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

碩士 === 長榮大學 === 經營管理研究所 === 97 === 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...

Full description

Bibliographic Details
Main Authors: Chia-Hua Chang, 張加樺
Other Authors: Chiung-Ying Lee
Format: Others
Language:zh-TW
Published: 2009
Online Access:http://ndltd.ncl.edu.tw/handle/8s7nyj
Description
Summary:碩士 === 長榮大學 === 經營管理研究所 === 97 === 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.