Effect of twitter investor engagement on cryptocurrencies during the COVID-19 pandemic

This study aims to examine whether the prices and returns of two cryptocurrencies, Dogecoin and Ethereum, are affected by Twitter engagement following the COVID-19 pandemic. We use the autoregressive integrated moving average with explanatory variables model to integrate the effects of investor attention and engagement on Dogecoin and Ethereum returns using data from December 31, 2020, to May 12, 2021. The results provide evidence supporting the hypothesis of a strong effect of Twitter investor engagement on Dogecoin returns; however, no potential impact is identified for Ethereum. These findings add to the growing evidence regarding the effect of social media on the cryptocurrency market and have useful implications for investors and corporate investment managers concerning investment decisions and trading strategies.     

An asymmetrical approach to understanding consumer characteristics in banking trust during the COVID-19 pandemic in Italy

This study aims to examine how perceived banking management, the perception of the context in which the banking system operates, and other consumer characteristics have interacted to create different recipes of banking trust during the second wave which began in October 2020 of the COVID-19 pandemic in Italy. To scrutinize this configurational reasoning, fuzzy set qualitative comparative analysis (fsQCA) was implemented. Using a sample of 1319 Italian respondents, this study suggests that high financial literacy combined with an optimistic attitude during the pandemic are key factors for achieving high banking trust. Furthermore, the results suggest that high perceived conspiracy is linked to low banking trust. These findings can help managers design differentiated strategies to attract depositors and invite the Italian government to double its efforts in restoring the people’s optimism.     

The role of economic structural factors in determining pandemic mortality rates: Evidence from the COVID-19 outbreak in France

Among the majority of research on individual factors leading to coronavirus mortality, age has been identified as a dominant factor. Health and other individual factors including gender, comorbidity, ethnicity and obesity have also been identified by other studies. In contrast, we examine the role of economic structural factors on COVID-19 mortality rates. Particularly, focusing on a densely populated region of France, we document evidence that higher economic “precariousness indicators” such as unemployment and poverty rates, lack of formal education and housing are important factors in determining COVID-19 mortality rates. Our study will help inform policy makers regarding the role of economic factors in managing pandemics.