News-based sentiment and bitcoin volatility

【Author】 Sapkota, Niranjan

【Source】INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS

【影响因子】8.235

【Abstract】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.

【Keywords】Bitcoin; News sentiments; Natural language processing; Range-based volatility; HAR-RV (heterogeneous autoregressive realized volatility)

【发表时间】2022 JUL

【收录时间】2022-08-15

【文献类型】实证数据

【主题类别】

区块链治理-市场治理-市场分析