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Conclusion Conclusion, Limitation, and Suggestion

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CHAPTER V Conclusion, Limitation, and Suggestion

5.1 Conclusion

This study seeks to examine whether logistic regression analysis can predict financial distress amongst public listed companies in Indonesia Stock Exchange IDX accurately or not. Author uses 216 as a sample and divides into two groups; healthy group 168 companies and distress group 48 companies. The observation starts in year 2008 till 2013. To minimize bias, author includes listed firms from all industries, with the exception of banks, insurance companies and investment trusts, secondary stocks of existing firms and foreign stocks, and Investment or Financial Trusts as they are often voluntarily liquidated. This study reveals that not all financial ratios can be used as significant predictors to predict financial distress amongst companies. However, there four financial ratios that give significant results and can be used to predict financial distress are: 5.1.1 Quick Asset Turnover QAT gives positive effect which means the higher the value the higher the probability of the company to faced financial distress. 5.1.2 Cash Flow to assets CFA gives negative effect which means the higher the value the lower probability of the company to faced financial distress. 53 5.1.3 Total Liabilities Total Asset TLTA gives negative effect which means the higher the value the lower probability of the company to faced financial distress. 5.1.4 Current Ratio CR gives positive effect which means the higher the value the higher the probability of the company to faced financial distress. The conclusion of this research is derived from the hypothesis testing to answer the problem statement. The hypothesis of Ha which states that logistic regression analysis can be used to predict corporate failure in Indonesia Stock Exchange IDX accurately is supported. The classification results show that logistic regression analysis is a more reliable technique for predict financially healthy companies than distress companies.It may happend because of the method that used in this study to divide the sample into healthy and distress group. But, overall classification results of 81 percent prove that the model can describe the financial condition of the companies.

5.2 Managerial Implication

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