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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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2025-07-01
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| 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. |
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| ISSN: | 2624-7852 |