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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:

Modal decomposition-based hybrid model for stock index prediction
Pin Lv, Yating Shu, Jia Xu, et al.
Expert Systems with Applications (2022) Vol. 202, pp. 117252-117252
Closed Access | Times Cited: 35

Showing 1-25 of 35 citing articles:

Forecasting long-term stock prices of global indices: A forward-validating Genetic Algorithm optimization approach for Support Vector Regression
Mohit Beniwal, Archana Singh, Nand Kumar
Applied Soft Computing (2023) Vol. 145, pp. 110566-110566
Closed Access | Times Cited: 39
Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method
Irene Karijadi, Shuo‐Yan Chou, Anindhita Dewabharata
Renewable Energy (2023) Vol. 218, pp. 119357-119357
Closed Access | Times Cited: 39
A hybrid approach of wavelet transform, ARIMA and LSTM model for the share price index futures forecasting
Junting Zhang, Haifei Liu, Wei Bai, et al.
The North American Journal of Economics and Finance (2023) Vol. 69, pp. 102022-102022
Closed Access | Times Cited: 24
Multi-decomposition in deep learning models for futures price prediction
Yuping Song, Jiefei Huang, Yang Xu, et al.
Expert Systems with Applications (2024) Vol. 246, pp. 123171-123171
Closed Access | Times Cited: 8
McVCsB: A new hybrid deep learning network for stock index prediction
Chenhao Cui, Peiwan Wang, Yong Li, et al.
Expert Systems with Applications (2023) Vol. 232, pp. 120902-120902
Closed Access | Times Cited: 20
A stock series prediction model based on variational mode decomposition and dual-channel attention network
Yepeng Liu, Siyuan Huang, Xiaoyi Tian, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 121708-121708
Closed Access | Times Cited: 18
Boosting the accuracy of stock market prediction via multi-layer hybrid MTL structure
Y.-W. Peter Hong
Intelligent Decision Technologies (2025)
Open Access
STAGE framework: A stock dynamic anomaly detection and trend prediction model based on graph attention network and sparse spatiotemporal convolutional network
Ming Wang Shi, Roznim Mohamad Rasli, Shir Li Wang
PLoS ONE (2025) Vol. 20, Iss. 3, pp. e0318939-e0318939
Open Access
A Machine Learning Approach for Investigating the Determinants of Stock Price Crash Risk: Exploiting Firm and CEO Characteristics
Yunuo Li, Huiyuan Xue, Shiyu Wei, et al.
Systems (2024) Vol. 12, Iss. 5, pp. 143-143
Open Access | Times Cited: 4
MDF-DMC: A stock prediction model combining multi-view stock data features with dynamic market correlation information
Zhen Hua Yang, Tianlong Zhao, Suwei Wang, et al.
Expert Systems with Applications (2023) Vol. 238, pp. 122134-122134
Closed Access | Times Cited: 10
Multi-step prediction of carbon emissions based on a secondary decomposition framework coupled with stacking ensemble strategy
Boting Zhang, Liwen Ling, Liling Zeng, et al.
Environmental Science and Pollution Research (2023) Vol. 30, Iss. 27, pp. 71063-71087
Open Access | Times Cited: 8
Can real-time investor sentiment help predict the high-frequency stock returns? Evidence from a mixed-frequency-rolling decomposition forecasting method
Yi Cai, Zhenpeng Tang, Ying Chen
The North American Journal of Economics and Finance (2024) Vol. 72, pp. 102147-102147
Closed Access | Times Cited: 2
Town gas daily load forecasting based on machine learning combinatorial algorithms: A case study in North China
Peng Xu, Yuwei Song, Jingbo Du, et al.
Chinese Journal of Chemical Engineering (2024) Vol. 75, pp. 239-252
Closed Access | Times Cited: 2
CEGH: A Hybrid Model Using CEEMD, Entropy, GRU, and History Attention for Intraday Stock Market Forecasting
YI-JIAO LIU, Xinghua Liu, Yuxin Zhang, et al.
Entropy (2022) Vol. 25, Iss. 1, pp. 71-71
Open Access | Times Cited: 12
A Survey on Stock Market Prediction Techniques
C A Krishnapriya, Ajay James
2020 International Conference on Power, Instrumentation, Control and Computing (PICC) (2023), pp. 1-6
Closed Access | Times Cited: 6
Forecasting Bitcoin Prices Using Deep Learning for Consumer-Centric Industrial Applications
Pradeep Kumar Roy, Abhinav Kumar, Ashish Singh, et al.
IEEE Transactions on Consumer Electronics (2023) Vol. 70, Iss. 1, pp. 1351-1358
Closed Access | Times Cited: 5
Advancing Financial Forecasts: A Deep Dive into Memory Attention and Long-Distance Loss in Stock Price Predictions
Shijie Yang, Yining Ding, Boyu Xie, et al.
Applied Sciences (2023) Vol. 13, Iss. 22, pp. 12160-12160
Open Access | Times Cited: 5
Volatility index prediction based on a hybrid deep learning system with multi-objective optimization and mode decomposition
Chaonan Tian, Tong Niu, Wei Wei
Expert Systems with Applications (2022) Vol. 213, pp. 119184-119184
Closed Access | Times Cited: 8
Improving Prediction of Bursa Malaysia Stock Index Using Time Series and Deep Learning Hybrid Model
Abang Mohammad Hudzaifah Abang Shakawi, Ani Shabri
Lecture notes on data engineering and communications technologies (2024), pp. 119-128
Closed Access | Times Cited: 1
Analyzing the critical steps in deep learning-based stock forecasting: a literature review
Zinnet Duygu Akşehır, Erdal Kılıç
PeerJ Computer Science (2024) Vol. 10, pp. e2312-e2312
Open Access | Times Cited: 1
Multi-scale contrast approach for stock index prediction with adaptive stock fusion
Jianliang Gao, Shenwei Wang, Changlong He, et al.
Expert Systems with Applications (2024), pp. 125590-125590
Closed Access | Times Cited: 1
Experimental analysis of similarity measurements for multivariate time series and its application to the stock market
Zhong-Liang Xiang, Rui Wang, Xiang-Ru Yu, et al.
Applied Intelligence (2023) Vol. 53, Iss. 21, pp. 25450-25466
Closed Access | Times Cited: 3
Adaptive Meta-Learning Probabilistic Inference Framework for Long Sequence Prediction
Jianping Zhu, Xin Guo, Chen Yang, et al.
Proceedings of the AAAI Conference on Artificial Intelligence (2024) Vol. 38, Iss. 15, pp. 17159-17166
Open Access
A parallel hybrid neural networks model for forecasting returns with candlestick technical trading strategy
Min Zhu, Yu Guo, Yuping Song
Expert Systems with Applications (2024) Vol. 255, pp. 124486-124486
Closed Access
Sglnet: A Self-Supervised Framework for Stock Price Prediction
Jiayi Xu, Yong Li
(2024)
Closed Access
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