"Let me get back to you" - A machine learning approach to measuring non-answers

46 Pages Posted: 4 May 2020 Last revised: 4 Apr 2022

See all articles by Andreas Barth

Andreas Barth

Goethe University Frankfurt - Department of Finance; Halle Institute for Economic Research; Saarland University

Sasan Mansouri

University of Groningen - Faculty of Economics and Business; Goethe University Frankfurt; Halle Institute for Economic Research

Fabian Woebbeking

Halle Institute for Economic Research; Martin Luther University of Halle-Wittenberg

Date Written: April 1, 2022

Abstract

Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,364 trigrams that signal non-answers in earnings call Q&A. We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. As both our method and glossary are free of financial context, we believe that the measure is applicable to other fields with a Q&A setup outside the contextual domain of financial earnings conference calls.

Keywords: Econlinguistics, textual analysis, natural language processing, multinomial inverse regression, MNIR, non-answers

JEL Classification: D80, D82, G10, G14, G30

Suggested Citation

Barth, Andreas and Mansouri, Sasan and Woebbeking, Fabian, "Let me get back to you" - A machine learning approach to measuring non-answers (April 1, 2022). Proceedings of Paris December 2020 Finance Meeting EUROFIDAI - ESSEC, Available at SSRN: https://ssrn.com/abstract=3567724 or http://dx.doi.org/10.2139/ssrn.3567724

Andreas Barth

Goethe University Frankfurt - Department of Finance ( email )

Theodor-W.-Adorno-Platz 3
Frankfurt, 60629
Germany

Halle Institute for Economic Research ( email )

P.O. Box 11 03 61
Kleine Maerkerstrasse 8
D-06017 Halle, 06108
Germany

Saarland University ( email )

Stadtwald
Saarbrucken, Saarland D-66123
Germany

Sasan Mansouri

University of Groningen - Faculty of Economics and Business ( email )

Postbus 72
9700 AB Groningen
Netherlands

Goethe University Frankfurt ( email )

Frankfurt am Main
Germany
015781284258 (Phone)

HOME PAGE: http://www.sasanm.de

Halle Institute for Economic Research

P.O. Box 11 03 61
Kleine Maerkerstrasse 8
D-06017 Halle, 06108
Germany

Fabian Woebbeking (Contact Author)

Halle Institute for Economic Research ( email )

P.O. Box 11 03 61
Kleine Maerkerstrasse 8
D-06017 Halle, 06108
Germany
+49 345 7753-851 (Phone)

HOME PAGE: http://https://www.iwh-halle.de/

Martin Luther University of Halle-Wittenberg

Emil-Abderhalden-Str. 7
Halle an der Saale
06099 Halle (Saale), DE Sachsen-Anhalt 06099
Germany

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