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Estimation of an Adaptive Stock Market Model with Heterogeneous Agents

  • Henrik Amilon
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    Standard economic models based on rational expectations and homogeneity have problems to explain the complex and volitile nature of financial markets. Recently, boundedly rational and heterogeneous agents models have been developed, and simulated returns are found to exhibit various stylized facts, such as volatility clustering and fat tails. Here, we estimate a simple version of such a model by the use of efficient method of moments, and compare the results to real data and traditional econometric models. We find that the model generates returns with properties similar to observed data, but that the fit generally is poor.

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    File URL: http://www.qfrc.uts.edu.au/research/research_papers/rp107.pdf
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    Paper provided by Quantitative Finance Research Centre, University of Technology, Sydney in its series Research Paper Series with number 107.

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    Length: 58 pages
    Date of creation: 01 Sep 2003
    Date of revision:
    Publication status: Published as: Amilon, H., 2008, "Estimation of an Adaptive Stock Market Model with Heterogeneous Agents", Journal of Empirical Finance, 15(2), 342-362.
    Handle: RePEc:uts:rpaper:107
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    1. Tim Bollerslev & Jeffrey M. Wooldridge, 1988. "Quasi-Maximum Likelihood Estimation of Dynamic Models with Time-Varying Covariances," Working papers 505, Massachusetts Institute of Technology (MIT), Department of Economics.
    2. Chavas, Jean-Paul, 2000. "On information and market dynamics: The case of the U.S. beef market," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 833-853, June.
    3. Gaunersdorfer, A. & Hommes, C.H. & Wagener, F.O.O., 2000. "Bifurcation Routes to Volatility Clustering," CeNDEF Working Papers 00-04, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    4. Cars H. Hommes, 2001. "Financial Markets as Nonlinear Adaptive Evolutionary Systems," Tinbergen Institute Discussion Papers 01-014/1, Tinbergen Institute.
    5. Westerhoff Frank H. & Reitz Stefan, 2003. "Nonlinearities and Cyclical Behavior: The Role of Chartists and Fundamentalists," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 7(4), pages 1-15, December.
    6. Gallant, A Ronald & Nychka, Douglas W, 1987. "Semi-nonparametric Maximum Likelihood Estimation," Econometrica, Econometric Society, vol. 55(2), pages 363-90, March.
    7. Peter Winker & Manfred Gilli, 2002. "Indirect Estimation of the Parameters of Agent Based Models of Financial Markets," Computing in Economics and Finance 2002 314, Society for Computational Economics.
    8. Tim Bollerslev, 1986. "Generalized autoregressive conditional heteroskedasticity," EERI Research Paper Series EERI RP 1986/01, Economics and Econometrics Research Institute (EERI), Brussels.
    9. Kai-Li Wang & Christopher Fawson & Christopher B. Barrett & James B. McDonald, 2001. "A flexible parametric GARCH model with an application to exchange rates," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(4), pages 521-536.
    10. Andrea Gaunersdorfer & Cars Hommes & Florian Wagener, 2001. "Adaptive Beliefs and the volatility of asset prices," CeNDEF Workshop Papers, January 2001 5A.1, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    11. Shu-Heng Chen & Thomas Lux & Michele Marchesi, 1999. "Testing for Non-Linear Structure in an Artificial Financial Market," Discussion Paper Serie B 447, University of Bonn, Germany.
    12. Pagan, Adrian, 1996. "The econometrics of financial markets," Journal of Empirical Finance, Elsevier, vol. 3(1), pages 15-102, May.
    13. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-54, July.
    14. Hommes, Cars H., 2006. "Heterogeneous Agent Models in Economics and Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 23, pages 1109-1186 Elsevier.
    15. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-96, July.
    16. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    17. Gilli, M. & Winker, P., 2003. "A global optimization heuristic for estimating agent based models," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 299-312, March.
    18. Peter Boswijk & Cars H. Hommes & Sebastiano Manzan, 2005. "Behavioral Heterogeneity in Stock Prices," Tinbergen Institute Discussion Papers 05-052/1, Tinbergen Institute.
    19. Gaunersdorfer, A. & Hommes, C.H., 2005. "A nonlinear structural model for volatility clustering," CeNDEF Working Papers 05-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    20. Vigfusson, Robert, 1997. "Switching between Chartists and Fundamentalists: A Markov Regime-Switching Approach," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 2(4), pages 291-305, October.
    21. Marianna Grimaldi & Paul De Grauwe, 2003. "Bubbling and Crashing Exchange Rates," CESifo Working Paper Series 1045, CESifo Group Munich.
