Predicting industry sectors from financial statements: an illustration of machine learning in accounting research

Van Der Heijden, Hans (2022) Predicting industry sectors from financial statements: an illustration of machine learning in accounting research. British Accounting Review. ISSN 0890-8389

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Abstract

The 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.

Item Type: Article
Schools and Departments: University of Sussex Business School > Accounting and Finance
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 06 May 2022 10:34
Last Modified: 06 May 2022 10:45
URI: http://sro.sussex.ac.uk/id/eprint/105737

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