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 with several competing methods.

中文翻译：

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多元分数成分分析

我们提出了一个分数协整时间序列的设置，它是根据潜在集成和短记忆组件制定的。它适应具有不同分数阶和不同强度协整的非平稳过程，适用于高维环境。在实现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组件提供了合理的拟合和具有竞争力的样本外性能。