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INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT International Peer Reviewed & Refereed Journals, Open Access Journal ISSN Approved Journal No: 2456-4184 | Impact factor: 8.76 | ESTD Year: 2016 Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.76 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI) |
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| Paper Title: | Stock price prediction using reinforcement learning |
| Authors Name: | Kaustubh Yewale , Rajesh Nasare , Mohammad fayyaz , Devesh Ambade , Aryan meshram |
| Download E-Certificate: | Download |
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IJNRD_217968
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| Published Paper Id: | IJNRD2404271 |
| Published In: | Volume 9 Issue 4, April-2024 |
| DOI: | |
| 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.” |
| 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 |
| Cite Article: | "Stock price prediction using reinforcement learning", International Journal of Novel Research and Development (www.ijnrd.org), ISSN:2456-4184, Vol.9, Issue 4, page no.c349-c356, April-2024, Available :http://www.ijnrd.org/papers/IJNRD2404271.pdf |
| Downloads: | 00038 |
| ISSN: |
2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID:IJNRD2404271 Registration ID: 217968 Published In: Volume 9 Issue 4, April-2024 DOI (Digital Object Identifier): Page No: c349-c356 Country: Nagpur, Maharashtra, India Research Area: Information Technology Publisher : IJ Publication Published Paper URL : https://www.ijnrd.org/viewpaperforall?paper=IJNRD2404271 Published Paper PDF: https://www.ijnrd.org/papers/IJNRD2404271 |
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