IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1802.03735.html
   My bibliography  Save this paper

Structural Estimation of Behavioral Heterogeneity

Author

Listed:
  • Zhentao Shi
  • Huanhuan Zheng

Abstract

We develop a behavioral asset pricing model in which agents trade in a market with information friction. Profit-maximizing agents switch between trading strategies in response to dynamic market conditions. Due to noisy private information about the fundamental value, the agents form different evaluations about heterogeneous strategies. We exploit a thin set---a small sub-population---to pointly identify this nonlinear model, and estimate the structural parameters using extended method of moments. Based on the estimated parameters, the model produces return time series that emulate the moments of the real data. These results are robust across different sample periods and estimation methods.

Suggested Citation

  • Zhentao Shi & Huanhuan Zheng, 2018. "Structural Estimation of Behavioral Heterogeneity," Papers 1802.03735, arXiv.org, revised Jun 2018.
    • Handle: RePEc:arx:papers:1802.03735
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1802.03735
    File Function: Latest version
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. 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.
    2. P. Gagliardini & C. Gourieroux & E. Renault, 2011. "Efficient Derivative Pricing by the Extended Method of Moments," Econometrica, Econometric Society, vol. 79(4), pages 1181-1232, 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. He, Xue-Zhong & Zheng, Huanhuan, 2016. "Trading heterogeneity under information uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 64-80.
    5. Antoine, Bertille & Renault, Eric, 2012. "Efficient minimum distance estimation with multiple rates of convergence," Journal of Econometrics, Elsevier, vol. 170(2), pages 350-367.
    6. Boswijk, H. Peter & Hommes, Cars H. & Manzan, Sebastiano, 2007. "Behavioral heterogeneity in stock prices," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1938-1970, June.
    7. Venkataraman, Kumar & Waisburd, Andrew C., 2007. "The Value of the Designated Market Maker," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 735-758, September.
    8. Huang, Weihong & Zheng, Huanhuan & Chia, Wai-Mun, 2010. "Financial crises and interacting heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 34(6), pages 1105-1122, June.
    9. Chang, Yoosoon & Choi, Yongok & Park, Joon Y., 2017. "A new approach to model regime switching," Journal of Econometrics, Elsevier, vol. 196(1), pages 127-143.
    10. Arthur Lewbel, 2019. "The Identification Zoo: Meanings of Identification in Econometrics," Journal of Economic Literature, American Economic Association, vol. 57(4), pages 835-903, December.
    11. Kim, Chang-Jin & Piger, Jeremy & Startz, Richard, 2008. "Estimation of Markov regime-switching regression models with endogenous switching," Journal of Econometrics, Elsevier, vol. 143(2), pages 263-273, April.
    12. Hirshleifer, David & Thakor, Anjan V, 1992. "Managerial Conservatism, Project Choice, and Debt," The Review of Financial Studies, Society for Financial Studies, vol. 5(3), pages 437-470.
    13. 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.
    14. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    15. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
    16. Allen, Helen & Taylor, Mark P, 1990. "Charts, Noise and Fundamentals in the London Foreign Exchange Market," Economic Journal, Royal Economic Society, vol. 100(400), pages 49-59, Supplemen.
    17. Komunjer, Ivana, 2012. "Global Identification In Nonlinear Models With Moment Restrictions," Econometric Theory, Cambridge University Press, vol. 28(4), pages 719-729, August.
    18. He, Xue-Zhong & Westerhoff, Frank H., 2005. "Commodity markets, price limiters and speculative price dynamics," Journal of Economic Dynamics and Control, Elsevier, vol. 29(9), pages 1577-1596, September.
    19. Shakeeb Khan & Elie Tamer, 2010. "Irregular Identification, Support Conditions, and Inverse Weight Estimation," Econometrica, Econometric Society, vol. 78(6), pages 2021-2042, November.
    20. Kim, Chang-Jin, 1994. "Dynamic linear models with Markov-switching," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 1-22.
    21. Franke, Reiner & Westerhoff, Frank, 2012. "Structural stochastic volatility in asset pricing dynamics: Estimation and model contest," Journal of Economic Dynamics and Control, Elsevier, vol. 36(8), pages 1193-1211.
    22. Smith, Richard J., 2007. "Efficient information theoretic inference for conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 138(2), pages 430-460, June.
    23. Jongen, Ron & Verschoor, Willem F.C. & Wolff, Christian C.P. & Zwinkels, Remco C.J., 2012. "Explaining dispersion in foreign exchange expectations: A heterogeneous agent approach," Journal of Economic Dynamics and Control, Elsevier, vol. 36(5), pages 719-735.
    24. Rothenberg, Thomas J, 1971. "Identification in Parametric Models," Econometrica, Econometric Society, vol. 39(3), pages 577-591, May.
    25. Hansen, Lars Peter & Heaton, John & Yaron, Amir, 1996. "Finite-Sample Properties of Some Alternative GMM Estimators," Journal of Business & Economic Statistics, American Statistical Association, vol. 14(3), pages 262-280, July.
    26. Chang-Jin Kim & Charles R. Nelson, 1999. "Has The U.S. Economy Become More Stable? A Bayesian Approach Based On A Markov-Switching Model Of The Business Cycle," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 608-616, November.
    27. Chiarella, Carl & He, Xue-Zhong & Huang, Weihong & Zheng, Huanhuan, 2012. "Estimating behavioural heterogeneity under regime switching," Journal of Economic Behavior & Organization, Elsevier, vol. 83(3), pages 446-460.
    28. Barberis, Nicholas & Greenwood, Robin & Jin, Lawrence & Shleifer, Andrei, 2018. "Extrapolation and bubbles," Journal of Financial Economics, Elsevier, vol. 129(2), pages 203-227.
    29. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    30. Piet Eichholtz & Ronald Huisman & Remco C. J. Zwinkels, 2015. "Fundamentals or trends? A long-term perspective on house prices," Applied Economics, Taylor & Francis Journals, vol. 47(10), pages 1050-1059, February.
    31. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    32. Gospodinov, Nikolay & Otsu, Taisuke, 2012. "Local GMM estimation of time series models with conditional moment restrictions," Journal of Econometrics, Elsevier, vol. 170(2), pages 476-490.
    33. ter Ellen, Saskia & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2013. "Dynamic expectation formation in the foreign exchange market," Journal of International Money and Finance, Elsevier, vol. 37(C), pages 75-97.
    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. Zheng, Huanhuan, 2020. "Coordinated bubbles and crashes," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    2. Huanhuan Zheng & Haiqiang Chen, 2019. "Price informativeness and adaptive trading," Journal of Evolutionary Economics, Springer, vol. 29(4), pages 1315-1342, September.

