Daniele Ballinari

Personal Details

First Name:	Daniele
Middle Name:
Last Name:	Ballinari
Suffix:
RePEc Short-ID:	pba1855
	[This author has chosen not to make the email address public]
	https://dballinari.github.io/

Affiliation

(50%) Schweizerische Nationalbank (SNB)

Bern/Zürich, Switzerland
http://www.snb.ch/
RePEc:edi:snbgvch (more details at EDIRC)

(50%) School of Economics and Political Science
Universität St. Gallen

Sankt Gallen, Switzerland
http://www.seps.unisg.ch/
RePEc:edi:vwasgch (more details at EDIRC)

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

1. Daniele Ballinari & Nora Bearth, 2024. "Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration," Papers 2409.04874, arXiv.org, revised Jan 2025.

   Cited by:

   1. Sven Klaassen & Jan Rabenseifner & Jannis Kueck & Philipp Bach, 2025. "Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators," Papers 2503.17290, arXiv.org, revised May 2025.

2. Daniele Ballinari & Alexander Wehrli, 2024. "Semiparametric inference for impulse response functions using double/debiased machine learning," Papers 2411.10009, arXiv.org.

   Cited by:

   1. Chris Hays & Manish Raghavan, 2025. "Double Machine Learning for Causal Inference under Shared-State Interference," Papers 2504.08836, arXiv.org.

3. Daniele Ballinari, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers 2403.01585, arXiv.org, revised Jun 2024.
   • Ballinari, Daniele, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Economics Letters, Elsevier, vol. 241(C).

   Cited by:

   1. Sven Klaassen & Jan Rabenseifner & Jannis Kueck & Philipp Bach, 2025. "Calibration Strategies for Robust Causal Estimation: Theoretical and Empirical Insights on Propensity Score-Based Estimators," Papers 2503.17290, arXiv.org, revised May 2025.
   2. Daniele Ballinari & Nora Bearth, 2024. "Improving the Finite Sample Estimation of Average Treatment Effects using Double/Debiased Machine Learning with Propensity Score Calibration," Papers 2409.04874, arXiv.org, revised Jan 2025.

Articles

1. Ballinari, Daniele, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Economics Letters, Elsevier, vol. 241(C).
   • Daniele Ballinari, 2024. "Calibrating doubly-robust estimators with unbalanced treatment assignment," Papers 2403.01585, arXiv.org, revised Jun 2024.
   See citations under working paper version above.
2. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).

   Cited by:

   1. Wen, Danyan & Zhang, Zihao & Nie, Jing & Cao, Yang, 2024. "Investor attention and anomalies: Evidence from the Chinese stock market," International Review of Financial Analysis, Elsevier, vol. 96(PB).
   2. Bouyaddou, Youssef & Jebabli, Ikram, 2025. "Integration of investor behavioral perspective and climate change in reinforcement learning for portfolio optimization," Research in International Business and Finance, Elsevier, vol. 73(PB).
   3. Sahar Arshad & Seemab Latif & Ahmad Salman & Rabia Latif, 2023. "Enhancing Profitability and Investor Confidence through Interpretable AI Models for Investment Decisions," Papers 2312.16223, arXiv.org, revised Jul 2024.
   4. Lu, Cheng & Ndiaye, Papa Momar & Simaan, Majeed, 2024. "Improved estimation of the correlation matrix using reinforcement learning and text-based networks," International Review of Financial Analysis, Elsevier, vol. 96(PA).
   5. Liu, Wenwen & Zhao, Peng & Luo, Ziyang & Tang, Miaomiao, 2024. "The dynamic impact of network attention on natural resources prices in pre-and post-Russian-Ukrainian war," Resources Policy, Elsevier, vol. 97(C).
   6. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
   7. Hoque, Mohammad Enamul & Billah, Mabruk & Alam, Md Rafayet & Lucey, Brian, 2024. "Does news related to digital economy and central bank digital currency affect digital economy ETFs? Evidence from TVP-VAR connectedness and wavelet local multiple correlation analyses," Global Finance Journal, Elsevier, vol. 61(C).

3. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.

