Peter Lerner | Searcharxiv

arXiv2022

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

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.

q-fin.TR↗

arXiv2014

Patience vs. Impatience of Stock Traders

An ability to postpone one's execution without penalty provides an important strategic advantage in high-frequency trading. To elucidate competition between traders one has to formulate to a quantitative theory of formation of the execution price from market expectations and quotes. This theory was provided in 2005 by Foucault, Kadan and Kandel. I derive asymptotic distribution of the bids/offers as a function of the ratio of patient and impatient traders using the dynamic version of the Foucault, Kadan and Kandel dynamic Limit Order Book (LOB) model. Dynamic version of the LOB model allows stylized but sufficiently realistic representation of the trading markets. In particular, dynamic LOB allows simulation of the distribution of execution times and spreads from high-frequency quotes. Significant analytic progress is made towards understanding of trading as competition for immediacy of execution between traders. The results are qualitatively compared with empirical volume-at-price distribution of highly liquid stocks.

q-fin.TR↗