    22. 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.
    23. Brock,W.A. & Hommes,C.H., 2001. "Evolutionary dynamics in financial markets with many trader types," Working papers 7, Wisconsin Madison - Social Systems.
    24. Tauchen, George E. & Gallant, A. Ronald, 1995. "Which Moments to Match," Working Papers 95-20, Duke University, Department of Economics.
    25. Goffe, William L. & Ferrier, Gary D. & Rogers, John, 1994. "Global optimization of statistical functions with simulated annealing," Journal of Econometrics, Elsevier, vol. 60(1-2), pages 65-99.
    26. Gourieroux, C & Monfort, A & Renault, E, 1993. "Indirect Inference," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 8(S), pages S85-118, Suppl. De.
    27. Chiarella, Carl & He, Xue-Zhong, 2003. "Dynamics of beliefs and learning under aL-processes -- the heterogeneous case," Journal of Economic Dynamics and Control, Elsevier, vol. 27(3), pages 503-531, January.
    28. Carl Chiarella & Tony He, 2002. "An Adaptive Model on Asset Pricing and Wealth Dynamics with Heterogeneous Trading Strategies," Computing in Economics and Finance 2002 135, Society for Computational Economics.
    29. Narasimhan Jegadeesh, 2001. "Profitability of Momentum Strategies: An Evaluation of Alternative Explanations," Journal of Finance, American Finance Association, vol. 56(2), pages 699-720, 04.
    30. Darrell Duffie & Kenneth J. Singleton, 1990. "Simulated Moments Estimation of Markov Models of Asset Prices," NBER Technical Working Papers 0087, National Bureau of Economic Research, Inc.
    31. Lux, T. & M. Marchesi, . "Volatility Clustering in Financial Markets: A Micro-Simulation of Interacting Agents," Discussion Paper Serie B 437, University of Bonn, Germany, revised Jul 1998.
    32. LeBaron, Blake, 2001. "Evolution And Time Horizons In An Agent-Based Stock Market," Macroeconomic Dynamics, Cambridge University Press, vol. 5(02), pages 225-254, April.
    33. Gaunersdorfer, Andrea, 2000. "Endogenous fluctuations in a simple asset pricing model with heterogeneous agents," Journal of Economic Dynamics and Control, Elsevier, vol. 24(5-7), pages 799-831, June.
    34. Xue-Zhong He & Carl Chiarella, 1999. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset-Pricing Model," Computing in Economics and Finance 1999 223, Society for Computational Economics.
    35. Andersen, Torben G. & Lund, Jesper, 1997. "Estimating continuous-time stochastic volatility models of the short-term interest rate," Journal of Econometrics, Elsevier, vol. 77(2), pages 343-377, April.
    36. W. Brian Arthur & John H. Holland & Blake LeBaron & Richard Palmer & Paul Taylor, 1996. "Asset Pricing Under Endogenous Expectation in an Artificial Stock Market," Working Papers 96-12-093, Santa Fe Institute.
    37. Routledge, Bryan R, 1999. "Adaptive Learning in Financial Markets," Review of Financial Studies, Society for Financial Studies, vol. 12(5), pages 1165-1202.
    38. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    39. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-64, December.
    40. Granger, E.J. & Swanson, N.R., 1996. "An introduction to stochastic Unit Root Processes," Papers 4-96-3, Pennsylvania State - Department of Economics.
    41. LeBaron, Blake & Arthur, W. Brian & Palmer, Richard, 1999. "Time series properties of an artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1487-1516, September.
    42. Frankel, Jeffrey A & Froot, Kenneth A, 1990. "Chartists, Fundamentalists, and Trading in the Foreign Exchange Market," American Economic Review, American Economic Association, vol. 80(2), pages 181-85, May.
    43. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
    44. Engle, Robert F, 1982. "Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation," Econometrica, Econometric Society, vol. 50(4), pages 987-1007, July.
    45. Yoon, Gawon, 2003. "A simple model that generates stylized facts of returns," University of California at San Diego, Economics Working Paper Series qt0q3576s4, Department of Economics, UC San Diego.
    46. Simone Alfarano & Thomas Lux & Friedrich Wagner, 2005. "Estimation of Agent-Based Models: The Case of an Asymmetric Herding Model," Computational Economics, Society for Computational Economics, vol. 26(1), pages 19-49, August.
    47. Bollerslev, Tim, 1987. "A Conditionally Heteroskedastic Time Series Model for Speculative Prices and Rates of Return," The Review of Economics and Statistics, MIT Press, vol. 69(3), pages 542-47, August.
    48. Baak, Saang Joon, 1999. "Tests for bounded rationality with a linear dynamic model distorted by heterogeneous expectations," Journal of Economic Dynamics and Control, Elsevier, vol. 23(9-10), pages 1517-1543, September.
    49. De Grauwe, Paul & Grimaldi, Marianna, 2006. "Exchange rate puzzles: A tale of switching attractors," European Economic Review, Elsevier, vol. 50(1), pages 1-33, January.
    50. repec:cup:etheor:v:12:y:1996:i:4:p:657-81 is not listed on IDEAS
    51. 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.
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