Volatility Clustering: A Nonlinear Theoretical Approach

Xuezhong (Tony) He (), Kai Li and Chuncheng Wan

No 365, Research Paper Series from Quantitative Finance Research Centre, University of Technology, Sydney

Abstract: This paper verifies the endogenous mechanism and economic intuition on volatility clustering using the coexistence of two locally stable attractors proposed by Gaunersdorfer, Hommes and Wagener (2008). By considering a simple asset pricing model with two types of boundedly rational traders, fundamentalists and trend followers, and noise traders, we provide conditions on the coexistence of locally stable steady state and invariant cycle 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.

Keywords: volatility clustering; fundamentalists and trend followers; bounded rationality; stability, coexisting attractors (search for similar items in EconPapers)
JEL-codes: D84 E32 G12 (search for similar items in EconPapers)
Pages: 45 pages
Date: 2015-11-01
New Economics Papers: this item is included in nep-ore
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Citations: View citations in EconPapers (1)

Published as: He, X., Li, K. and Wang, C., 2016, "Volatility Clustering: A Nonlinear Theoretical Approach", Journal of Economic Behavior and Organization, 130, 274-297.

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https://www.uts.edu.au/sites/default/files/qfr-archive-03/QFR-rp365.pdf (application/pdf)

Related works:
Journal Article: Volatility clustering: A nonlinear theoretical approach (2016)
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