應用COPULA函數於金磚五國投資組合相關性及風險值評估

Apply Copula Function in the Evaluation of Dependence and VaR for BRICS Portfolios

黃泰源(Tai-Yuan Huang)

指導教授 ： 李沃牆

共同指導教授 ： 池秉聰(Ping-Tsung Chih)

淡江大學/商管學院/財務金融學系碩士班/碩士(2013年)

https://doi.org/10.6846/TKU.2013.00917

摘要

本研究使用VAR-COV、CCC、DCC，和以Copula為基礎的GJR-GARCH模型（Copula based GJR-GARCH Model）四種方法，並參考 Huang et al. （2009）的模型方法，以評估金磚五國投資組合之風險值，後續利用Kupiec（1995）提出的概似比檢定（Likelihood Ratio Test, LR test）和穿透率評估風險值模型的準確性。
實證結果發現，由於金磚五國投資組合相關性提高，導致無法有效的分散風險；概似比檢定希臘赤字危機後，用Copula函數轉換之GJR-GARCH模型在99%信賴區間估計的風險值為最合理，反之，其他三種方法無法找出合理的風險值，因此，比起傳統線性結構，非線性比較能提供相對合理的風險值；最後，在全樣本期間中，相對其他Copula函數，以Student's t-Copula及 SJC-Copula函數轉換之金磚五國投資組合風險值為最佳。

關鍵字

金磚五國 ； 相關係數 ； Copula函數 ； 風險值

並列摘要

The study applies VAR-COV, CCC, DCC, and Copula based GJR-GARCH Model to evaluate Value at Risk for portfolios of BRICS. To refer to procedure Huang et al. (2009) proposed. On the other hand, the study applies Likelihood Ratio Test which Kupiec (1995) proposed and penetration ratio to evaluate the accuracy of VaR model.
The empirical results demonstrate the relationship between BRICS index has significant increasing that didn’t have diversified effect of risk. By likelihood ratio test, Copula based GJR-GARCH model can correctly forecast 99 percentage VaR but VAR-COV, CCC, DCC model can’t forecast VaR rationally after Greek government debt crisis. Compared with traditional linear structure, nonlinear structure are relatively correct on VaR forecasting. Finally, consider full sample estimated Student's t Copula and SJC Copula have significantly effect to fitting the relationship between portfolios of BRICS VaR but the others haven’t.

並列關鍵字

BRICS ； Correlation coefficient ； Copula function ； GARCH model ； VaR

參考文獻

5. 曾智業(2012)，國際投資組合之風險值評估，淡江大學財務金融所碩士論文。

6. 陳冠璋(2010)，Copula之估計法比較與模型診斷，國立臺北大學統計所碩士論文。

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