Independent thesis Advanced level (degree of Master of Fine Arts (Two Years)), 40 credits / 60 HE credits
Background: This thesis investigates the influence of vaccination programs in the rate of return by covering the most important stock market index OMX Stockholm 30, Which includes 30 firms for the period between 6 January 2020 to 30, December 2022. Based on previous studies, in present market conditions, the outbreak of COVID-19 has impacted the financial market around the world. The decline in stock prices during the pandemic created uncertainty among investors, exacerbated by the significant increase in infections and deaths, which destabilized financial markets. Therefore, the study of the causal relationship between the number of vaccinated people and the Swedish market index has become appropriate since COVID-19 has a huge impact on returns, therefore the vaccination program becomes a hope that restores life to what it was before the outbreak of the deadly epidemic. Hence, it is essential to explore the causal relationship between the number of vaccinated individuals and the Swedish market index. Given the substantial impact of COVID-19 on returns, vaccination programs offer hope for a return to pre-pandemic conditions. Therefore, this study aims to provide evidence of Granger causality regression across different time periods to elucidate the relationship between OMXS30 and the number of vaccinated people. This research is valuable because the Granger causality hypothesis will help determine whether the increase in the number of vaccinated individuals can be employed to forecast the Swedish market index.
Purpose: This study aims to analyze the relationship between OMXS30, the GDP of the Euro area, and the number of vaccinated people over 2 years from 2020 to 2021. During this period, segments of time associated with financial crises have been isolated from the dataset and analyzed separately to determine if a consistent relationship exists among the variables. The primary objective is to establish the Granger causality relationship between OMXS30 and the number of vaccinated people, and separately, between the GDP of the Euro area and the number of vaccinated people. This analysis aims to discern whether one variable leads or influences the other. Identifying the Granger causality correlation is vital for understanding the patterns of correlation within empirical datasets and assessing the nature and strength of the Granger causal relationship between the selected variables.
Method:
We used a variety of statistical methods in our thesis to thoroughly assess our data. To comprehend the connections between various variables, we first built a correlation matrix as well as descriptive statistics. We used the Augmented Dickey-Fuller (ADF) test to determine whether time series data were stationary. To investigate the links between factors that predict outcomes required the use of Granger Causality tests. We used the Toda, Yamamoto, Dolado, and Lütkepohl Granger Causality (TYDL-GC) test, which is renowned for its precision in determining causal relationships. And in the final step of our analysis, we employed a panel data model.
Conclusion:
The findings in this study showed that there is a relationship between the OMXS30 and DGTVC for the first, second, and fourth periods of the selected period that the vaccination program led to an increase in mean stock prices meanwhile for the third period there is no effect of the COVID vaccine on OMXS30, during the COVID-19 vaccination program. The study also finds that the relationship between DR and DGTCC confirmed that infection cases and death cases had a strong negative effect on stock returns and higher volatility. For The third variable that has been chosen GDP of the Euro area shows there is no link between GDP and DGTVC.
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2022-08-25, Jönköping University, Gjuterigatan 5, 553 18 Jönköping, Jönköping, 10:24 (English)