Open Access Journal Article

An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction

by Diego Vallarino a,*
a
Independent Researcher, Atlanta, GA, US
*
Author to whom correspondence should be addressed.
JEA  2025 4(3):109; https://doi.org/10.58567/jea04030001
Received: 2 October 2024 / Accepted: 21 April 2025 / Published Online: 9 May 2025
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Abstract

Forecasting stock prices remains a fundamental yet complex challenge in financial economics due to the nonlinearity, volatility, and exogenous shocks characterizing market behavior. This paper proposes a hybrid deep learning framework that integrates Long Short-Term Memory (LSTM) networks for time-series modeling with Transformer-based architectures for textual sentiment extraction from financial news. The goal is to enhance predictive accuracy by combining structured historical data with unstructured semantic signals. Using three years of daily data from Apple Inc. (AAPL), the model captures endogenous price dynamics via LSTM and incorporates contemporaneous market sentiment through FinBERT, a Transformer model pretrained on financial text. Empirical results show that the hybrid model outperforms price-only baselines across multiple evaluation metrics, including mean squared error (MSE) and directional accuracy. The incorporation of sentiment features proves particularly valuable around earnings announcements and event-driven volatility regimes. This study contributes to the literature on machine learning in finance by demonstrating the complementary strengths of multimodal learning, offering a more interpretable and robust framework for stock price prediction. The findings also open avenues for future research in real-time forecasting, reinforcement learning integration, and the application of hybrid models across diverse asset classes.

Keywords: Stock Price Prediction; RNN; LSTM; Transformers; Sentiment Analysis; Financial Forecasting;
Copyright: © 2025 by Vallarino. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). 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.
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APA Style
Vallarino, D. (2025). An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis, 4(3), 109. doi:10.58567/jea04030001
ACS Style
Vallarino, D. An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis, 2025, 4, 109. doi:10.58567/jea04030001
AMA Style
Vallarino D. An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis; 2025, 4(3):109. doi:10.58567/jea04030001
Chicago/Turabian Style
Vallarino, Diego 2025. "An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction" Journal of Economic Analysis 4, no.3:109. doi:10.58567/jea04030001

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ACS Style
Vallarino, D. An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis, 2025, 4, 109. doi:10.58567/jea04030001
AMA Style
Vallarino D. An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis; 2025, 4(3):109. doi:10.58567/jea04030001
Chicago/Turabian Style
Vallarino, Diego 2025. "An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction" Journal of Economic Analysis 4, no.3:109. doi:10.58567/jea04030001
APA style
Vallarino, D. (2025). An AI-Enhanced Forecasting Framework: Integrating LSTM and Transformer-Based Sentiment for Stock Price Prediction. Journal of Economic Analysis, 4(3), 109. doi:10.58567/jea04030001

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