碩士 / 淡江大學 / 企業管理學系碩士在職專班 / 106 / Due to the changes of economic environment, business failure events occurred endlessly, thus, predicting the risk of business failure has become the most important subject for banks. This research uses Logistic Regression Model to identify the main independent variables for the public offering companies, which were delisted from 2015 to 2017 owing to financial distress, in three years prior to the occurrence of financial distress.
The independent variables in this research are debt ratio, fixed asset on equity, current ratio, quick ratio, accounts receivable turnover ratio, total asset turnover ratio, ROE (return on equity), and ROA (return on assets).The empirical results show that the debt ratio and the ROA are at significant level. The higher debt ratio or the less ROA, the higher possibility financial distress happened. Furthermore, the results cannot be explained when shareholders'' equity being the denominator is negative in some financial ratios, such as fixed asset on equity and ROE.
The financial distress prediction model is effective for the public offering companies in three years before the occurrence of financial distress in Logistic Regression, and the predictive accuracy could be approximately up to 85.4%. As a result, the model is useful for banks to identify if the companies have the possibilities of the occurrence of financial distress when they assess financial conditions and recheck their credit system.
| Identifer | oai:union.ndltd.org:TW/106TKU05121049 |
| Date | January 2018 |
| Creators | Cheng-Hsing Tseng, 曾政興 |
| Contributors | 李文雄 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 69 |
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