Polytomous response financial distress models: The role of accounting, market and macroeconomic variables

Mario Hernandez Tinoco, Phil Holmes and Nick Wilson

International Review of Financial Analysis, 2018, vol. 59, issue C, 276-289

Abstract: We apply polytomous response logit models to investigate financial distress and bankruptcy across three states for UK listed companies over a period exceeding 30 years and utilising around 20,000 company year observations. Results suggest combining accounting, market and macroeconomic variables enhances the performance, accuracy and timeliness of models of corporate credit risk. Models produced contribute to the prediction and early warning systems literature by investigating the distress/failure process with enhanced granularity. We employ marginal effects to assess individual covariates' impact on the probability of falling into each state. The new insights on individual risk factors are confirmed by analysis of vectors of changes in predicted probabilities of falling into a state of financial distress and corporate failure following changes in the level of individual covariates. Resulting models provide a better understanding of different risk factors and can help practitioners detect financial distress and failure in a timely fashion.

Keywords: Bankruptcy prediction; Financial distress; Listed companies (search for similar items in EconPapers)
Date: 2018
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Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:finana:v:59:y:2018:i:c:p:276-289

DOI: 10.1016/j.irfa.2018.03.017

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