Capturing Analysts’ Questioning Strategies in Earnings Calls via a Question Cornering Score (QCS)

Giulia D'Agostino, Chris Reed, Andrea Rocci

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The study of questions in the setting of dialogical interactions in corporate communication has the purpose of understanding and capitalizing on the opinions that the questioner has with respect to the questioned company. Particularly, financial analysts have the maximal incentive to be right in their forecasts about the company’s performance, but they are also incentivized and expected to maintain a good relationship with the management– and therefore, not to be too challenging in their questions. While avoiding overt adversarialness, analysts adopt alternative strategies to seek the desired information; among which modulating the cornering quality of questions. This paper presents a way of measuring such cornering property, automatically extracting feature scores, and comparing the results with a manually annotated gold standard. Results encourage further research along this stream, particularly towards the study of replies and their degree of answerhood with respect to the cornering quality of the prompting question.
Original languageEnglish
Title of host publicationProceedings of the Eighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning
Pages107-118
Publication statusPublished - 3 Aug 2024
EventEighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning - International Convention Center Jeju, Jeju Island, Korea, Republic of
Duration: 3 Aug 20249 Aug 2024
https://ijcai24.org/

Conference

ConferenceEighth Financial Technology and Natural Language Processing and the 1st Agent AI for Scenario Planning
Abbreviated titleIJCAI 2024
Country/TerritoryKorea, Republic of
CityJeju Island
Period3/08/249/08/24
Internet address

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