Day Of Week Effect Research Articles

An Investigation of the Effect of Covid-19 on Efficient Market Hypothesis (EMH) Anomalies: Econometric Approach

The research aims to analyze the influence of the Covid-19 crisis on changes in the daily return pattern of the LQ45 Index, and to see whether the daily return pattern of the LQ45 Index is efficient as argued by the EMH (Efficient Market Hypothesis). The observation period was before and during Covid 19. Data analysis used an econometric approach to test any EMH anomalies, as well as running the ARCH-GARCH model due to the use of dummy variables. The analysis results show that Covid-19 has no effect on the daily return pattern of LQ45, The Week Four effect is proven, but The Day of Week effect, Monday effect and Weekend effect are not found. Another finding that the trading day anomaly testing model is sensitive to the error term distribution, also suggests that good news or bad news in volatility not only depends on the asymmetric model but also the choice of error term distribution.

Day of Week Effect on Financial Market: Evidence in Vietnam during Normal Period and COVID-19 Pandemic

The article is focused on examining the existence of the day-of-the-week (DOW) effect on the Vietnamese stock market. This study uses the daily series of closed market indexes data from 2014 to 2021 and extends to a deep-dive review of the outbreak period of the COVID-19 pandemic. Furthermore, the regression model with dummy variables and parametric and non-parametric methods are employed to identify the existence of the DOW effect on stock market returns and volatility. The empirical results obtained from the above models have demonstrated that the day-of-the-week effect impacts stock returns shown in three out of four indices, especially on Mondays and Fridays. At the same time, no statistical evidence supports the presence of any significant daily patterns for either the COVID-19 outbreak phase or in the HNX30. Particularly, the highest return occurs on Monday, and the lowest volatility usually appears on Friday in all three HOSE Indexes. This study contributed further evidence for not only the presence of the day-of-the-effect patterns on the Vietnamese stock market but also path the ways to analyze the stock returns and variance of financial assets during the COVID-19 epidemic.

Mortality and readmission differences associated with after-hours hospital admission: A population-based cohort study in Queensland Australia.

Policy makers and health system managers are seeking evidence on the risks involved for patients associated with after-hours care. This study of approximately 1 million patients who were admitted to the 25 largest public hospitals in Queensland Australia sought to quantify mortality and readmission differences associated with after-hours hospital admission. Logistic regression was used to assess whether there were any differences in mortality and readmissions based on the time inpatients were admitted to hospital (after-hours versus within hours). Patient and staffing data, including the variation in physician and nursing staff numbers and seniority were included as explicit predictors within patient outcome models. After adjusting for case-mix confounding, statistically significant higher mortality was observed for patients admitted on weekends via the hospital's emergency department compared to within hours. This finding of elevated mortality risk after-hours held true in sensitivity analyses which explored broader definitions of after-hours care: an "Extended" definition comprising a weekend extending into Friday night and early Monday morning; and a "Twilight" definition comprising weekends and weeknights.There were no significant differences in 30-day readmissions for emergency or elective patients admitted after-hours. Increased mortality risks for elective patients was found to be an evening/weekend effect rather than a day-of-week effect. Workforce metrics that played a role in observed outcome differences within hours/after-hours were more a time of day rather than day of week effect, i.e. staffing impacts differ more between day and night than the weekday versus weekend. Patients admitted after-hours have significantly higher mortality than patients admitted within hours. This study confirms an association between mortality differences and the time patients were admitted to hospital, and identifies characteristics of patients and staffing that affect those outcomes.

The day-of-week (DOW) effect on liberalism-conservatism: Evidence from a large-scale online survey in China.

