英文标题：
《Portfolio return distributions: Sample statistics with non-stationary
correlations》
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作者：
Desislava Chetalova, Thilo A. Schmitt, Rudi Sch\\\"afer and Thomas Guhr
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最新提交年份：
2014
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英文摘要：
We consider random vectors drawn from a multivariate normal distribution and compute the sample statistics in the presence of non-stationary correlations. For this purpose, we construct an ensemble of random correlation matrices and average the normal distribution over this ensemble. The resulting distribution contains a modified Bessel function of the second kind whose behavior differs significantly from the multivariate normal distribution, in the central part as well as in the tails. This result is then applied to asset returns. We compare with empirical return distributions using daily data from the Nasdaq Composite Index in the period from 1992 to 2012. The comparison reveals good agreement, the average portfolio return distribution describes the data well especially in the central part of the distribution. This in turn confirms our ansatz to model the non-stationarity by an ensemble average.
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中文摘要：
我们考虑从多元正态分布中提取的随机向量，并在存在非平稳相关性的情况下计算样本统计。为此，我们构造了一个随机相关矩阵集合，并在此集合上平均正态分布。由此产生的分布包含第二类修正贝塞尔函数，其行为在中部和尾部与多元正态分布显著不同。然后将该结果应用于资产回报。我们使用纳斯达克综合指数1992年至2012年期间的每日数据与经验收益率分布进行了比较。比较显示出良好的一致性，平均投资组合收益分布很好地描述了数据，尤其是在分布的中心部分。这反过来证实了我们的ansatz通过集合平均来模拟非平稳性。
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分类信息：

一级分类：Quantitative Finance 数量金融学
二级分类：Statistical Finance 统计金融
分类描述：Statistical, econometric and econophysics analyses with applications to financial markets and economic data
统计、计量经济学和经济物理学分析及其在金融市场和经济数据中的应用
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