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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:

Machine Learning for Stock Selection
Keywan Christian Rasekhschaffe, Robert C. Jones
Financial Analysts Journal (2019) Vol. 75, Iss. 3, pp. 70-88
Closed Access | Times Cited: 180

Showing 1-25 of 180 citing articles:

Machine Learning vs. Economic Restrictions: Evidence from Stock Return Predictability
Doron Avramov, Si Cheng, Lior Metzker
Management Science (2022) Vol. 69, Iss. 5, pp. 2587-2619
Closed Access | Times Cited: 108
Predicting Future Earnings Changes Using Machine Learning and Detailed Financial Data
XI CHEN, YANG HA CHO, Yiwei Dou, et al.
Journal of Accounting Research (2022) Vol. 60, Iss. 2, pp. 467-515
Closed Access | Times Cited: 90
Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis
Salman Bahoo, Marco Cucculelli, Xhoana Goga, et al.
SN Business & Economics (2024) Vol. 4, Iss. 2
Open Access | Times Cited: 52
Is Artificial Intelligence Ready to Assess an Enterprise’s Financial Security?
Oleksandr Melnychenko
Journal of risk and financial management (2020) Vol. 13, Iss. 9, pp. 191-191
Open Access | Times Cited: 86
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
Machine learning and the cross-section of emerging market stock returns
Matthias X. Hanauer, Tobias Kalsbach
Emerging Markets Review (2023) Vol. 55, pp. 101022-101022
Closed Access | Times Cited: 25
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
Explainable deep learning model for stock price forecasting using textual analysis
Mohammad Abdullah, Zunaidah Sulong, Mohammad Ashraful Ferdous Chowdhury
Expert Systems with Applications (2024) Vol. 249, pp. 123740-123740
Closed Access | Times Cited: 15
Quantum machine learning on near-term quantum devices: Current state of supervised and unsupervised techniques for real-world applications
Yaswitha Gujju, Atsushi Matsuo, Rudy Raymond
Physical Review Applied (2024) Vol. 21, Iss. 6
Open Access | Times Cited: 12
Which uncertainty measure better predicts gold prices? New evidence from a CNN-LSTM approach
Wanhai You, Jianyong Chen, Haoqi Xie, et al.
The North American Journal of Economics and Finance (2025), pp. 102375-102375
Closed Access | Times Cited: 1
Machine Learning Versus Economic Restrictions: Evidence from Stock Return Predictability
Doron Avramov, Si Cheng, Lior Metzker
SSRN Electronic Journal (2019)
Closed Access | Times Cited: 60
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
Stock Price Prediction Using a Frequency Decomposition Based GRU Transformer Neural Network
Chengyu Li, Guoqi Qian
Applied Sciences (2022) Vol. 13, Iss. 1, pp. 222-222
Open Access | Times Cited: 36
Machine learning methods in finance: Recent applications and prospects
Daniel Hoang, Kevin Wiegratz
European Financial Management (2022) Vol. 29, Iss. 5, pp. 1657-1701
Open Access | Times Cited: 35
Oil futures volatility predictability: New evidence based on machine learning models
Xinjie Lu, Feng Ma, Jin Xu, et al.
International Review of Financial Analysis (2022) Vol. 83, pp. 102299-102299
Closed Access | Times Cited: 33
The Adaptive Markets Hypothesis
Andrew W. Lo, Ruixun Zhang
Oxford University Press eBooks (2024)
Closed Access | Times Cited: 6
Gold Price Forecast Based on LSTM-CNN Model
Zhanhong He, Junhao Zhou, Hong‐Ning Dai, et al.
2021 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech) (2019), pp. 1046-1053
Open Access | Times Cited: 47
Empirical asset pricing via machine learning: evidence from the European stock market
Wolfgang Drobetz, Tizian Otto
Journal of Asset Management (2021) Vol. 22, Iss. 7, pp. 507-538
Open Access | Times Cited: 38
The Financial System Red in Tooth and Claw: 75 Years of Co-Evolving Markets and Technology
Andrew W. Lo
Financial Analysts Journal (2021) Vol. 77, Iss. 3, pp. 5-33
Open Access | Times Cited: 35
Investors’ Subjective Utility Preferences and Optimal Portfolio Selection: A Dominance Ranking-Driven Multi-Attribute Decision Model
Shufei Li, Xingfu Xu, Chong Cheng
(2025)
Closed Access
Building portfolios based on machine learning predictions
Tomasz Kaczmarek, Katarzyna Perez
Economic Research-Ekonomska Istraživanja (2021) Vol. 35, Iss. 1, pp. 19-37
Open Access | Times Cited: 28
Exploring the effectiveness of deep neural networks with technical analysis applied to stock market prediction
Ming-Che Lee, Jia-Wei Chang, Jason C. Hung, et al.
Computer Science and Information Systems (2021) Vol. 18, Iss. 2, pp. 401-418
Open Access | Times Cited: 28
Identifying research trends of machine learning in business: a topic modeling approach
Paritosh Pramanik, Rabin K. Jana
Measuring Business Excellence (2022) Vol. 27, Iss. 4, pp. 602-633
Closed Access | Times Cited: 21
Beyond Fama-French Factors: Alpha from Short-Term Signals
David Blitz, Matthias X. Hanauer, Iman Honarvar, et al.
Financial Analysts Journal (2023) Vol. 79, Iss. 4, pp. 96-117
Closed Access | Times Cited: 11
Fundamental Analysis via Machine Learning
Kai Cao, Haifeng You
Financial Analysts Journal (2024) Vol. 80, Iss. 2, pp. 74-98
Open Access | Times Cited: 4
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