摘要翻译：
我们提出了一个分数协整时间序列的设置，它是由潜在的、集成的和短记忆分量组成的。它能适应不同分数阶的非平稳过程和不同强度的协整，适用于高维环境。在已实现的协方差矩阵的应用中，我们发现与几种竞争方法相比，正交短内存和长内存分量提供了合理的拟合和竞争性的样本外性能。
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英文标题：
《Multivariate Fractional Components Analysis》
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作者：
Tobias Hartl and Roland Weigand
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最新提交年份：
2019
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分类信息：

一级分类：Economics        经济学
二级分类：Econometrics        计量经济学
分类描述：Econometric Theory, Micro-Econometrics, Macro-Econometrics, Empirical Content of Economic Relations discovered via New Methods, Methodological Aspects of the Application of Statistical Inference to Economic Data.
计量经济学理论，微观计量经济学，宏观计量经济学，通过新方法发现的经济关系的实证内容，统计推论应用于经济数据的方法论方面。
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英文摘要：
  We propose a setup for fractionally cointegrated time series which is formulated in terms of latent integrated and short-memory components. It accommodates nonstationary processes with different fractional orders and cointegration of different strengths and is applicable in high-dimensional settings. In an application to realized covariance matrices, we find that orthogonal short- and long-memory components provide a reasonable fit and competitive out-of-sample performance compared to several competing methods.
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PDF链接：
https://arxiv.org/pdf/1812.09149