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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Adaptive stock trading strategies with deep reinforcement learning methods
Xing Wu, Haolei Chen, Jianjia Wang, et al.
Information Sciences (2020) Vol. 538, pp. 142-158
Closed Access | Times Cited: 196

Showing 1-25 of 196 citing articles:

AI in Finance: Challenges, Techniques, and Opportunities
Longbing Cao
ACM Computing Surveys (2022) Vol. 55, Iss. 3, pp. 1-38
Closed Access | Times Cited: 156
Reinforcement learning algorithms: A brief survey
Ashish Kumar Shakya, G. N. Pillai, Sohom Chakrabarty
Expert Systems with Applications (2023) Vol. 231, pp. 120495-120495
Closed Access | Times Cited: 153
An Overview of Machine Learning, Deep Learning, and Reinforcement Learning-Based Techniques in Quantitative Finance: Recent Progress and Challenges
Santosh Sahu, Anil Mokhade, Neeraj Dhanraj Bokde
Applied Sciences (2023) Vol. 13, Iss. 3, pp. 1956-1956
Open Access | Times Cited: 88
Multi-step-ahead stock price index forecasting using long short-term memory model with multivariate empirical mode decomposition
Changrui Deng, Yanmei Huang, Najmul Hasan, et al.
Information Sciences (2022) Vol. 607, pp. 297-321
Closed Access | Times Cited: 77
A Systematic Study on Reinforcement Learning Based Applications
Keerthana Sivamayilvelan, R Elakkiya, Belqasem Aljafari, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1512-1512
Open Access | Times Cited: 64
Reinforcement learning-based multi-strategy cuckoo search algorithm for 3D UAV path planning
Xiaobing Yu, Wenguan Luo
Expert Systems with Applications (2023) Vol. 223, pp. 119910-119910
Closed Access | Times Cited: 52
Artificial intelligence techniques in financial trading: A systematic literature review
Fatima Dakalbab, Manar Abu Talib, Qassim Nasir, et al.
Journal of King Saud University - Computer and Information Sciences (2024) Vol. 36, Iss. 3, pp. 102015-102015
Open Access | Times Cited: 15
Sentiment analysis of Chinese stock reviews based on BERT model
Mingzheng Li, Lei Chen, Jing Zhao, et al.
Applied Intelligence (2021) Vol. 51, Iss. 7, pp. 5016-5024
Closed Access | Times Cited: 65
Multi-scale local cues and hierarchical attention-based LSTM for stock price trend prediction
Xiao Teng, Xiang Zhang, Zhigang Luo
Neurocomputing (2022) Vol. 505, pp. 92-100
Closed Access | Times Cited: 45
Learning financial asset-specific trading rules via deep reinforcement learning
Mehran Taghian, Ahmad Asadi, Reza Safabakhsh
Expert Systems with Applications (2022) Vol. 195, pp. 116523-116523
Open Access | Times Cited: 42
Artificial Intelligence in Accounting and Finance: Challenges and Opportunities
Ziwei Yi, Xinwei Cao, Zuyan Chen, et al.
IEEE Access (2023) Vol. 11, pp. 129100-129123
Open Access | Times Cited: 26
Deep LSTM and LSTM-Attention Q-learning based reinforcement learning in oil and gas sector prediction
David Opeoluwa Oyewola, Sulaiman Awwal Akinwunmi, Temidayo Oluwatosin Omotehinwa
Knowledge-Based Systems (2023) Vol. 284, pp. 111290-111290
Open Access | Times Cited: 23
What Is Quantitative Research? An Overview and Guidelines
Weng Marc Lim
Australasian Marketing Journal (AMJ) (2024)
Closed Access | Times Cited: 13
Deep reinforcement learning for portfolio management of markets with a dynamic number of assets
Carlos Betancourt, Wenhui Chen
Expert Systems with Applications (2020) Vol. 164, pp. 114002-114002
Closed Access | Times Cited: 57
A Q-learning agent for automated trading in equity stock markets
Jagdish Chakole, Mugdha S. Kolhe, Grishma D. Mahapurush, et al.
Expert Systems with Applications (2020) Vol. 163, pp. 113761-113761
Closed Access | Times Cited: 50
Price graphs: Utilizing the structural information of financial time series for stock prediction
Junran Wu, Ke Xu, Xueyuan Chen, et al.
Information Sciences (2021) Vol. 588, pp. 405-424
Open Access | Times Cited: 48
Multi-type data fusion framework based on deep reinforcement learning for algorithmic trading
Peipei Liu, Yunfeng Zhang, Fangxun Bao, et al.
Applied Intelligence (2022) Vol. 53, Iss. 2, pp. 1683-1706
Closed Access | Times Cited: 31
Stock ranking prediction using a graph aggregation network based on stock price and stock relationship information
Guowei Song, Tianlong Zhao, Suwei Wang, et al.
Information Sciences (2023) Vol. 643, pp. 119236-119236
Closed Access | Times Cited: 21
Asset correlation based deep reinforcement learning for the portfolio selection
Tianlong Zhao, Xiang Ma, Xuemei Li, et al.
Expert Systems with Applications (2023) Vol. 221, pp. 119707-119707
Closed Access | Times Cited: 20
Multi-period portfolio optimization using a deep reinforcement learning hyper-heuristic approach
Tianxiang Cui, Nanjiang Du, Xiaoying Yang, et al.
Technological Forecasting and Social Change (2023) Vol. 198, pp. 122944-122944
Open Access | Times Cited: 20
A multi-agent reinforcement learning framework for optimizing financial trading strategies based on TimesNet
Yuling Huang, Chujin Zhou, Kai Cui, et al.
Expert Systems with Applications (2023) Vol. 237, pp. 121502-121502
Closed Access | Times Cited: 19
Multi-factor stock trading strategy based on DQN with multi-BiGRU and multi-head ProbSparse self-attention
Wenjie Liu, Yuchen Gu, Y. F. Ge
Applied Intelligence (2024) Vol. 54, Iss. 7, pp. 5417-5440
Open Access | Times Cited: 5
A parallel multi-module deep reinforcement learning algorithm for stock trading
Cong Ma, Jiangshe Zhang, Junmin Liu, et al.
Neurocomputing (2021) Vol. 449, pp. 290-302
Closed Access | Times Cited: 39
Learning to trade in financial time series using high-frequency through wavelet transformation and deep reinforcement learning
Jimin Lee, Hayeong Koh, Hi Jun Choe
Applied Intelligence (2021) Vol. 51, Iss. 8, pp. 6202-6223
Closed Access | Times Cited: 34
A hierarchical attention network for stock prediction based on attentive multi-view news learning
Xingtong Chen, Xiang Ma, Hua Wang, et al.
Neurocomputing (2022) Vol. 504, pp. 1-15
Closed Access | Times Cited: 27
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