IDEAS home Printed from https://ideas.repec.org/a/wly/isacfm/v21y2014i2p105-128.html
   My bibliography  Save this article

Analysis Of An Option Market Dynamics Based On A Heterogeneous Agent Model

Author

Listed:
  • Saki Kawakubo
  • Kiyoshi Izumi
  • Shinobu Yoshimura

Abstract

We propose a two‐market model in which an option market and its underlying market interact. Many artificial markets representing stock markets have been developed, and these models have been actively used to investigate the effects of market rules. However, no artificial market model for derivatives has been intensively studied, even though derivative markets are increasingly important. We tested stylized facts that can be observed in an option market and our model can replicate fat‐tailed distributions, positive skew of the return and positive autocorrelation of the square of return of implied volatility. We found that the speed of volatility mean reversion for fundamentalists and the existence of chartists are important factors for replicating the positive skew of an option market. The value of fat‐tailed distributions and positive skewness of the return get closer to the real value by coupling an option market and an underlying market. Copyright © 2014 John Wiley & Sons, Ltd.

Suggested Citation

  • Saki Kawakubo & Kiyoshi Izumi & Shinobu Yoshimura, 2014. "Analysis Of An Option Market Dynamics Based On A Heterogeneous Agent Model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(2), pages 105-128, April.
  • Handle: RePEc:wly:isacfm:v:21:y:2014:i:2:p:105-128
    DOI: 10.1002/isaf.1353
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/isaf.1353
    Download Restriction: no

    File URL: https://libkey.io/10.1002/isaf.1353?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Chiarella, Carl & Iori, Giulia, 2009. "The impact of heterogeneous trading rules on the limit order book and order flows," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 525-537.
    2. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
    3. Frijns, Bart & Lehnert, Thorsten & Zwinkels, Remco C.J., 2010. "Behavioral heterogeneity in the option market," Journal of Economic Dynamics and Control, Elsevier, vol. 34(11), pages 2273-2287, November.
    4. Vince Darley & Alexander V Outkin, 2007. "A NASDAQ Market Simulation:Insights on a Major Market from the Science of Complex Adaptive Systems," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 6217, August.
    5. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    6. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
    7. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dammak, Wael & Boutouria, Nahla & Ben Hamad, Salah & de Peretti, Christian, 2023. "Investor behavior in the currency option market during the COVID-19 pandemic," The Journal of Economic Asymmetries, Elsevier, vol. 28(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Detlef Seese & Christof Weinhardt & Frank Schlottmann (ed.), 2008. "Handbook on Information Technology in Finance," International Handbooks on Information Systems, Springer, number 978-3-540-49487-4, November.
    2. 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.
    3. 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.
    4. Georges, Christophre, 2008. "Staggered updating in an artificial financial market," Journal of Economic Dynamics and Control, Elsevier, vol. 32(9), pages 2809-2825, September.
    5. Xue-Zhong He & Youwei Li, 2017. "The adaptiveness in stock markets: testing the stylized facts in the DAX 30," Journal of Evolutionary Economics, Springer, vol. 27(5), pages 1071-1094, November.
    6. Sylvain Prado, 2011. "Free lunch in the oil market: a note on Long Memory," EconomiX Working Papers 2011-23, University of Paris Nanterre, EconomiX.
    7. Kin‐Yip Ho & Zhaoyong Zhang, 2012. "Dynamic Linkages among Financial Markets in the Greater China Region: A Multivariate Asymmetric Approach," The World Economy, Wiley Blackwell, vol. 35(4), pages 500-523, April.
    8. Yosra Mefteh Rekik & Younes Boujelbene, 2015. "Price Dynamics and Market Volatility: Behavioral Heterogeneity under Switching Trading Strategies on Artificial Financial Market," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 6(2), pages 33-43, April.
    9. 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.
    10. Alessio Emanuele Biondo, 2019. "Order book modeling and financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 469-489, September.
    11. Wang, Yudong & Liu, Li & Ma, Feng & Wu, Chongfeng, 2016. "What the investors need to know about forecasting oil futures return volatility," Energy Economics, Elsevier, vol. 57(C), pages 128-139.
    12. Lof, Matthijs, 2012. "Heterogeneity in stock prices: A STAR model with multivariate transition function," Journal of Economic Dynamics and Control, Elsevier, vol. 36(12), pages 1845-1854.
    13. Qi Nan Zhai, 2015. "Asset Pricing Under Ambiguity and Heterogeneity," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 1-2015, January-A.
    14. 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.
    15. Nasr, Adnen Ben & Lux, Thomas & Ajmi, Ahdi Noomen & Gupta, Rangan, 2016. "Forecasting the volatility of the Dow Jones Islamic Stock Market Index: Long memory vs. regime switching," International Review of Economics & Finance, Elsevier, vol. 45(C), pages 559-571.
    16. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    17. Franses,Philip Hans & Dijk,Dick van, 2000. "Non-Linear Time Series Models in Empirical Finance," Cambridge Books, Cambridge University Press, number 9780521779654.
    18. Beatriz Vaz de Melo Mendes & André Fluminense Carneiro, 2020. "A Comprehensive Statistical Analysis of the Six Major Crypto-Currencies from August 2015 through June 2020," JRFM, MDPI, vol. 13(9), pages 1-21, August.
    19. Biondo, Alessio Emanuele, 2018. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 12, pages 1-21.
    20. Slim, Skander & Koubaa, Yosra & BenSaïda, Ahmed, 2017. "Value-at-Risk under Lévy GARCH models: Evidence from global stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 46(C), pages 30-53.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:isacfm:v:21:y:2014:i:2:p:105-128. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1099-1174/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.