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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 26-50 of 409 citing articles:

Follow the Trail: Machine Learning for Fraud Detection in Fintech Applications
Branka Stojanović, Josip Božić, Katharina Hofer-Schmitz, et al.
Sensors (2021) Vol. 21, Iss. 5, pp. 1594-1594
Open Access | Times Cited: 63
Prediction of stock market index based on ISSA-BP neural network
Xin Liu, Junhong Guo, Hua Wang, et al.
Expert Systems with Applications (2022) Vol. 204, pp. 117604-117604
Closed Access | Times Cited: 61
Stock-Price Forecasting Based on XGBoost and LSTM
Pham Hoang Vuong, Tan Dat Trinh, Tieu Khoi, et al.
Computer Systems Science and Engineering (2021) Vol. 40, Iss. 1, pp. 237-246
Open Access | Times Cited: 56
Prediction of wind turbine blade icing fault based on selective deep ensemble model
Jin Xiao, Chunyan Li, Бо Лю, et al.
Knowledge-Based Systems (2022) Vol. 242, pp. 108290-108290
Closed Access | Times Cited: 56
Forecasting stock market for an efficient portfolio by combining XGBoost and Hilbert–Huang​ transform
Arsalan Dezhkam, Mohammad Taghi Manzuri
Engineering Applications of Artificial Intelligence (2022) Vol. 118, pp. 105626-105626
Closed Access | Times Cited: 55
Interpretable deep learning LSTM model for intelligent economic decision-making
Sangjin Park, Jae‐Suk Yang
Knowledge-Based Systems (2022) Vol. 248, pp. 108907-108907
Closed Access | Times Cited: 47
Neural network predictions of the high-frequency CSI300 first distant futures trading volume
Xiaojie Xu, Yun Zhang
Financial markets and portfolio management (2022) Vol. 37, Iss. 2, pp. 191-207
Closed Access | Times Cited: 40
High-frequency CSI300 futures trading volume predicting through the neural network
Xiaojie Xu, Yun Zhang
Asian Journal of Economics and Banking (2023) Vol. 8, Iss. 1, pp. 26-53
Open Access | Times Cited: 32
Machine learning techniques for stock price prediction and graphic signal recognition
Junde Chen, Yuxin Wen, Yaser A. Nanehkaran, et al.
Engineering Applications of Artificial Intelligence (2023) Vol. 121, pp. 106038-106038
Closed Access | Times Cited: 25
Modelling bank customer behaviour using feature engineering and classification techniques
Mohammad Zoynul Abedin, Petr Hájek, Taimur Sharif, et al.
Research in International Business and Finance (2023) Vol. 65, pp. 101913-101913
Open Access | Times Cited: 24
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
Machine learning in business and finance: a literature review and research opportunities
Hanyao Gao, Gang Kou, Haiming Liang, et al.
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 10
A hybrid model for stock price prediction based on multi-view heterogeneous data
Wen Long, Jing Gao, Kehan Bai, et al.
Financial Innovation (2024) Vol. 10, Iss. 1
Open Access | Times Cited: 9
Optimizing portfolio selection through stock ranking and matching: A reinforcement learning approach
Chaher Alzaman
Expert Systems with Applications (2025), pp. 126430-126430
Closed Access | Times Cited: 1
LSTM–Transformer-Based Robust Hybrid Deep Learning Model for Financial Time Series Forecasting
Md Rizwanul Kabir, Dipayan Bhadra, Moinul Ridoy, et al.
Sci (2025) Vol. 7, Iss. 1, pp. 7-7
Open Access | Times Cited: 1
Using CNN to Model Stock Prices
Mitja Steinbacher, Matej Steinbacher, Matjaž Steinbacher
Computational Economics (2025)
Closed Access | Times Cited: 1
A Novel Approach to Short-Term Stock Price Movement Prediction using Transfer Learning
Thi-Thu Nguyen, Seokhoon Yoon
Applied Sciences (2019) Vol. 9, Iss. 22, pp. 4745-4745
Open Access | Times Cited: 62
Deep Learning for Price Movement Prediction Using Convolutional Neural Network and Long Short-Term Memory
Can Yang, Junjie Zhai, Guihua Tao
Mathematical Problems in Engineering (2020) Vol. 2020, pp. 1-13
Open Access | Times Cited: 58
A Labeling Method for Financial Time Series Prediction Based on Trends
Dingming Wu, Xiaolong Wang, Jingyong Su, et al.
Entropy (2020) Vol. 22, Iss. 10, pp. 1162-1162
Open Access | Times Cited: 56
A graph‐based convolutional neural network stock price prediction with leading indicators
Jimmy Ming‐Tai Wu, Zhongcui Li, Gautam Srivastava, et al.
Software Practice and Experience (2020) Vol. 51, Iss. 3, pp. 628-644
Closed Access | Times Cited: 52
Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators
Yaohao Peng, Pedro Henrique Melo Albuquerque, Herbert Kimura, et al.
Machine Learning with Applications (2021) Vol. 5, pp. 100060-100060
Open Access | Times Cited: 52
Price graphs: Utilizing the structural information of financial time series for stock prediction
Junran Wu, Ke Xu, Xueyuan Chen, et al.
Information Sciences (2021) Vol. 588, pp. 405-424
Open Access | Times Cited: 49
Predictive intelligence using ANFIS‐induced OWAWA for complex stock market prediction
Walayat Hussain, José M. Merigó, Muhammad Raheel Raza
International Journal of Intelligent Systems (2021) Vol. 37, Iss. 8, pp. 4586-4611
Open Access | Times Cited: 42
Efficient Prediction of Court Judgments Using an LSTM+CNN Neural Network Model with an Optimal Feature Set
Daniyal Alghazzawi, Omaimah Bamasag, Aiiad Albeshri, et al.
Mathematics (2022) Vol. 10, Iss. 5, pp. 683-683
Open Access | Times Cited: 37
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

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