Paper Title

Stock price prediction using reinforcement learning

Article Identifiers

Registration ID: IJNRD_217968

Published ID: IJNRD2404271

DOI: Click Here to Get

Authors

Kaustubh Yewale , Rajesh Nasare , Mohammad fayyaz , Devesh Ambade , Aryan meshram

Keywords

Stock Price Prediction, Reinforcement Learning, Financial Markets, Machine Learning, Trading Strategies, Forecasting, Historical Data, Market Dynamics, Stock Market, Algorithmic Trading, Reinforcement Learning Agent, Predictive Models, Portfolio Optimization

Abstract

The application of reinforcement learning techniques for stock price prediction is explored in this research study, which is important given the volatility of the financial markets. Stock price dynamics are often difficult for traditional tools to understand. A remedy is provided by reinforcement learning, an area of artificial intelligence that focuses on sequential decision-making. It starts by describing the intricacies of the stock market and presents fundamentals of reinforcement learning, such as Q-learning and Markov Decision Processes, modified for stock price modeling. A trading agent based on reinforcement learning is developed through empirical analysis and tested against historical stock data. The RL model performs better than more established techniques like LSTM and ARIMA, demonstrating its ability to recognize non-linear patterns and adjust to shifting market conditions. The results highlight the potential of reinforcement learning, which provides better accuracy and flexibility. The study emphasizes the necessity for cautious real-world financial system deployment as it addresses practical consequences and constraints. As a result, this study presents a novel application of reinforcement learning to stock price prediction, which holds the potential to improve financial market risk management and decision-making.”

How To Cite (APA)

Kaustubh Yewale, Rajesh Nasare, Mohammad fayyaz, Devesh Ambade , & Aryan meshram (April-2024). Stock price prediction using reinforcement learning. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 9(4), c349-c356. https://ijnrd.org/papers/IJNRD2404271.pdf

Issue

Volume 9 Issue 4, April-2024

Pages : c349-c356

Other Publication Details

Paper Reg. ID: IJNRD_217968

Published Paper Id: IJNRD2404271

Downloads: 000121986

Research Area: Information Technology 

Country: Nagpur, Maharashtra, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2404271.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2404271

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Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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Call For Paper - Volume 10 | Issue 10 | October 2025

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Important Dates for Current issue

Paper Submission Open For: October 2025

Current Issue: Volume 10 | Issue 10 | October 2025

Impact Factor: 8.76

Last Date for Paper Submission: Till 31-Oct-2025

Notification of Review Result: Within 1-2 Days after Submitting paper.

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