   Cited by:

   1. Audrino, Francesco & Serwart, Jan, 2024. "Yield curve trading strategies exploiting sentiment data," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
   2. Qing Liu & Hosung Son, 2024. "Methods for aggregating investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-22, December.
   3. Martina Halouskov'a & v{S}tefan Ly'ocsa, 2025. "Forecasting U.S. equity market volatility with attention and sentiment to the economy," Papers 2503.19767, arXiv.org.
   4. John Hua Fan & Sebastian Binnewies & Sanuri De Silva, 2023. "Wisdom of crowds and commodity pricing," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 43(8), pages 1040-1068, August.

4. Audrino, Francesco & Sigrist, Fabio & Ballinari, Daniele, 2020. "The impact of sentiment and attention measures on stock market volatility," International Journal of Forecasting, Elsevier, vol. 36(2), pages 334-357.

   Cited by:

   1. Reyes, Tomas & Batista, Julian A. & Chacon, Alvaro & Martinez, Diego & Kausel, Edgar E., 2023. "Attention-driven reaction to extreme earnings surprises," The Quarterly Review of Economics and Finance, Elsevier, vol. 92(C), pages 230-248.
   2. Nico Knuth & Andreas Nastansky, 2025. "Anwendung von Deep Learning in der Prognose der Volatilität des DAX: Ein Vergleich der Prognosegüte von GARCH und LSTM," Statistische Diskussionsbeiträge 59, Universität Potsdam, Wirtschafts- und Sozialwissenschaftliche Fakultät.
   3. Jaydip Sen & Subhasis Dasgupta, 2023. "Portfolio Optimization: A Comparative Study," Papers 2307.05048, arXiv.org.
   4. Rui Liu & Jiayou Liang & Haolong Chen & Yujia Hu, 2024. "Analyst Reports and Stock Performance: Evidence from the Chinese Market," Papers 2411.08726, arXiv.org, revised Mar 2025.
   5. Gianna Figà-Talamanca & Marco Patacca, 2024. "An explorative analysis of sentiment impact on S&P 500 components returns, volatility and downside risk," Annals of Operations Research, Springer, vol. 342(3), pages 2095-2117, November.
   6. Martina Halouskov'a & Daniel Stav{s}ek & Mat'uv{s} Horv'ath, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Papers 2205.05985, arXiv.org, revised Aug 2022.
   7. Ballinari, Daniele & Audrino, Francesco & Sigrist, Fabio, 2022. "When does attention matter? The effect of investor attention on stock market volatility around news releases," International Review of Financial Analysis, Elsevier, vol. 82(C).
   8. Minh Vo, 2025. "Measuring and Forecasting Stock Market Volatilities with High-Frequency Data," Computational Economics, Springer;Society for Computational Economics, vol. 65(6), pages 3503-3544, June.
   9. Audrino, Francesco & Serwart, Jan, 2024. "Yield curve trading strategies exploiting sentiment data," The North American Journal of Economics and Finance, Elsevier, vol. 74(C).
   10. Qing Liu & Hosung Son, 2024. "Methods for aggregating investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-22, December.
   11. Ding, Hui & Huang, Yisu & Wang, Jiqian, 2023. "Have the predictability of oil changed during the COVID-19 pandemic: Evidence from international stock markets," International Review of Financial Analysis, Elsevier, vol. 87(C).
   12. Anastasiou, Dimitris & Ballis, Antonis & Drakos, Konstantinos, 2022. "Constructing a positive sentiment index for COVID-19: Evidence from G20 stock markets," International Review of Financial Analysis, Elsevier, vol. 81(C).
   13. Zhu, Haibin & Bai, Lu & He, Lidan & Liu, Zhi, 2023. "Forecasting realized volatility with machine learning: Panel data perspective," Journal of Empirical Finance, Elsevier, vol. 73(C), pages 251-271.
   14. Lin Wang & Wuyue An & Feng‐Ting Li, 2024. "Text‐based corn futures price forecasting using improved neural basis expansion network," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2042-2063, September.
   15. Mohamed Arbi Madani, 2025. "The S&P 500 sectoral indices responses to economic news sentiment," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(2), pages 2042-2060, April.
