An application of VaR in financial distress alert model for listed and OTC companies in Taiwan

• Main Author: 林珮君
• Other Authors: Her-Jiun Sheu
• Format: Others
• Language: zh-TW
• Published: 2004
• Online Access: http://ndltd.ncl.edu.tw/handle/93627934158477334590

碩士 === 國立交通大學 === 經營管理研究所 === 92 === Since researches showed that Taiwan stock market is efficient, it is suspected that further study of the data of stock price index can increase the predictive ability of alert model. VaR is treated as additional variables to enhance the predictive ability of alert model in this study. The additional variables of VaR index are: Sample Moving Average, Exponentially Weighted Moving Average, Historical Simulation, Boostrap, and Monte Carlo Simulation. The results are summarized as follows: (1) With the increasing of the predictive period, the predictive ability of alert model is decreased. From the viewpoint of tradtional 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. It is implied that the company may have the trouble of turnover. (2) 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. (3) 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.