Friday and Monday Effect in the Webtoon Market

2016 ◽  
Vol 9 (1) ◽  
pp. 119-133
Author(s):  
Hyunseong Jeon ◽  
◽  
Hyung-Deok Shin
Keyword(s):  
Monday Effect

scholarly journals The Monday Effect Revisited: A Diary and Sleep Actigraphy Study

2020 ◽  
Vol 4 (2) ◽  
pp. 167-176
Author(s):  
Achim Elfering ◽  
Christin Gerhardt ◽  
Diana Pereira ◽  
Anna Schenker ◽  
Maria U. Kottwitz
Keyword(s):  
Sleep Duration ◽  
Sleep Onset ◽  
Monday Morning ◽  
Sleep Onset Latency ◽  
Onset Latency ◽  
Social Stressors ◽  
Monday Effect ◽  
Work Related ◽  
Cognitive Failure ◽  
Delayed Sleep

Abstract Purpose Accidents are more likely to occur during the morning hours of Mondays (Monday effect). This might be due to a higher level of cognitive failure on Monday morning at work. Methods In a pilot actigraphy study across one working week, we explored this Monday effect and regressed daily self-reported workplace cognitive failure on weekdays (Monday versus other days), background social stressors at work, delayed sleep onset and sleep duration. Diary data were gathered from 40 full-time employees. Results Confirming our assumptions, results revealed work-related cognitive failure and sleep-onset latency on the previous night to be higher on Mondays compared to other workdays. Work-related cognitive failure correlated positively with delayed sleep-onset latency and background social stressors. In multilevel regression analysis, Monday significantly explained variations in workplace cognitive failure. The addition of background social stressors at work and sleep-onset latency to the regression model showed unique contributions to the prediction of workplace cognitive failure. No significant two-way or three-way interactions between working days, sleep-onset latency or sleep duration, and background social stressors were found. Conclusion Peak levels of cognitive failure on Monday morning and the association of cognitive failure with social stressors at work contribute to understanding the mechanisms involved in the increased prevalence of occupational accidents on Monday morning. Occupational safety interventions should address both social stressors at work and individual sleep hygiene.

Extreme price moves: an INGARCH approach to model coexceedances in commodity markets

2020 ◽  
Author(s):  
Bernardina Algieri ◽  
Arturo Leccadito
Keyword(s):  
Goodness Of Fit ◽  
Emerging Market ◽  
Explanatory Power ◽  
Commodity Markets ◽  
Credit Spread ◽  
Market Demand ◽  
Factors Affecting ◽  
Monday Effect ◽  
Tail Events ◽  
Weather Anomalies

Abstract This study presents a set of integer-valued generalised autoregressive conditional heteroskedastic models to identify possible transmission channels of joint extreme price moves (coexceedances) across a group of agricultural commodities. These models are very useful to identify factors affecting joint tail events and they are superior in terms of goodness of fit to models without autoregressive components. Emerging market demand, crude oil, exchange rate, stock market conditions and credit spread explain extreme joint returns. Psychological factors and the Monday effect play a role in affecting extreme events, while weather anomalies (El Niño and La Niña episodes) do not have explanatory power.

scholarly journals Day Of The Week dan Monday Effect: Fenomena yang Terbuktikan Tidak Konsisten Di Pasar Modal Indonesia

2008 ◽  
Vol 1 (1) ◽  
Author(s):  
Sumiyana Sumiyana
Keyword(s):  
Regression Analysis ◽  
Stock Exchange ◽  
Short Interval ◽  
Return Periods ◽  
Trading Frequency ◽  
Monday Effect ◽  
Methodological Research ◽  
Intraday Data ◽  
Day Of The Week ◽  
Observation Period

This research critiques Sumiyana (2007a) that is actually weak methodological research design. Sumiyana (2007a) investigates trading and nontrading periods return only, or it doesn’t split intra-day return into short interval period. Although Sumiyana (2007a) found strongly the phenomenon of the Monday effect, but it could not capture the inside occurrence in the intra-trading periods. This study examines the day of the week and Monday effect phenomena in the Indonesian Stock Exchange using intraday data in every 30 minutes interval. Samples of the data are the firms listed in LQ45. Sequentially, samples are filtered to stocks that actively traded in the Indonesian Stock Exchange based on trading frequency in observation period from January to December 2006. This study uses regression analysis with multiple dummies constructed by separating trading periods in every day into 12 return periods. This research finds that day of the week phenomena occur consistently in Indonesian Stock Exchange, but the occurrence are not evenly in the same day. In addition, this study concludes that Monday effect exists partially and incidentally only.

Further Evidence on the “Monday Effect” in Workers' Compensation

ILR Review ◽  
2006 ◽  
Vol 59 (3) ◽  
pp. 438-450 ◽  
Author(s):  
Michele Campolieti ◽  
Douglas E. Hyatt
Keyword(s):  
Workers Compensation ◽  
Monday Effect

A twist on the Monday effect in stock prices

1989 ◽  
Vol 13 (4-5) ◽  
pp. 641-650 ◽  
Author(s):  
Jeffrey F. Jaffe ◽  
Randolph Westerfield ◽  
Christopher Ma
Keyword(s):  
Stock Prices ◽  
Monday Effect

Analysis of Monday Effect in Indian Stock Market

2011 ◽  
Vol 5 (4) ◽  
pp. 170-177 ◽  
Author(s):  
P. Nageswari ◽  
M. Selvam ◽  
J. Gayathri
Keyword(s):  
Stock Market ◽  
Monday Effect ◽  
Indian Stock Market

scholarly journals Bad Friday, Monday Effect and Political Issue: Application of ARCH-GARCH Model to Analyze Seasonal Pattern of Stock Return

2018 ◽  
Vol 7 (3.30) ◽  
pp. 38
Author(s):  
Maria Rio Rita ◽  
Sugeng Wahyudi ◽  
Harjum Muharam
Keyword(s):  
Stock Prices ◽  
Trading Volume ◽  
Stock Return ◽  
Seasonal Pattern ◽  
Garch Model ◽  
Statistical Characteristics ◽  
Political Issue ◽  
Political Issues ◽  
Monday Effect ◽  
The Garch Model

At the end of 2016, Indonesia was shaken by a demonstration of the election of the Governor of Jakarta Capital Special Region and political issues related to religious defamation. Does this condition have an impact on stock prices and returns? The aim of this study is to test the week day pattern in IDX using LQ-45 stocks during selected observation period of August 2016-January 2017. Then a GARCH model is used to investigate the presence of week day pattern in the stock market. Therefore, the GARCH model is able to describe observed statistical characteristics of many time series of financial assets return. The test results show that there is a difference in average stock return during the trading day. The lowest and the highest return are observed on Monday and Wednesday, respectively. Meanwhile, the average negative return on Friday is not proven to significantly drive the occurrence of Monday effect. Return on Monday is influenced by the frequency of trading, not by trading volume. Is there anything to do with the psychological aspect of investors solely in assessing risk acceptance to stocks? Research agenda related to this is very relevant to do in the future.  

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