Price Clustering and Discreteness: Is there Chaos behind the Noise?

TL;DR

This paper investigates the 'compass rose' patterns in stock returns, revealing evidence of nonlinear and possibly deterministic dynamics through wavelet denoising and surrogate data analysis.

Contribution

It introduces a wavelet-based denoising approach to uncover underlying nonlinear dynamics in stock returns, challenging the notion that observed patterns are solely noise.

Findings

Evidence of non-periodic cyclical dynamics in stock returns

Detection of strong nonlinear signatures in data

Indications of deterministic processes behind stock return patterns

Abstract

We investigate the "compass rose" (Crack, T.F. and Ledoit, O. (1996), Journal of Finance, 51(2), pg. 751-762) patterns revealed in phase portraits (delay plots) of stock returns. The structures observed in these diagrams have been attributed mainly to price clustering and discreteness. Using wavelet based denoising, we examine the noise-free versions of a set of FTSE100 stock returns time series. We reveal evidence of non-periodic cyclical dynamics. As a second stage we apply Surrogate Data Analysis on the original and denoised stock returns. Our results suggest that there is a strong nonlinear and possibly deterministic signature in the data generating processes of the stock returns sequences.