Past research has shown that psychological states tend to fluctuate across the days of a week, which is referred to as the day-of-week (DOW) effect. This study investigated the DOW effect on liberalism-conservatism among Chinese people by testing two competing hypotheses. According to the cognitive states hypothesis, it was predicted that liberalism would be high on Mondays but gradually decrease to Fridays due to the depletion of cognitive resources over the weekdays. In contrast, the affective states hypothesis predicted the opposite, considering the more positive affect brought by the approaching weekends. Both hypotheses predicted the level of liberalism would peak at weekends. Data (n = 171,830) were collected via an online questionnaire, the Chinese Political Compass (CPC) survey, which includes 50 items to measure people' liberalism-conservatism in three domains (i.e., political, economic, and social). The results showed the level of liberalism decreased gradually from Mondays until Wednesdays, rebounded from Wednesdays to Fridays, and peaked at weekends. The V-shaped pattern suggested that the DOW fluctuation in liberalism-conservatism could derive from the synergy of both cognitive and affective processes, instead of either one alone. The findings have important implications for practice and policy-making, including the recent pilot scheme of 4-day workweek.

Day of week effect: an empirical study for Indian Stock Markets

Day of week effect: an empirical study for Indian Stock Markets

Stock Market Reactions before and during the COVID-19 Pandemic: Evidence from Indonesia

Research on market reactions to the phenomenon of The Day of Week Effect, Week Four Effect, Rogalsky Effect, and January Effect in several world capital markets finds different results. This study aims to determine the reaction of the Indonesian capital market before and during the Covid-19 pandemic which is associated with the phenomenon of the day of the week effect, week four effect, Rogalski effect, and January effect. By conducting a study of previous theoretical research, after that a survey was carried out to obtain data phenomena, classifying the closing daily JCI before and during the Covid-19 pandemic, calculating actual returns, calculating expected returns and abnormal returns, then classifying return or abnormal return data into 4 phenomena namely The Day of The Week Effect, Week Four Effect, Rogalsky Effect, and January Effect. For The Day of The Week Effect, return data is classified into Monday and non-Monday returns. For Week Four Effect, return data is classified into Monday week 1, 2, 3, and Monday week 4.5. For the Rogalsky Effect, returned data are classified into Monday, April, and Monday non-April. For the January Effect, returned data are classified into January 1st week and January 2nd week. Then do the Data Normality Test and Hypothesis Testing. This study produces empirical evidence that there is no phenomenon of the day of the week, week four effect, Rogalski effect, and January effect before and during the Covid-19 pandemic outbreak on the Indonesia Stock Exchange.

Day of the Week Effect in Cryptocurrencies' Returns and Volatility

Calendar anomalies as the seasonal tendencies in stock returns are the signal of irregular behaviour of stock markets. These anomalies have been comprehensively studied in many matured as well as emerging stock markets. But there is lack of exploration of calendar anomalies in the cryptocurrency market. So, the present treatise is an attempt to fill this lacuna by studying day of the week effect on cryptocurrencies' returns and volatility. This study is based on the prices of eight cryptocurrencies (viz. Bitcoin, EOS, Ethereum, Bitcoin Cash, Litecoin, Tether, XRP and Stellar) for a period starting from July 2017 and up to March 2020. The series of daily and day-wise returns were initially studied for stationarity using Ng-Perron tests and augmented Dickey–Fuller test. The results from these tests confirmed that the cryptocurrencies' return series are stationary. The day of the week effect on cryptocurrencies returns was studied by introducing the dummies for each day of the week in the ordinary least square regression equation. The residuals from the ordinary least square regression equation were tested for ARCH effect using Engle's ARCH test. The results from the test confirmed the presence of ARCH effect in all series. The GARCH (1,1) model and PARCH model were further applied to account for ARCH effect and these models confirmed the presence of the day of the week effect in all the cryptocurrencies' returns and volatility except for day of week effect in Bitcoin and Tether returns. So, the significant day of the week effect was present in all cryptocurrencies' returns and volatility but the significant day of the week effect was absent in Bitcoin's returns and Tether's returns. These findings of significant day effect may help the existing and potential investors in taking investment decision in contemporary scenario of no ban in cryptocurrency market in India.

The effect of cold and heat waves on mortality in Urmia a cold region in the North West of Iran.

