Non linear behaviour of stock market volatility

TL;DR

This paper models stock market volatility using a continuous time random walk approach, revealing non-stationary behavior, a consistent market response to shocks, and non-linear stabilization effects driven by diverse participant time horizons.

Contribution

It introduces a novel continuous time random walk method for fast volatility evaluation and uncovers non-linear, stabilizing market responses to external shocks over two years.

Findings

Market volatility is non-stationary.

Market response to shocks remains constant over time.

Autocorrelation of volatility increments is about -0.4.

Abstract

We exploit a continuous time random walk description of stock prices to obtain a fast and accurate evaluation of their volatility from intraday data. We show that financial markets are usefully described as open physical systems. Indeed we find that the process determining market volatility is not stationary while the market response to external volatility shocks stays constant over the time period of more than two years covered by our experimental data. Furthermore the autocorrelation function of volatility increments yields a value of about -0.4 at one-day time lag that is nearly equal for all stocks we analyze. Conditioning the evaluation of the autocorrelation function, we show that the market response is non-linear and strongly stabilizing when external shocks push for higher volatility. This market behavior can be explained by the action of participants with different time horizon.