Journal of Applied Finance & Banking

Probability Bankruptcy Using Support Vector Regression Machines

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  • Abstract

     

    Bankruptcy is a decision made by a court after examining the assets and liabilities of individuals even businesses in which they are not able to pay their bills. Due to the importance of prevent bankruptcy to be happened in such business, a calculation which can predict probability bankruptcy is necessary. This paper aims to investigate probability bankruptcy using Support Vector Regression. There are 6 variables for 2016 to 2018 period coming from 17 coal mining companies from Indonesia. The model built by using Support Vector Regression indicates a good performance because it has the highest coefficient of determination compared to previous research.

     

    JEL classification numbers: C23, C33, C63, E37, G17, G33, L72.

    Keywords: Probability Bankruptcy, Coal Mining, Support Vector Regression, Mean Square Error, Mean Absolute Error, Coefficient of Determination, Financial Ratio.