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International Journal for Research Trends and Innovation
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ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Impact Factor : 8.14
Issue per Year : 12
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Issue Published : 115
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| Paper Title: | Multi-Stock Trading Strategy Using Ensemble Deep Reinforcement Learning for Automated Stock Trading |
| Authors Name: | Krisha Lakhani , Durvang Parab , Prof. Sheeja Nair |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_188014
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| Published Paper Id: | IJRTI2309017 |
| Published In: | Volume 8 Issue 9, September-2023 |
| DOI: | |
| Abstract: | This study suggests a multi-stock trading approach for automated stock trading utilizing an ensemble deep reinforcement learning framework. Designing an automated trading solution for single stock trading is the problem at hand, with the stock trading process being viewed as a Markov Decision Process (MDP). The trading agent, which comprises actor, critic, and ensemble networks using Proximal Policy Optimization, Advantage Actor-Critic, and Deep Deterministic Policy Gradient algorithms, is trained using Deep Reinforcement Learning (DRL) techniques. Performance is assessed based on the strategy's cumulative return, Sharpe ratio, and maximum drawdown. The results show a lower maximum drawdown, which suggests better risk management. |
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| Cite Article: | "Multi-Stock Trading Strategy Using Ensemble Deep Reinforcement Learning for Automated Stock Trading", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.8, Issue 9, page no.113 - 121, September-2023, Available :http://www.ijrti.org/papers/IJRTI2309017.pdf |
| Downloads: | 000205404 |
| ISSN: |
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 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: IJRTI2309017
Registration ID:188014
Published In: Volume 8 Issue 9, September-2023
DOI (Digital Object Identifier):
Page No: 113 - 121 Country: MUMBAI, MAHARASHTRA, India Research Area: Computer Science & Technology Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2309017 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2309017 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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