Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures

Volume: 60, Issue: 6, Pages: 1371 - 1391
Published: Jun 1, 2014
Abstract
Managers and researchers alike have long recognized the importance of corporate textual risk disclosures. Yet it is a nontrivial task to discover and quantify variables of interest from unstructured text. In this paper, we develop a variation of the latent Dirichlet allocation topic model and its learning algorithm for simultaneously discovering and quantifying risk types from textual risk disclosures. We conduct comprehensive evaluations in...
Paper Details
Title
Simultaneously Discovering and Quantifying Risk Types from Textual Risk Disclosures
Published Date
Jun 1, 2014
Volume
60
Issue
6
Pages
1371 - 1391
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