Economic sentiment and the cryptocurrency market in the post-COVID-19 era

This paper analyzes the interactions, dependence and dynamic network connectedness among economic based-news sentiment index (ESI) and the top eight crypto-currencies with particular attention on the postCOVID-19 pandemic era. We explore these features by applying novel econometric frameworks such as wavelets coherence, cross quantilogram, and DCC-GARCH-based connectedness techniques on a dataset that covers both the first and second waves of the COVID-19 outbreak. First, results from the wavelets approach show convincing evidence of low covariances between ESI and both returns and volume while results of correlations highlight the potential diversification opportunities of some crypto-currencies, especially during bullish market condition since the COVID-19 pandemic. Results from the directional predictability show that across all market conditions, there are strong evidence that ESI can predict the price return of stable-coins (Tether and USD) compared to the price return of Bitcoin, Ethereum and Dogicoin that ESI predicts only under bullish market condition. For changes in volume, we find that the predictive power of ESI is more pronounced and heterogeneous, cutting across different quantiles of the different classes of cryptocurrencies, especially Bitcoin (BTC) and Dogicoin (DOG). The analysis of dynamic connectedness show that the level of connectedness among ESI and both price return and changes in volume of trade of the chosen cryptocurrencies increased sharply during the peak of the COVID-19 pandemic. In both cases, Tether and ESI are the main destination of volatility shocks Ripple and Bitcoin are the dominant sources of shocks. We document the importance of economic sentiment for investors in the management of their cryptocurrency assets during periods of financial downturns as witnessed since the COVID-19 pandemic.