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Thomas Renault

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First Name:Thomas
Middle Name:
Last Name:Renault
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RePEc Short-ID:pre517
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http://www.thomas-renault.com
Twitter: @captaineco_fr

Affiliation

Centre d'Économie de la Sorbonne
Université Paris 1 (Panthéon-Sorbonne)

Paris, France
https://centredeconomiesorbonne.cnrs.fr/
RePEc:edi:cenp1fr (more details at EDIRC)

Research output

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Jump to: Articles

Articles

  1. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.
  2. Picault, Matthieu & Renault, Thomas, 2017. "Words are not all created equal: A new measure of ECB communication," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.

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.

Articles

  1. Renault, Thomas, 2017. "Intraday online investor sentiment and return patterns in the U.S. stock market," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 25-40.

    Cited by:

    1. Simon Porcher & Thomas Renault, 2021. "Social distancing beliefs and human mobility: Evidence from Twitter," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-03205158, HAL.
    2. Isabelle Royer & Lionel Garreau & Thomas Roulet, 2019. "La quantification des données qualitatives : intérêts et difficultés en sciences de gestion," Post-Print hal-02303982, HAL.
    3. Broadstock, David C. & Zhang, Dayong, 2019. "Social-media and intraday stock returns: The pricing power of sentiment," Finance Research Letters, Elsevier, vol. 30(C), pages 116-123.
    4. Chen, Rongda & Wu, Ling & Jin, Chenglu & Wang, Shengnan, 2021. "Unintended investor sentiment on bank financial products: Evidence from China," Emerging Markets Review, Elsevier, vol. 49(C).
    5. Gao, Ya & Han, Xing & Li, Youwei & Xiong, Xiong, 2019. "Overnight Momentum, Informational Shocks, and Late-Informed Trading in China," MPRA Paper 96784, University Library of Munich, Germany.
    6. Kommel, Karl Arnold & Sillasoo, Martin & Lublóy, Ágnes, 2019. "Could crowdsourced financial analysis replace the equity research by investment banks?," Finance Research Letters, Elsevier, vol. 29(C), pages 280-284.
    7. Sergey Nasekin & Cathy Yi-Hsuan Chen, 2020. "Deep learning-based cryptocurrency sentiment construction," Digital Finance, Springer, vol. 2(1), pages 39-67, September.
    8. Christina Bannier & Thomas Pauls & Andreas Walter, 2019. "Content analysis of business communication: introducing a German dictionary," Journal of Business Economics, Springer, vol. 89(1), pages 79-123, February.
    9. Di, Li & Shaiban, Mohammed Sharaf & Hasanov, Akram Shavkatovich, 2021. "The power of investor sentiment in explaining bank stock performance: Listed conventional vs. Islamic banks," Pacific-Basin Finance Journal, Elsevier, vol. 66(C).
    10. Guégan, Dominique & Renault, Thomas, 2021. "Does investor sentiment on social media provide robust information for Bitcoin returns predictability?," Finance Research Letters, Elsevier, vol. 38(C).
    11. Teplova, T. & Sokolova, T. & Tomtosov, A. & Buchko, D. & Nikulin, D., 2022. "The sentiment of private investors in explaining the differences in the trade characteristics of the Russian market stocks," Journal of the New Economic Association, New Economic Association, vol. 53(1), pages 53-84.
    12. Chen, Cathy Yi-Hsuan & Després, Roméo & Guo, Li & Renault, Thomas, 2019. "What makes cryptocurrencies special? Investor sentiment and return predictability during the bubble," IRTG 1792 Discussion Papers 2019-016, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    13. Wen, Zhuzhu & Gong, Xu & Ma, Diandian & Xu, Yahua, 2021. "Intraday momentum and return predictability: Evidence from the crude oil market," Economic Modelling, Elsevier, vol. 95(C), pages 374-384.
    14. Steyn, Dimitri H. W. & Greyling, Talita & Rossouw, Stephanie & Mwamba, John M., 2020. "Sentiment, emotions and stock market predictability in developed and emerging markets," GLO Discussion Paper Series 502, Global Labor Organization (GLO).
