What are you saying? Using topic to detect financial misreporting

• Main Authors: BROWN, Nerissa C., CROWLEY, Richard M., ELLIOTT, W. Brooke
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: topic modeling; disclosure; latent Dirichlet allocation; financial misreporting; Accounting; Corporate Finance
• Online Access: https://ink.library.smu.edu.sg/soa_research/1828; https://ink.library.smu.edu.sg/context/soa_research/article/2855/viewcontent/BROWN_et_al_2020_Journal_of_Accounting_Research.pdf; https://ink.library.smu.edu.sg/context/soa_research/article/2855/filename/0/type/additional/viewcontent/BCE_Online_Appendix.pdf
• Institution: Singapore Management University

We use a machine learning technique to assess whether the thematic content of financial statement disclosures (labeled topic) is incrementally informative in predicting intentional misreporting. Using a Bayesian topic modeling algorithm, we determine and empirically quantify the topic content of a l...