Multiscale behaviour of volatility autocorrelations in a financial market

TL;DR

This paper analyzes NYSE daily returns and finds that volatility autocorrelations follow power-law distributions across multiple time scales from one day to one year, revealing complex multiscale behavior.

Contribution

It demonstrates the multiscale nature of volatility autocorrelations in financial markets through a scaling analysis of daily returns.

Findings

Volatility correlations follow power-law behavior.

Autocorrelations exhibit multiscale properties.

Power-law behavior extends from one day to one year.

Abstract

We perform a scaling analysis on NYSE daily returns. We show that volatility correlations are power-laws on a time range from one day to one year and, more important, that they exhibit a multiscale behaviour.