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Predicting financial distress probability of Indonesian plantation and mining firms

Author

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  • Christianto Tano
  • Yunieta Anny Nainggolan

Abstract

We aim to predict financial distress probability of Indonesian firms by employing recent established model and incorporating corporate governance measurements. We examine plantation and mining industry because the growth of these industries has been declining due to the diminishing of commodities price which could provide a case of industries with high financial distress probability. Our findings show that only stock price, stock returns volatility and net income could predict financial distress within one year but not within three year model. We also find that by incorporating the corporate governance measurements, the model goodness-of-fit could be improved. However, we do not find that our corporate governance measures could be used as accurate predictors. Finally, the model shows to be able to predict financial distress of Indonesian plantation and mining firms for the year 2016 with accuracy of 76.920% using cut-off percentage of 0.999%.

Suggested Citation

  • Christianto Tano & Yunieta Anny Nainggolan, 2019. "Predicting financial distress probability of Indonesian plantation and mining firms," International Journal of Trade and Global Markets, Inderscience Enterprises Ltd, vol. 12(2), pages 199-217.
    • Handle: RePEc:ids:ijtrgm:v:12:y:2019:i:2:p:199-217
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