Thomas Renault

Economics and Econometrics · 2017–2020

A researcher in the Science corpus: 3 papers; trusts 31 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Economics and Econometrics — 31 citations into it; #11,279 of 23,481 by trust here, #13,168 by citations
• Finance — 24 citations into it; #5,254 of 10,518 by trust here, #9,027 by citations
• Accounting — 17 citations into it
• Information Systems — 11 citations into it
• Management Science and Operations Research — 11 citations into it; #5,531 of 11,946 by trust here, #9,931 by citations

Whom Thomas Renault trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diego García
2. Joseph E. Engelberg
3. Alec Go
4. Tim Loughran
5. Paul C. Tetlock
6. Werner Antweiler
7. J. Cookson
8. Colm Kearney
9. Bo Pang
10. Licheng Sun

Who trusts Thomas Renault overall

1. Shaen Corbet
2. C. Larkin
3. Brian M. Lucey
4. Piotr Kokoszka
5. Andrew Meegan

Papers from Thomas Renault's perspective

Ordered by how strongly the researchers Thomas Renault trusts endorse each paper. Same corpus, a different order for every researcher.

1. Is All That Talk Just Noise? The Information Content of Internet Stock Message Boards
2. Yahoo! for Amazon: Sentiment Extraction from Small Talk on the Web
3. Internet Appendix for "When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks" *
4. More than Words: Quantifying Language to Measure Firms' Fundamentals
5. Thumbs up? Sentiment Classification using Machine Learning Techniques
6. How are Shorts Informed? Short Sellers, News, and Information Processing
7. When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10-Ks
8. The Sum of All FEARS: Investor Sentiment and Asset Prices
9. How are shorts informed
10. Managing with Style: The Effect of Managers on Firm Policies

Their papers

• Intraday online investor sentiment and return patterns in the U.S. stock market (2017) — 373 citations
• Economic uncertainty before and during the COVID-19 pandemic (2020) — 873 citations
• Does investor sentiment on social media provide robust information for Bitcoin returns predictability? (2020) — 110 citations