Predicting Stock Market Trends using Deep Learning Techniques

Akruthi Shere; MR.M.Venkateshwarlu; Sahithi Reddy; Sree Akshaya; Rohan Naga Sai; Akshitha Reddy

Predicting Stock Market Trends using Deep Learning Techniques

March 2026

Vol-12, Issue-2

Paper ID: 28195

ISSN: 2395-4396

Downloads: 0

Abstract & Details

Research Area

Computer Science and Engineering

Keywords

stock market prediction deep learning neural networks LSTM time series forecasting financial forecasting machine learning stock price prediction algorithmic trading data-driven finance

Abstract

This project explores the development of an advanced predictive model for stock market prices using a hybrid deep learning architecture that combines a Convolutional Neural Network (CNN) and a Long Short-Term Memory (LSTM) network. The primary goal is to leverage the unique strengths of both algorithms to achieve superior prediction accuracy compared to traditional time-series models. The model's performance will be evaluated using standard regression metrics, such as Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE), to quantify the accuracy of the predicted next-day closing price. The CNN part digs into recent price data and technical indicators to find sharp, local patterns like sudden spikes or short-term trends. The LSTM component, on the other hand, understands how those patterns evolve over time it remembers and learns from past behavior. This hybrid approach aims to provide a robust framework for financial forecasting by effectively processing both the spatial and temporal characteristics of stock market data. This hybrid CNN-LSTM model gives us the best of both worlds.

License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author Information

#	Name	Institute / Affiliation
1	Akruthi Shere	Sphoorthy Engineering College
2	MR.M.Venkateshwarlu	Sphoorthy Engineering College
3	Sahithi Reddy	Sphoorthy Engineering College
4	Sree Akshaya	Sphoorthy Engineering College
5	Rohan Naga Sai	Sphoorthy Engineering College
6	Akshitha Reddy	Sphoorthy Engineering College

How to Cite

Use the following formats to cite this article in your research.

APA Style

Shere, Akruthi, MR.M.Venkateshwarlu, Reddy, Sahithi, Akshaya, Sree, Sai, Rohan Naga, & Reddy, Akshitha (2026). Predicting Stock Market Trends using Deep Learning Techniques. International Journal of Advance Research and Innovative Ideas In Education, 12(2), 554-561.

MLA Style

Shere, Akruthi, et al. "Predicting Stock Market Trends using Deep Learning Techniques." International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, 2026, pp. 554-561.

IEEE Style

Akruthi Shere, MR.M.Venkateshwarlu, Sahithi Reddy, Sree Akshaya, Rohan Naga Sai, and Akshitha Reddy, "Predicting Stock Market Trends using Deep Learning Techniques," International Journal of Advance Research and Innovative Ideas In Education, vol. 12, no. 2, pp. 554-561, 2026.

Vancouver Style

Shere Akruthi, MR.M.Venkateshwarlu, Reddy Sahithi, Akshaya Sree, Sai Rohan Naga, Reddy Akshitha. Predicting Stock Market Trends using Deep Learning Techniques. International Journal of Advance Research and Innovative Ideas In Education. 2026;12(2):554-561.

Harvard Style

Shere, Akruthi, MR.M.Venkateshwarlu, Reddy, Sahithi, Akshaya, Sree, Sai, Rohan Naga, & Reddy, Akshitha (2026) 'Predicting Stock Market Trends using Deep Learning Techniques', International Journal of Advance Research and Innovative Ideas In Education, 12(2), pp. 554-561.

Chicago Style

Shere, Akruthi, et al. "Predicting Stock Market Trends using Deep Learning Techniques." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 554-561.

Turabian Style

Shere, Akruthi, et al. "Predicting Stock Market Trends using Deep Learning Techniques." International Journal of Advance Research and Innovative Ideas In Education 12, no. 2 (2026): 554-561.