替代抽样方案下的Epps效应
The Epps effect under alternative sampling schemes
摘要：
时间和测量时间尺度的选择是我们选择如何在金融中表示信息和数据的基础。这一选择意味着用于描述金融体系的统计可衡量指标的单位和汇总尺度。它还定义了我们如何衡量不同交易工具之间的关系。当我们从高频时间尺度（当单个交易和报价事件发生时）转移到中尺度（当相关性以符合各种潜在模型的方式出现时）时，仍然不清楚选择什么样的时间和采样率才能忠实地捕捉系统动态和资产相关性，以便做出决策。Epps效应是将相关性的出现与采样时间尺度的选择相耦合的关键现象学。在这里，我们考虑和比较不同的抽样方案下的Epps效应，以对比三种时间的选择：日历时间，交易量时间和交易时间。使用基于霍克斯过程的玩具模型，我们能够实现符合经验动力学的模拟结果。具体地说，我们发现，埃普斯效应是目前在所有三个定义的时间和相关性出现更快的贸易时间相比，日历时间，而相关性出现在量的时间呈线性。
英文摘要：
Time and the choice of measurement time scales is fundamental to how we choose to represent information and data in finance. This choice implies both the units and the aggregation scales for the resulting statistical measurables used to describe a financial system. It also defines how we measure the relationship between different traded instruments. As we move from high-frequency time scales, when individual trade and quote events occur, to the mesoscales when correlations emerge in ways that can conform to various latent models; it remains unclear what choice of time and sampling rates are appropriate to faithfully capture system dynamics and asset correlations for decision making. The Epps effect is the key phenomenology that couples the emergence of correlations to the choice of sampling time scales. Here we consider and compare the Epps effect under different sampling schemes in order to contrast three choices of time: calendar time, volume time and trade time. Using a toy model based on a Hawkes process, we are able to achieve simulation results that conform well with empirical dynamics. Concretely, we find that the Epps effect is present under all three definitions of time and that correlations emerge faster under trade time compared to calendar time, whereas correlations emerge linearly under volume time.
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