Predicting Corporate Financial Distress in Taiwan
Date Issued
2007
Date
2007
Author(s)
Shen, Chang-Han
DOI
zh-TW
Abstract
Since the late 1990s, the amount of credit risk taken by banks has increased so that the ability to predict company’s default probability has become a critical issue of risk management. This thesis aims to develop a financial distress prediction model, which is based on the KMV model and utilizes historical default probability data from the S&P and Taiwan Ratings Corporation. We hope this model will meet the requirements under the New Basel Capital Accord.
Moreover, this thesis focuses on comparing the forecast accuracy of option pricing model and credit scoring model. We use the KMV-S&P model developed in our research as a representative of option pricing model, and choose a Z-Score model for Taiwan’s companies to represent the credit scoring model. Through intra-cohort analysis, logit regression method and power curve, we investigate the relative informativeness regarding financial distress of the models. The findings of our research are as follows:
1.As for the KMV-S&P model, first-order correlation stock price volatility and total debt are the best agents of equity volatility and default point, respectively.
2.We compare the KMV-S&P model and local Z-Score model in their predicting corporate financial distress with the intra-cohort analysis and logit regression methods; the results indicate that both models have significant predictive ability. However, the alternative method, power curve, concludes that the KMV-S&P model outperforms the local Z-Score model.
3.Although the power curve shows that KMV-S&P model is superior in predicting financial distress of Taiwan’s companies, the intra-cohort analysis and logit regression methods indicate that both models have equal predictive abilities. Therefore, we suggest that both models provide incremental information in measuring credit risk.
Subjects
信用風險
財務危機
違約機率
選擇權評價模型
信用評分模型
Credit Risk
Financial Distress
Probability of Default
Option Pricing Model
Credit Scoring Model
Type
thesis
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