| 王泓娜,宋立新.基于偏态分布的风险度量计算[J].,2012,(4):615-618 |
| 基于偏态分布的风险度量计算 |
| Computing of risk measurement based on skewed distributions |
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| DOI：10.7511/dllgxb201204025 |
| 中文关键词: APARCH Skewed-\%t\%分布 Skewed-GED 在险价值 期望损失 |
| 英文关键词: APARCH Skewed- t distribution Skewed-GED value-at-risk expected shortfall |
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| 中文摘要: |
| 金融时间序列具有尖峰厚尾性,同时在股市中又存在着杠杆效应．对股票指数收盘价格的对数收益率序列建立ARMA-APARCH模型,在对数收益率序列分别满足Skewed-\%t\%分布和Skewed-GED的假设下,给出了在险价值及期望损失的计算方法．对\%t\%分布与Skewed-\%t\%分布、GED与Skewed-GED分别进行对比性实证分析,结果表明,在两个偏态分布假设下计算得到的期望损失估计结果更为保守,更能够捕捉到股市的尾部风险． |
| 英文摘要: |
| Financial time series have the sharp peak and fat-tailed characteristics and leverage in stock market. The ARMA-APARCH model is established based on logarithm yield ratio series of the stock index closing price and value-at-risk (VaR) and expected shortfall (ES) computing methods are provided in the assumption of the sequence of logarithm yield ratio series satisfying the distributions of Skewed-\%t\% and Skewed-GED respectively. Having compared \%t\% distribution with Skewed-\%t\% distribution, GED and Skewed-GED, it is proved that the ES estimations considering asymmetrical distribution are more conservative and more efficient to capture the tail risk of stock market. |
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