企業財務危機預警機制之實證—以「財務重點專區」為例

張加樺

doi:10.6833/CJCU.2009.00091

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企業財務危機預警機制之實證—以「財務重點專區」為例

A Study of Enterprises’ Financial Distress Warning System: An Application of "Financial Reference Database"

張加樺 , Masters　　Advisor：李瓊映　　

繁體中文 DOI： 10.6833/CJCU.2009.00091

財務重點專區；財務預警模型；羅吉斯迴歸； Financial reference database ； financial distress warning model ； logistic regression

Abstract │ Reference (42) │ Times Cited (2) │ Altmetrics

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A Study of Enterprises’ Financial Distress Warning System: An Application of "Financial Reference Database"
Taiwan’s stock exchange corporation established "Financial reference database" which could provide entire zones of the market observation post system (MOPS) from June 2, 2007 and could offer investment indicators to the investors. The contents of the zones were the integrated financial information from listed and OTC firms that turned into investment indicators. Above contents contained eight dimensions initially, and then transferred to nine dimensions consequently after increasing the new one. The reference indicators of the zones were adopted to gain an enterprises’ financial reference database on this research, and to confirm predicted accuracy of enterprise finance distress while higher precision rate being gathered from using reference indicators of the zone. The research applied logistic regression model to set up financial distress warning models. Traditional regression and logistic regression model were defined as Model 1 and 2, respectively. Key study information was selected and evaluated from all financial distress companies. Then data collection of sample companies included pre-one periods and pre-two periods before the financial distress events happened.
The results demonstrated the discriminate rate of enterprises’ financial distress with our reference indicators seemed too lower while comparing outcomes of similar methodology in recent literatures. The evidences were supported that “debt ratio” and “operating cash flow” could be the best predicted variables from further test with logistic regression model and both of them could be attributed to financial dimensions.

Reference ( 42 ) 〈TOP〉

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