   16. Alin Marius Andries & Steven Ongena & Nicu Sprincean & Radu Tunaru, 2020. "Risk Spillovers and Interconnectedness between Systemically Important Institutions," Swiss Finance Institute Research Paper Series 20-40, Swiss Finance Institute.
       • Andrieş, Alin Marius & Ongena, Steven & Sprincean, Nicu & Tunaru, Radu, 2022. "Risk spillovers and interconnectedness between systemically important institutions," Journal of Financial Stability, Elsevier, vol. 58(C).
   17. Cheraghali, Hamid & Høydal, Hannah & Lysebo, Caroline & Molnár, Peter, 2023. "Consumer attention and company performance: Evidence from luxury companies," Finance Research Letters, Elsevier, vol. 58(PA).
   18. Chun, Dohyun & Cho, Hoon & Ryu, Doojin, 2023. "Discovering the drivers of stock market volatility in a data-rich world," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 82(C).
   19. Qingjie Zhou & Panpan Zhu & Yinpeng Zhang, 2023. "Contagion Spillover from Bitcoin to Carbon Futures Pricing: Perspective from Investor Attention," Energies, MDPI, vol. 16(2), pages 1-22, January.
   20. Ma, Tian & Li, Ganghui & Zhang, Huajing, 2024. "Stock return predictability using economic narrative: Evidence from energy sectors," Journal of Commodity Markets, Elsevier, vol. 35(C).
   21. Doris Chenguang Wu & Shiteng Zhong & Richard T R Qiu & Ji Wu, 2022. "Are customer reviews just reviews? Hotel forecasting using sentiment analysis," Tourism Economics, , vol. 28(3), pages 795-816, May.
   22. Abakah, Emmanuel Joel Aikins & Adeabah, David & Tiwari, Aviral Kumar & Abdullah, Mohammad, 2023. "Effect of Russia–Ukraine war sentiment on blockchain and FinTech stocks," International Review of Financial Analysis, Elsevier, vol. 90(C).
   23. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
   24. Tim Matthies & Thomas Lohden & Stephan Leible & Jun-Patrick Raabe, 2023. "To the Moon: Analyzing Collective Trading Events on the Wings of Sentiment Analysis," Papers 2308.09968, arXiv.org.
   25. Liang, Chao & Luo, Qin & Li, Yan & Huynh, Luu Duc Toan, 2023. "Global financial stress index and long-term volatility forecast for international stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 88(C).
   26. Zhang, Zhikai & He, Mengxi & Zhang, Yaojie & Wang, Yudong, 2021. "Realized skewness and the short-term predictability for aggregate stock market volatility," Economic Modelling, Elsevier, vol. 103(C).
   27. Liang, Chao & Tang, Linchun & Li, Yan & Wei, Yu, 2020. "Which sentiment index is more informative to forecast stock market volatility? Evidence from China," International Review of Financial Analysis, Elsevier, vol. 71(C).
   28. Naimoli, Antonio, 2023. "The information content of sentiment indices in forecasting Value at Risk and Expected Shortfall: a Complete Realized Exponential GARCH-X approach," International Economics, Elsevier, vol. 176(C).
   29. Gong, Xue & Zhang, Weiguo & Wang, Junbo & Wang, Chao, 2022. "Investor sentiment and stock volatility: New evidence," International Review of Financial Analysis, Elsevier, vol. 80(C).
   30. Mathieu Rosenbaum & Jianfei Zhang, 2022. "On the universality of the volatility formation process: when machine learning and rough volatility agree," Papers 2206.14114, arXiv.org.
   31. Chong Zhang & Xinyi Liu & Zhongmou Zhang & Mingyu Jin & Lingyao Li & Zhenting Wang & Wenyue Hua & Dong Shu & Suiyuan Zhu & Xiaobo Jin & Sujian Li & Mengnan Du & Yongfeng Zhang, 2024. "When AI Meets Finance (StockAgent): Large Language Model-based Stock Trading in Simulated Real-world Environments," Papers 2407.18957, arXiv.org, revised Sep 2024.
   32. Li, Zhao-Chen & Xie, Chi & Wang, Gang-Jin & Zhu, You & Zeng, Zhi-Jian & Gong, Jue, 2024. "Forecasting global stock market volatilities: A shrinkage heterogeneous autoregressive (HAR) model with a large cross-market predictor set," International Review of Economics & Finance, Elsevier, vol. 93(PB), pages 673-711.
