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The purpose of this paper is to examine the existence of the day-of-the-week effect in the Indian stock market.

Generalized Autoregressive Conditional Heteroskedasticity (GARCH) (1, 1), Exponential GARCH (EGARCH) (1, 1) and Threshold GARCH (TGARCH) (1, 1) models are employed to examine the day-of-the-week effect in the Indian stock market for the period of 28 years from 3rd July, 1990 to 31st March, 2022.

The empirical results derived from the GARCH models indicate the existence of day-of-the-week effects on stock returns and volatility of the Indian stock market. The study reveals that all the days of the week are positive and significant in National Stock Exchange (NSE)-Nifty market returns. The findings confirm the persistence of ARCH and GARCH effects in the daily return series. Moreover, the asymmetric GARCH models show that the daily stock returns exhibit significant asymmetric (leverage) effects.

The results of this study established that the Indian stock market is not efficient and there exists an opportunity to the traders for predicting the future prices and earning abnormal profits in the Indian stock market. The findings of the study are important for traders, investors and portfolio managers to earn abnormal returns by cross-border diversification.

First, to the best of the authors' knowledge, this paper is the first to study the day-of-the-week effect in Indian stock market considering the most recent and longer time period (1990–2022). Second, unlike previous research, this study used GARCH models (GARCH, EGARCH and TGARCH) to capture the volatility clustering in the data.

The purpose of this study is to examine the impact of thin trading on the day‐of‐the‐week effect in the emerging equity markets of the United Arab Emirates (UAE). Researchers have stated that emerging markets are typically characterized by low liquidity, thin trading and possibly less well‐informed investors with access to unreliable information and considerable volatility. It is well known that thin trading can affect the results of empirical studies on patterns of equity markets by introducing a serious bias into the results.

This study applies a stochastic dominance approach to detect the day‐of‐the‐week effect. The reason for utilizing this approach is that the parametric tests are not strictly appropriate for assets with non‐normally distributed returns. In fact, stochastic dominance is a useful tool for making comparisons among distributions without relying on parametric assumptions.

The findings indicate that there is day‐of‐the‐week effect in published daily prices, while daily effect vanishes when data are corrected to remove any measurement bias arising from thin trading. The stochastic dominance results show that the day‐of‐the‐week effect in the UAE equity markets is not present when we correct raw data for thin and infrequent trading.

There has been no research in the literature testing the day‐of‐the‐week effect on the emerging financial markets in the UAE. The study provides empirical evidence on their degree of market efficiency. If the day‐of‐the‐week effect exists, this means that the Abu Dhabi Securities Markets and the Dubai Financial Markets are inefficient. These results will help investors to develop a good investment strategy

The presence of a day-of-the-week effect has been investigated by many researchers over many years, using a variety of financial data and methods. However, differences in methodology between studies could have led to conflicting results. The purpose of this paper is to expand on an existing study to observe whether an analysis of the same data set with some added years and using a different statistical technique provide the same results.

The study examines the presence of a day-of-the-week effect on the Johannesburg Stock Exchange (JSE) indices for the period March 1995-2016, using a GARCH model.

The findings show that, contrary to the original study, the day-of-the week effect is present in both volatility and return equations. The highest and lowest returns are observed on Monday and Friday, respectively, while volatility is observed on all five days from Monday to Friday.

This study adds to the existing literature on day-of-the-week effect of JSE indices, where different patterns or, in some cases, no pattern have been noted. Few previous studies on the day-of-the-week effect observed the effect at micro-level for separate industries or made use of a GARCH model. The present study thus expands on the study of Mbululu and Chipeta (2012), by adding four additional observation years and using a different statistical technique, to observe differences that arise from a different time period and statistical technique. The results indicate that a day-of-the-week effect is mostly a function of the statistical technique applied.

The purpose of this paper is to empirically investigate the Saturday effect in three emerging stock markets (Bahrain, Kuwait, and Saudi Arabia) by taking into consideration the thin trading that is normal in such capital markets.

The paper applies the stochastic dominance (SD) approach, which is not distribution‐dependent and can shed light on the utility and wealth implications of portfolio preferences by exploiting information in higher order moments, to investigate empirically the existence of the Saturday effect in the three Gulf stock markets.

The findings indicate that the Saturday effect does not manifest itself in the three Gulf stock markets and that the SD results show that the Saturday effect in these markets is not present when raw data are corrected for thin and infrequent trading.

This paper is believed to be the first to use SD approach to examine the Saturday effect.

The purpose of this paper is to examine the day-of-the-week effects of Bitcoin (BTC) markets on the exchange level from January 2014 to September 2018.

