A new traders’ game? — Empirical analysis of response functions in a historical perspective

Traders on financial markets generate non–Markovian effects in various ways, particularly through their competition with one another which can be interpreted as a game between different (types of) traders. To quantify the market mechanisms, we empirically analyze self–response functions for pairs of different stocks and the corresponding trade sign correlators. While the non–Markovian dynamics in the self–responses is liquidity–driven, it is expectation–driven in the cross–responses which is related to the emergence of correlations. We empirically study the non–stationarity of these responses over time. In our previous data analysis, we only investigated the crisis year 2008. We now considerably extend this by also analyzing the years 2007, 2014 and 2021. To improve statistics, we also work out averaged response functions for the different years. We find significant variations over time revealing changes in the traders’ game.