標題: 以財務資料,總體經濟與會計師意見建構財務危機預警模型
Constructing Financial Distress Model using Financial Ratios, Macroeconomic Factors and Auditor's Opinions.
作者: 徐子琄
Hsu Tzu-Chuan
蔡璧徽
Tsai Bi-Huei
管理科學系所
關鍵字: 財務危機;總體經濟;會計師意見;Financial Distress;Macroeconomic;Auditor's Opinions
公開日期: 2005
摘要: 本研究主要探討會計師出具意見對公司發生財務危機是否具有預警效果,即加入會計師意見之財務危機預警模型是否比傳統只考慮財務比率之財務危機預警模型佳;並探討加入總體經濟因素是否能提高財務預警模型之預測能力。 研究主題有三:1.探討會計師出具意見對公司發生財務危機是否具有預警的效果。2.探討加入會計師意見之財務危機預警模型的預測能力是否較傳統只考慮財務比率之統計模型為佳。3.探討納入總體經濟因素是否能提高財務危機預警模型之預測能力。 研究結果發現:會計師出具對「繼續經營假設有疑慮」意見對公司是否發生財務危機具有預警之效果,且財務比率加會計師出具意見組合對公司發生財務危機之預測能力比傳統只考慮財務比率變數組合佳,其中又以財務比率加上會計師出具對「繼續經營假設有疑慮」意見組合在對樣本外公司發生財務危機上有最佳之預測能力;而在加入總體經濟變數後的確能夠提升模型對公司發生財務危機之預測能力,也證明了會計師在出具意見時,若能將總體經濟因素一併納入考量,則能對公司是否發生財務危機有更佳的判斷。
This study attempts to examine the predicting ability of auditor’s opinions for financial distress and to prove that the performance of ratio-plus-auditor’s qualified opinions model is superior to statistical model in financial distress prediction. We also attempt to examine the predicting ability of macroeconomic factors. The purposes of this study are to examine three issues. First, the nature of auditor’s opinions give rise to the belief that they can signal financial distress. Secondly, the performance of ratio-plus-auditor’s qualified opinions model is superior to statistical model in financial distress prediction. Third, macroeconomic factors can enhance predicting ability for financial distress. The results of this study show that, the nature of auditor’s going–concern opinions can signal financial distress; in holdout sample, the performance of ratio-plus-auditor’s qualified opinions model is superior to statistical model in financial distress prediction. Among these models, auditor’s going–concern opinions perform the best. Finally, macroeconomic factors can enhance predicting ability for financial distress. The results suggest that auditor’s opinions could be improved by properly incorporating these macroeconomic factors into their decision making process.
URI: http://140.113.39.130/cdrfb3/record/nctu/#GT009331518
http://hdl.handle.net/11536/79386
Appears in Collections:Thesis