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A Dynamic Analysis Of The Microstructure Of Moving Average Rules In A Double Auction Market

Author

Listed:
  • Chiarella, Carl
  • He, Xue-Zhong
  • Pellizzari, Paolo

Abstract

Inspired by the theoretically oriented dynamic analysis of moving average rules in the model of Chiarella, He, and Hommes (CHH) [Journal of Economic Dynamics and Control 30 (2006), 1729—1753], this paper conducts a dynamic analysis of a more realistic microstructure model of continuous double auctions in which the probability of heterogeneous agents trading is determined by the rules of either fundamentalists mean-reverting to the fundamental or chartists choosing moving average rules based on their relative performance. With such a realistic market microstructure, the model is able not only to obtain the results of the CHH model but also to characterize most of the stylized facts including volatility clustering, insignificant autocorrelations (ACs) of returns, and significant slowly decaying ACs of the absolute returns. The results seem to suggest that a comprehensive explanation of several statistical properties of returns is possible in a framework where both behavioral traits and realistic microstructure have a role.

Suggested Citation

  • 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.
    • Handle: RePEc:cup:macdyn:v:16:y:2012:i:04:p:556-575_00
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    Cited by:

    1. Paolo Pellizzari & Dan Ladley, 2014. "The simplicity of optimal trading in order book markets," Working Papers 2014:05, Department of Economics, University of Venice "Ca' Foscari".
    2. Zhao, Zhijun & Zhang, Xiaoqi, 2022. "A continuous heterogeneous-agent model for the co-evolution of asset price and wealth distribution in financial market," Chaos, Solitons & Fractals, Elsevier, vol. 155(C).
    3. Wang, Lijun & An, Haizhong & Liu, Xiaojia & Huang, Xuan, 2016. "Selecting dynamic moving average trading rules in the crude oil futures market using a genetic approach," Applied Energy, Elsevier, vol. 162(C), pages 1608-1618.
    4. Qixuan Luo & Yu Shi & Xuan Zhou & Handong Li, 2021. "Research on the Effects of Institutional Liquidation Strategies on the Market Based on Multi-agent Model," Computational Economics, Springer;Society for Computational Economics, vol. 58(4), pages 1025-1049, December.
    5. Dong, Xinyue & Ma, Rong & Li, Honggang, 2019. "Stock index pegging and extreme markets," International Review of Financial Analysis, Elsevier, vol. 64(C), pages 13-21.
    6. He, Xue-Zhong & Lin, Shen, 2022. "Reinforcement Learning Equilibrium in Limit Order Markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    7. Ma, Rong & Zhang, Yin & Li, Honggang, 2017. "Traders’ behavioral coupling and market phase transition," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 486(C), pages 618-627.
    8. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Qixuan Luo & Shijia Song & Handong Li, 2023. "Research on the Effects of Liquidation Strategies in the Multi-asset Artificial Market," Computational Economics, Springer;Society for Computational Economics, vol. 62(4), pages 1721-1750, December.
    10. Kun Xing & Honggang Li, 2024. "Market Ecology: Trading Strategies and Market Volatility," Computational Economics, Springer;Society for Computational Economics, vol. 64(6), pages 3333-3351, December.
    11. Xinyue Dong & Honggang Li, 2019. "The Effect of Extremely Small Price Limits: Evidence from the Early Period of the Chinese Stock Market," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 55(7), pages 1516-1530, May.
    12. Zhou, Xuan & Lin, Shen & He, Xue-Zhong, 2025. "Reinforcement learning and rational expectations equilibrium in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 172(C).
    13. Mingjie Ji & Honggang Li, 2016. "Exploring Price Fluctuations in a Double Auction Market," Computational Economics, Springer;Society for Computational Economics, vol. 48(2), pages 189-209, August.
    14. Xuan Zhou & Honggang Li, 2019. "Buying on Margin and Short Selling in an Artificial Double Auction Market," Computational Economics, Springer;Society for Computational Economics, vol. 54(4), pages 1473-1489, December.
    15. Shijia Song & Handong Li, 2025. "Improving Price Generation: A Novel Agent-Based Model for Capturing Persistent Jumps in Asset Prices," Computational Economics, Springer;Society for Computational Economics, vol. 66(1), pages 421-452, July.

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets

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