   33. Bolin Lei & Yuping Song, 2024. "Volatility forecasting for stock market incorporating media reports, investors' sentiment, and attention based on MTGNN model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1706-1730, August.
   34. Wenting Liu & Zhaozhong Gui & Guilin Jiang & Lihua Tang & Lichun Zhou & Wan Leng & Xulong Zhang & Yujiang Liu, 2023. "Stock Volatility Prediction Based on Transformer Model Using Mixed-Frequency Data," Papers 2309.16196, arXiv.org.
   35. Roland Füss & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia In The Cross-Section of Global Equity," Working Papers on Finance 1913, University of St. Gallen, School of Finance, revised May 2020.
   36. Horváth, Roman & Kalistová, Anna & Lyócsa, Štefan & Miškufová, Marta & Moravcová, Michala, 2025. "Do hurricanes cause storm on the stock market? The case of US energy companies," International Review of Financial Analysis, Elsevier, vol. 97(C).
   37. Wei Zhang & Kai Yan & Dehua Shen, 2021. "Can the Baidu Index predict realized volatility in the Chinese stock market?," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-31, December.
   38. Huang, Yisu & Xu, Weiju & Huang, Dengshi & Zhao, Chenchen, 2023. "Chinese crude oil futures volatility and sustainability: An uncertainty indices perspective," Resources Policy, Elsevier, vol. 80(C).
   39. Vladimir Pyrlik & Pavel Elizarov & Aleksandra Leonova, 2021. "Forecasting Realized Volatility Using Machine Learning and Mixed-Frequency Data (the Case of the Russian Stock Market)," CERGE-EI Working Papers wp713, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
   40. Bouri, Elie & Gradojevic, Nikola & Nekhili, Ramzi, 2024. "Fear, extreme fear and U.S. stock market returns," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 656(C).
   41. Gaoshan Wang & Guangjin Yu & Xiaohong Shen, 2020. "The Effect of Online Investor Sentiment on Stock Movements: An LSTM Approach," Complexity, Hindawi, vol. 2020, pages 1-11, December.
   42. Weiguo Zhang & Xue Gong & Chao Wang & Xin Ye, 2021. "Predicting stock market volatility based on textual sentiment: A nonlinear analysis," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(8), pages 1479-1500, December.
   43. Qing Liu & Hosung Son, 2024. "Data selection and collection for constructing investor sentiment from social media," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-13, December.
   44. Mikhaylov, Dmitry, 2023. "Macroeconomic Forecasting with the Use of News Data," Working Papers w20220250, Russian Presidential Academy of National Economy and Public Administration.
   45. Filip, Angela Maria & Pochea, Maria Miruna, 2023. "Intentional and spurious herding behavior: A sentiment driven analysis," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
   46. He, Mengxi & Wen, Danyan & Xing, Lu & Zhang, Yaojie, 2024. "Industry volatility concentration and the predictability of aggregate stock market volatility," International Review of Economics & Finance, Elsevier, vol. 95(C).
   47. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020. "Fear of the coronavirus and the stock markets," EconStor Preprints 219336, ZBW - Leibniz Information Centre for Economics.
       • Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš & Molnár, Peter, 2020. "Fear of the coronavirus and the stock markets," Finance Research Letters, Elsevier, vol. 36(C).
   48. Wang, Gaoshan & Yu, Guangjin & Shen, Xiaohong, 2021. "The effect of online environmental news on green industry stocks: The mediating role of investor sentiment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 573(C).
   49. Tzu-Pu Chang & Yu-Wei Chan & Ping-Huang Wang, 2023. "Forecasting TAIEX and FITX with Affirmative and Doubtful Investor Sentiments," Bulletin of Applied Economics, Risk Market Journals, vol. 10(2), pages 127-140.
