Title: Predicting financial distress probability of Indonesian plantation and mining firms

Authors: Christianto Tano; Yunieta Anny Nainggolan

Addresses: School of Business and Management, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, Jawa Barat, 40132, Indonesia ' School of Business and Management, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung, Jawa Barat, 40132, Indonesia

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%.

Keywords: corporate governance; financial distress; Indonesia market; mining industry; plantation industry.

DOI: 10.1504/IJTGM.2019.100353

International Journal of Trade and Global Markets, 2019 Vol.12 No.2, pp.199 - 217

Received: 20 Sep 2018
Accepted: 17 Jan 2019
Published online: 26 Jun 2019 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article