经济管理
經濟管理
경제관리
Economic Management Journal(EMJ)
2009年
9期
123~128
,共null页
财务困境预警模型 中国上市公司 逐步判别分析 指标选择 预警时点
財務睏境預警模型 中國上市公司 逐步判彆分析 指標選擇 預警時點
재무곤경예경모형 중국상시공사 축보판별분석 지표선택 예경시점
financial distress prediction model; Chinese listed companies; stepwise discriminant analysis; financial ratio selection; discriminant time point
针对我国上市公司财务困境预警模型研究中在指标、预警时点及模型选择方面的不足,本文从影响公司财务困境的各个方面分析并选择构建模型所需指标,选取2005~2009年120家被ST公司和240家财务正常公司为统计样本,运用逐步判别分析法基于2002~2009年的信息构建Z模型并进行比较分析。研究表明:Z模型与传统指标所构建的模型相比,本文构建的模型的判别正确率更高;根据我国上市公司股价的变化,应该选择t-3年作为预警时点并采用基于t-3年数据构建的模型;用另外的样本(96家)检验的结果发现,针对财务困境组,距困境发生的3年前该模型的判别正确率是81.25%。
針對我國上市公司財務睏境預警模型研究中在指標、預警時點及模型選擇方麵的不足,本文從影響公司財務睏境的各箇方麵分析併選擇構建模型所需指標,選取2005~2009年120傢被ST公司和240傢財務正常公司為統計樣本,運用逐步判彆分析法基于2002~2009年的信息構建Z模型併進行比較分析。研究錶明:Z模型與傳統指標所構建的模型相比,本文構建的模型的判彆正確率更高;根據我國上市公司股價的變化,應該選擇t-3年作為預警時點併採用基于t-3年數據構建的模型;用另外的樣本(96傢)檢驗的結果髮現,針對財務睏境組,距睏境髮生的3年前該模型的判彆正確率是81.25%。
침대아국상시공사재무곤경예경모형연구중재지표、예경시점급모형선택방면적불족,본문종영향공사재무곤경적각개방면분석병선택구건모형소수지표,선취2005~2009년120가피ST공사화240가재무정상공사위통계양본,운용축보판별분석법기우2002~2009년적신식구건Z모형병진행비교분석。연구표명:Z모형여전통지표소구건적모형상비,본문구건적모형적판별정학솔경고;근거아국상시공사고개적변화,응해선택t-3년작위예경시점병채용기우t-3년수거구건적모형;용령외적양본(96가)검험적결과발현,침대재무곤경조,거곤경발생적3년전해모형적판별정학솔시81.25%。
For limitations in financial ratio selection, discriminant time point definition and exact model confirmation with studies of financial distress prediction in China, we make an in--depth analysis of financial ratios, then pick up 120 ST firms and their matched 240 non--distressed firms through 2005--2009 as the sample, use stepwise discriminate analysis to establish Z--score models based on information from 2002--2008. Conclusions are: (1)Compared with the model constructed by traditional financial ratios, the discriminate accuracy is higher with the model constructed by us. (2) With studying movements of the stock price between ST firms and non--distressed firms, we confirm the discriminant time point should be t--3, and the discriminant model should be constructed by data in t--3. (3)With another sample(96 firms) that is not for model establishment to test the model's predictive power, to the financial distressed firms, when we make a discrimination three years before being distressed, the accuracy is 81.25%, thus it's a Well discriminator for distinguishing distressed firms three years ahead.