   50. Liu, Yuanyuan & Niu, Zibo & Suleman, Muhammad Tahir & Yin, Libo & Zhang, Hongwei, 2022. "Forecasting the volatility of crude oil futures: The role of oil investor attention and its regime switching characteristics under a high-frequency framework," Energy, Elsevier, vol. 238(PA).
   51. Martina Halouskov'a & v{S}tefan Ly'ocsa, 2025. "Forecasting U.S. equity market volatility with attention and sentiment to the economy," Papers 2503.19767, arXiv.org.
   52. Bickley, Steve J. & Brumpton, Martin & Chan, Ho Fai & Colthurst, Richard & Torgler, Benno, 2021. "The stabilizing effect of social distancing: Cross-country differences in financial market response to COVID-19 pandemic policies," Research in International Business and Finance, Elsevier, vol. 58(C).
   53. Wang, Ping & Han, Wei & Huang, Chengcheng & Duong, Duy, 2022. "Forecasting realised volatility from search volume and overnight sentiment: Evidence from China," Research in International Business and Finance, Elsevier, vol. 62(C).
   54. Masoud Ataei, 2025. "Modeling Regime Structure and Informational Drivers of Stock Market Volatility via the Financial Chaos Index," Papers 2504.18958, arXiv.org.
   55. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
   56. Yongan Xu & Jianqiong Wang & Zhonglu Chen & Chao Liang, 2023. "Sentiment indices and stock returns: Evidence from China," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 1063-1080, January.
   57. Guglielmo Maria Caporale & Kyriacos Kyriacou & Nicola Spagnolo, 2023. "Aggregate Insider Trading and Stock Market Volatility in the UK," CESifo Working Paper Series 10511, CESifo.
       • Caporale, Guglielmo Maria & Kyriacou, Kyriacos & Spagnolo, Nicola, 2023. "Aggregate insider trading and stock market volatility in the UK," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 89(C).
   58. v{S}tefan Ly'ocsa & Tom'av{s} Pl'ihal, 2022. "Russia's Ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Papers 2205.09179, arXiv.org.
   59. Yan Li & Weiping Li, 2021. "Empirical Analysis of MSCI China A-Shares," JRFM, MDPI, vol. 14(11), pages 1-25, October.
   60. Bai, Xiwen & Lam, Jasmine Siu Lee & Jakher, Astha, 2021. "Shipping sentiment and the dry bulk shipping freight market: New evidence from newspaper coverage," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 155(C).
   61. Alexander Jaax & Annabelle Mourougane & Frederic Gonzales, 2024. "Nowcasting services trade for the G7 economies," The World Economy, Wiley Blackwell, vol. 47(4), pages 1336-1386, April.
   62. Luo, Qin & Bu, Jinfeng & Xu, Weiju & Huang, Dengshi, 2023. "Stock market volatility prediction: Evidence from a new bagging model," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 445-456.
   63. Szczygielski, Jan Jakub & Charteris, Ailie & Obojska, Lidia & Brzeszczyński, Janusz, 2024. "Recession fears and stock markets: An application of directional wavelet coherence and a machine learning-based economic agent-determined Google fear index," Research in International Business and Finance, Elsevier, vol. 72(PA).
   64. Mingchen Li & Kun Yang & Wencan Lin & Yunjie Wei & Shouyang Wang, 2024. "An interval constraint-based trading strategy with social sentiment for the stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
   65. Gunay, Samet & Sraieb, Mohamed M. & Muhammed, Shahnawaz, 2024. "Decrypting Metaverse crypto Market: A nonlinear analysis of investor sentiment," International Review of Financial Analysis, Elsevier, vol. 96(PB).
   66. Wang, Hua & Xu, Liao & Sharma, Susan Sunila, 2021. "Does investor attention increase stock market volatility during the COVID-19 pandemic?," Pacific-Basin Finance Journal, Elsevier, vol. 69(C).
   67. Aromi, J. Daniel & Clements, Adam, 2021. "Facial expressions and the business cycle," Economic Modelling, Elsevier, vol. 102(C).
   68. Lansing, Kevin J. & LeRoy, Stephen F. & Ma, Jun, 2022. "Examining the sources of excess return predictability: Stochastic volatility or market inefficiency?," Journal of Economic Behavior & Organization, Elsevier, vol. 197(C), pages 50-72.
