News-based sentiment and bitcoin volatility

In this work, I studied whether news media sentiments have an impact on Bitcoin volatility. In doing so, I applied three different range-based volatility estimates along with two different sentiments, namely psychological sentiments and financial sentiments, incorporating four various sentiment dictionaries. By analyzing 17,490 news coverages by 91 major English-language newspapers listed in the LexisNexis database from around the globe from January 2012 until August 2021, I found news media sentiments to play a significant role in Bitcoin volatility. Following the heterogeneous autoregressive model for realized volatility (HAR-RV)—which uses the heterogeneous market idea to create a simple additive volatility model at different scales to learn which factor is influencing the time series—along with news sentiments as explanatory variables, showed a better fit and higher forecasting accuracy. Furthermore, I also found that psychological sentiments have medium-term and financial sentiments have long-term effects on Bitcoin volatility. Moreover, the National Research Council Emotion Lexicon showed the main emotional drivers of Bitcoin volatility to be anticipation and trust. •In this work, I studied whether news media sentiments have an impact on Bitcoin volatility.•Analyzed 17,490 news items on Bitcoin by major English-language newspapers using two categories of sentiment dictionaries.•I extended the heterogeneous autoregressive model for realized volatility with psychological and financial sentiments.•I found psychological sentiments have medium-term and financial sentiments have long-term effects on Bitcoin volatility.•The emotion lexicon showed the main drivers of Bitcoin volatility to be anticipation and trust of the optimistic investors.