to assess whether these anomalies are adaptive as portrayed by the relatively recent theory of adaptive market hypothesis (AMH). The scope of reviewed studies is also extended to developed and emerging markets to gain a broad comparison of the findings. This review revealed that non-linear dependence has been revealed in stock returns suggesting that non-linear models are best fit to test for the stock market efficiency. Reviewed studies produced contradictory findings with some supporting and others rejecting weak-form efficiency. Thus, most studies support the AMH, which suggests that market efficiencies and anomalies are time changing. This chapter concludes that most of the existing studies on AMH have been carried out in markets other than Africa, and hence, further empirical studies on the evolving and changing nature of efficiency in African stock markets are recommended.

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The week-of-the-month effect in stock returns: The evidence from the S&P Composite Index

Cited by 10 publications

References 26 publications

Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets

Calendar Anomalies, Market Regimes, and the Adaptive Market Hypothesis in African Stock Markets

Turn-of-month effect in the Indian currency market

Are African Stock Markets Inefficient or Adaptive? Empirical Literature

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