Open Access
Subscription Access
A Deep Learning Framework for Stock Prediction: Sentiment Analysis and Risk Management
Abstract
We made a practical tool for the prediction of stock prices, as well as for making trades. It uses refined computer programs - particularly inspired by how the brain works - linked with information found from public opinion. This setup combines multiple forecasting models with carefully chosen indicators; it adapts to the changing market conditions and handles potential downsides. Testing on over thirty large American companies between 2015 and 2025. It showed strong results and steady reliability when faced with new data; the predictions were correct around half the time. Trading tests using lifelike scenarios, such as covering fees alongside shifts in price, showed a 65.91% gain with Microsoft stock (Case Stock), coupled with a 0.611 Sharpe ratio. Examining gave such results, and assessing potential dangers revealed that this system is straightforward as well as adjusts well with market changes simultaneously. Ultimately, we are blending advanced technology, unique information sources, along strong safety measures. This proves worthwhile for automated trades.
References
Shimaa Ouf, Mona El Hawary, Amal Aboutabl and Sherif Adel, “A Deep Learning-Based LSTM for Stock Price Prediction Using Twitter Sentiment Analysis” http://dx.doi.org/10.14569/IJACSA.2024.0151223
Narayana Darapaneni, Anwesh Reddy Paduri, Himank Sharma, Milind Manjrekar, Nutan Hindlekar, Pranali Bhagat, Usha Aiyer, Yogesh Agarwal, "https://arxiv.org/pdf/2204.05783.pdf
Yan Zhao, Jie Zhang, "Deep Learning-based Integrated Framework for Stock Price Prediction with Public Sentiment," https://www.sciencedirect.com/science/article/abs/pii/S15684946220097
X
SÖ Akyüz, "Predicting Stock Market by Sentiment Analysis and Deep Learning Models," https://ideas.repec.org/a/wut/journl/v34y2024i2p85-107id6.html
Chi-Yuan Lee, Eva Anderl, "Does business news sentiment matter in the energy stock market? Adopting sentiment analysis for short-term stock market prediction in the energy industry," https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2025.
/full
W jun Gu, "Predicting Stock Prices with FinBERT-LSTM: Integrating News Sentiment and Price Data," https://dl.acm.org/doi/10.1145/3694860.3694870
A Sebastian, A Narayanan, "Multi-variate LSTM with attention mechanism for the Indian financial market integrating news sentiment," Data Science and Engineering, Vol. 26, 2025. https://www.sciencedirect.com/science/article/pii/S2667096825000321
Y Wang, "LSTM stock prediction model based on blockchain and sentiment analysis," https://www.sciencedirect.com/science/article/pii/S2667295225000200
T. Fischer, C. Krauss, "Deep learning with long short-term memory networks for financial market predictions," https://www.sciencedirect.com/science/article/abs/pii/S0377221717310652
R. Akita, A. Yoshihara, T. Matsubara, K. Uehara, "Deep learning for stock prediction using numerical and textual information," https://ieeexplore.ieee.org/document/7550882
Refbacks
- There are currently no refbacks.