ORIGINAL RESEARCH article
Front. Blockchain
Sec. Financial Blockchain
Volume 8 - 2025 | doi: 10.3389/fbloc.2025.1627769
This article is part of the Research TopicBlockchain in the Age of AIView all articles
Short-Term Cryptocurrency Price Forecasting Based on News Headline Analysis
Provisionally accepted
- Putilov Institute for Informatics and Mathematical Modeling, Apatity, Russia
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The article presents a method for short-term cryptocurrency price forecasting using news headlines. Leveraging machine learning-based classification with BERT and GPT models, as well as GloVe vector representations, the study analyses the impact of news on asset prices within one hour of publication. The proposed cascade classifier model enhances prediction accuracy by first 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, achieving an accuracy of 79%.
Keywords: cryptocurrency, Short-term forecasting, machine learning, Global Vectors for word representation (GloVe), bidirectional encoder representations from transformers (BERT), Generative Pre-trained Transformer (GPT), Bitcoin (BTC)
Received: 13 May 2025; Accepted: 14 Jul 2025.
Copyright: © 2025 Dikovitsky. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Vladimir Dikovitsky, Putilov Institute for Informatics and Mathematical Modeling, Apatity, Russia
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