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Wealth share analysis with "fundamentalist/chartist" heterogeneous agents

Author

Listed:
  • Hai-Chuan Xu

    (TJU)

  • Wei Zhang

    (TJU)

  • Xiong Xiong

    (TJU)

  • Wei-Xing Zhou

    (ECUST)

Abstract

We build a multiassets heterogeneous agents model with fundamentalists and chartists, who make investment decisions by maximizing the constant relative risk aversion utility function. We verify that the model can reproduce the main stylized facts in real markets, such as fat-tailed return distribution and long-term memory in volatility. Based on the calibrated model, we study the impacts of the key strategies' parameters on investors' wealth shares. We find that, as chartists' exponential moving average periods increase, their wealth shares also show an increasing trend. This means that higher memory length can help to improve their wealth shares. This effect saturates when the exponential moving average periods are sufficiently long. On the other hand, the mean reversion parameter has no obvious impacts on wealth shares of either type of traders. It suggests that no matter whether fundamentalists take moderate strategy or aggressive strategy on the mistake of stock prices, it will have no different impact on their wealth shares in the long run.

Suggested Citation

  • Hai-Chuan Xu & Wei Zhang & Xiong Xiong & Wei-Xing Zhou, 2014. "Wealth share analysis with "fundamentalist/chartist" heterogeneous agents," Papers 1405.5939, arXiv.org.
  • Handle: RePEc:arx:papers:1405.5939
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    References listed on IDEAS

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    1. C. Chiarella & X-Z. He, 2001. "Asset price and wealth dynamics under heterogeneous expectations," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 509-526.
    2. Ochiai, Tomoshiro & Nacher, Jose C., 2014. "Volatility-constrained correlation identifies the directionality of the influence between Japan’s Nikkei 225 and other financial markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 393(C), pages 364-375.
    3. Lawrence Blume & David Easley, 2006. "If You're so Smart, why Aren't You Rich? Belief Selection in Complete and Incomplete Markets," Econometrica, Econometric Society, vol. 74(4), pages 929-966, July.
    4. Anufriev, Mikhail & Dindo, Pietro, 2010. "Wealth-driven selection in a financial market with heterogeneous agents," Journal of Economic Behavior & Organization, Elsevier, vol. 73(3), pages 327-358, March.
    5. Campbell, John Y. & Viceira, Luis M., 2002. "Strategic Asset Allocation: Portfolio Choice for Long-Term Investors," OUP Catalogue, Oxford University Press, number 9780198296942.
    6. Rabah Amir & Igor Evstigneev & Klaus Schenk-Hoppé, 2013. "Asset market games of survival: a synthesis of evolutionary and dynamic games," Annals of Finance, Springer, vol. 9(2), pages 121-144, May.
    7. LeBaron, Blake, 2012. "Heterogeneous gain learning and the dynamics of asset prices," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 424-445.
    8. Gao-Feng Gu & Wei-Xing Zhou, 2008. "Emergence of long memory in stock volatility from a modified Mike-Farmer model," Papers 0807.4639, arXiv.org, revised May 2009.
    9. Yurii Fedyk & Christian Heyerdahl-Larsen & Johan Walden, 2013. "Market Selection and Welfare in a Multi-asset Economy," Review of Finance, European Finance Association, vol. 17(3), pages 1179-1237.
    10. Witte, Björn-Christopher, 2013. "Fundamental traders' ‘tragedy of the commons’: Information costs and other determinants for the survival of experts and noise traders in financial markets," Economic Modelling, Elsevier, vol. 32(C), pages 377-385.
    11. Chiarella, Carl & Dieci, Roberto & Gardini, Laura, 2006. "Asset price and wealth dynamics in a financial market with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 30(9-10), pages 1755-1786.
    12. Wei Zhang & Yongjie Zhang & Xiong Xiong & Xi Jin, 2006. "Bsv Investors Versus Rational Investors: An Agent-Based Computational Finance Model," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 5(03), pages 455-466.
    13. Chen, Shu-Heng & Huang, Ya-Chi, 2008. "Risk preference, forecasting accuracy and survival dynamics: Simulations based on a multi-asset agent-based artificial stock market," Journal of Economic Behavior & Organization, Elsevier, vol. 67(3-4), pages 702-717, September.
    14. Levy, Haim & Levy, Moshe & Solomon, Sorin, 2000. "Microscopic Simulation of Financial Markets," Elsevier Monographs, Elsevier, edition 1, number 9780124458901.
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    Cited by:

    1. Antoine Kopp & Rebecca Westphal & Didier Sornette, 2022. "Agent-based model generating stylized facts of fixed income markets," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 17(4), pages 947-992, October.
    2. Gao-Feng Gu & Xiong Xiong & Hai-Chuan Xu & Wei Zhang & Yongjie Zhang & Wei Chen & Wei-Xing Zhou, 2021. "An empirical behavioral order-driven model with price limit rules," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 7(1), pages 1-24, December.
    3. Mario A Bertella & Felipe R Pires & Henio H A Rego & Jonathas N Silva & Irena Vodenska & H Eugene Stanley, 2017. "Confidence and self-attribution bias in an artificial stock market," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-20, February.

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