在西元2006年底，新版巴賽爾協定即將實施，屆時各金融業將可運用內部評等法去評估客戶之違約率，雖然可由內部評等系統去估算違約機率，但在資本適足率方面，仍然是依照巴賽爾協定之平均的精神所訂定，因此較無彈性，且是屬於較消極的管理方式。本研究認為金融業應以積極的方式去處理信用風險方面的議題，除建立內部評等系統外，應建構另外一套信用風險估算系統，搭配協定所規定之內容，去管理其信用風險。
綜合上述，本研究將以CreditMetricsTM為基礎，建構一個信用風險估算系統，並運用Jarrow, Lando and Turnbull（1997）之模型，解決了因台灣市場上公司債資料不足而難以估算其信用價差的情況。
最後運用本研究所建立之系統，估算某銀行所提供放款資料之信用風險，並加以探討。實證結果發現，本研究所建構之系統，對於新增放款於信用風險之邊際效果，具有高度之敏感性，因此金融機構在建立其內部評等系統時，可搭配本研究之系統，對於信用風險作積極式管理，如此一來，金融機構對於信用風險之管理將充滿彈性又不失嚴謹。

The New Basel Capital Accord will be implemented in the end of 2006 the Christian era. Although it allows the financial institution can estimate the Probability of Default of their customers by themselves, the procedure of calculating the Minimum Capital Requirement must follow the regulations of accord. It follows the average spirit to set the Minimum Capital Requirement, so it can’t reflect the real Credit Risk of their portfolio of risky assets. Finally we can say that the Credit Risk management style is passive. This research thinks that to manage the Credit Risk must be positive, so the research wants to establish another system to measure the Credit Risk and to help the old Credit Risk management.
According to the Above-mentioned, we will establish a Credit Risk system based on CreditMericsTM and the Credit Spread will be calculated found on the model of Jarrow, Lando and Turnbull（1997）. It solves the problem that the data of bonds is not complete in Taiwan market. Finally, we use the Credit Risk system to calculate the Credit Risk of some loan materials that are supplied by the some one bank. And we find that the Credit Risk system we establish can appear the marginal effect to Credit Risk clearly when there are some new loans be added to the old portfolio. So the system will help the financial institutions in Taiwan to manage the Credit Risk and it will give a lot of useful information for Credit Risk.

1. Black, F., and M. Scholes, “The Pricing of Option and
Corporate Liabilities,” Journal of Political Economy, 81
（May/June 1973）, 637-59.

2. Cox, D., and H. Miller, The Theory of Stochastic
Processes, Chapman and Hall, London,（1972）.

3. Duffie, D., and K. Singleton, “An Econometric Model of
the Term Structure of Interest-Rate Swap Yields,”
Journal of Finance, 52（1997）, 1287-1321

4. Gupton, G. M., C. C. Finger, and M. Bhatia,
CreditMetrics™—Technical Document, New York, J. P.
Morgan,（1997）.

5. Hahnebstein L., “Calibrating the CreditMetricsTM
Correlation Concept for Nonpublicly-Traded Corporations-
Empirical Evidence from Germany,” Working paper,
（2003）.

6. Israel, R., J. Rosenthal, and J. Wei, “Finding
Generators for Markov Chain via Empirical Transition
Matrices, with Application to Credit Ratings,”
Mathematical Finance, 11,（2000）, 245-265

7. Jarrow, R., and S. Turnbull, “Pricing Derivatives on
Financial Securities Subject to CreditRisk,” Journal of
Finance, 50,（1995）, 53–86.

8. Jarrow, R., D. Lando, and S. Turnbull, “A Markov Model
for the Term Structure of Credit Risk Spreads,” Review
of Financial Studies, 10,（1997）, 482-523.

9. Kulkarni, V.G., Modeling, Analysis, Design, and Control
of Stochastic Stochastic Systems,（1999）.

10. Lando, D., “On Cox Processes and Credit Risky
Securities,” Review of Derivatives Research, 2
（1998）, 99-120

11. Merton, R. C., “On the Pricing of Corporate Debt: The
Risk Structure of Interest Rates,” Journal of finance,
29（1974）, 449-470.

12. Truck, S. and E. Ozturkmen, “Adjustment and
Application of Transition Matrices in Credit Risk
Models.” Working paper（2003）.

13. The New Basel Capital Accord: an explanatory note,
（Jan. 2001）.

14. Vasicek, O. A., “Credit Valuation,” KMV Technical
Document, KMV,（March 1984）.（http://www.kmv.com）

15. 林佳蓉，「信用風險模型之發展與衡量-以中長期資金運用制度
為例」，中山大學財務管理學系碩士論文，（民89）。

16. 徐中敏，「國內企業戶違約損失率研究」，信用資訊月刊，
（民93）。