    15. 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).
    16. Aigbe Akhigbe & Melinda Newman & Ann Marie Whyte, 2022. "Localized sentiment trading in heterogeneous labor markets: evidence from free agent signings," Review of Quantitative Finance and Accounting, Springer, vol. 58(3), pages 1249-1276, April.
    17. Jing Zhou & Silin Ye & Wei Lan & Yunwen Jiang, 2021. "The effect of social media on corporate violations: Evidence from Weibo posts in China," International Review of Finance, International Review of Finance Ltd., vol. 21(3), pages 966-988, September.
    18. Chen, C. Y-H. & Härdle, W. K. & Klochkov, Y., 2019. "Influencers and Communities in Social Networks," Cambridge Working Papers in Economics 1998, Faculty of Economics, University of Cambridge.
    19. Rui Fan & Oleksandr Talavera & Vu Tran, 2022. "Information flows and the law of one price," Discussion Papers 22-05, Department of Economics, University of Birmingham.
    20. Saurabh, Samant & Dey, Kushankur, 2020. "Unraveling the relationship between social moods and the stock market: Evidence from the United Kingdom," Journal of Behavioral and Experimental Finance, Elsevier, vol. 26(C).
    21. Kelley Bergsma & Andy Fodor & Vijay Singal & Jitendra Tayal, 2020. "Option trading after the opening bell and intraday stock return predictability," Financial Management, Financial Management Association International, vol. 49(3), pages 769-804, September.
    22. Xiaojun Chu & Jianying Qiu, 2021. "Forecasting stock returns using first half an hour order imbalance," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3236-3245, July.
    23. Long, Wen & Zhao, Manyi & Tang, Yeran, 2021. "Can the Chinese volatility index reflect investor sentiment?," International Review of Financial Analysis, Elsevier, vol. 73(C).
    24. Alexis Bogroff & Dominique Guégan, 2019. "Artificial Intelligence, Data, Ethics. An Holistic Approach for Risks and Regulation," Working Papers 2019: 19, Department of Economics, University of Venice "Ca' Foscari".
    25. Zachary McGurk & Adam Nowak & Joshua C. Hall, 2019. "Stock Returns and Investor Sentiment: Textual Analysis and Social Media," Working Papers 19-03, Department of Economics, West Virginia University.
    26. Karam KIM & Doojin RYU, 2020. "Predictive ability of investor sentiment for the stock market," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(4), pages 33-46, December.
    27. Zhou, Zhongbao & Gao, Meng & Liu, Qing & Xiao, Helu, 2020. "Forecasting stock price movements with multiple data sources: Evidence from stock market in China," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 542(C).
    28. Alexis Bogroff & Dominique Guegan, 2019. "Artificial Intelligence, Data, Ethics: An Holistic Approach for Risks and Regulation," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-02181597, HAL.
    29. Dong, Hang & Gil-Bazo, Javier, 2020. "Sentiment stocks," International Review of Financial Analysis, Elsevier, vol. 72(C).
    30. Thomas Renault, 2020. "Sentiment analysis and machine learning in finance: a comparison of methods and models on one million messages," Digital Finance, Springer, vol. 2(1), pages 1-13, September.
    31. Florian Röder & Andreas Walter, 2019. "What Drives Investment Flows Into Social Trading Portfolios?," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 42(2), pages 383-411, July.
    32. Xiaohong Shen & Gaoshan Wang & Yue Wang, 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.
    33. Alexis Bogroff & Dominique Guegan, 2019. "Artificial Intelligence, Data, Ethics: An Holistic Approach for Risks and Regulation," Post-Print halshs-02181597, HAL.
    34. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media bots and stock markets," European Financial Management, European Financial Management Association, vol. 26(3), pages 753-777, June.
    35. Kokoszka, Piotr & Miao, Hong & Petersen, Alexander & Shang, Han Lin, 2019. "Forecasting of density functions with an application to cross-sectional and intraday returns," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1304-1317.
