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Predicting industry sectors from financial statements: an illustration of machine learning in accounting research
journal contribution
posted on 2023-06-10, 03:24 authored by Hans Van Der HeijdenHans Van Der HeijdenThe main aim and contribution of this study is to outline and demonstrate the usefulness of a machine learning approach to address prediction-based research problems in accounting research, and to contrast this approach with a more conventional explanation-based approach familiar to most accounting scholars. To illustrate the approach, the study applies machine learning to predict a firm’s industry sector using the firm’s publicly available financial statement data. The results show that an algorithm can predict an industry sector with just this data to a high degree of accuracy, especially if a non-linear classifier is used instead of a linear classifier. Additionally, the algorithms were able to carry out an industry-firm pairing exercise taken from introductory accounting text books and MBA cases, with predicted answers showing a high degree of accuracy in carrying out this exercise. The study shows how machine learning approaches and algorithms can be valuable to a range of accounting domains where prediction rather than explanation of the dependent variable is the main area of concern.
History
Publication status
- Published
File Version
- Accepted version
Journal
British Accounting ReviewISSN
0890-8389Publisher
ElsevierExternal DOI
Department affiliated with
- Accounting and Finance Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2022-05-06First Compliant Deposit (FCD) Date
2022-05-05Usage metrics
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