Market Mill Dependence Pattern in the Stock Market: Individual Portraits

TL;DR

This study analyzes individual dependence patterns in stock price movements, revealing stable asymmetric market mill patterns across 2000 stocks that influence their trend-following or contrarian behavior.

Contribution

It introduces a methodology for identifying and classifying stable asymmetric dependence patterns in individual stocks based on bivariate distribution analysis.

Findings

Individual dependence patterns are stable over time.

Stocks can be classified into three main groups: correlation, anticorrelation, and market mill.

Dependence patterns influence trend-following or contrarian dynamics.

Abstract

This paper continues a series of studies of dependence patterns following from properties of the bivariate probability distribution P(x,y) of two consecutive price increments x (push) and y (response). The paper focuses on individual differences of the P(x,y) for 2000 stocks using a methodology of identification of asymmetric market mill patterns developed in [1,2]. We show that individual asymmetry patterns (portraits) are remarkably stable over time and can be classified into three major groups - correlation, anticorrelation and market mill. We analyze the conditional dynamics resulting from the properties of P(x,y) for all groups and demonstrate that it is trend-following at small push magnitudes and contrarian at large ones