Permutation approach, high frequency trading and variety of micro patterns in financial time series

TL;DR

This paper uses a permutation approach to analyze how high frequency trading influences micro patterns in financial time series, revealing a decrease in pattern dominance over time due to increased trading frequency.

Contribution

Introduces a permutation-based method to study the impact of high frequency trading on micro patterns in financial data over time.

Findings

Variety of micro patterns evolve through time.

The scale of markets with no dominant patterns has decreased.

Higher frequency trading correlates with reduced pattern dominance.

Abstract

Permutation approach is suggested as a method to investigate financial time series in micro scales. The method is used to see how high frequency trading in recent years has affected the micro patterns which may be seen in financial time series. Tick to tick exchange rates are considered as examples. It is seen that variety of patterns evolve through time; and that the scale over which the target markets have no dominant patterns, have decreased steadily over time with the emergence of higher frequency trading.