An optimization strategy for portfolio management leveraging deep reinforcement learning for automated stock trading
Gurunath T. Chavangt.chavan@gmail.comDepartment of Information TechnologyVishwakarma Institute of TechnologyPune, Maharashtra, 411048, IndiaView full profile → , *Santosh H. LavateCorresponding authorlavate.santosh@gmail.comDepartment of Electronics and Telecommunication EngineeringAISSMS College of EngineeringPune, Maharashtra, 411001, IndiaView full profile → , Pradip Ram Selokarselokarpr@rknec.eduDepartment of Electronics and Communication EngineeringRamdeobaba UniversityNagpur, Maharashtra, 440013, IndiaView full profile → , Deepti Raverkardeepti.amb@gmail.comDepartment of Computer EngineeringJSPM’s Rajarshi Shahu College of Engineering (RSCOE)Pune, Maharashtra, 411033, IndiaView full profile → , Aniket Prakashrao Munshianiketpmunshi@gmail.comDepartment of Electrical EngineeringYeshwantrao Chavan College of EngineeringNagpur, Maharashtra, 441110, IndiaView full profile → , Kriti Kusumkriti.ksm05@gmail.comSymbiosis School of Planning Architecture and DesignNagpur CampusSymbiosis International UniversityPune, Maharashtra, 440008, IndiaView full profile →
* Corresponding author · click or hover a name for details
- Received:
- 23 Oct 2024
- Published Online:
- 31 May 2025
- Article type:
- Research Article
- Language:
- EN
- Article no.:
- JIOS-1901
- Pages:
- 1177–1187
Abstract
Keywords
Subject Classifications
References
[1] G. Meng, “Leveraging Knowledge Distillation for Efficient Deep Reinforcement Learning in Resource-Constrained Environments,” 2023 International Conference on Image Processing, Computer Vision and Machine Learning (ICICML), Chengdu, China, pp. 811-814 (2023).
[2] K. Arulkumaran, M. P. Deisenroth, M. Brundage, and A. A. Bharath, “Deep reinforcement learning: A brief survey”, IEEE Signal Processing Magazine, vol. 34, no. 6, pp. 26-38 (2017).
[3] You Huang and Yuanlong Yu, “Distilling deep neural networks with reinforcement learning”, 2018 IEEE International Conference on Information and Automation (ICIA), pp. 133-138 (2018).
[4] Y. Ansari, M. J. Khan, T. Anees, S. U. R. Malik, and M. U. Akram, “A Deep Reinforcement Learning-Based Decision Support System for Automated Stock Market Trading,” in IEEE Access, vol. 10, pp. 127469-127501 (2022).
[5] R. Dash and P. K. Dash, “A hybrid stock trading framework integrating technical analysis with machine learning techniques”, J. Finance Data Sci., vol. 2, no. 1, pp. 42-57 (2016).
[6] D. Kumar, P. K. Sarangi and R. Verma, “A systematic review of stock market prediction using machine learning and statistical techniques”, Mater. Today Proc., vol. 49, pp. 3187-3191 (Jan. 2022).
[7] J. B. Chakole, M. S. Kolhe, G. D. Mahapurush, A. Yadav and M. P. Kurhekar, “A Q-learning agent for automated trading in equity stock markets”, Expert Syst. Appl., vol. 163 (Jan. 2021).
[8] V. S. Nalawade , B. S. Yunnus , M. G. Shankar , C. P. Balasaheb , and T. A. Aspan, “Exploring the Role of Reinforcement Learning in Personal Finance Management: A Comprehensive Literature Survey”, IJRAET, vol. 13, no. 2, pp. 21–26 (Mar. 2025).
[9] D. Andriosopoulos, M. Doumpos, P. M. Pardalos and C. Zopounidis, “Computational approaches and data analytics in financial services”, J. Oper. Res. Soc., vol. 70, no. 10, pp. 1579-1580 (Oct. 2019).
[10] S. M. Stefanov, “Linear programming problems and matrix games,” J. Interdiscip. Math., vol. 27, no. 1, pp. 57–65 (2024), doi: 10.47974/JIM-1653.
[11] Y. Li, P. Ni and V. Chang, “Application of deep reinforcement learning in stock trading strategies and stock forecasting”, Computing, vol. 102, no. 6, pp. 1305-1322 (Jun. 2020).
[12] C. Liu and H. Malik, “A new investment strategy based on data mining and neural networks”, Proc. Int. Joint Conf. Neural Netw. (IJCNN), pp. 3094-3099 (Jul. 2014).