       • Kevin J. Lansing & Stephen F. LeRoy & Jun Ma, 2022. "Examining the Sources of Excess Return Predictability: Stochastic Volatility or Market Inefficiency?," Working Paper Series 2018-14, Federal Reserve Bank of San Francisco.
   69. Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2021. "A machine learning approach to volatility forecasting," CREATES Research Papers 2021-03, Department of Economics and Business Economics, Aarhus University.
       • Kim Christensen & Mathias Siggaard & Bezirgen Veliyev, 2023. "A Machine Learning Approach to Volatility Forecasting," Journal of Financial Econometrics, Oxford University Press, vol. 21(5), pages 1680-1727.
   70. Zhu, Xuehong & Niu, Zibo & Zhang, Hongwei & Huang, Jiaxin & Zuo, Xuguang, 2022. "Can gold and bitcoin hedge against the COVID-19 related news sentiment risk? New evidence from a NARDL approach," Resources Policy, Elsevier, vol. 79(C).
   71. Ballinari, Daniele & Behrendt, Simon, 2020. "Structural breaks in online investor sentiment: A note on the nonstationarity of financial chatter," Finance Research Letters, Elsevier, vol. 35(C).
   72. Halousková, Martina & Stašek, Daniel & Horváth, Matúš, 2022. "The role of investor attention in global asset price variation during the invasion of Ukraine," Finance Research Letters, Elsevier, vol. 50(C).
   73. Hu, Nan & Yin, Xuebao & Yao, Yuhang, 2025. "A novel HAR-type realized volatility forecasting model using graph neural network," International Review of Financial Analysis, Elsevier, vol. 98(C).
   74. Yang Gao & Chengjie Zhao & Bianxia Sun & Wandi Zhao, 2022. "Effects of investor sentiment on stock volatility: new evidences from multi-source data in China’s green stock markets," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 8(1), pages 1-30, December.
   75. Riccardo Ricciardi, 2025. "Users’ self-description on social media: a methodology to integrate labels and textual information," Quality & Quantity: International Journal of Methodology, Springer, vol. 59(2), pages 1033-1057, April.
   76. Fernando Díaz & Pablo A Henríquez, 2021. "Social sentiment segregation: Evidence from Twitter and Google Trends in Chile during the COVID-19 dynamic quarantine strategy," PLOS ONE, Public Library of Science, vol. 16(7), pages 1-29, July.
   77. Liu, Wenwen & Zhao, Peng & Luo, Ziyang & Tang, Miaomiao, 2024. "The dynamic impact of network attention on natural resources prices in pre-and post-Russian-Ukrainian war," Resources Policy, Elsevier, vol. 97(C).
   78. Lyócsa, Štefan & Plíhal, Tomáš, 2022. "Russia’s ruble during the onset of the Russian invasion of Ukraine in early 2022: The role of implied volatility and attention," Finance Research Letters, Elsevier, vol. 48(C).
   79. Francesco Audrino & Jonathan Chassot, 2024. "HARd to Beat: The Overlooked Impact of Rolling Windows in the Era of Machine Learning," Papers 2406.08041, arXiv.org.
   80. Anubha Goel & Puneet Pasricha & Martin Magris & Juho Kanniainen, 2025. "Foundation Time-Series AI Model for Realized Volatility Forecasting," Papers 2505.11163, arXiv.org.
   81. Naimoli, Antonio, 2022. "The information content of sentiment indices for forecasting Value at Risk and Expected Shortfall in equity markets," MPRA Paper 112588, University Library of Munich, Germany.
   82. Xiaohong Shen & Gaoshan Wang & Yue Wang & Alfred Peris, 2021. "The Influence of Research Reports on Stock Returns: The Mediating Effect of Machine-Learning-Based Investor Sentiment," Discrete Dynamics in Nature and Society, Hindawi, vol. 2021, pages 1-14, December.
   83. Lyócsa, Štefan & Baumöhl, Eduard & Výrost, Tomáš, 2022. "YOLO trading: Riding with the herd during the GameStop episode," Finance Research Letters, Elsevier, vol. 46(PA).
       • Lyócsa, Štefan & Baumöhl, Eduard & Vŷrost, Tomáš, 2021. "YOLO trading: Riding with the herd during the GameStop episode," EconStor Preprints 230679, ZBW - Leibniz Information Centre for Economics.