The in-depth study on the day-of-the-week effects is conducted by using data consisting of Bitcoin prices denominated in 20 fiat currencies from 23 Bitcoin trading exchanges through the method of rolling sample for calendar effect proposed by Zhang et al. (2017).

It is shown by the empirical results that different patterns of the day-of-the-week effects are observed on Bitcoin denominated in various fiat currencies by referring to the price data collected from exchanges. Furthermore, the patterns of the day-of-the-week effects are also available after adjusting Bitcoin prices denominated in domestic currencies into USD.

Because of the discontinuity of data for some daily return series, estimation with dynamic variance is not applicable. It is assumed that the error item follows normal distribution with constant variance.

The day-of-the-week effects are wide-spread in Bitcoin markets, and they are not mainly caused by movements of foreign exchange rates. Actually, empirical findings in this study provide evidence for inefficiency of Bitcoin markets.

In a recent study, Liano, Liano and Manakyan (1999) conclude that the pattern of day‐of‐the‐week effects in stock indices differs between Democratic administrations and Republican administrations. Specifically, the weekend effect is more pronounced during Republican administrations. This paper re‐examines this issue. It incorporates into the analysis the implications of Connolly's (1989) findings that the weekend effect has disappeared since 1975. We confirm Connolly's results. However, contrary to Liano et al. (1999), we conclude that day‐of‐the‐week effects are not significantly moderated by the political administration.

The purpose of this paper is to investigate the day of the week effect on the Ghana Stock Exchange (GSE) by using the GSE all-share index from November 1990 to August 2012. The presence of the day of the week effect has been reported on several markets.

The study utilizes one-sample t-test, dummy variable regression, autoregressive and generalized autoregressive conditional heteroskedastic models to investigate whether day of the week effect exist on the GSE.

The study reveals the presence of day of the week effect on the GSE, specifically, highest returns on Tuesday and lowest on Thursday. Monday, Wednesday and Friday also record significant positive returns, however, the significance returns is captured by a strong auto-regression in the returns. Therefore, investors may not have the opportunity to increase their returns by timing their investments. Further, the significance of the anomalies is not robust across time since different sub periods with different trading days per week shows different results.

The study provides additional evidence on the day of the week effect by using utilizing frontier market data.

The anomalous patterns in foreign exchange markets have received relatively little attention in the literature. This paper empirically investigates the Day-of-the-Week effect in the yen-dollar currency market for three decades and confirms that such effect did exist for the period 1973–1989, but it disappears for the 1990s. The results remain unchanged when the business condition effect, the January effect, the holiday effect, and the first and last day of the month effect are controlled. The results suggest that financial deregulation in Japan has made foreign currency markets more efficient in recent years.

The purpose of this paper is to test prominent calendar anomalies for Indian securities markets those are commonly reported for advanced markets.

The study considers closing values of 11 different indices of National Stock Exchange India, for the period 1994-2014. By using dummy variable regression technique, five different calendar anomalies namely day of the week effect, month of the year effect, mid-year effect, Halloween effect, and trading-month effect are tested. Also, the evidence of volatility clustering has been tested through the application of generalized autoregressive conditional heteroscedasticity (GARCH)-M models.

The results display weak evidence in support of a positive Wednesday effect. The results also display weak evidence in support of a positive April and December effect. The results show strong evidence in support of a positive September effect. The Halloween effect was not found significant. The test of mid-year effect provides evidence that the returns obtained on the second-half or the year are considerably higher than those obtained during the first half. The test of interactions effects showed possible presence of interactions among various effects. The GARCH-based tests display strong evidence in support of volatility clustering.

The results have several implications for investors, regulators, and researchers. For investors, the trading strategies based on results obtained have been discussed. Similarly, certain key implications for regulators have been described.

The originality of the paper lies in the long time frame and multiple indices covered. Also, the study analyses five different calendar anomalies and the interactions among these effects. These analyses provide useful insights regarding returns predictability for the Indian securities markets.

The purpose of this paper is to examine whether Real Estate Investment Trusts (REITs) returns on the different days of the week differ from each other.

It uses European Public Real Estate Association (EPRA)/National Association of Real Estate Investment Trusts (NAREIT) UK index daily closing values (GBP) and its two sub-indices FTSE EPRA/NAREIT UK REITs and non-REITs as dependent variables. It employs Kruskal-Wallis tests and dummy-variable regression to test the hypothesis.

The overall findings provide evidence that return anomalies exist in the UK REITs.

Thought significant, the absolute returns differences are modest for investors to gain superior returns in UK REITs. However, by recognising the day-of-the-week effect, investors can buy/sell UK REITs more effectively.

This research brings updated evidence of the contested calendar anomalies issues in REITs.