In this paper we consider a portfolio selection problem defined for irregularly spaced observations. We use the Independent Component Analysis for the identification of the dependence structure and continuous-time GARCH models for the marginals. We discuss both estimation and simulation of market prices in a context where the time grid of price quotations differs across assets. We present an empirical analysis of the proposed approach using two high-frequency datasets that provides better out-of-sample results than competing portfolio strategies except for the case of severe market conditions with frequent rebalancements.

中文翻译：

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不规则时间网格的投资组合选择：使用 ICA-COGARCH(1, 1) 方法的示例

在本文中，我们考虑为不规则间隔观察定义的投资组合选择问题。我们使用独立成分分析来识别边际的依赖结构和连续时间 GARCH 模型。我们在报价时间网格因资产而异的情况下讨论市场价格的估计和模拟。我们使用两个高频数据集对所提出的方法进行了实证分析，这些数据集提供了比竞争投资组合策略更好的样本外结果，但在严重的市场条件和频繁重新平衡的情况下除外。