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標題: | 建構信用指數與計算各分券的基礎相關性:以臺灣金融業與非金融業為例 To Construct Credit Index and Its Base Correlation: The Cases of Financial and non-Financial Industries |
作者: | Ying-Hung Lin 林盈宏 |
指導教授: | 李賢源(Shyan Yuan Lee) |
關鍵字: | 信用組合,信用指數,違約相關性,基礎相關性,KMV模型,LHP模型,信用風險, Credit Portfolio,credit index,default correlations,base correlations,KMV model,LHP model,credit risk, |
出版年 : | 2014 |
學位: | 碩士 |
摘要: | 世界上有許多尚未具有完整信用市場的地區。如何正確地建構這些地區的信用市場是分析此地區信用風險的第一步。本文延續Lee, Chung and Tao (2011) 的方法,用Moody’s KMV顧問公司的信用風險結構式模型建構類似CDX. NA. IG. 的信用組合;在模擬抽樣時,以解析解得出違約時點並加入變異減縮法改善穩定性;再以J.P. Morgan 的LHP (Large Homogeneous Pool) 基礎相關性模型計算基礎相關性。最後以模擬得出之指數信用價差、基礎相關性以及首次支付費用進行分析。本研究以臺灣市場的資料為例,分別對上市櫃金融業以及臺灣50的非金融業成分股進行模擬計算。實證結果發現:此分析方式確實在評估市場信用風險上具備一定可信度。此外,本方法也顯示金融業市場和非金融業市場對於重大衝擊事件(例如:金融海嘯)的影響有何差異。 There are lots of area which does not have complete credit market. To analyze the credit risk of these area, first we have to construct these credit markets correctly. This article extends the study method of Lee, Chung and Tao (2011). By Moody’s KMV structure model, we can price a credit portfolio similar to CDX. NA. IG by simulation. In order to reduce the variation of simulation results, I used analytic solution of default time and variance reduction method when sampling. Then calculation by J.P. Morgan's LHP (Large Homogeneous Pool) model, we get the base correlation with respect to each upper attachment point. Finally, we can analyze the credit index, base correlation and the upfront fee for each tranche. The empirical results uses Taiwan's market data. There are two samples: first is the listed and the OTC financial firms; another sample is the industrial firms of constituent stocks of Taiwan 50 index. It shows that this study method is credible. Moreover, this method also shows the difference impacts of big financial events (such as financial crisis) between financial firms and industrial firms. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/56316 |
全文授權: | 有償授權 |
顯示於系所單位: | 財務金融學系 |
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