| 中国股指收益率的非对称拉普拉斯分布实证检验 |
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| 引用本文： | 曾五一,刘飞.中国股指收益率的非对称拉普拉斯分布实证检验[J].统计与信息论坛,2012,27(12):27-31. |
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| 作者姓名： | 曾五一 刘飞 |
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| 作者单位： | 厦门大学经济学院,福建厦门,361005 |
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| 摘 要： | 应用非对称拉普拉斯分布拟合沪深两市股指日、周收益率数据。研究结果表明:非对称拉普拉斯分布能够比正态分布更好地反映两市股指的日、周收益率数据的尖峰、厚尾、偏态特征。由于非对称拉普拉斯分布有显性的表达式,便于开展参数估计和数字特征的计算,因此对于股指期货投资者而言,在计算股指收益率的VaR、CVaR进行风险测量时,采用非对称拉普拉斯分布将是较好的选择。
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| 关 键 词： | 非对称拉普拉斯分布 股指收益率 尖峰 厚尾 |
An Empirical Study on Asymmetric Laplace Distribution of Stock Index Returns in China |
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| ZENG Wu-yi
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LIU Fei.An Empirical Study on Asymmetric Laplace Distribution of Stock Index Returns in China[J].Statistics & Information Tribune,2012,27(12):27-31. |
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| Authors: | ZENG Wu-yi LIU Fei |
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| Affiliation: | (School of Economies, Xiamen University, Xiamen 361005, China) |
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| Abstract: | The paper fits daily and weekly stock index return data in Shanghai Composite Index and Shenzhen Component Index using asymmetric Laplace distribution. It concludes that asymmetric Laplace distribution is better fitted than normal distribution about the characteristics of leptokurtic, heavy tail, skewness. And the daily return is better fitted than weekly return. When we choose the distribution for calculating VaR and CVaR on stock index return, asymmetric Laplace distribution will be a better choice for stock index risk manager. |
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| Keywords: | asymmetric Laplace distribution stock index returns leptokurtic heavy tail |
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