    36. Chen, Cathy Yi-Hsuan & Härdle, Wolfgang Karl & Klochkov, Yegor, 2019. "SONIC: SOcial Network with Influencers and Communities," IRTG 1792 Discussion Papers 2019-025, Humboldt University of Berlin, International Research Training Group 1792 "High Dimensional Nonstationary Time Series".
    37. Jie Ren & Hang Dong & Balaji Padmanabhan & Jeffrey V. Nickerson, 2021. "How does social media sentiment impact mass media sentiment? A study of news in the financial markets," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(9), pages 1183-1197, September.
    38. Marco Caiffa & Vincenzo Farina & Lucrezia Fattobene, 2020. "All that glitters is not gold: CEOs' celebrity beyond media content," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 25(3), pages 444-460, July.
    39. Rui Fan & Oleksandr Talavera & Vu Tran, 2020. "Social media and price discovery: the case of cross-listed firms," Discussion Papers 20-05, Department of Economics, University of Birmingham.
    40. Emna Mnif & Anis Jarboui & M. Kabir Hassan & Khaireddine Mouakhar, 2020. "Big data tools for Islamic financial analysis," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 27(1), pages 10-21, January.
    41. Rossouw, Stephanie & Greyling, Talita, 2020. "Big Data and Happiness," GLO Discussion Paper Series 634, Global Labor Organization (GLO).
    42. 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.
    43. Mariano González-Sánchez & M. Encina Morales de Vega, 2021. "Influence of Bloomberg’s Investor Sentiment Index: Evidence from European Union Financial Sector," Mathematics, MDPI, vol. 9(4), pages 1-21, February.
    44. Alomari, Mohammad & Al Rababa’a, Abdel Razzaq & El-Nader, Ghaith & Alkhataybeh, Ahmad & Ur Rehman, Mobeen, 2021. "Examining the effects of news and media sentiments on volatility and correlation: Evidence from the UK," The Quarterly Review of Economics and Finance, Elsevier, vol. 82(C), pages 280-297.
    45. Dan Gabriel Anghel, 2020. "What Can Machine Learning Tell Us About Intraday Price Patterns in a Frontier Stock Market?," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 11(5), pages 205-220, October.
    46. Mohammad Alomari & Abdel Razzaq Al rababa’a & Ghaith El-Nader & Ahmad Alkhataybeh, 2021. "Who’s behind the wheel? The role of social and media news in driving the stock–bond correlation," Review of Quantitative Finance and Accounting, Springer, vol. 57(3), pages 959-1007, October.
    47. 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.
    48. Lan, Yueqin & Huang, Yong & Yan, Chao, 2021. "Investor sentiment and stock price: Empirical evidence from Chinese SEOs," Economic Modelling, Elsevier, vol. 94(C), pages 703-714.
    49. Renato Camodeca & Alex Almici & Umberto Sagliaschi, 2018. "Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach," Sustainability, MDPI, vol. 10(12), pages 1-34, November.
    50. Zhang, Yaojie & Ma, Feng & Zhu, Bo, 2019. "Intraday momentum and stock return predictability: Evidence from China," Economic Modelling, Elsevier, vol. 76(C), pages 319-329.
    51. Nguyen, Quyen & Diaz-Rainey, Ivan & Kuruppuarachchi, Duminda, 2021. "Predicting corporate carbon footprints for climate finance risk analyses: A machine learning approach," Energy Economics, Elsevier, vol. 95(C).
    52. Shu-Ling Lin & Jun Lu, 2020. "Did Institutional Investors’ Behavior Affect U.S.-China Equity Market Sentiment? Evidence from the U.S.-China Trade Turbulence," Mathematics, MDPI, vol. 8(6), pages 1-17, June.
    53. Fu, Junhui & Wu, Xiang & Liu, Yufang & Chen, Rongda, 2021. "Firm-specific investor sentiment and stock price crash risk," Finance Research Letters, Elsevier, vol. 38(C).
    54. 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.
    55. Yu, Jing-Rung & Chiou, W. Paul & Hung, Cing-Hung & Dong, Wen-Kuei & Chang, Yi-Hsuan, 2022. "Dynamic rebalancing portfolio models with analyses of investor sentiment," International Review of Economics & Finance, Elsevier, vol. 77(C), pages 1-13.
    56. Yanhui Chen & Hanhui Zhao & Ziyu Li & Jinrong Lu, 2020. "A dynamic analysis of the relationship between investor sentiment and stock market realized volatility: Evidence from China," PLOS ONE, Public Library of Science, vol. 15(12), pages 1-18, December.

