Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity

TL;DR

This paper tests the fractal markets hypothesis's ability to predict market dynamics during crises by analyzing liquidity and investment horizons, introducing new measures, and comparing predictions with actual market behavior during the 2008 financial crisis.

Contribution

It introduces novel measures of trading activity based on scaling variance and demonstrates their effectiveness in explaining market behavior during turbulence.

Findings

Fractal markets hypothesis predictions align well with observed market dynamics during the crisis.

New measures of trading activity at different investment horizons are effective.

Market behavior during the crisis supports the heterogeneity and complexity assumptions of the hypothesis.

Abstract

We investigate whether fractal markets hypothesis and its focus on liquidity and invest- ment horizons give reasonable predictions about dynamics of the financial markets during the turbulences such as the Global Financial Crisis of late 2000s. Compared to the mainstream efficient markets hypothesis, fractal markets hypothesis considers financial markets as com- plex systems consisting of many heterogenous agents, which are distinguishable mainly with respect to their investment horizon. In the paper, several novel measures of trading activity at different investment horizons are introduced through scaling of variance of the underlying processes. On the three most liquid US indices - DJI, NASDAQ and S&P500 - we show that predictions of fractal markets hypothesis actually fit the observed behavior quite well.