在現今的風險管理上，債劵投資組合所關心的不再僅僅是違約風險 (default
risk)，更需要探討的是其信用風險 (credit risk)。風險值 (Value-at-Risk) 是一個廣泛應用的風險測量指標，在本篇論文，我們使用信用計量模型(CreditMetricsmodel ) 來評估債劵投資組合的風險值。然而，當債劵投資組合極其龐大且複雜時，估計風險值是困難的。因此，運用維度簡化的方法 (dimesional reduction technique) 來減少所需生成之隨機變數是必要的。在此引入因素模型 (factor model ) 來解決維度簡化的問題，並在最後觀察其簡化前後風險值有無明顯的差異。

Under current risk management, a bond portfolio is not only concerned about
the default risk, but also needs to study its credit risk. Value-at-Risk (VaR) is used
commonly in risk measurement. In this paper, we apply the CreditMetrics model to assess the VaR of the portfolio of bonds. However, it is hard to assess VaR as the portfolio of bonds is extremely large and complicated. Therefore, using the technique of dimension reduction is needed to reduce the required number of random variables. Here, we introduce the factor model to solve the problem of
dimension reduction. Finally, we also note the difference of VaR before and after
this reduction.

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