The Study of Assessing the China Business in Predicting Default Risk: Weighted Hybrid Model

• Main Authors: Ting-Yuan Chou, 周定遠
• Other Authors: 林修葳
• Format: Others
• Language: zh-TW
• Published: 2014
• Online Access: http://ndltd.ncl.edu.tw/handle/vvs34w

碩士 === 國立臺灣大學 === 國際企業學研究所 === 102 === Aiming at better estimating the probability of corporate defaults, which has typically been the key element in risk management, this study explores the limitations of KMV Model and Altman Z-score as well as Logit accounting-based Model. Specifically, it incorporates both market and accounting-based models and examines the suitable weights on the two types of models of based on characteristic variables including earnings-price ratio, and liquidity. The new model, Revised Hybrid Model, (RHM), outperforms in type I and type II errors the two individual models. This study include both firms that actually defaulted and the ones that should be defined as with stealth default; Using the weighing variable based on previous literatures, I document that the refined-Revised Hybrid Model (RHM) performs better on predicting default rates than KMV Model and Logit models. It also has lower Type I error when Type II error has been controlled than the original models.