Price response functions and spread impact in correlated financial markets

TL;DR

This paper investigates how different methods of measuring price response in stock markets affect results, emphasizing the importance of order effects, immediate responses, and spread size on price impact in correlated markets.

Contribution

It systematically compares price response definitions, highlights the significance of trade order and immediate effects, and quantifies spread impact on price response in NASDAQ stocks.

Findings

Results are consistent across two time scale definitions.

Order between trade signs and returns significantly affects response signals.

Immediate price response dominates, with delayed effects being minimal.

Abstract

Recent research on the response of stock prices to trading activity revealed long lasting effects, even across stocks of different companies. These results imply non-Markovian effects in price formation and when trading many stocks at the same time, in particular trading costs and price correlations. How the price response is measured depends on data set and research focus. However, it is important to clarify, how the details of the price response definition modify the results. Here, we evaluate different price response implementations for the Trades and Quotes (TAQ) data set from the NASDAQ stock market and find that the results are qualitatively the same for two different definitions of time scale, but the response can vary by up to a factor of two. Further, we show the key importance of the order between trade signs and returns, displaying the changes in the signal strength. Moreover, we confirm the dominating contribution of immediate price response directly after a trade, as we find that delayed responses are suppressed. Finally, we test the impact of the spread in the price response, detecting that large spreads have stronger impact.