Publikace: How well do investor sentiment and ensemble learning predict Bitcoin prices?
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Hájek, Petr
Hikkerova, Lubica
Sahut, Jean -Michel
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Elsevier Science BV
Abstrakt
Investor sentiment is widely recognized as the major determinant of cryptocurrency prices. Although earlier research has revealed the influence of investor sentiment on cryptocurrency prices, it has not yet generated cohesive empirical findings on an important question: How effective is investor sentiment in predicting cryptocurrency prices? To address this gap, we propose a novel prediction model based on the Bitcoin Misery Index, using trading data for cryptocurrency rather than judgments from individuals who are not Bitcoin investors, as well as bagged support vector regression (BSVR), to forecast Bitcoin prices. The empirical analysis is performed for the period between March 2018 and May 2022. The results of this study suggest that the addition of the sentiment index enhances the predictive performance of BSVR signifi-cantly. Moreover, the proposed prediction system, enhanced with an automatic feature selection component, outperforms state-of-the-art methods for predicting cryptocurrency for the next 30 days.
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Klíčová slova
Bitcoin, Price, Cryptocurrency, Sentiment, Prediction, Feature selection, Support vector regression, Bitcoin, Cena, Kryptoměna, Sentiment, Predikce, Výběr prvků, Regrese podpůrných vektorů