Few studies have investigated the different extreme temperature effects (heat-cold) of one geographical location at the same time in Iran. This study was conducted to assess the impact of heat and cold waves on mortality in Urmia city, which has a cold and mountainous climate. Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of heat (HW) and cold waves (CW) on mortality in subgroups, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. The heat/cold effect was divided into two general categories A-main effect (the effect caused by temperature), B-added effect (the effect caused by persistence of extreme temperature). Results show that there was no relation between HW and respiratory and cardiovascular death, but in main effects, HW(H1) significantly increased, the risk of Non-Accidental Death (NAD) in lag 0 (Cumulative Excess Risk (CER) NAD=31(CI; 4-65)). Also in added effects, HW had a significant effect on NAD (CER H1; NAD; lag;0-2=31(CI; 5, 51), CER H2; NAD; lag;0-2=26(CI; 6, 48)). There was no relation between CW and respiratory death and cardiovascular death, but in added effects, CW(C1) significantly decreased, the risk of non-accidental death in initial lags (CER C1; NAD; lag;0-2=-19 (CI; -35, -2)). It seems that high temperatures and heat waves increase the risk of non-accidental mortality in northwest of Iran.

Trading Procedures, Evolving Settlement Systems and The Day of Week Effect in the U. K. and French Stock Markets

Trading Procedures, Evolving Settlement Systems and The Day of Week Effect in the U. K. and French Stock Markets

Day of Week Effect in Indian Stock Markets

The present study examines the day of week effect in Indian stock markets. The stock returns data of 17 indices have been collected from BSE (Bombay Stock Exchange) and NSE (National Stock Exchange) for the sample period from April 2009 to June 2018. Descriptive statistics explains the characteristics of returns distributions of trading days of week. Using regression with dummy variables the results indicate significant positive returns on Monday for the all the selected indices under the sample period. It is concluded that the day of week effect is present in the Indian stock markets and markets are inefficient.

Diurnal temperature range and mortality in Tabriz (the northwest of Iran)

Recently there has been a lot of interest in global warming and temperature variation's effect on health. This study evaluates the impact of Diurnal Temperature Range (DTR) on mortality in Tabriz, northwest of Iran. Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of DTR on cause, age and gender specific mortality, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. As the effect of DTR may vary between the hot season (from May to October) and cold season (from November to April of the next year), we conducted analyses separately for these two seasons. In high DTR values (all percentiles), the Cumulative Relative Risk (CRR) of Non-Accidental Death, Respiratory Death and Cardiovascular Death increased in the cold season. In full year and high DTR value (percentile 90), the CRR of respiratory deaths increased as well (CRR, Lag 0-6:1.32(1.006, 1.75). Although there was no clear significant effect in low DTR values, high values of DTR increase the risk of mortality in the cold season, in Tabriz, Iran.

Diurnal Temperature Range and Mortality in Tabriz (the Northwest of Iran)

Introduction: Recently there has been a lot of interest in global warming and temperature variation's effect on health. This study evaluates the impact of Diurnal Temperature Range (DTR) on mortality in Tabriz, northwest of Iran.Methods: Distributed Lag Non-linear Models combined with a quasi-Poisson regression were used to assess the impact of DTR on cause, age and gender specific mortality, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. As the effect of DTR may vary between the hot season (from May to October) and cold season (from November to April of the next year), we conducted analyses separately for these two seasons.Results: In high DTR values (all percentiles), the Cumulative Relative Risk (CRR) of Non-Accidental Death, Respiratory Death and Cardiovascular Death increased in the cold season. In all seasons and high DTR value (percentile 90), the CRR (lag 0-6) of respiratory deaths increased as well.Conclusion: Although there was no clear significant effect in low DTR values, high values of DTR increase the risk of mortality in the cold season, in Tabriz, Iran.

