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

35 Pages Posted: 4 May 2020 Last revised: 28 Oct 2020

See all articles by Andreas Barth

Andreas Barth

Goethe University Frankfurt - Department of Finance

Sasan Mansouri

Goethe University Frankfurt - Department of Finance

Fabian Woebbeking

Goethe University Frankfurt - Department of Finance

Date Written: June 6, 2020

Abstract

It is relatively easy for us humans to detect when a question we asked has not been answered - we teach this skill to a computer. Using a supervised machine learning framework on a large training set of questions and answers, we identify 1,027 trigrams that signal non-answers. We show that this glossary has economic relevance by applying it to contemporaneous stock market reactions after earnings conference calls. Our findings suggest that obstructing the flow of information leads to significantly lower cumulative abnormal stock returns and higher implied volatility. Our metric is designed to be of general applicability for Q&A situations, and hence, is capable of identifying non-answers 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 (June 6, 2020). 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

Sasan Mansouri

Goethe University Frankfurt - Department of Finance ( email )

Grüneburgplatz 1
Frankfurt am Main, 60323
Germany
+49(0)6979833727 (Phone)

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

Fabian Woebbeking (Contact Author)

Goethe University Frankfurt - Department of Finance ( email )

Theodor-W.-Adorno-Platz 3
Frankfurt, 60323
Germany
+49 (69) 798 33731 (Phone)

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