<abstract xmlns="http://www.w3.org/1999/xhtml">
<p>The paper demonstrates the power of alternative data. Relying on the indicators obtained by mining online publicly available news articles, authors analyze their impact on Bitcoin returns. This research shows that in the first quarter of 2022 Bitcoin returns could be explained by the sentiment of information obtained from news published on online portals. However, we find negative relation between Bitcoin news sentiment and its returns. Such result can be explained as anomaly of researched period which is characterized by inception of global political crisis caused by the war in Eastern Europe and turmoil on crypto market. Our research also confirms that the news about Ethereum, Bitcoins’ investment substitute, affected Bitcoin's returns as well. On the other hand, the obtained results show that there is no relation between the lexical readability of the news (i.e., the clarity with which the text is written, measured by the fog index) and the returns on Bitcoin in the analyzed period. Collected evidences speak in favor of Bitcoin’s market inefficiency. In this paper we also demonstrate that returns forecasts based on online news are more accurate in comparison to those generated by ARMA-GARCH model, a conventional financial tool for predicting returns.</p>
</abstract>

The paper demonstrates the power of alternative data. Relying on the indicators obtained by mining online publicly available news articles, authors analyze their impact on Bitcoin returns. This research shows that in the first quarter of 2022 Bitcoin returns could be explained by the sentiment of information obtained from news published on online portals. However, we find negative relation between Bitcoin news sentiment and its returns. Such result can be explained as anomaly of researched period which is characterized by inception of global political crisis caused by the war in Eastern Europe and turmoil on crypto market. Our research also confirms that the news about Ethereum, Bitcoins’ investment substitute, affected Bitcoin's returns as well. On the other hand, the obtained results show that there is no relation between the lexical readability of the news (i.e., the clarity with which the text is written, measured by the fog index) and the returns on Bitcoin in the analyzed period. Collected evidences speak in favor of Bitcoin’s market inefficiency. In this paper we also demonstrate that returns forecasts based on online news are more accurate in comparison to those generated by ARMA-GARCH model, a conventional financial tool for predicting returns.

Are All Text News Just a Noise for Investors? Impact of Online Texts on Bitcoin Returns

Economic Themes

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The paper demonstrates the power of alternative data. Relying on the indicators obtained by mining online publicly available news articles, authors analyze...

Are All Text News Just a Noise for Investors? Impact of Online Texts on Bitcoin Returns

Online veröffentlicht: 14. Sept. 2023

Seitenbereich: 121 - 144

Eingereicht: 14. Nov. 2022

Akzeptiert: 20. Juni 2023

DOI: https://doi.org/10.2478/ethemes-2023-0007

Schlüsselwörter
Bitcoin, text mining, prediction, sentiment analysis, readability, returns, cryptocurrencies

© 2023 Aleksandar Damjanović et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Are All Text News Just a Noise for Investors? Impact of Online Texts on Bitcoin Returns

Online veröffentlicht: 14. Sept. 2023

Seitenbereich: 121 - 144

Eingereicht: 14. Nov. 2022

Akzeptiert: 20. Juni 2023

DOI: https://doi.org/10.2478/ethemes-2023-0007

SchlüsselwörterBitcoin, text mining, prediction, sentiment analysis, readability, returns, cryptocurrencies

© 2023 Aleksandar Damjanović et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
Bitcoin, text mining, prediction, sentiment analysis, readability, returns, cryptocurrencies