桂林理工大学学报
桂林理工大學學報
계림리공대학학보
JOURNAL OF GUILIN UNIVERSITY OF TECHNOLOGY
2014年
2期
396-400
,共5页
Copula%CTE%非对称Laplace分布
Copula%CTE%非對稱Laplace分佈
Copula%CTE%비대칭Laplace분포
Copula%CTE%asymmetric Laplace distribution
采用Copula函数结合非对称Laplace分布的方法来刻画股票收益的尖峰、厚尾及偏倚性，计算了以上证指数和深证成指为组合的对数收益率的CTE，与传统的正态假设进行了对比，证实了“在资本收益率不服从正态分布时，用VaR方法来度量风险就不再准确”的结论，Copula函数结合非对称Laplace分布的方法可以较好的计算投资组合的CTE。
採用Copula函數結閤非對稱Laplace分佈的方法來刻畫股票收益的尖峰、厚尾及偏倚性，計算瞭以上證指數和深證成指為組閤的對數收益率的CTE，與傳統的正態假設進行瞭對比，證實瞭“在資本收益率不服從正態分佈時，用VaR方法來度量風險就不再準確”的結論，Copula函數結閤非對稱Laplace分佈的方法可以較好的計算投資組閤的CTE。
채용Copula함수결합비대칭Laplace분포적방법래각화고표수익적첨봉、후미급편의성，계산료이상증지수화심증성지위조합적대수수익솔적CTE，여전통적정태가설진행료대비，증실료“재자본수익솔불복종정태분포시，용VaR방법래도량풍험취불재준학”적결론，Copula함수결합비대칭Laplace분포적방법가이교호적계산투자조합적CTE。
In order to improve the VaR model,a better method of risk measurement,Conditional Tail Expecta-tion (CTE)is adopted.As actual distribution of asset earning rate possesses the characteristics of steep peaks, heavy tails and skew,traditional normal distribution cannot properly describe these characteristics.To solve this problem,a new approach by combining copula function technique with asymmetric Laplace distribution is used.Finally,the VaR and CTE of the portfolios are computed by Monte Carlo simulation.The empirical a-nalysis describe that the Copula method is much better than the Gaussian one.
