News-based sentiment and bitcoin volatility

Niranjan Sapkota

International Review of Financial Analysis, 2022, vol. 82, issue C

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) (search for similar items in EconPapers)
JEL-codes: G11 G14 G17 G41 (search for similar items in EconPapers)
Date: 2022
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Citations: View citations in EconPapers (23)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:82:y:2022:i:c:s1057521922001454

DOI: 10.1016/j.irfa.2022.102183

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