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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:

Building News Measures from Textual Data and an Application to Volatility Forecasting
Massimiliano Caporin, Francesco Poli
Econometrics (2017) Vol. 5, Iss. 3, pp. 35-35
Open Access | Times Cited: 39

Showing 1-25 of 39 citing articles:

The impact of sentiment and attention measures on stock market volatility
Francesco Audrino, Fabio Sigrist, Daniele Ballinari
International Journal of Forecasting (2019) Vol. 36, Iss. 2, pp. 334-357
Open Access | Times Cited: 239
A Machine Learning Approach to Volatility Forecasting
Kim Christensen, Mathias Siggaard, Bezirgen Veliyev
Journal of Financial Econometrics (2022) Vol. 21, Iss. 5, pp. 1680-1727
Open Access | Times Cited: 90
The impact of Baidu Index sentiment on the volatility of China's stock markets
Jianchun Fang, Giray Gözgör, Chi Keung Marco Lau, et al.
Finance research letters (2019) Vol. 32, pp. 101099-101099
Open Access | Times Cited: 115
ECONOMETRICS MEETS SENTIMENT: AN OVERVIEW OF METHODOLOGY AND APPLICATIONS
Andres Algaba, David Ardia, Keven Bluteau, et al.
Journal of Economic Surveys (2020) Vol. 34, Iss. 3, pp. 512-547
Open Access | Times Cited: 109
Influences of sentiment from news articles on EU carbon prices
Jing Ye, Minggao Xue
Energy Economics (2021) Vol. 101, pp. 105393-105393
Closed Access | Times Cited: 48
Is Baidu index really powerful to predict the Chinese stock market volatility? New evidence from the internet information
Qiaoqi Lang, Jiqian Wang, Feng Ma, et al.
China Finance Review International (2021) Vol. 13, Iss. 2, pp. 263-284
Closed Access | Times Cited: 45
Forecasting the S&P 500 Index Using Mathematical-Based Sentiment Analysis and Deep Learning Models: A FinBERT Transformer Model and LSTM
Ji-Hwan Kim, Hui-Sang Kim, Sun‐Yong Choi
Axioms (2023) Vol. 12, Iss. 9, pp. 835-835
Open Access | Times Cited: 17
A sentiment analysis approach to the prediction of market volatility
Justina Deveikyte, Hélyette Geman, Carlo Piccari, et al.
Frontiers in Artificial Intelligence (2022) Vol. 5
Open Access | Times Cited: 26
Hunting the quicksilver: Using textual news and causality analysis to predict market volatility
Ameet Kumar Banerjee, Andreia Dionísio, H. K. Pradhan, et al.
International Review of Financial Analysis (2021) Vol. 77, pp. 101848-101848
Open Access | Times Cited: 27
How to calm down the markets? The effects of COVID-19 economic policy responses on financial market uncertainty
Oleg Deev, Tomáš Plíhal
Research in International Business and Finance (2022) Vol. 60, pp. 101613-101613
Open Access | Times Cited: 20
The US banking crisis in 2023: Intraday attention and price variation of banks at risk
Štefan Lyócsa, Martina Halousková, Erik Haugom
Finance research letters (2023) Vol. 57, pp. 104209-104209
Open Access | Times Cited: 11
Time and frequency relationship between household investors’ sentiment index and US industry stock returns
Muhammad Asif Khan, José Arreola Hernández, Syed Jawad Hussain Shahzad
Finance research letters (2019) Vol. 36, pp. 101318-101318
Closed Access | Times Cited: 32
A Hybrid Neural Network Model for Sentiment Analysis of Financial Texts Using Topic Extraction, Pre-Trained Model, and Enhanced Attention Mechanism Methods
Ganglong Duan, Shunfei Yan, Meng Zhang
IEEE Access (2024) Vol. 12, pp. 98207-98224
Open Access | Times Cited: 3
The R Package sentometrics to Compute, Aggregate, and Predict with Textual Sentiment
David Ardia, Keven Bluteau, Samuel Borms, et al.
Journal of Statistical Software (2021) Vol. 99, Iss. 2
Open Access | Times Cited: 20
How do big markets react to investors’ sentiments on firm tweets?
Ahmed Hassanein, Mohamed M. Mostafa, Kameleddine Benameur, et al.
Journal of Sustainable Finance & Investment (2021) Vol. 14, Iss. 1, pp. 1-23
Closed Access | Times Cited: 19
Forecasting Crude Oil Volatility Using the Deep Learning‐Based Hybrid Models With Common Factors
Ke Yang, Nan Hu, Fengping Tian
Journal of Futures Markets (2024) Vol. 44, Iss. 8, pp. 1429-1446
Closed Access | Times Cited: 2
The R Package sentometrics to Compute, Aggregate and Predict with Textual Sentiment
David Ardia, Keven Bluteau, Samuel Borms, et al.
SSRN Electronic Journal (2017)
Open Access | Times Cited: 20
Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK
Mohammad Alomari, Abdel Razzaq Al Rababa’a, Ghaith El-Nader, et al.
The Quarterly Review of Economics and Finance (2021) Vol. 82, pp. 280-297
Closed Access | Times Cited: 14
Impact of public news sentiment on stock market index return and volatility
Gianluca Anese, Marco Corazza, Michele Costola, et al.
Computational Management Science (2023) Vol. 20, Iss. 1
Closed Access | Times Cited: 4
The extra value of online investor sentiment measures on forecasting stock return volatility: A large-scale longitudinal evaluation based on Chinese stock market
Ping Lin, Shaohui Ma, Robert Fildes
Expert Systems with Applications (2023) Vol. 238, pp. 121927-121927
Closed Access | Times Cited: 4
News and intraday jumps: Evidence from regularization and class imbalance
Massimiliano Caporin, Francesco Poli
The North American Journal of Economics and Finance (2022) Vol. 62, pp. 101743-101743
Closed Access | Times Cited: 7
Media Coverage and Decomposition of Stock Market Volatility:Based on the Generalized Dynamic Factor Model
Haishu Qiao, Yaya Su
Emerging Markets Finance and Trade (2019) Vol. 56, Iss. 3, pp. 613-625
Closed Access | Times Cited: 10
The Impact of Sentiment and Attention Measures on Stock Market Volatility
Francesco Audrino, Fabio Sigrist, Daniele Ballinari
SSRN Electronic Journal (2018)
Closed Access | Times Cited: 10
Econometrics Meets Sentiment: An Overview of Methodology and Applications
Andres Algaba, David Ardia, Keven Bluteau, et al.
SSRN Electronic Journal (2019)
Open Access | Times Cited: 10
Forecasting oil futures realized range‐based volatility with jumps, leverage effect, and regime switching: New evidence from MIDAS models
Xinjie Lu, Feng Ma, Jiqian Wang, et al.
Journal of Forecasting (2021) Vol. 41, Iss. 4, pp. 853-868
Closed Access | Times Cited: 6
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