    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. Mengling Li & Huanhuan Zheng, 2017. "Heterogeneous trading and complex price dynamics," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 12(2), pages 437-442, July.
    2. He, Xue-Zhong & Zheng, Huanhuan, 2016. "Trading heterogeneity under information uncertainty," Journal of Economic Behavior & Organization, Elsevier, vol. 130(C), pages 64-80.
    3. 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.
    4. Kukacka, Jiri & Barunik, Jozef, 2017. "Estimation of financial agent-based models with simulated maximum likelihood," Journal of Economic Dynamics and Control, Elsevier, vol. 85(C), pages 21-45.
    5. Huanhuan Zheng & Haiqiang Chen, 2019. "Price informativeness and adaptive trading," Journal of Evolutionary Economics, Springer, vol. 29(4), pages 1315-1342, September.
    6. Saskia ter Ellen & Willem F.C. Verschoor, 2017. "Heterogeneous beliefs and asset price dynamics: a survey of recent evidence," Working Paper 2017/22, Norges Bank.
    7. Schmitt, Noemi & Westerhoff, Frank, 2017. "On the bimodality of the distribution of the S&P 500's distortion: Empirical evidence and theoretical explanations," Journal of Economic Dynamics and Control, Elsevier, vol. 80(C), pages 34-53.
    8. Saskia ter Ellen & Willem F. C. Verschoor, 2018. "Heterogeneous Beliefs and Asset Price Dynamics: A Survey of Recent Evidence," Dynamic Modeling and Econometrics in Economics and Finance, in: Fredj Jawadi (ed.), Uncertainty, Expectations and Asset Price Dynamics, pages 53-79, Springer.
    9. Zheng, Huanhuan, 2020. "Coordinated bubbles and crashes," Journal of Economic Dynamics and Control, Elsevier, vol. 120(C).
    10. Zheng, Min & Liu, Ruipeng & Li, Youwei, 2018. "Long memory in financial markets: A heterogeneous agent model perspective," International Review of Financial Analysis, Elsevier, vol. 58(C), pages 38-51.
    11. Roberto Dieci & Xue-Zhong He, 2018. "Heterogeneous Agent Models in Finance," Research Paper Series 389, Quantitative Finance Research Centre, University of Technology, Sydney.
    12. Zhenxi Chen & Weihong Huang & Huanhuan Zheng, 2018. "Estimating heterogeneous agents behavior in a two-market financial system," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 13(3), pages 491-510, October.
    13. Changtai Li & Weihong Huang & Wei-Siang Wang & Wai-Mun Chia, 2023. "Price Change and Trading Volume: Behavioral Heterogeneity in Stock Market," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 677-713, February.
    14. Schmitt, Noemi & Westerhoff, Frank, 2014. "Speculative behavior and the dynamics of interacting stock markets," Journal of Economic Dynamics and Control, Elsevier, vol. 45(C), pages 262-288.
    15. Guillaume Coqueret, 2016. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02088097, HAL.
    16. Schmitt, Noemi & Westerhoff, Frank, 2021. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 117-136.
    17. Wai-Mun Chia & Mengling Li & Huanhuan Zheng, 2017. "Behavioral heterogeneity in the Australian housing market," Applied Economics, Taylor & Francis Journals, vol. 49(9), pages 872-885, February.
    18. Guillaume Coqueret, 2017. "Empirical properties of a heterogeneous agent model in large dimensions," Post-Print hal-02000726, HAL.
    19. 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.
    20. Huang, Weihong & Zheng, Huanhuan, 2012. "Financial crises and regime-dependent dynamics," Journal of Economic Behavior & Organization, Elsevier, vol. 82(2), pages 445-461.

    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:arx:papers:1802.03735. 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: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    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.