Credit Risk Analysis of Listed Corporations in China: Application of Merton(1974)

Abstract

[[abstract]]隨著金融市場發展逐漸擴張，信用風險管理的重要性愈趨重要，而在金融市場逐漸發展成熟的中國市場上，如何建構出可衡量並預警企業是否發生財務危機之模型，應為當前首要課題，本研究將利用Altman Z-score模型與Merton模型，來預測中國上海A股之上市公司發生財務危機的可能性，以及Merton模型之預測效率。本文以在2005年至2012期間的上海A股之上市公司為研究樣本，並依據SSE產業類別將總樣本分類為工業類、商業類、公用事業類、地產類以及綜合類等五個產業，討論中國上市企業之違約機率，同時說明Merton模型在預測違約的型I誤差與型II誤差。研究結果發現，在金融危機期間，中國上市公司的違約機率均呈現下跌的趨勢，而 產業的違約機率則呈現落後的趨勢。若以型I誤差最小化來選擇最適模型，負債門檻以短債1%、長債99%，且違約機率超過50%視為違約為最適模型；若以型II誤差最小化做為選擇模型標準，負債門檻為短債100%、長債0%，並利用外部信評機構所公告的投機等級公司的平均違約機率為違約門檻的模型配置效率最佳。[[abstract]]With the gradual expansion of financial market development the importance of credit risk management become increasingly important Gradually developed in the financial markets on the Chinese market how to construct a measurable model and make it able to warn whether a company is in financial crisis should be the primary issue for the current This study will use the Altman Z-score model and Merton model to predict the possibility of financial crises in Shanghai listed companies as well as the Merton model prediction efficiency In this paper I use the 2005-2012 period Shanghai listed companies as samples and based on the SSE industry categories classified as industrial commercial utilities real estate classes as the total sample and integrated class five industries to discuss listed companies probability of default in China It also describes Merton model in predicting type I error and the type II error The results showed that during the financial crisis China's probability of default of listed companies showed a downward trend while the industry's probability of default is showing behind the trend In terms of type I error is minimized to select the optimal model for short-term debt liabilities threshold to 1% of long-term debt 99% and more than 50% probability of default as default for the optimal model; If in terms of type II error is minimized as the standard to choose model debt threshold should be 100% of short-term debt and 0% long-term debt It would be most efficient for the allocation to use the announcements of external credit rating agencies and take the average probability of default of speculative grade companies as default threshol