COVID-19 and liquidity risk, exploring the relationship dynamics between liquidity cost and stock market returns

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>