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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:

Deep learning-based feature engineering for stock price movement prediction
Wen Long, Zhichen Lu, Ling-Xiao Cui
Knowledge-Based Systems (2018) Vol. 164, pp. 163-173
Closed Access | Times Cited: 409

Showing 1-25 of 409 citing articles:

Deep Learning for Time Series Forecasting: A Survey
J. F. Torres, Dalil Hadjout, Abderrazak Sebaa, et al.
Big Data (2020) Vol. 9, Iss. 1, pp. 3-21
Closed Access | Times Cited: 517
Applications of deep learning in stock market prediction: Recent progress
Weiwei Jiang
Expert Systems with Applications (2021) Vol. 184, pp. 115537-115537
Open Access | Times Cited: 480
Predicting Stock Market Trends Using Machine Learning and Deep Learning Algorithms Via Continuous and Binary Data; a Comparative Analysis
Mojtaba Nabipour, Pooyan Nayyeri, Hamed Jabani, et al.
IEEE Access (2020) Vol. 8, pp. 150199-150212
Open Access | Times Cited: 338
Deep Learning for Stock Market Prediction
Mojtaba Nabipour, Pooyan Nayyeri, Hamed Jabani, et al.
Entropy (2020) Vol. 22, Iss. 8, pp. 840-840
Open Access | Times Cited: 287
Short-term stock market price trend prediction using a comprehensive deep learning system
Jingyi Shen, M. Omair Shafiq
Journal Of Big Data (2020) Vol. 7, Iss. 1
Open Access | Times Cited: 283
Portfolio optimization with return prediction using deep learning and machine learning
Yilin Ma, Ruizhu Han, Weizhong Wang
Expert Systems with Applications (2020) Vol. 165, pp. 113973-113973
Closed Access | Times Cited: 208
A graph-based CNN-LSTM stock price prediction algorithm with leading indicators
Jimmy Ming‐Tai Wu, Zhongcui Li, Norbert Herencsár, et al.
Multimedia Systems (2021) Vol. 29, Iss. 3, pp. 1751-1770
Open Access | Times Cited: 189
A comprehensive survey on deep neural networks for stock market: The need, challenges, and future directions
Ankit Thakkar, Kinjal Chaudhari
Expert Systems with Applications (2021) Vol. 177, pp. 114800-114800
Closed Access | Times Cited: 173
Portfolio formation with preselection using deep learning from long-term financial data
Wuyu Wang, Weizi Li, Ning Zhang, et al.
Expert Systems with Applications (2019) Vol. 143, pp. 113042-113042
Open Access | Times Cited: 156
Stock market index prediction using deep Transformer model
Chaojie Wang, Yuanyuan Chen, Shuqi Zhang, et al.
Expert Systems with Applications (2022) Vol. 208, pp. 118128-118128
Closed Access | Times Cited: 142
Forecasting stock index price using the CEEMDAN-LSTM model
Yu Lin, Yan Yan, Jiali Xu, et al.
The North American Journal of Economics and Finance (2021) Vol. 57, pp. 101421-101421
Closed Access | Times Cited: 129
Artificial Intelligence Applied to Stock Market Trading: A Review
Fernando G. D. C. Ferreira, Amir H. Gandomi, Rodrigo T. N. Cardoso
IEEE Access (2021) Vol. 9, pp. 30898-30917
Open Access | Times Cited: 110
Deep Learning-based Integrated Framework for stock price movement prediction
Yanli Zhao, Guang Yang
Applied Soft Computing (2022) Vol. 133, pp. 109921-109921
Closed Access | Times Cited: 74
An ensemble of a boosted hybrid of deep learning models and technical analysis for forecasting stock prices
Amadu Fullah Kamara, Enhong Chen, Zhen Pan
Information Sciences (2022) Vol. 594, pp. 1-19
Closed Access | Times Cited: 71
A survey on machine learning models for financial time series forecasting
Yajiao Tang, Zhenyu Song, Yulin Zhu, et al.
Neurocomputing (2022) Vol. 512, pp. 363-380
Closed Access | Times Cited: 71
Financial Time Series Forecasting with the Deep Learning Ensemble Model
Kaijian He, Qian Yang, Lei Ji, et al.
Mathematics (2023) Vol. 11, Iss. 4, pp. 1054-1054
Open Access | Times Cited: 56
A high-frequency trading volume prediction model using neural networks
Xiaojie Xu, Yun Zhang
Decision Analytics Journal (2023) Vol. 7, pp. 100235-100235
Open Access | Times Cited: 44
Automated data processing and feature engineering for deep learning and big data applications: A survey
Alhassan Mumuni, Fuseini Mumuni
Journal of Information and Intelligence (2024)
Open Access | Times Cited: 32
Prediction of dynamic shear modulus of saturated coral sand based on explainable artificial intelligence
Bin Ruan, Guo Yang, Zhenglong Zhou, et al.
Construction and Building Materials (2025) Vol. 461, pp. 139878-139878
Closed Access | Times Cited: 3
Data Science in Economics: Comprehensive Review of Advanced Machine Learning and Deep Learning Methods
Saeed Nosratabadi, Amirhosein Mosavi, Puhong Duan, et al.
Mathematics (2020) Vol. 8, Iss. 10, pp. 1799-1799
Open Access | Times Cited: 120
A seasonal-trend decomposition-based dendritic neuron model for financial time series prediction
Houtian He, Shangce Gao, Ting Jin, et al.
Applied Soft Computing (2021) Vol. 108, pp. 107488-107488
Open Access | Times Cited: 93
A decision-theoretic rough set model with q-rung orthopair fuzzy information and its application in stock investment evaluation
Guolin Tang, Francisco Chiclana, Пэйдэ Лю
Applied Soft Computing (2020) Vol. 91, pp. 106212-106212
Closed Access | Times Cited: 85
Predicting the Trend of Stock Market Index Using the Hybrid Neural Network Based on Multiple Time Scale Feature Learning
Yaping Hao, Qiang Gao
Applied Sciences (2020) Vol. 10, Iss. 11, pp. 3961-3961
Open Access | Times Cited: 79
Prediction-Based Portfolio Optimization Models Using Deep Neural Networks
Yilin Ma, Ruizhu Han, Weizhong Wang
IEEE Access (2020) Vol. 8, pp. 115393-115405
Open Access | Times Cited: 78
A Survey of Forex and Stock Price Prediction Using Deep Learning
Zexin Hu, Yiqi Zhao, Matloob Khushi
Applied System Innovation (2021) Vol. 4, Iss. 1, pp. 9-9
Open Access | Times Cited: 65
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