Abstract
<abstract> The impact on economic aspects of the COVID-19 is continuing under discussion. This study unveils effects of the pandemic on relationship dynamics between liquidity cost and stock market returns. Using the time series and machine learning techniques, the analysis is based on the Dow Jones Industrial Average (DJI) index. If the entire dataset was examined, the liquidity cost was found to be positive and significantly related to the DJI index returns. From the VAR estimation, the market returns were significantly explained by past values of the liquidity cost. The statistical Granger-causality was also observed between variables. If the relationship was analyzed during peak restrictions, the results were changed. The liquidity cost was observed to be negative and insignificantly related to the DJI index returns. The market returns were not associated with lags of the liquidity cost. In addition, the Granger-causality was not found between variables. If effects associated with easing restrictions were examined, the liquidity cost was found to be positive and significantly associated with returns on the DJI index. Meanwhile, the returns were more sensitive to the liquidity cost. However, the market returns were not explained by lags of the liquidity cost. The liquidity cost did not Granger-cause returns. The findings suggest that the liquidity cost must be priced in returns due to the pandemic-related uncertainty. </abstract>
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.