Revealing the risk perception of investors using machine learning

URN to cite this document:: urn:nbn:de:bvb:355-epub-587775
DOI to cite this document:: 10.5283/epub.58777

Koelbl, Marina ; Laschinger, Ralf

; Steininger, Bertram I.

; Schäfers, Wolfgang

License: Creative Commons Attribution 4.0
PDF - Published Version
(4MB)

Date of publication of this fulltext: 14 Aug 2024 06:40

Alternative links to fulltext:DOI Publisher

Details

Preview

Export bibliographical data

Abstract

Corporate disclosures convey crucial information to financial market participants. While machine learning algorithms are commonly used to extract this information, they often overlook the use of idiosyncratic terminology and industry-specific vocabulary within documents. This study uses an unsupervised machine learning algorithm, the Structural Topic Model, to overcome these issues. Our findings ...