The market drives ETFs or ETFs the market: causality without Granger

2022/04/07 by P. B. Lerner, Peter Lerner, Lerner, Peter
Decision Sciences · Economics, Econometrics and Finance · Mathematics · #Applications (stat.AP) #Complex Systems and Time Series Analysis #FOS: Computer and information sciences #FOS: Economics and business #Financial Markets and Investment Strategies #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods #Trading and Market Microstructure (q-fin.TR) #q-fin.ST #q-fin.TR #stat.AP

paper · pdf · doi:10.48550/arxiv.2204.03760

arxiv created 2022/04/07 · openalex publication_date 2022/04/07 · arxiv updated 2022/04/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

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.

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