  2. Picault, Matthieu & Renault, Thomas, 2017. "Words are not all created equal: A new measure of ECB communication," Journal of International Money and Finance, Elsevier, vol. 79(C), pages 136-156.

    Cited by:

    1. Isabelle Royer & Lionel Garreau & Thomas Roulet, 2019. "La quantification des données qualitatives : intérêts et difficultés en sciences de gestion," Post-Print hal-02303982, HAL.
    2. Tillmann, Peter, 2021. "Financial markets and dissent in the ECB’s Governing Council," European Economic Review, Elsevier, vol. 139(C).
    3. Paloviita, Maritta & Haavio, Markus & Jalasjoki, Pirkka & Kilponen, Juha & Vänni, Ilona, 2020. "Reading between the lines : Using text analysis to estimate the loss function of the ECB," Research Discussion Papers 12/2020, Bank of Finland.
    4. Matthieu PICAULT & Julien PINTER & Thomas RENAULT, 2021. "Media sentiment on monetary policy: determinants and relevance for inflation expectations," LEO Working Papers / DR LEO 2895, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    5. Hubert, Paul & Labondance, Fabien, 2021. "The signaling effects of central bank tone," European Economic Review, Elsevier, vol. 133(C).
    6. Cour-Thimann, Philippine & Jung, Alexander, 2020. "Interest rate setting and communication at the ECB," Working Paper Series 2443, European Central Bank.
    7. Paul Hubert & Fabien Labondance, 2020. "Central Bank Tone and the Dispersion of Views within Monetary Policy Committees," Sciences Po publications 02/2020, Sciences Po.
    8. Hamza Bennani & Pavel Gertler & Roman Horvath & Nicolas Fanta, 2020. "Does Central Bank Communication Signal Future Monetary Policy in a (post)-Crisis Era? The Case of the ECB," Post-Print hal-02486315, HAL.
    9. Beaupain, Renaud & Girard, Alexandre, 2020. "The value of understanding central bank communication," Economic Modelling, Elsevier, vol. 85(C), pages 154-165.
    10. Aakriti Mathur & Rajeswari Sengupta, 2019. "Analysing monetary policy statements of the Reserve Bank of India," IHEID Working Papers 08-2019, Economics Section, The Graduate Institute of International Studies.
    11. Young Joon Lee & Soohyon Kim & Ki Young Park, 2019. "Deciphering Monetary Policy Board Minutes with Text Mining: The Case of South Korea," Korean Economic Review, Korean Economic Association, vol. 35, pages 471-511.
    12. Fernandes, Cecilia Melo, 2021. "ECB communication as a stabilization and coordination device: evidence from ex-ante inflation uncertainty," Working Paper Series 2582, European Central Bank.
    13. Hüning, Hendrik, 2020. "Swiss National Bank communication and investors’ uncertainty," The North American Journal of Economics and Finance, Elsevier, vol. 51(C).
    14. Paweł Baranowski & Wirginia Doryń & Tomasz Łyziak & Ewa Stanisławska, 2020. "Words and deeds in managing expectations: empirical evidence on an inflation targeting economy," NBP Working Papers 326, Narodowy Bank Polski, Economic Research Department.
    15. Ki Young Park & Youngjoon Lee & Soohyon Kim, 2019. "Deciphering Monetary Policy Board Minutes through Text Mining Approach: The Case of Korea," Working Papers 2019-1, Economic Research Institute, Bank of Korea.
    16. Hartwell Christopher A., 2019. "Complexity, Uncertainty, and Monetary Policy: Can the ECB Avoid the Unconventional Becoming the ‘New Normal’?," The Economists' Voice, De Gruyter, vol. 16(1), pages 1-13, December.
