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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:

Stock market prediction with deep learning: The case of China
Qingfu Liu, Zhenyi Tao, Yiuman Tse, et al.
Finance research letters (2021) Vol. 46, pp. 102209-102209
Closed Access | Times Cited: 54

Showing 1-25 of 54 citing articles:

An exploratory data analysis approach for analyzing financial accounting data using machine learning
Potta Chakri, Saurabh Pratap, Lakshay, et al.
Decision Analytics Journal (2023) Vol. 7, pp. 100212-100212
Open Access | Times Cited: 25
SMP-DL: a novel stock market prediction approach based on deep learning for effective trend forecasting
Warda M. Shaban, Eman Ashraf, Ahmed Elsaid Slama
Neural Computing and Applications (2023) Vol. 36, Iss. 4, pp. 1849-1873
Open Access | Times Cited: 23
Machine learning goes global: Cross-sectional return predictability in international stock markets
Nusret Cakici, Christian Fieberg, Daniel Metko, et al.
Journal of Economic Dynamics and Control (2023) Vol. 155, pp. 104725-104725
Open Access | Times Cited: 22
Machine learning models predicting returns: Why most popular performance metrics are misleading and proposal for an efficient metric
Jean Dessain
Expert Systems with Applications (2022) Vol. 199, pp. 116970-116970
Open Access | Times Cited: 37
Forecasts for international financial series with VMD algorithms
Wei Guo, Qingfu Liu, Zhidan Luo, et al.
Journal of Asian Economics (2022) Vol. 80, pp. 101458-101458
Closed Access | Times Cited: 29
Stock price predictive analysis: An application of hybrid Barnacles Mating Optimizer with Artificial Neural Network
Zuriani Mustaffa, Mohd Herwan Sulaiman
International Journal of Cognitive Computing in Engineering (2023) Vol. 4, pp. 109-117
Open Access | Times Cited: 20
Forecasting relative returns for S&P 500 stocks using machine learning
Htet Htet Htun, Michael Biehl, Nicolai Petkov
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 7
Predicting the Brazilian Stock Market with Sentiment Analysis, Technical Indicators and Stock Prices: A Deep Learning Approach
Arthur Emanuel de Oliveira Carosia, Ana Estela Antunes da Silva, Guilherme Palermo Coelho
Computational Economics (2024)
Closed Access | Times Cited: 6
Implementation of Long Short-Term Memory and Gated Recurrent Units on grouped time-series data to predict stock prices accurately
Armin Lawi, Hendra Mesra, Supri Amir
Journal Of Big Data (2022) Vol. 9, Iss. 1
Open Access | Times Cited: 23
Integrated GCN-LSTM stock prices movement prediction based on knowledge-incorporated graphs construction
Yong Shi, Yunong Wang, Yi Qu, et al.
International Journal of Machine Learning and Cybernetics (2023) Vol. 15, Iss. 1, pp. 161-176
Closed Access | Times Cited: 14
Comprehensive Stock Market Insight: Bayesian Networks for Multi-output Forecasting
Ali Ben Mrad, Brahim Hnich, Amine Lahiani, et al.
Computational Economics (2025)
Closed Access
ML computational inference techniques and indicator metrics for analyzing uncertainties in stock market data
Santosh Kumar Henge, Sanjeev Kumar Mandal, Amit Sharma, et al.
Multimedia Tools and Applications (2025)
Closed Access
Multi-perspective Learning Based on Transformer for Stock Price Trend
Xiliang Li, Shuoru Chen, Xiaoyan Qiao, et al.
International Journal of Computational Intelligence Systems (2025) Vol. 18, Iss. 1
Open Access
Forecasting of Stock Market from Borsa Istanbul Banks Using MGRU with Modified Jellyfish Search Optimization Algorithms
R. Mahaveerakannan, Cuddapah Anitha, S. Devi
Lecture notes in networks and systems (2025), pp. 275-288
Closed Access
Algorithmic trading using continuous action space deep reinforcement learning
Naseh Majidi, Mahdi Shamsi, Farokh Marvasti
Expert Systems with Applications (2023) Vol. 235, pp. 121245-121245
Open Access | Times Cited: 12
Examining Daily Closing Price Prediction of the NSE Index using an Optimized Artificial Neural Network: A Study of Stock Market
Umar Bashir, Kuljeet Singh, Vibhakar Mansotra
Journal of Scientific Research (2025) Vol. 17, Iss. 1, pp. 195-209
Open Access
Multifactor prediction model for stock market analysis based on deep learning techniques
Kangyi Wang
Scientific Reports (2025) Vol. 15, Iss. 1
Open Access
AE-ACG: A novel deep learning-based method for stock price movement prediction
Shicheng Li, Xiaoyong Huang, Zhonghou Cheng, et al.
Finance research letters (2023) Vol. 58, pp. 104304-104304
Closed Access | Times Cited: 8
Selective genetic algorithm labeling: A new data labeling method for machine learning stock market trading systems
Yechan Han, Jaeyun Kim, David Enke
Engineering Applications of Artificial Intelligence (2024) Vol. 135, pp. 108680-108680
Closed Access | Times Cited: 2
Forecasting cryptocurrencies’ price with the financial stress index: a graph neural network prediction strategy
Wei Yin, Ziling Chen, Xinxin Luo, et al.
Applied Economics Letters (2022) Vol. 31, Iss. 7, pp. 630-639
Open Access | Times Cited: 9
Portfolios with return and volatility prediction for the energy stock market
Yilin Ma, Yudong Wang, Weizhong Wang, et al.
Energy (2023) Vol. 270, pp. 126958-126958
Closed Access | Times Cited: 5
Improving Stock Trend Prediction with Multi-granularity Denoising Contrastive Learning
Mingjie Wang, Feng Chen, Jianxiong Guo, et al.
2022 International Joint Conference on Neural Networks (IJCNN) (2023), pp. 1-10
Closed Access | Times Cited: 5
Stock Prediction and analysis Using Supervised Machine Learning Algorithms
Ajinkya Yelne, Deepti P. Theng
(2021), pp. 1-6
Closed Access | Times Cited: 12
Choices Matter When Training Machine Learning Models for Return Prediction
Clint Howard
Financial Analysts Journal (2024) Vol. 80, Iss. 4, pp. 81-107
Closed Access | Times Cited: 1
A Stock Prediction Method Based on Deep Reinforcement Learning and Sentiment Analysis
S. X. Du, Hailong Shen
Applied Sciences (2024) Vol. 14, Iss. 19, pp. 8747-8747
Open Access | Times Cited: 1
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