论文标题
市场推动ETF或ETFS市场：没有Granger的因果关系
The market drives ETFs or ETFs the market: causality without Granger
论文作者
论文摘要
本文开发了一种基于学习的计量经济学方法，以确定财务时间序列的因果关系。该方法应用于单个股票的每日交易的不平衡，以及报道用纳秒时间邮票进行SEC的ETF。根据我们的方法，我们得出结论，仅ETF的交易失衡比整个市场的交易失衡更具信息性。特征是，与单个股票相关的大量不平衡消息在8：1的比例中占主导地位的不平衡信息。
This paper develops a deep learning-based econometric methodology to determine the causality of the financial time series. This method is applied to the imbalances in daily transactions in individual stocks, as well as the ETFs reported to SEC with a nanosecond time stamp. Based on our method, we conclude that transaction imbalances of ETFs alone are more informative than the transaction imbalances in the entire market. Characteristically, a sheer number of imbalance messages related to the individual stocks dominates the imbalance messages due to the ETF in the proportion of 8:1.
