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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:

Volatility forecasting using deep neural network with time-series feature embedding
Wei-Jie Chen, Jingjing Yao, Yuan‐Hai Shao
Economic Research-Ekonomska Istraživanja (2022) Vol. 36, Iss. 1, pp. 1377-1401
Open Access | Times Cited: 16

Showing 16 citing articles:

Options-driven volatility forecasting
Nikolas Michael, Mihai Cucuringu, Sam Howison
Quantitative Finance (2025), pp. 1-28
Open Access
Forecasting realized volatility through financial turbulence and neural networks
Hugo Gobato Souto, Amir Moradi
Economics and Business Review/˜The œPoznań University of Economics Review (2023) Vol. 9, Iss. 2
Open Access | Times Cited: 12
Forecasting the Volatility of the Russian Stock Market in the Context of International Economic Sanctions
A. G. Glebova, А. А. Ковалева
Finance Theory and Practice (2024) Vol. 28, Iss. 1, pp. 20-29
Open Access | Times Cited: 4
How good are different machine and deep learning models in forecasting the future price of metals? Full sample versus sub-sample
A.S. Amirtha Varshini, Parthajit Kayal, Moinak Maiti
Resources Policy (2024) Vol. 92, pp. 105040-105040
Open Access | Times Cited: 3
Can transformers transform financial forecasting?
Hugo Gobato Souto, Amir Moradi
China Finance Review International (2024)
Closed Access | Times Cited: 3
Charting new avenues in financial forecasting with TimesNet: The impact of intraperiod and interperiod variations on realized volatility prediction
Hugo Gobato Souto
Expert Systems with Applications (2024) Vol. 255, pp. 124851-124851
Closed Access | Times Cited: 2
Optimizing multi-time series forecasting for enhanced cloud resource utilization based on machine learning
Mateusz Smendowski, Piotr Nawrocki
Knowledge-Based Systems (2024) Vol. 304, pp. 112489-112489
Open Access | Times Cited: 2
Linex and double-linex regression for parameter estimation and forecasting
Efthymios G. Tsionas
Annals of Operations Research (2022) Vol. 323, Iss. 1-2, pp. 229-245
Closed Access | Times Cited: 4
Options-driven Volatility Forecasting
Nikolas Michael, Mihai Cucuringu, Sam Howison
SSRN Electronic Journal (2024)
Closed Access
Time-mixing and Feature-mixing Modelling for Realized Volatility Forecast: Evidence from TSMixer Model
Hugo Gobato Souto, Storm Koert Heuvel, Francisco Louzada
The Journal of Finance and Data Science (2024), pp. 100143-100143
Open Access
Diffusion Convolution Neural Network-Based Multiview Gesture Recognition for Athletes in Dynamic Scenes
Qingyun Wang, Hua Li
Journal of Circuits Systems and Computers (2023) Vol. 33, Iss. 06
Closed Access | Times Cited: 1
TimesNet for Realized Volatility Prediction
Hugo Gobato Souto
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 1
Adaptive MLELM-AE model for efficient prediction of stock market data
Ajit Kumar Rout, Abhisek Sethy, Soumya Ranjan Nayak
Journal of Statistics and Management Systems (2022) Vol. 25, Iss. 7, pp. 1541-1552
Closed Access | Times Cited: 1
Neural Networks in Forecasting Financial Volatility
Wenbo Ge, Pooia Lalbakhsh, Leigh Isai, et al.
Lecture notes in computer science (2023), pp. 178-189
Closed Access
Novel Deep Learning Network Architectures for Time Series Forecasting
Jitendra Kumar Katariya, D. Yadav, C. Gayathri, et al.
(2023), pp. 392-398
Closed Access
FORECASTING FINANCIAL VOLATILITY USING DEEP LEARNING APPROACH
Yaroslav Verbytskyi
(2022)
Open Access
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