The problem of the firm bankruptcy prediction was investigated by foreign researchers in the 1930s and it still remains relevant. Since the publishing of Altman＇s （1968） major work, based on multiple discriminant a...The problem of the firm bankruptcy prediction was investigated by foreign researchers in the 1930s and it still remains relevant. Since the publishing of Altman＇s （1968） major work, based on multiple discriminant analysis （MDA）, this methodological area has considerably changed. Taking into consideration that new data have appeared in the course of time, companies＇ average size has changed, and the accounting standards have changed （Altman, Haldeman, ＆ Narayanan, 1977）, methods and models should be renewed so as to be appropriate for current situation. The purpose of this paper1 is to reveal factors causing bankruptcy and use models appropriate for prediction bankruptcy in the area of a construction industry during the financial crisis. This investigation has been carried out on the basis of logit and probit analysis. The main reasons of bankruptcy revealed in the course of this investigation are the following： （1） non-optimal capital structure formation; （2） ineffective liquidity management; （3） decrease in assets profitability; and （4） decrease in short-term assets turnover. The most reliable indicators which give warning of bankruptcy ahead of others are financial instability and liquidity ratios.展开更多
Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the autho...Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the authors propose a ridge-forward quadratic discriminant(RFQD) analysis method via screening relevant predictors in a successive manner to reduce misclassification rate.The authors use extended Bayesian information criterion to determine the final model and prove that RFQD is selection consistent.Monte Carlo simulations are conducted to examine its performance.展开更多
文摘The problem of the firm bankruptcy prediction was investigated by foreign researchers in the 1930s and it still remains relevant. Since the publishing of Altman＇s （1968） major work, based on multiple discriminant analysis （MDA）, this methodological area has considerably changed. Taking into consideration that new data have appeared in the course of time, companies＇ average size has changed, and the accounting standards have changed （Altman, Haldeman, ＆ Narayanan, 1977）, methods and models should be renewed so as to be appropriate for current situation. The purpose of this paper1 is to reveal factors causing bankruptcy and use models appropriate for prediction bankruptcy in the area of a construction industry during the financial crisis. This investigation has been carried out on the basis of logit and probit analysis. The main reasons of bankruptcy revealed in the course of this investigation are the following： （1） non-optimal capital structure formation; （2） ineffective liquidity management; （3） decrease in assets profitability; and （4） decrease in short-term assets turnover. The most reliable indicators which give warning of bankruptcy ahead of others are financial instability and liquidity ratios.
基金supported by the National Natural Science Foundation of China under Grant No.11401391
文摘Quadratic discriminant analysis is a classical and popular classification tool,but it fails to work in high-dimensional situations where the dimension p is larger than the sample size n.To address this issue,the authors propose a ridge-forward quadratic discriminant(RFQD) analysis method via screening relevant predictors in a successive manner to reduce misclassification rate.The authors use extended Bayesian information criterion to determine the final model and prove that RFQD is selection consistent.Monte Carlo simulations are conducted to examine its performance.
