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Moving average rules as a source of market instability

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  • Chiarella, Carl
  • He, Xue-Zhong
  • Hommes, Cars

Abstract

Despite the pervasiveness of the efficient markets paradigm in the academic finance literature, the use of various moving average (MA) trading rules remains popular with financial market practitioners. This paper proposes a stochastic dynamic financial market model in which demand for traded assets has both a fundamentalist and a chartist component. The chartist demand is governed by the difference between current price and a (long-run) MA. Our simulations show that the MA is a source of market instability, and the interaction of the MA and market noises can lead to the tendency for the market price to take long excursions away from the fundamental. The model reveals various market price phenomena, the coexistence of apparent market efficiency and a large chartist component, price resistance levels, long memory and skewness and kurtosis of returns.

Suggested Citation

  • Chiarella, Carl & He, Xue-Zhong & Hommes, Cars, 2006. "Moving average rules as a source of market instability," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 370(1), pages 12-17.
    • Handle: RePEc:eee:phsmap:v:370:y:2006:i:1:p:12-17
    DOI: 10.1016/j.physa.2006.04.026
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    References listed on IDEAS

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    1. Chiarella, Carl & He, Xue-Zhong & Hommes, Cars, 2006. "A dynamic analysis of moving average rules," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1729-1753.
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    10. Malliaris, A.G. & Kyrtsou, C., 2009. "Editorial introduction of the special issue: "Energy sector pricing and macroeconomic dynamics"," Energy Economics, Elsevier, vol. 31(6), pages 825-826, November.
    11. Chiarella, Carl & He, Xue-Zhong & Pellizzari, Paolo, 2012. "A Dynamic Analysis Of The Microstructure Of Moving Average Rules In A Double Auction Market," Macroeconomic Dynamics, Cambridge University Press, vol. 16(4), pages 556-575, September.
    12. Franke, Reiner, 2010. "On the specification of noise in two agent-based asset pricing models," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1140-1152, June.
    13. Carl Chiarella & Xue-Zhong He & Min Zheng, 2007. "The Stochastic Dynamics of Speculative Prices," Research Paper Series 208, Quantitative Finance Research Centre, University of Technology, Sydney.
    14. Ron Bird & Xiaojun Gao & Danny Yeung, 2017. "Time-series and cross-sectional momentum strategies under alternative implementation strategies," Australian Journal of Management, Australian School of Business, vol. 42(2), pages 230-251, May.
    15. Fabio Della Rossa & Lorenzo Giannini & Pietro DeLellis, 2020. "Herding or wisdom of the crowd? Controlling efficiency in a partially rational financial market," PLOS ONE, Public Library of Science, vol. 15(9), pages 1-16, September.
    16. Marcus Davidsson, 2014. "Tactic Asset Allocation and Conditional Return Expectations," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 3(2), pages 1-1.
    17. Peng Chen & Dongyun Yi & Chengli Zhao, 2020. "Trading Strategy for Market Situation Estimation Based on Hidden Markov Model," Mathematics, MDPI, vol. 8(7), pages 1-13, July.
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    20. Christopher D. Clack & Elias Court & Dmitrijs Zaparanuks, 2020. "Dynamic Coupling and Market Instability," Papers 2005.13621, arXiv.org.

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