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Thomas Renault

Personal Details

First Name:Thomas
Middle Name:
Last Name:Renault
Suffix:
RePEc Short-ID:pre517
[This author has chosen not to make the email address public]
http://www.thomas-renault.com
Twitter: @captaineco_fr

Affiliation

Maison des Sciences Économiques
Université Paris 1 (Panthéon-Sorbonne)

Paris, France
http://mse.univ-paris1.fr/

: 01 44 07 81 00
01 44 07 81 09
106 - 112 boulevard de l'Hôpital, 75647 Paris cedex 13
RePEc:edi:msep1fr (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. Renato Camodeca & Alex Almici & Umberto Sagliaschi, 2018. "Sustainability Disclosure in Integrated Reporting: Does It Matter to Investors? A Cheap Talk Approach," Sustainability, MDPI, Open Access Journal, vol. 10(12), pages 1-34, November.

  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. 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.

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