   84. Roland Fuess & Massimo Guidolin & Christian Koeppel, 2019. "Sentiment Risk Premia in the Cross-Section of Global Equity and Currency Returns," BAFFI CAREFIN Working Papers 19116, BAFFI CAREFIN, Centre for Applied Research on International Markets Banking Finance and Regulation, Universita' Bocconi, Milano, Italy.
   85. Ruzita Abdul-Rahim & Airil Khalid & Zulkefly Abdul Karim & Mamunur Rashid, 2022. "Exploring the Driving Forces of Stock-Cryptocurrency Comovements during COVID-19 Pandemic: An Analysis Using Wavelet Coherence and Seemingly Unrelated Regression," Mathematics, MDPI, vol. 10(12), pages 1-19, June.
   86. Tseng‐Chan Tseng & Hung‐Cheng Lai & Jih‐Kuang Chen, 2022. "Impacts of relatively rational and irrational investor sentiment on realized volatility," Asian Economic Journal, East Asian Economic Association, vol. 36(4), pages 458-478, December.
   87. Adam Clements & Yin Liao & Yusui Tang, 2022. "Moving beyond Volatility Index (VIX): HARnessing the term structure of implied volatility," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 86-99, January.
   88. Lyócsa, Štefan & Halousková, Martina & Haugom, Erik, 2023. "The US banking crisis in 2023: Intraday attention and price variation of banks at risk," Finance Research Letters, Elsevier, vol. 57(C).
   89. Cerqueti, Roy & Ficcadenti, Valerio & Mattera, Raffaele, 2024. "Investors’ attention and network spillover for commodity market forecasting," Socio-Economic Planning Sciences, Elsevier, vol. 95(C).
   90. Ying Wang & Hongwei Zhang & Wang Gao & Cai Yang, 2023. "Spillover effects from news to travel and leisure stocks during the COVID-19 pandemic: Evidence from the time and frequency domains," Tourism Economics, , vol. 29(2), pages 460-487, March.
   91. Ma, Feng & Wang, Jiqian & Wahab, M.I.M. & Ma, Yuanhui, 2023. "Stock market volatility predictability in a data-rich world: A new insight," International Journal of Forecasting, Elsevier, vol. 39(4), pages 1804-1819.
   92. Panpan Zhu & Qingjie Zhou & Yinpeng Zhang, 2024. "Investor attention and consumer price index inflation rate: Evidence from the United States," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-12, December.
   93. Yuping Song & Yuetong Zhang & Po Ning & Jiayi Peng & Chunyu Kao & Liang Hao, 2025. "Transformer-Based Downside Risk Forecasting: A Data-Driven Approach with Realized Downward Semi-Variance," Mathematics, MDPI, vol. 13(8), pages 1-28, April.
   94. Michele Costola & Michael Donadelli & Luca Gerotto & Ivan Gufler, 2022. "Global risks, the macroeconomy, and asset prices," Empirical Economics, Springer, vol. 63(5), pages 2357-2388, November.
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5. Ballinari, Daniele & Behrendt, Simon, 2020. "Structural breaks in online investor sentiment: A note on the nonstationarity of financial chatter," Finance Research Letters, Elsevier, vol. 35(C).

   Cited by:

   1. Daniele Ballinari & Simon Behrendt, 2021. "How to gauge investor behavior? A comparison of online investor sentiment measures," Digital Finance, Springer, vol. 3(2), pages 169-204, June.
   2. Bianca Raluca Baditoiu & Roxana Ioan & Valentin Partenie Munteanu & Alexandru Buglea, 2023. "Investors’ reactions on the publication of integrated reports. Evidence from European stock markets," E&M Economics and Management, Technical University of Liberec, Faculty of Economics, vol. 26(2), pages 158-171, June.

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NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.

1. NEP-BIG: Big Data (3) 2024-04-01 2024-10-14 2024-12-16. Author is listed
2. NEP-CMP: Computational Economics (3) 2024-04-01 2024-10-14 2024-12-16. Author is listed
3. NEP-ECM: Econometrics (3) 2024-04-01 2024-10-14 2024-12-16. Author is listed
4. NEP-ETS: Econometric Time Series (1) 2024-12-16. Author is listed
5. NEP-IPR: Intellectual Property Rights (1) 2024-10-14. Author is listed

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