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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 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.

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 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.

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 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.

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.

Access to daily store level scanner data has been increasingly easier in recent years in Japan and time series analysis based on a sales response model is becoming realistic. Introduces a new method of combining time series analysis and regression analysis on the price promotion effect, which enables simultaneous decomposition of store level scanner sales into trend (including seasonality), day‐of‐the‐week effect and explanatory variable effect due to price promotion. The method was applied to daily store level scanner sales of milk, showing evidence of the existence of day‐of‐the‐week effect. Further, a method of incorporating several kinds of price‐cut variables in regression analysis and the analyzed results were presented.

This chapter examines investor overreaction and seasonality in the stock markets of Korea, Hong Kong and Japan using data for the period of 1985–2004. Evidence suggests little to no reversals following days of excessive increase, but all three indices reversed 35% to 45% following days of excessive decline. Seasonality analysis revealed month-of-the-year effects, day-of-the-week effects, the Friday (weekend) effect and the January effect. The Monday effect was not evident.

Intraday volatility characteristics throughout the trading week are examined at the emerging Borsa Istanbul (BIST) stock exchange. Using five-minute (and 15-minute) intervals, accentuated intraday volatility patterns at the microstructure level are examined during the stock market open and close in the morning and in the afternoon sessions. Volatility is highest when markets open in the morning. The second highest is during the afternoon open. The third highest is before the market closes for the day. Volatility before the market close has increased in recent years. These characteristics are seen every trading day. There are also differences: Monday returns are lowest, Friday returns are highest, and Monday morning volatility is highest of the entire trading week. Day-of-the-week and intraday accentuated volatility smile anomalies are jointly investigated using the longest intraday sample period in the emerging country stock exchange literature. Investment companies and professionals can utilize the results for risk management and hedging by avoiding highly volatile opening and closing periods. Arbitrageurs, speculators, and risk takers should trade during these highly volatile periods. Heightened volatility is increased difficulty in price discovery, thus inefficiency. Market participants, exchanges, and public prefer efficient markets. The research presents evidence of trading days, and periods during the trading day, when the exchange becomes more efficient. This is the first research that explores day-of-the-week effect from intraday volatility perspective in an emerging market, and provides useful recommendations in designing risk management strategies at market microstructure level.