    17. Youngjoon Lee & Soohyon Kim & Ki Young Park, 2019. "Measuring Monetary Policy Surprises Using Text Mining: The Case of Korea," Working Papers 2019-11, Economic Research Institute, Bank of Korea.
    18. Andres Algaba & David Ardia & Keven Bluteau & Samuel Borms & Kris Boudt, 2020. "Econometrics Meets Sentiment: An Overview Of Methodology And Applications," Journal of Economic Surveys, Wiley Blackwell, vol. 34(3), pages 512-547, July.
    19. Marozzi, Armando, 2021. "The ECB's tracker: nowcasting the press conferences of the ECB," Working Paper Series 2609, European Central Bank.
    20. Guo, Junjie & Guo, Yumei & Miao, Shan & Pang, Xin, 2021. "An investigation of semantic similarity in PBOC’s communication on RMB volatility," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 441-455.
    21. Paweł Baranowski & Hamza Bennani & Wirginia Doryń, 2020. "Do ECB introductory statements help to predict monetary policy: evidence from tone analysis," NBP Working Papers 323, Narodowy Bank Polski, Economic Research Department.
    22. Adam Hale Shapiro & Daniel J. Wilson, 2019. "Taking the Fed at its Word: A New Approach to Estimating Central Bank Objectives Using Text Analysis," Working Paper Series 2019-2, Federal Reserve Bank of San Francisco.
    23. Callan Windsor, 2021. "The Intellectual Ideas Inside Central Banks: What'S Changed (Or Not) Since The Crisis?," Journal of Economic Surveys, Wiley Blackwell, vol. 35(2), pages 539-565, April.
    24. Martin T. Bohl & Dimitrios Kanelis & Pierre L. Siklos, 2022. "How Central Bank Mandates Influence Content and Tone of Communication Over Time," CQE Working Papers 9622, Center for Quantitative Economics (CQE), University of Muenster.
    25. Möller, Rouven & Reichmann, Doron, 2021. "ECB language and stock returns – A textual analysis of ECB press conferences," The Quarterly Review of Economics and Finance, Elsevier, vol. 80(C), pages 590-604.
    26. Youngjoon Lee & Soohyon Kim & Ki Young Park, 2018. "Deciphering Monetary Policy Committee Minutes with Text Mining Approach: A Case of South Korea," Working papers 2018rwp-132, Yonsei University, Yonsei Economics Research Institute.
    27. Martin Baumgaertner & Johannes Zahner, 2021. "Whatever it takes to understand a central banker - Embedding their words using neural networks," MAGKS Papers on Economics 202130, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    28. Baranowski, Paweł & Doryń, Wirginia & Łyziak, Tomasz & Stanisławska, Ewa, 2021. "Words and deeds in managing expectations: Empirical evidence from an inflation targeting economy," Economic Modelling, Elsevier, vol. 95(C), pages 49-67.
    29. Apel, Mikael & Blix Grimaldi, Marianna & Hull, Isaiah, 2019. "How Much Information Do Monetary Policy Committees Disclose? Evidence from the FOMC's Minutes and Transcripts," Working Paper Series 381, Sveriges Riksbank (Central Bank of Sweden).
    30. Peter Tillmann, 2020. "Financial Markets and Dissent in the ECB’s Governing Council," MAGKS Papers on Economics 202048, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    31. Firrell, Alastair & Reinold, Kate, 2020. "Uncertainty and voting on the Bank of England’s Monetary Policy Committee," Bank of England working papers 898, Bank of England.

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