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The Impact of Imitation on Long Memory in an Order-Driven Market

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  • Blake LeBaron

    (International Business School, Brandeis University, 415 South Street, Mailstop 32, Waltham, MA 02453-2728, USA. E-mails: blebaron@brandeis.edu, www.brandeis.edu/ blebaron)

  • Ryuichi Yamamoto

    (Department of International Business, National Chengchi University, 64 Sec.2, Zhi-Nan Road, Taipei, Taiwan)

Abstract

Recent research has documented that learning and evolution are capable of generating many well-known features in financial times series. We extend the results of LeBaron and Yamamoto (2007) to explore the impact of varying amounts of imitation and agent learning in a simple order-driven market. We show that in our framework, imitation is critical to the generation of long memory persistence in many financial time series. This shows that imitation across trader behavior is probably crucial for understanding the dynamics of prices and trading volume. Eastern Economic Journal (2008) 34, 504–517. doi:10.1057/eej.2008.32

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  • Blake LeBaron & Ryuichi Yamamoto, 2008. "The Impact of Imitation on Long Memory in an Order-Driven Market," Eastern Economic Journal, Palgrave Macmillan;Eastern Economic Association, vol. 34(4), pages 504-517.
    • Handle: RePEc:pal:easeco:v:34:y:2008:i:4:p:504-517
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    Cited by:

    1. Danilo Liuzzi & Paolo Pellizzari & Marco Tolotti, 2019. "Fast traders and slow price adjustments: an artificial market with strategic interaction and transaction costs," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 643-662, September.
    2. Kunal Saha & Vinodh Madhavan & Chandrashekhar G. R. & David McMillan, 2020. "Pitfalls in long memory research," Cogent Economics & Finance, Taylor & Francis Journals, vol. 8(1), pages 1733280-173, January.
    3. Recchioni, Maria Cristina & Tedeschi, Gabriele & Gallegati, Mauro, 2015. "A calibration procedure for analyzing stock price dynamics in an agent-based framework," Journal of Economic Dynamics and Control, Elsevier, vol. 60(C), pages 1-25.
    4. Stefan, F.M. & Atman, A.P.F., 2015. "Is there any connection between the network morphology and the fluctuations of the stock market index?," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 419(C), pages 630-641.
    5. Gabriele Tedeschi & Stefania Vitali & Mauro Gallegati, 2014. "The dynamic of innovation networks: a switching model on technological change," Journal of Evolutionary Economics, Springer, vol. 24(4), pages 817-834, September.
    6. Yuki Sato & Kiyoshi Kanazawa, 2023. "Exact solution to a generalised Lillo-Mike-Farmer model with heterogeneous order-splitting strategies," Papers 2306.13378, arXiv.org, revised Nov 2023.
    7. Marina Balboa & Paulo M. M. Rodrigues & Antonio Rubia & A. M. Robert Taylor, 2021. "Multivariate fractional integration tests allowing for conditional heteroskedasticity with an application to return volatility and trading volume," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 36(5), pages 544-565, August.
    8. Erdinc Akyildirim & Shaen Corbet & Guzhan Gulay & Duc Khuong Nguyen & Ahmet Sensoy, 2019. "Order Flow Persistence in Equity Spot and Futures Markets: Evidence from a Dynamic Emerging Market," Working Papers 2019-011, Department of Research, Ipag Business School.
    9. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
    10. Tedeschi, Gabriele & Recchioni, Maria Cristina & Berardi, Simone, 2019. "An approach to identifying micro behavior: How banks’ strategies influence financial cycles," Journal of Economic Behavior & Organization, Elsevier, vol. 162(C), pages 329-346.
    11. Bence Toth & Imon Palit & Fabrizio Lillo & J. Doyne Farmer, 2011. "Why is order flow so persistent?," Papers 1108.1632, arXiv.org, revised Nov 2014.
    12. Luis Goncalves de Faria, 2022. "An Agent-Based Model With Realistic Financial Time Series: A Method for Agent-Based Models Validation," Papers 2206.09772, arXiv.org.
    13. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    14. Yamamoto, Ryuichi, 2011. "Order aggressiveness, pre-trade transparency, and long memory in an order-driven market," Journal of Economic Dynamics and Control, Elsevier, vol. 35(11), pages 1938-1963.
    15. Chiarella, Carl & He, Xue-Zhong & Wei, Lijian, 2015. "Learning, information processing and order submission in limit order markets," Journal of Economic Dynamics and Control, Elsevier, vol. 61(C), pages 245-268.
    16. Gabriel Bobeica & Elena Bojesteanu, 2008. "Long Memory in Volatility. An Investigation on the Central and Eastern European Exchange Rates," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 7-18.
    17. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    18. Simone Berardi & Gabriele Tedeschi, 2016. "How banks’ strategies influence financial cycles: An approach to identifying micro behavior," Working Papers 2016/24, Economics Department, Universitat Jaume I, Castellón (Spain).
    19. Ryuichi Yamamoto, 2011. "Volatility clustering and herding agents: does it matter what they observe?," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 6(1), pages 41-59, May.
    20. Stefan, F.M. & Atman, A.P.F., 2023. "Asymmetric rate of returns and wealth distribution influenced by the introduction of technical analysis into a behavioral agent-based model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 630(C).
    21. Recchioni, Maria Cristina & Tedeschi, Gabriele & Berardi, Simone, 2014. "Bank's strategies during the financial crisis," FinMaP-Working Papers 25, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    22. Berardi, Simone & Tedeschi, Gabriele, 2017. "From banks' strategies to financial (in)stability," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 255-272.
    23. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    24. Tóth, Bence & Palit, Imon & Lillo, Fabrizio & Farmer, J. Doyne, 2015. "Why is equity order flow so persistent?," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 218-239.
    25. Hazem Krichene & Mhamed-Ali El-Aroui, 2018. "Artificial stock markets with different maturity levels: simulation of information asymmetry and herd behavior using agent-based and network models," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 511-535, October.

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