Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system

Tsionas, Mike G. and Michaelides, Panayotis G. (2017) Neglected chaos in international stock markets: Bayesian analysis of the joint return–volatility dynamical system. Physica A: Statistical Mechanics and Its Applications, 482. pp. 95-107. ISSN 0378-4371

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Abstract

We use a novel Bayesian inference procedure for the Lyapunov exponent in the dynamical system of returns and their unobserved volatility. In the dynamical system, computation of largest Lyapunov exponent by traditional methods is impossible as the stochastic nature has to be taken explicitly into account due to unobserved volatility. We apply the new techniques to daily stock return data for a group of six countries, namely USA, UK, Switzerland, Netherlands, Germany and France, from 2003 to 2014, by means of Sequential Monte Carlo for Bayesian inference. The evidence points to the direction that there is indeed noisy chaos both before and after the recent financial crisis. However, when a much simpler model is examined where the interaction between returns and volatility is not taken into consideration jointly, the hypothesis of chaotic dynamics does not receive much support by the data (“neglected chaos”).

Item Type:	Article
Official URL:	http://www.sciencedirect.com/science/journal/03784...
Additional Information:	© 2017 Elsevier B.V
Divisions:	Systemic Risk Centre
Subjects:	H Social Sciences > HA Statistics H Social Sciences > HG Finance
Date Deposited:	09 Jun 2017 13:05
Last Modified:	12 Dec 2024 01:29
URI:	http://eprints.lse.ac.uk/id/eprint/80749

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