金融相关性计算中的补偿效应
Compensating asynchrony effects in the calculation of financial correlations
摘要：
提出了一种补偿异步时间序列相关性计算中统计误差的方法。该方法是基于一个潜在的时间序列的假设。我们建立了一个模型，并将其应用于金融数据，以检查对较小的回报间隔（Epps效应）的计算相关性的下降。我们表明，这种统计效应是一个主要原因的Epps效应。因此，我们能够仅使用交易价格和交易时间对其进行量化和补偿。
英文摘要：
We present a method to compensate statistical errors in the calculation of correlations on asynchronous time series. The method is based on the assumption of an underlying time series. We set up a model and apply it to financial data to examine the decrease of calculated correlations towards smaller return intervals (Epps effect). We show that this statistical effect is a major cause of the Epps effect. Hence, we are able to quantify and to compensate it using only trading prices and trading times.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
