Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Faculty Publications Conference Paper Faculty Publications- Conference Papers Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Praveenraj, D. David Winster; Hemalatha, D.; Al-Farouni, Mohammed; Priya, S.; Arunkumar, B.; Mittal, Prakhar Title A name given to the resource Utilizing Transforming Portfolio Management Through Automation Using Advanced Deep Reinforcement Learning Algorithms for Optimized Investment Strategies Date A point or period of time associated with an event in the lifecycle of the resource 01-01-2025 Source A related resource from which the described resource is derived 2025 International Conference on Automation and Computation, AUTOCOM 2025;pp.1368-1372 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1109/AUTOCOM64127.2025.10956627" target="_blank" rel="noreferrer noopener">https://doi.org/10.1109/AUTOCOM64127.2025.10956627</a> <br /><br /><a href="https://www.scopus.com/pages/publications/105003906937?origin=resultslist" target="_blank" rel="noreferrer noopener">https://www.scopus.com/pages/publications/105003906937?origin=resultslist</a> Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Praveenraj D.D.W., School of Business and Management, Christ University, Bangalore, India; Hemalatha D., School of Business and Management, Christ University, Bangalore, India; Al-Farouni M., College of Technical Engineering, The Islamic University, Department of Computers Techniques Engineering, Najaf, Iraq; Priya S., Kcg College of Technology, India; Arunkumar B., Karpagam Academy of Higher Education, Department of Computer Science Engineering, Coimbatore, India; Mittal P., Department of It, Atricure, Mason, OH, United States Description An account of the resource This paper focuses on the future possibility of enhancing the applications of DRL in autonomously managing a portfolio for better investment plans. Having used past financial data and a highly developed case of DRL, the proposed system shows better performance compared to conventional investment strategies and indices. This process includes data gathering from the financial databases, the steps of preprocessing and feature extraction, and the use of the DQN structure. After that, the system's training and validation are done by a finite portion of real-world data and a large number of synthesized data to improve stability. The result shows that the new method achieves superior cumulative return, Sharpe ratio, maximum drawdown, and annualized volatility; therefore, it suggests that the proposed system can flexibly predict the fluctuating stock market trends and make appropriate investment decisions. Thus, the present research adds importance to the use of DRL in improving return potential and risk management in portfolio management. Thus, this study adds to the existing literature and practice by allowing for the automation of the optimization and testing for investment solutions at a larger scale, while opening up opportunities for future developments in the application of financial technology and investment tools. 2025 IEEE. Subject The topic of the resource Asset Allocation; Automated Trading Systems; Deep Reinforcement Learning; Financial Data Analysis; Investment Strategies; Machine Learning; Portfolio Management; Risk Management Publisher An entity responsible for making the resource available Institute of Electrical and Electronics Engineers Inc. Relation A related resource ISBN: 979-833154237-5; Language A language of the resource English Type The nature or genre of the resource Conference paper Rights Information about rights held in and over the resource Restricted Access; Hardcopy may be available in the library Format The file format, physical medium, or dimensions of the resource online