Diurnal temperature range and mortality in Urmia, the Northwest of Iran

Diurnal Temperature Range (DTR) is a meteorological index which represents temperature variation within a day. This study assesses the impact of high and low values of DTR on mortality. Distributed Lag Non-linear Models combined with a quasi-Poisson regression model was used to assess the impact of DTR on cause, age and gender specific mortality, controlled for potential confounders such as long-term trend of daily mortality, day of week effect, holidays, mean temperature, humidity, wind speed and air pollutants. As the effect of DTR may vary between the hot season (from May to October) and cold season (from November to April of the next year), we conducted analyses separately for these two seasons. In high DTR values (all percentiles), the Cumulative Relative Risk (CRR) of Non-Accidental Death, Respiratory Death and Cardiovascular Death increased in the full year and hot season, and especially in lag (0−6) of the hot season. In the cold season and high DTR values (all percentiles), the CRR of Non-Accidental Death and Cardiovascular Death decreased, but the CRR of Respiratory Death increased. Although there was no clear significant effect in low DTR values. High values of DTR increase the risk of mortality, especially in the heat season, in Urmia, Iran.

Measuring Physical Activity with Hip Accelerometry among U.S. Older Adults: How Many Days Are Enough?

IntroductionAccelerometers are increasingly used in research. Four to 7 days of monitoring is preferred to estimate average activity but may be burdensome for older adults. We aimed to investigate: 1) 7-day accelerometry protocol adherence, 2) demographic predictors of adherence, 3) day of the week effect, and 4) average activity calculated from 7 versus fewer days among older adults.MethodsWe used the 2003–2006 older adult hip accelerometry data from the National Health and Nutrition Examination Survey (NHANES) sample. We determined proportions with 1–7 valid (10–20 hours) wear days and identified wear day correlates using ordinal logistic regression. We determined the day of week effect on 5 accelerometry measures (counts per minute, CPM; % sedentary behavior; % light-lifestyle activity; % moderate-vigorous activity, MVPA; total activity counts) using multivariate linear regression and compared averages estimated over 2 or 3 versus 7 days using correlations, linear regression, and Bland-Altman plots.ResultsAmong 2,208 participants aged 65+, 85% of participants had ≥2 and 44% had 7 valid wear days. Increasing age (p = 0.01) and non-white race (p < 0.001) were associated with fewer days. Daily CPM, % MVPA, and total daily activity counts were similar Monday through Saturday, but significantly lower on Sundays (p < 0.001). Daily % sedentary behavior and % light-lifestyle activity were significantly different on Saturdays (p = 0.04–0.045) and Sundays (p < 0.001) compared to weekdays. Among participants with 7 valid days, 2 or 3 day averages were highly correlated with 7 day averages for all 5 accelerometry measures (2 versus 7 days: r = 0.90–0.93, 3 versus 7 days: r = 0.94–0.96).ConclusionsProtocols of 2–3 days, adjusting for Sundays (average CPM, % moderate-vigorous activity, and average total daily activity counts) or weekends (% sedentary behavior and % light-lifestyle activity), give reliable estimates of older adult activity.

Random Walk, Capital Market Efficiency and Predicting Stock Return: A Case Study of Karachi Stock Exchange

This research aims to investigate the presence of weak form of efficiency and stock return predictability in Pakistani Equity Market. The daily return on stock here is used to verify the weak form of market efficiency in Karachi Stock Exchange (KSE). For this purpose a data set from August 1998 to August 2013 was obtained and applied ADF, PP test, Run test, Autocorrelation and OLS model. These entire tests are applied to check the hypothesis of Randomness in stock returns. The result revealed that return distribution of KSE is not normally distributed and short term predictability exists in KSE. There is day of week effect. The study has important implications for investors and regulatory authority. This study is limited to the sample element and period. Future study may be conducted by taking Tuesday as a first day of week followed by Monday holiday to testify daily predictability in KSE.

