2019
DOI: 10.1016/j.jbef.2019.02.009
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Monday mornings: Individual investor trading on days of the week and times within a day

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Cited by 9 publications
(7 citation statements)
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“…Research related to the anomaly of the day-ofthe-week effect, which began in 1930 with a study by Kelly and is still ongoing, as shown by the recent studies from Richards and Willows (2019), found that the returns on Mondays are always negative compared to other days, so this phenomenon is called the Monday effect anomaly. This anomaly can generally only be explained by the existence of persistent seasonal ties in the capital market.…”
Section: Resultsmentioning
confidence: 99%
“…Research related to the anomaly of the day-ofthe-week effect, which began in 1930 with a study by Kelly and is still ongoing, as shown by the recent studies from Richards and Willows (2019), found that the returns on Mondays are always negative compared to other days, so this phenomenon is called the Monday effect anomaly. This anomaly can generally only be explained by the existence of persistent seasonal ties in the capital market.…”
Section: Resultsmentioning
confidence: 99%
“…The significant differences in traded volume across days are also observed in China, India, South Korea, Taiwan, Thailand, Indonesia, Philippines and Pakistan where Monday is the least traded day in each market—except for China and NSE Nifty (India). In a recent enquiry, Richards and Willows (2019) present that Mondays in China are the least traded day in the week. Moreover, the day‐of‐the‐week effect in volume is not discovered only in Malaysia.…”
Section: Conclusion and Discussionmentioning
confidence: 99%
“…Similarly, Berument and Kiymaz (2001) claim that the time series data are subject to variation across time that makes simple OLS inefficient to predict results. Recently, Richards and Willows (2019), Miss, Charifzadeh, and Herberger (2020), Anjum, 2020, and Ali and Ülkü (2020) incorporated GARCH and variants of GARCH to test day‐of‐the‐week effect in time series data. Thus, to account for heteroscedasticity generalized autoregressive conditional heteroscedasticity (GARCH) is employed.…”
Section: Methodology and Datamentioning
confidence: 99%
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“…This prompts towards the magnitude of transaction costs and the trading volume. Richards and Willows (2019) investigated the trading behavior of 7200 UK investors and found that they prefer to selling their losses on Mondays. According to them, mornings and Mondays induce a bad mood compared with other days of the week, so investors may integrate the selling of losses with Monday mornings to create congruence between their emotions and their behavior.…”
Section: Introductionmentioning
confidence: 99%