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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:

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

Showing 1-25 of 38 citing articles:

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
Estimating Stock Market Betas via Machine Learning
Wolfgang Drobetz, Fabian Hollstein, Tizian Otto, et al.
Journal of Financial and Quantitative Analysis (2024), pp. 1-37
Closed Access | Times Cited: 7
Machine learning and the cross-section of cryptocurrency returns
Nusret Cakici, Syed Jawad Hussain Shahzad, Barbara Będowska-Sójka, et al.
International Review of Financial Analysis (2024) Vol. 94, pp. 103244-103244
Closed Access | Times Cited: 6
Credit Card Default Prediction: An Empirical Analysis on Predictive Performance Using Statistical and Machine Learning Methods
Rakshith Bhandary, Bidyut Kumar Ghosh
Journal of risk and financial management (2025) Vol. 18, Iss. 1, pp. 23-23
Open Access
Forecasting Stock Market Crashes via Machine Learning
Hubert Dichtl, Wolfgang Drobetz, Tizian Otto
Journal of Financial Stability (2022) Vol. 65, pp. 101099-101099
Closed Access | Times Cited: 18
Towards Virtual 3D Asset Price Prediction Based on Machine Learning
Jakob J. Korbel, Umar H. Siddiq, Rüdiger Zarnekow
Journal of theoretical and applied electronic commerce research (2022) Vol. 17, Iss. 3, pp. 924-948
Open Access | Times Cited: 16
Stock return prediction with multiple measures using neural network models
C. Edward Wang
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 3
Predicting Corporate Bond Illiquidity via Machine Learning
Axel Cabrol, Wolfgang Drobetz, Tizian Otto, et al.
Financial Analysts Journal (2024) Vol. 80, Iss. 3, pp. 103-127
Open Access | Times Cited: 3
Interaction effects in the cross-section of country and industry returns
Zaghum Umar, Adam Zaremba, Mehmet Umutlu, et al.
Journal of Banking & Finance (2024) Vol. 165, pp. 107200-107200
Closed Access | Times Cited: 2
Machine learning techniques for cross-sectional equity returns’ prediction
Christian Fieberg, Daniel Metko, Thorsten Poddig, et al.
OR Spectrum (2022) Vol. 45, Iss. 1, pp. 289-323
Open Access | Times Cited: 10
Stock Market Anomalies and Machine Learning Across the Globe
Vitor Azevedo, Sebastian Kaiser, Sebastian Müller
SSRN Electronic Journal (2022)
Closed 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
Forecasting Korean Stock Returns with Machine Learning
Hohsuk Noh, Hyuna Jang, Cheol‐Won Yang
Asia-Pacific Journal of Financial Studies (2023) Vol. 52, Iss. 2, pp. 193-241
Open Access | Times Cited: 4
Exploring Low-Risk Anomalies: A Dynamic CAPM Utilizing a Machine Learning Approach
Jiawei Wang, Zhen Chen
Mathematics (2023) Vol. 11, Iss. 14, pp. 3220-3220
Open Access | Times Cited: 4
Enhancing Digital Cryptocurrency Trading Price Prediction with an Attention-Based Convolutional and Recurrent Neural Network Approach: The Case of Ethereum
Dawei Shang, Z. J. Guo, Hui Wang
Finance research letters (2024) Vol. 67, pp. 105846-105846
Closed Access | Times Cited: 1
Asset Pricing and Portfolio Investment Management Using Machine Learning: Research Trend Analysis Using Scientometrics
Chao Meng, Chen Chen, Heng Xu, et al.
Economics (2024) Vol. 18, Iss. 1
Open Access | Times Cited: 1
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
What drives stock returns across countries? Insights from machine learning models
Nusret Cakici, Adam Zaremba
International Review of Financial Analysis (2024), pp. 103569-103569
Open Access | Times Cited: 1
Estimating Security Betas via Machine Learning
Wolfgang Drobetz, Fabian Hollstein, Tizian Otto, et al.
SSRN Electronic Journal (2021)
Closed Access | Times Cited: 10
The Term Structure of Machine Learning Alpha
David Blitz, Matthias X. Hanauer, Tobias Hoogteijling, et al.
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 3
From Reactive to Proactive Volatility Modeling with Hemisphere Neural Networks
Philippe Goulet Coulombe, Mikael Frenette, Karin Klieber
SSRN Electronic Journal (2023)
Open Access | Times Cited: 3
Prediction-based mean–variance portfolios with risk budgeting based on neural networks
Yilin Ma, Yudong Wang, Weizhong Wang, et al.
Expert Systems with Applications (2023) Vol. 230, pp. 120638-120638
Closed Access | Times Cited: 3
Machine Learning Goes Global: Cross-Sectional Return Predictability in International Stock Markets
Nusret Cakici, Christian Fieberg, Daniel Metko, et al.
SSRN Electronic Journal (2022)
Closed Access | Times Cited: 3
Generative AI for European Asset Pricing: Alleviating the Momentum Anomaly
Matthias Mattusch
SSRN Electronic Journal (2024)
Closed Access
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