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Applying the method of simulated moments to estimate a small agent-based asset pricing model

  • Franke, Reiner
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    The paper takes a recent agent-based asset pricing model by Manzan and Westerhoff from the literature and applies the method of simulated moments to estimate its six parameters. In selecting the moments, the focus is on the fat tails and autocorrelation patterns of the daily returns of several stock market indices and foreign exchange rates. It is argued that it may be meaningful to abandon the econometrically optimal weighting matrix in the objective function and instead invoke the moments' t-statistics in an intuitively appealing way. This modification gives rise to estimations whose moment matching, given the model's parsimony, can be largely considered to be satisfactory. Also the parameter estimates across different markets make good economic sense.

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    File URL: http://www.sciencedirect.com/science/article/B6VFG-4WM0J81-1/2/b7c4995032a5f43a2e84944fcb79b138
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    Article provided by Elsevier in its journal Journal of Empirical Finance.

    Volume (Year): 16 (2009)
    Issue (Month): 5 (December)
    Pages: 804-815

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    Handle: RePEc:eee:empfin:v:16:y:2009:i:5:p:804-815
    Contact details of provider: Web page: http://www.elsevier.com/locate/jempfin

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    1. Duffie, Darrell & Singleton, Kenneth J, 1993. "Simulated Moments Estimation of Markov Models of Asset Prices," Econometrica, Econometric Society, vol. 61(4), pages 929-52, July.
    2. Lee, Bong-Soo & Ingram, Beth Fisher, 1991. "Simulation estimation of time-series models," Journal of Econometrics, Elsevier, vol. 47(2-3), pages 197-205, February.
    3. Reiner Franke & Simone Alfarano, 2007. "A Simple Asymmetric Herding Model to Distinguish Between Stock and Foreign Exchange Markets," Working Papers wp07-01, Warwick Business School, Finance Group.
    4. Kocherlakota, Narayana R., 1990. "On tests of representative consumer asset pricing models," Journal of Monetary Economics, Elsevier, vol. 26(2), pages 285-304, October.
    5. Carrasco, Marine & Florens, Jean-Pierre, 2002. "Simulation-Based Method of Moments and Efficiency," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(4), pages 482-92, October.
    6. Ching-Sheng Mao, 1990. "Hypothesis testing and finite sample properties of generalized method of moments estimators: a Monte Carlo study," Working Paper 90-12, Federal Reserve Bank of Richmond.
    7. Peter Winker & Manfred Gilli & Vahidin Jeleskovic, 2007. "An Objective Function for Simulation Based Inference on Exchange Rate Data," Swiss Finance Institute Research Paper Series 07-01, Swiss Finance Institute.
    8. Carl Chiarella & Roberto Dieci & Xue-Zhong He, 2008. "Heterogeneity, Market Mechanisms, and Asset Price Dynamics," Research Paper Series 231, Quantitative Finance Research Centre, University of Technology, Sydney.
    9. Jean Boivin & Marc P. Giannoni, 2006. "Has Monetary Policy Become More Effective?," The Review of Economics and Statistics, MIT Press, vol. 88(3), pages 445-462, August.
    10. G. Fagiolo & C. Birchenhall & P. Windrum, 2007. "Empirical Validation in Agent-based Models: Introduction to the Special Issue," Computational Economics, Society for Computational Economics, vol. 30(3), pages 189-194, October.
    11. Manzan, S. & Westerhoff, F., 2002. "Heterogeneous Expectations, Exchange Rate Dynamics and Predictability," CeNDEF Working Papers 02-14, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    12. Manzan, S. & Westerhoff, F., 2002. "Representativeness of News and Exchange Rate Dynamics," CeNDEF Working Papers 02-13, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    13. Hommes, C.H. & Wagener, F.O.O., 2008. "Complex evolutionary systems in behavioral finance," CeNDEF Working Papers 08-05, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
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