Cover Image

The Impact of News Sentiment on the Bitcoin Price via Machine Learning and Deep Learning‐Based NLP Models

Fuente: Wiley Open Access

Saved in:

Bibliographic Details
Main Authors:	Yunus Emre Gür, Emre Ünal
Format:	Artículo Open Access
Published:	Wiley 2025
Subjects:	Journal of Forecasting
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Learning and Machine Learning Insights Into the Global Economic Drivers of the Bitcoin Price
by: Nezir Köse, et al.
Published: (2025)

A Hybrid Deep Learning Model for Coal Index Forecasting Based on Sentiment Analysis and Decomposition–Reconstruction Methods
by: Yi Xiao, et al.
Published: (2025)

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices
by: Talha Omer, et al.
Published: (2026)

Forecasting Disaggregated Producer Prices: A Fusion of Machine Learning and Econometric Techniques
by: Soňa Benecká
Published: (2026)

On Capturing Multi‐Scale Market Dynamics for High‐Frequency Stock Price Forecasting Using a Hybrid Attention‐Based Deep Learning Model
by: Runze Jiang, et al.
Published: (2026)

Forecasting Natural Gas Futures Prices Using Hybrid Machine Learning Models During Turbulent Market Conditions: The Case of the Russian–Ukraine Crisis
by: Pavan Kumar Nagula, et al.
Published: (2025)

A Comparative Forecasting Framework for Turkey–Germany Trade: Evidence From Time Series and Artificial Neural Networks Models
by: Seyma Nur Unal, et al.
Published: (2025)

Correction to “Smart Forecasting of Carbon Prices Using Machine Learning and Neural Networks: When ARIMA Meets XGBoost and LSTM”
Published: (2026)

Image‐Based Deep Learning Models for Stock Predictions: Combining Line, Candlestick, and Bar Charts
by: Wei‐Chao Lin, et al.
Published: (2026)

Forecasting European Union Electronic Trading Systems Phase 4 Spot Prices Using Data‐Driven Hybrid Deep Learning Models: Integrating Energy and Market Activity as Controls
by: Noman Arshed, et al.
Published: (2026)

Predicting Equity Premium: A New Momentum Indicator Selection Strategy With Machine Learning
by: Yong Qu, et al.
Published: (2024)

When Are Statistical Forecast Gains Economically Relevant? Evidence From Bitcoin Returns
by: Rehan Arain, et al.
Published: (2025)

Forecasting Bitcoin returns: Econometric time series analysis vs. machine learning
by: Theo Berger, et al.
Published: (2024)

Stock Return Prediction Based on a Functional Capital Asset Pricing Model
by: Ufuk Beyaztas, et al.
Published: (2025)

Forecasting With Machine Learning Shadow‐Rate VARs
by: Michael Grammatikopoulos
Published: (2025)

Innovative Techniques to Predict Churn in the French Insurance Industry: Integration of Machine Learning With the Grabit Model
by: Christophe Schalck, et al.
Published: (2025)

Fire Prediction and Risk Identification With Interpretable Machine Learning
by: Shan Dai, et al.
Published: (2025)

Spread Option Pricing Method Based on Nonparametric Predictive Inference Copula
by: Ting He
Published: (2025)

A Deep Learning Test of the Martingale Difference Hypothesis
by: João A. Bastos
Published: (2025)

Using DSGE and Machine Learning to Forecast Public Debt for France
by: Emmanouil Sofianos, et al.
Published: (2026)

Forecasting the Volatility of US Oil and Gas Firms With Machine Learning
by: Juan D. Díaz, et al.
Published: (2024)

Explainable Soybean Futures Price Forecasting Based on Multi‐Source Feature Fusion
by: Binrong Wu, et al.
Published: (2024)

A New Multivariate Decomposition–Ensemble Approach With Multisource Heterogeneous Data for Crude Oil Price Forecasting
by: Zhengling Zhao, et al.
Published: (2026)

Using a Wage–Price‐Setting Model to Forecast US Inflation
by: Nguyen Duc Do
Published: (2024)

Seasonal Decomposition‐Enhanced Deep Learning Architecture for Probabilistic Forecasting
by: Keyan Jin, et al.
Published: (2025)

Machine Learning Forecasts of Tail‐Risk Spillovers in Carbon and Energy Markets
by: Shengnan Liu, et al.
Published: (2026)

Nowcasting World Trade With Machine Learning: A Three‐Step Approach
by: Menzie Chinn, et al.
Published: (2026)

Adaptive Model Integration for Stock Price Forecasting With CNN‐ATTN‐BiLSTM
by: Yi Xiao, et al.
Published: (2026)

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches
by: Björn Schulte‐Tillmann, et al.
Published: (2026)

Deciphering Long‐Term Economic Growth: An Exploration With Leading Machine Learning Techniques
by: Zin Mar Oo, et al.
Published: (2025)

Forecasting Corporate Default Risk Across Multiple Horizons With Interpretable Machine Learning
by: Qingli Dong, et al.
Published: (2026)

Forecasting and Pricing in the Carbon Credits Market
by: Yiyang Chen, et al.
Published: (2026)

Predicting EU Emissions Allowance Prices Using Macroeconomic Indicators and Hybrid AI Models
by: Saptarshi Ganguly, et al.
Published: (2026)

A Novel Interpretable Deep Learning‐Based Wind Speed and Power Generation Forecasting Using Multiscale Attention and Post Hoc Feature Importance Mechanism
by: Haoyu Fang, et al.
Published: (2025)

Forecasting House Prices: The Role of Market Interconnectedness
by: Zac Chen, et al.
Published: (2026)

Deep Dive Into Churn Prediction in the Banking Sector: The Challenge of Hyperparameter Selection and Imbalanced Learning
by: Vasileios Gkonis, et al.
Published: (2024)

On the Optimal Selection of Time‐Lag Embedding Dimension for Deep Learning Approaches in Financial Forecasting With Big Data
by: Mohammadreza Ghadimpour, et al.
Published: (2025)

Measuring the Default Risk of Small Business Loans: Improved Credit Risk Prediction Using Deep Learning
by: Yiannis Dendramis, et al.
Published: (2025)

A Multiscale Transformer Model for Long Time Series Forecasting Based on Discrete Wavelet Transform and Residual Learning Modules
by: Menghan Li, et al.
Published: (2025)

Can Attention Mechanisms Improve Carbon Price Forecasting Accuracy?
by: Ting Yao, et al.
Published: (2025)