In this paper, we test the role of news in the predictability of return volatility of digital currency market during the COVID-19 pandemic We use hourly data for crypto currencies and daily data for the news indicator, thus, the GARCH MIDAS framework which allows for mixed data frequencies is adopted We validate the presupposition that fear-induced news triggered by the COVID-19 pandemic increases the return volatilities of the crypto currencies compared with the period before the pandemic We also establish that the predictive model that incorporates the news effects forecasts the return volatility better than the benchmark model, historical average
The return volatility of crypto currencies during the COVID-19 pandemic: Assessing the news effect