本研究主要探討在考慮風險值變數後,是否可以有效提高公司財務預警模型 的預測能力。 研究結論:隨著預測時間的增加,模型的預測能力越差;就傳統財務比率變 數而言,主要影響變數在前一季為股東權益報酬率與每股盈餘,而在前兩季以後, 負債比率都達1%顯著水準以上,其他顯著變數包括純益率、資本營業報酬率等獲 利能力的變數,在前兩年則為應收帳款週轉率變數。在危機發生前一季,當傳統 財務比率變數模型引進風險值後,所有風險值都超越1%顯著水準。在危機發生前 兩季在測試樣本中都有提高模型的預測能力;但前三季、前一年、前兩年都沒有 顯著提升模型的預測能力。
VaR is treated as additional variables to enhance the predictive ability of alert mode in this study. The additional variables of the VaR index are: Sample Moving Average, Exponentially Weighted Moving Average, Historical Simulation, Boostrap, and Monte Carlo Simulation. The results are summarized as follows: From the viewpoint of traditional financial variable, the significant variables of the season before are the return of equity and earning per share. With two former seasons considered, the results of the alert model showed that variables of debt ratio all reached the 1% significant level. Two years before the distress, the most significant variable is the receivables turnover ratio. Taking one season before the distress, the alert model with VaR variable among the models studied, reaches the 1% significant level. The VaR of Sample Moving Average method, Boostrap method and Monte Carlo Simulation method could comparatively induce more the predictive ability. Two seasons before the distress, the alert model with VaR variable could not significantly increase the predictive ability in the retained sample. However, by using the testing sample, the predictive ability for all model are enhanced. As to three seasons, the one-year and the two years before the distress, none model showed increasing predictive ability.