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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:

Tree-Based Conditional Portfolio Sorts: The Relation between Past and Future Stock Returns
Benjamin Moritz, Tom Zimmermann
SSRN Electronic Journal (2016)
Closed Access | Times Cited: 120

Showing 1-25 of 120 citing articles:

Empirical Asset Pricing via Machine Learning
Shihao Gu, Bryan Kelly, Dacheng Xiu
Review of Financial Studies (2020) Vol. 33, Iss. 5, pp. 2223-2273
Open Access | Times Cited: 1399
Shrinking the cross-section
Serhiy Kozak, Stefan Nagel, Shrihari Santosh
Journal of Financial Economics (2019) Vol. 135, Iss. 2, pp. 271-292
Closed Access | Times Cited: 569
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500
Christopher Krauß, Xuan Anh, Nicolas Huck
European Journal of Operational Research (2016) Vol. 259, Iss. 2, pp. 689-702
Closed Access | Times Cited: 488
Stock Market Prediction Using LSTM Recurrent Neural Network
Adil Moghar, Mhamed Hamiche
Procedia Computer Science (2020) Vol. 170, pp. 1168-1173
Open Access | Times Cited: 476
Empirical Asset Pricing via Machine Learning
Shihao Gu, Bryan Kelly, Dacheng Xiu
(2018)
Open Access | Times Cited: 351
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
Forest Through the Trees: Building Cross-Sections of Stock Returns
Svetlana Bryzgalova, Markus Pelger, Jason Zhu
SSRN Electronic Journal (2019)
Closed Access | Times Cited: 130
Deep Learning in Asset Pricing
Luyang Chen, Markus Pelger, Jason Zhu
SSRN Electronic Journal (2019)
Open Access | Times Cited: 98
ESG score prediction through random forest algorithm
Valeria D’Amato, Rita L. D’Ecclesia, Susanna Levantesi
Computational Management Science (2021) Vol. 19, Iss. 2, pp. 347-373
Closed Access | Times Cited: 71
A comprehensive review on multiple hybrid deep learning approaches for stock prediction
Jaimin Shah, Darsh Vaidya, Manan Shah
Intelligent Systems with Applications (2022) Vol. 16, pp. 200111-200111
Open Access | Times Cited: 67
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
Using methods from machine learning to evaluate behavioral models of choice under risk and ambiguity
Alexander Peysakhovich, Jeffrey Naecker
Journal of Economic Behavior & Organization (2016) Vol. 133, pp. 373-384
Closed Access | Times Cited: 73
Fundamental ratios as predictors of ESG scores: a machine learning approach
Valeria D’Amato, Rita L. D’Ecclesia, Susanna Levantesi
Decisions in Economics and Finance (2021) Vol. 44, Iss. 2, pp. 1087-1110
Closed Access | Times Cited: 51
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
The economic and financial properties of crude oil: A review
Korbinian Lang, Benjamin Auer
The North American Journal of Economics and Finance (2019) Vol. 52, pp. 100914-100914
Closed Access | Times Cited: 53
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
Intelligent Finance: Emerging Applications and Challenges of Machine Learning in Asset Pricing
Yang Jiang
Advances in Economics Management and Political Sciences (2025) Vol. 156, Iss. 1, pp. 11-20
Closed Access
Spanning the Achievable Stochastic Discount Factor with Asset Pricing Trees
Cil Bemelmans, Rasmus Lönn, Anastasija Tetereva
(2025)
Closed Access
Enhancing real estate investment trust return forecasts using machine learning
Kahshin Leow, Thies Lindenthal
Real Estate Economics (2025)
Open Access
Threshold-based portfolio: the role of the threshold and its applications
Sang Il Lee, Seong Joon Yoo
The Journal of Supercomputing (2018) Vol. 76, Iss. 10, pp. 8040-8057
Closed Access | Times Cited: 44
AlphaPortfolio for Investment and Economically Interpretable AI
Lin William Cong, Ke Tang, Jingyuan Wang, et al.
SSRN Electronic Journal (2020)
Closed Access | Times Cited: 34
Machine learning in empirical asset pricing
Alois Weigand
Financial markets and portfolio management (2019) Vol. 33, Iss. 1, pp. 93-104
Closed Access | Times Cited: 32
Machine Learning for Active Portfolio Management
Söhnke M. Bartram, Jürgen Branke, Giuliano De Rossi, et al.
The Journal of Financial Data Science (2021) Vol. 3, Iss. 3, pp. 9-30
Open Access | Times Cited: 25
Enhancing stock market anomalies with machine learning
Vitor Azevedo, Christopher Hoegner
Review of Quantitative Finance and Accounting (2022) Vol. 60, Iss. 1, pp. 195-230
Open Access | Times Cited: 16
Deep Learning and the Cross-Section of Expected Returns
Marcial Messmer
SSRN Electronic Journal (2017)
Closed Access | Times Cited: 29
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