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Determinants of Corporate Failure: The Case of the Johannesburg Stock Exchange

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  • Mabe, Queen Magadi
  • Lin, Wei

Abstract

The aim of this paper is to estimate the probability of default for JSE listed companies. Our distinctive contribution is to use the multi-sector approach in estimating corporate failure instead of estimating failure in one sector, as failing companies are faced with the same challenge regardless of the sectors they operate in. The study creates a platform to identify the effect of Book-value to Market-value ratio on the probability to default, as this variable is often used as a proxy for corporate default in asset pricing models. Moreover, the use of Classification and Regression Trees uncovers other variables as reliable predictors to estimate corporate failure as the model is designed to choose the covariates with respect to classification ability. Our study also serves to add to the literature on how Logistic model performance compares to Machine Learning methods such as Classification and Regression Trees and Support Vector Machines. The study is the first to apply Support Vector Machines to predict failure on South African listed companies.

Suggested Citation

  • Mabe, Queen Magadi & Lin, Wei, 2018. "Determinants of Corporate Failure: The Case of the Johannesburg Stock Exchange," MPRA Paper 88485, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:88485
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    Cited by:

    1. Abraham Simon Otim Emuron & Tian Yixiang, 2020. "Financial distress and non‐executive director compensation: Evidence from state‐owned enterprises in South Africa post King III," African Development Review, African Development Bank, vol. 32(2), pages 228-239, June.

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    More about this item

    Keywords

    Corporate default; Logistic Regression; Support Vector Machines; Classification and Regression Trees.;
    All these keywords.

    JEL classification:

    • C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
    • G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation

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