Panel regression method to analyse the stock market returns due to Covid-19 / Nur Mardziah Aziz Jaafar and Noraini Noordin

• Main Authors: Aziz Jaafar, Nur Mardziah, Noordin, Noraini
• Format: Article
• Language: English
• Published: Universiti Teknologi MARA Cawangan Pulau Pinang 2021
• Subjects: Regression. Correlation; Multivariate analysis. Cluster analysis. Longitudinal method; Regression analysis. Correlation analysis. Spatial analysis (Statistics)
• Online Access: https://ir.uitm.edu.my/id/eprint/6067/1/6067.pdf; https://ir.uitm.edu.my/id/eprint/6067/; https://uppp.uitm.edu.my/
• Institution: Universiti Teknologi Mara

Malaysia's earliest COVID-19 patients, reported on January 25, 2020, were travellers from China to Malaysia through Singapore. The detected confirmed cases, which were associated with religious gatherings were scarce in number before March 2020. The Prime Minister of Malaysia called for the 'Movement Control Order' beginning March 18, 2020. This study aimed to determine the aftereffects of COVID-19 pandemic outbreaks on stock markets by measuring the correlation between market returns and daily growth of total new and death cases of COVID-19. Panel regression methods, namely pooled ordinary least square and fixed-effect methods were used in this study where the dependent variable is stock market returns and independent variables were i) daily growth new death cases COVID-19 ii) natural algorithm market capitalisation iii) Brent Crude Oil Price from January 2, 2020, until March 31, 2020. Findings showed that during MCO for every one confirmed case increase, the stock returns decreased to -0.172 and for every one confirmed death increase, the stock returns decreased to -0.066. Thus, the stock market returns reported significant negatives to both total new cases and death cases' daily growth. The estimated market returns were also negatively influenced by new cases of and deaths due to COVID-19. Besides helping investors make the right decision during a pandemic crisis, the findings can be expanded in future research, by increasing the data frame, independent variables and finding the impact of more specific indices of the sector.