Abstract:
The stock market is an essential component of any economy, and the
day-of-the-week effect has been a topic of interest for researchers for several
years. This study aims to examine the day-of-the-week effect in the Colombo
Stock Exchange, focusing on analyzing how the effect has changed during the
pandemic and economic crisis.
Design/methodology/approach: The study employed the ordinary least squares
(OLS) regression model, using a dummy variable for each day of the week. The
study utilized daily data from January 2006 to December 2022. The sample was
divided into subsamples of normal and crisis periods. The normal subsample
covers January 2006 to December 2019, while the crisis subsample covers
January 2020 to December 2022. Additionally, the crisis subsample was further
divided into a pandemic and economic crisis period, covering January 2020 to
December 2021 and January 2020 to December 2022, respectively.
Findings: The results indicate that the Monday and Tuesday effects are negative,
while the Thursday and Friday effects are positive. The Wednesday effect is not
statistically significant. During the pandemic, the negative effect of Monday and
Tuesday weakened, while the Thursday effect strengthened. During the economic
crisis, the negative effect of Tuesday and the positive effect of Friday weakened,
while the Thursday effect remained significant.
Practical implications: The findings of this study have practical implications for
investors and policymakers in the CSE. Investors may use this information to
adjust their investment strategies by taking advantage of the observed day-of-the week effect. Policymakers may use this information to design policies that
mitigate the negative impact of the day-of-the-week effect on the stock market.
Originality value: This study provides new insights on the day-of-the-week
effect in the Colombo Stock Exchange during the pandemic and economic crisis,
contributing to the existing literature and informing investors and policymakers.
Research limitations: The study employs a simple OLS regression model, and
more sophisticated models may yield different results.
