Volatility clustering: A nonlinear theoretical approach

He, XZ; Li, K; Wang, C

Volatility clustering: A nonlinear theoretical approach

He, XZ

Li, K

Wang, C

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Publication Type:: Journal Article
Citation:: Journal of Economic Behavior and Organization, 2016, 130 pp. 274 - 297
Issue Date:: 2016-10-01

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Field	Value	Language
dc.contributor.author	He, XZ https://orcid.org/0000-0003-1446-9996	en_US
dc.contributor.author	Li, K https://orcid.org/0000-0003-1620-8829	en_US
dc.contributor.author	Wang, C	en_US
dc.date.issued	2016-10-01	en_US
dc.identifier.citation	Journal of Economic Behavior and Organization, 2016, 130 pp. 274 - 297	en_US
dc.identifier.issn	0167-2681	en_US
dc.identifier.uri	http://hdl.handle.net/10453/122123
dc.description.abstract	© 2016 Elsevier B.V. This paper verifies the endogenous mechanism and economic intuition on volatility clustering using the coexistence of two locally stable attractors proposed by Gaunersdorfer et al. (2008). By considering a simple asset pricing model with two types of boundedly rational traders, fundamentalists and trend followers, and noise traders, we provide theoretical conditions on the coexistence of a locally stable steady state and a locally stable invariant circle of the underlying nonlinear deterministic financial market model and show numerically that the interaction of the coexistence of the deterministic dynamics and noise processes can endogenously generate volatility clustering and long range dependence in volatility observed in financial markets. Economically, volatility clustering occurs when neither the fundamental nor trend following traders dominate the market and when traders switch more often between the two strategies.	en_US
dc.relation	http://purl.org/au-research/grants/arc/DP130103210
dc.relation.ispartof	Journal of Economic Behavior and Organization	en_US
dc.relation.isbasedon	10.1016/j.jebo.2016.07.020	en_US
dc.subject.classification	Economics	en_US
dc.title	Volatility clustering: A nonlinear theoretical approach	en_US
dc.type	Journal Article
utslib.citation.volume	130	en_US
utslib.for	1402 Applied Economics	en_US
utslib.for	1401 Economic Theory	en_US
utslib.for	1403 Econometrics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Business
pubs.organisational-group	/University of Technology Sydney/Faculty of Business/Finance Discipline
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	closed_access
pubs.publication-status	Published	en_US
pubs.volume	130	en_US

Abstract:

© 2016 Elsevier B.V. This paper verifies the endogenous mechanism and economic intuition on volatility clustering using the coexistence of two locally stable attractors proposed by Gaunersdorfer et al. (2008). By considering a simple asset pricing model with two types of boundedly rational traders, fundamentalists and trend followers, and noise traders, we provide theoretical conditions on the coexistence of a locally stable steady state and a locally stable invariant circle of the underlying nonlinear deterministic financial market model and show numerically that the interaction of the coexistence of the deterministic dynamics and noise processes can endogenously generate volatility clustering and long range dependence in volatility observed in financial markets. Economically, volatility clustering occurs when neither the fundamental nor trend following traders dominate the market and when traders switch more often between the two strategies.

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http://hdl.handle.net/10453/122123