  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.
