臺灣博碩士論文加值系統

本研究利用主成份分析方法計算美國利率期限結構之風險值，依Frye （1997）之方法將主成份分析結果與情境模擬方法結合，探討主成份因子與總體經濟間之關係，利用改變資料型態、依照聯準會升降息循環切割樣本期間，來觀察三個主成份因子解釋能力間的變化，最後，分析三個利差指標與主成份因子間的關係，探討主成份因子是否隱含總體經濟面的訊息。結果發現，當金融市場出現危機時，第二主成份因子與第三主成份因子的解釋能力大幅提昇，表示當時利率期限結構 「斜率」與「曲度」出現變化，也因此得知，主成份因子除了在計算利率風險值外，其解釋能力也隱含整體利率期限結構的改變，進而隱含當時的金融環境狀況。

In this thesis, we use principal components analysis to calculate the VaR of interest rates related with the term structure in U.S., according to Frye (1997) which combine principal component analysis results with scenario simulation methods, to explore the relationship between the principal components factors and overall economy by changing the data type、separating the data period by Federal interest rate rising/falling cycle, in order to observe the different with three principal components factors explanatory power. Finally, analysis the connection with three yield spread indexes and principal components factors, to explore whether the principal components factors implied the information about the macroeconomic. The results show that when the financial market crisis, the second factor and the third factor explanatory power substantial increase, which means that the slope of term structure and the curve of term structure have change. Therefore, principal component factor not only can evaluate the VaR about rates, but also can implied the whole term structure change and the current financial environment.

摘要 ii
ABSTRACT iii
目錄 iv
表目錄 vi
圖目錄 vii
一 、緒論 1
1-1 研究動機 1
1-2 研究目的 2
1-3 本文架構 3
二 、文獻回顧 4
2-1 利率期間結構之相關文獻 4
2-2 風險值衡量之相關文獻 5
2-3 利率風險管理的方法 6
2-4 利差之相關文獻 8
三 、研究方法 9
3-1 資料來源 9
3-2 利率期限結構之估計 9
3-3 主成份分析 10
四 、資料與主成份分析結果 12
4-1 全樣本期間 13
4-2 標準化之差異 20
4-3 Fed貨幣政策轉變之差異 22
五 、主成份因子與利差之關係 37
5-1 利差介紹 37
5-2 利差對於總體經濟之關係 41
5-3 主成份因子與利差在總體經濟上之解釋 44
六 、結論與後續作法 45
參考文獻 47
附錄 49

一、英文文獻：
1. Estrella and Hardouvelis (1991), The Term Structure as a Predictor of Real Economic Activity

2. Frye, J. (1997), “Principles of Risk: Finding VAR through Factor-Based Interest Rate Scenarios.”, In VAR: Understanding and Applying Value at Risk.London: Risk Publicarion, :275-288.

3. Golub, B. W., & Tilman, L. M. (1997). “Measuring Yield Curve Risk Using Principal Components, Analysis, Value, At Risk, And Key Rate Durations.” The Journal of Portfolio Management, 23(4), 72-84.

4. Ho, T. S. Y. (1992), “Key Rate Durations：Measuring of Interest Rate Risk,” The Journal of Fixed Income, 2(2), September, 29-44.

5. J. P. Morgan (1996), “RiskMetrics Technical Document.” 4th ed., Morgan Guaranty Trust Company.

6. John C. Hull (2014). “Options, Futures and Other Derivatives.”
9rd ed. New Jersey: Prentice-Hall.

7. Litterman, R., and J. Scheinkman (1991), “Common Factors Affecting
Bond Returns,” The Journal of Fixed Income, June, 54-61.

8. Singh, M. K. (1997) “Value at Risk Using Principal Component Analysis,” The Journal of Portfolio Management, 24(1), Fall, 101-112.

9. Svensson, Lars E. O, (1994), “Estimating and Interpreting Forward Interest Rates: Sweden 1992-1994,” National Bureau of Economic Research.

10. Zhang, H. (1993). Treasury yield curves and Cointegration. Applied Economics, 25(3), 361-367.


二、中文文獻：
1. 葉仕國、林丙輝，民國九十一年，「以主成份分析方法計算台灣利率期限結構的風險值」，台灣管理學刊，第一卷第二期，頁275-288