ANOMALI PASAR PADA RETURN SAHAM LQ 45 DI BURSA EFEK INDONESIA: FENOMENA THE DAY OF WEEK EFFECT, WEEK FOUR EFFECT, ROGALSKY EFFECT, DAN JANUARY EFFECT

Market anomalies appears on all forms of efficient markets, both weak form, semi-strong and strongform. But plenty of evidence to link the anomaly with semi-strong form efficient market exploited togenerate abnormal returns. Market anomalies that is often discussed is the Day of the Week Effect,January Effect, Week Four Effect and other market anomalies. Empirical research is intended todetermine whether there is the phenomenon of the day of the week effect, week four effect, the effectrogalsky and January effect on LQ 45 stocks in the Indonesia Stock Exchange year period 2014-2015.Based on the analysis of data, shows that there is the phenomenon of the day of week effect on thecompany LQ-45 in Indonesia Stock Exchange 2014-2015 period, there is the phenomenon of weekfour effect on the LQ-45 in Indonesia Stock Exchange 2014-2015 period, there are phenomenonRogalski Effect on the LQ-45 in Indonesia Stock Exchange 2014-2015 period and there is no Januaryeffect phenomenon in the LQ-45 in Indonesia Stock Exchange 2014-2015 period.Keywords: the day of the week effect, week four effect, rogalsky effect and january effect

A multicentre cohort study assessing day of week effect and outcome from emergency appendicectomy

BackgroundThere is evidence to suggest that patients undergoing treatment at weekends may be subject to different care processes and outcomes compared with weekdays. This study aimed to determine whether clinical...

Empirical Investigation of Efficient Market Hypothesis in Vietnam Stock Market

This research examines the efficiency of Vietnam stock market at weak form level by using daily and weekly observations of market index and eight selected stocks of real estate and seafood processing companies for the period from 2007 to 2010. Parametric and nonparametric tests including auto correlation test, run test, variance ratio test, regression test, ARCH, GARCH (1,1) have been employed in this study. The results from all tests fail to support the hypothesis of weak form efficiency with the daily data, even in case, returns are adjusted for thin trading. However, with weekly data, the results obtained from run test and autocorrelation test do not completely reject the hypothesis of weak form efficiency while the result given from variance ratio test fully provides the evidence against a random walk. Besides that, the findings of no clear calendar effect by examining the day of week effect also give the evidence that even if the anomalies existed in the sample period, the practitioners who implement strategies to take advantage of anomalous behavior can cause the anomalies to disappear.

What's unusual in online disease outbreak news?

BackgroundAccurate and timely detection of public health events of international concern is necessary to help support risk assessment and response and save lives. Novel event-based methods that use the World Wide Web as a signal source offer potential to extend health surveillance into areas where traditional indicator networks are lacking. In this paper we address the issue of systematically evaluating online health news to support automatic alerting using daily disease-country counts text mined from real world data using BioCaster. For 18 data sets produced by BioCaster, we compare 5 aberration detection algorithms (EARS C2, C3, W2, F-statistic and EWMA) for performance against expert moderated ProMED-mail postings.ResultsWe report sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), mean alerts/100 days and F1, at 95% confidence interval (CI) for 287 ProMED-mail postings on 18 outbreaks across 14 countries over a 366 day period. Results indicate that W2 had the best F1 with a slight benefit for day of week effect over C2. In drill down analysis we indicate issues arising from the granular choice of country-level modeling, sudden drops in reporting due to day of week effects and reporting bias. Automatic alerting has been implemented in BioCaster available from http://born.nii.ac.jp.ConclusionsOnline health news alerts have the potential to enhance manual analytical methods by increasing throughput, timeliness and detection rates. Systematic evaluation of health news aberrations is necessary to push forward our understanding of the complex relationship between news report volumes and case numbers and to select the best performing features and algorithms.

Does the day-of-the-week effect on volatility improve the volatility forecasts?

This study tests the presence of the day-of-the-week effect on stock market volatility of six European stock markets. Using a GARCH or GARCH-GJR specifications for the variance equation, we find that the day of week effect is present in volatility equation. Finally, we test whether the statistically significant in-sample findings regarding seasonality in volatility lead to better out-of-sample forecasts of volatility.