Short-term cryptocurrency price forecasting based on news headline analysis

IntroductionThis article presents a method for short-term cryptocurrency price forecasting utilizing news headlines.MethodsThe study analyzes the impact of news on asset prices within one hour of publication, employing machine learning-based classification with BERT and GPT models, as well as GloVe...

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Bibliographic Details
Main Author: Vladimir Dikovitsky
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Blockchain
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Online Access:https://www.frontiersin.org/articles/10.3389/fbloc.2025.1627769/full
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Summary:IntroductionThis article presents a method for short-term cryptocurrency price forecasting utilizing news headlines.MethodsThe study analyzes the impact of news on asset prices within one hour of publication, employing machine learning-based classification with BERT and GPT models, as well as GloVe vector representations.ResultsThe proposed cascade classifier model enhances prediction accuracy by initially assessing the strength of a news item and subsequently forecasting the direction of price movement. Experimental results demonstrate the effectiveness of the developed classification model.DiscussionThe model achieves an accuracy of 79% in predicting price movements, confirming the potential of leveraging news headlines to improve short-term forecasts in cryptocurrency markets.
ISSN:2624-7852