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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Main Author: Vladimir Dikovitsky
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Blockchain
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fbloc.2025.1627769/full
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author Vladimir Dikovitsky
author_facet Vladimir Dikovitsky
author_sort Vladimir Dikovitsky
collection DOAJ
description 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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spelling doaj-art-401b7563d2e94b139011c8e090dce4282025-08-20T02:46:17ZengFrontiers Media S.A.Frontiers in Blockchain2624-78522025-07-01810.3389/fbloc.2025.16277691627769Short-term cryptocurrency price forecasting based on news headline analysisVladimir DikovitskyIntroductionThis 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.https://www.frontiersin.org/articles/10.3389/fbloc.2025.1627769/fullcryptocurrencyshort-term forecastingmachine learningGlobal Vectors for word representation (GloVe)bidirectional encoder representations from transformers (BERT)Generative Pre-trained Transformer (GPT)
spellingShingle Vladimir Dikovitsky
Short-term cryptocurrency price forecasting based on news headline analysis
Frontiers in Blockchain
cryptocurrency
short-term forecasting
machine learning
Global Vectors for word representation (GloVe)
bidirectional encoder representations from transformers (BERT)
Generative Pre-trained Transformer (GPT)
title Short-term cryptocurrency price forecasting based on news headline analysis
title_full Short-term cryptocurrency price forecasting based on news headline analysis
title_fullStr Short-term cryptocurrency price forecasting based on news headline analysis
title_full_unstemmed Short-term cryptocurrency price forecasting based on news headline analysis
title_short Short-term cryptocurrency price forecasting based on news headline analysis
title_sort short term cryptocurrency price forecasting based on news headline analysis
topic cryptocurrency
short-term forecasting
machine learning
Global Vectors for word representation (GloVe)
bidirectional encoder representations from transformers (BERT)
Generative Pre-trained Transformer (GPT)
url https://www.frontiersin.org/articles/10.3389/fbloc.2025.1627769/full
work_keys_str_mv AT vladimirdikovitsky shorttermcryptocurrencypriceforecastingbasedonnewsheadlineanalysis