Predicting industry sectors from financial statements: An illustration of machine learning in accounting research |
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| Affiliation: | 1. School of Accounting, Southwestern University of Finance and Economics, Chengdu, 611130, China;2. School of Economics and Management, Harbin Institute of Technology, Shenzhen, 518055, China;3. Department of Accounting and Information Systems, Rutgers Business School-Newark and New Brunswick, Rutgers University, 1 Washington Square Park, Room #934, Newark, NJ, 07102, USA;4. Department of Finance and Economics, Rutgers Business School-Newark and New Brunswick, Rutgers University, 100 Rockafeller Road, Room #5135, Piscataway, NJ, 08854, USA;1. Department of Economics, Management, Institutions of the University of Naples Federico II, Italy;2. Department of Accounting and Economic Analyses, Nord University, Norway;1. School of Economics and Business Administration, Saint Mary''s College of California, USA;2. College of Business, Hankuk University of Foreign Studies, South Korea;3. School of Accounting and Finance, Hong Kong Polytechnic University, Hong Kong;4. Barowsky School of Business, Dominican University of California, USA;1. Southampton Business School, University of Southampton, Southampton, SO17 1BJ, UK;2. School of Business and Economics, Loughborough University, Leicestershire, LE11 3TU, UK;3. Birmingham Business School, University of Birmingham, Birmingham, B15 2TT, UK;1. University of South Australia, Business, Adelaide, South Australia, SA, 5000, Australia;2. Universitas Mahasaraswati Denpasar, Bali, Indonesia;3. University of Pretoria, Department of Financial Management, Hatfield, 0028, South Africa |
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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. |
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