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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:

Topological tail dependence: Evidence from forecasting realized volatility
Hugo Gobato Souto
The Journal of Finance and Data Science (2023) Vol. 9, pp. 100107-100107
Open Access | Times Cited: 14

Showing 14 citing articles:

Topology Unveiled: A New Horizon for Economic and Financial Modeling
Yicheng Wei, Junzo Watada, Zijin Wang
Mathematics (2025) Vol. 13, Iss. 2, pp. 325-325
Open Access
Evaluating the Efficacy of NHITS for Forecasting Stock Realized Volatility: A Comparative Analysis with Established Models
Hugo Gobato Souto
Computational Economics (2025)
Closed Access
A novel loss function for neural network models exploring stock realized volatility using Wasserstein Distance
Hugo Gobato Souto, Amir Moradi
Decision Analytics Journal (2023) Vol. 10, pp. 100369-100369
Open Access | Times Cited: 9
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: 3
A generalization of the Topological Tail Dependence theory: From indices to individual stocks
Hugo Gobato Souto, Amir Moradi
Decision Analytics Journal (2024) Vol. 12, pp. 100512-100512
Open Access | Times Cited: 2
NHITS for Forecasting Stock Realized Volatility
Hugo Gobato Souto
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 4
TimesNet for Realized Volatility Prediction
Hugo Gobato Souto
SSRN Electronic Journal (2023)
Closed Access | Times Cited: 1
Yang & Zhang’s realized volatility: Automated estimation in Python
Hugo Gobato Souto, Amir Moradi
Software Impacts (2024) Vol. 19, pp. 100613-100613
Open Access
Wasserstein distance loss function for financial time series deep learning
Hugo Gobato Souto, Amir Moradi
Software Impacts (2024) Vol. 20, pp. 100639-100639
Open Access
FinTDA: Python package for estimating market change through persistent homology diagrams
Hugo Gobato Souto, Ismail Baris, Storm Koert Heuvel, et al.
Software Impacts (2024) Vol. 20, pp. 100637-100637
Open Access
THE DURATION OF THE IMPACT OF THE “INVESTOR FEAR INDEX” ON THE RUSSIAN STOCK MARKET
Lyudmila I. Tenkovskaya
Economics Profession Business (2024), Iss. 1, pp. 77-84
Open Access
Forecasting Bitcoin Volatility and Value-at-Risk Using Stacking Machine Learning Models With Intraday Data
Arash Pourrezaee, Ehsan Hajizadeh
Computational Economics (2024)
Closed Access
Identifying extreme events in the stock market: A topological data analysis
Anish Rai, Buddha Nath Sharma, Salam Rabindrajit Luwang, et al.
Chaos An Interdisciplinary Journal of Nonlinear Science (2024) Vol. 34, Iss. 10
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
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