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Indirect Estimation of the Parameters of Agent Based Models of Financial Markets

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  • Peter Winker and Manfred Gilli

Abstract

Agent based models take into account limited rational behaviour of individuals acting on financial markets. Explicit simulation of this behaviour and the resulting interaction of individuals provide a description of aggregate financial market time series. At least for some parameter settings, the outcome of such simulations exhibit marked similarities with actual financial market time series. The goal of this paper is twofold. First, we compare simulation results of agent based models with observed time series based on characteristic moments like ARCH--effects or excess kurtosis. Second, we try to estimate the parameters of the agent based model from the observed data using a simulated indirect estimation method based on the characteristic moments. The paper presents details of this estimation approach and first results for the US/DM exchange rate.

Suggested Citation

  • Peter Winker and Manfred Gilli, 2001. "Indirect Estimation of the Parameters of Agent Based Models of Financial Markets," Computing in Economics and Finance 2001 59, Society for Computational Economics.
  • Handle: RePEc:sce:scecf1:59
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    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. John G. Riley & Richard Zeckhauser, 1980. "Optimal Selling Strategies:," UCLA Economics Working Papers 180, UCLA Department of Economics.
    3. Stiglitz, Joseph E, 1987. "The Causes and Consequences of the Dependence of Quality on Price," Journal of Economic Literature, American Economic Association, vol. 25(1), pages 1-48, March.
    4. Arnold, Michael A & Lippman, Steven A, 1998. "Posted Prices versus Bargaining in Markets with Asymmetric Information," Economic Inquiry, Western Economic Association International, vol. 36(3), pages 450-457, July.
    5. Peter Diamond, 1985. "Search Theory," Working papers 389, Massachusetts Institute of Technology (MIT), Department of Economics.
    6. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    7. Tesfatsion, Leigh, 2001. "Introduction to the special issue on agent-based computational economics," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 281-293, March.
    8. Jean-Michel Grandmont, 1998. "Expectations Formation and Stability of Large Socioeconomic Systems," Econometrica, Econometric Society, vol. 66(4), pages 741-782, July.
    9. Bester, Helmut, 1994. "Price commitment in search markets," Journal of Economic Behavior & Organization, Elsevier, vol. 25(1), pages 109-120, September.
    10. 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.
    11. Wang, Ruqu, 1995. "Bargaining versus posted-price selling," European Economic Review, Elsevier, vol. 39(9), pages 1747-1764, December.
    12. Spear, Stephen E, 1989. "Learning Rational Expectations under Computability Constraints," Econometrica, Econometric Society, vol. 57(4), pages 889-910, July.
    13. F J Anscombe & R J Aumann, 2000. "A Definition of Subjective Probability," Levine's Working Paper Archive 7591, David K. Levine.
    14. Bester, Helmut, 1993. "Bargaining versus Price Competition in Markets with Quality Uncertainty," American Economic Review, American Economic Association, vol. 83(1), pages 278-288, March.
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    Cited by:

    1. 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.
    2. Xue-Zhong He & Youwei Li, 2017. "The adaptiveness in stock markets: testing the stylized facts in the DAX 30," Journal of Evolutionary Economics, Springer, pages 1071-1094.
    3. Amilon, Henrik, 2008. "Estimation of an adaptive stock market model with heterogeneous agents," Journal of Empirical Finance, Elsevier, vol. 15(2), pages 342-362, March.
    4. Hommes, C.H., 2005. "Heterogeneous Agent Models in Economics and Finance, In: Handbook of Computational Economics II: Agent-Based Computational Economics, edited by Leigh Tesfatsion and Ken Judd , Elsevier, Amsterdam 2006," CeNDEF Working Papers 05-03, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    5. 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.
    6. Witte, Björn-Christopher, 2011. "Removing systematic patterns in returns in a financial market model by artificially intelligent traders," BERG Working Paper Series 82, Bamberg University, Bamberg Economic Research Group.
    7. 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.
    8. 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.
    9. Carlo Bianchi & Pasquale Cirillo & Mauro Gallegati & Pietro Vagliasindi, 2007. "Validating and Calibrating Agent-Based Models: A Case Study," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 245-264, October.
    10. Kampouridis, Michael & Chen, Shu-Heng & Tsang, Edward, 2012. "Market fraction hypothesis: A proposed test," International Review of Financial Analysis, Elsevier, vol. 23(C), pages 41-54.
    11. Jacob Grazzini & Matteo Richiardi & Lisa Sella, 2012. "Indirect estimation of agent-based models.An application to a simple diffusion model," LABORatorio R. Revelli Working Papers Series 118, LABORatorio R. Revelli, Centre for Employment Studies.
    12. repec:eee:dyncon:v:85:y:2017:i:c:p:21-45 is not listed on IDEAS
    13. He, Xue-Zhong & Li, Youwei, 2015. "Testing of a market fraction model and power-law behaviour in the DAX 30," Journal of Empirical Finance, Elsevier, pages 1-17.
    14. 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.
    15. 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.
    16. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2009. "Behavioural heterogeneity and shift-contagion: Evidence from the Asian crisis," Journal of Economic Dynamics and Control, Elsevier, vol. 33(11), pages 1929-1944, November.
    17. Grazzini, Jakob & Richiardi, Matteo, 2015. "Estimation of ergodic agent-based models by simulated minimum distance," Journal of Economic Dynamics and Control, Elsevier, vol. 51(C), pages 148-165.
    18. Radu T. Pruna & Maria Polukarov & Nicholas R. Jennings, 2016. "A new structural stochastic volatility model of asset pricing and its stylized facts," Papers 1604.08824, arXiv.org.
    19. 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.
    20. Jakob Grazzini & Matteo G. Richiardi, 2013. "Consistent Estimation of Agent-Based Models by Simulated Minimum Distance," LABORatorio R. Revelli Working Papers Series 130, LABORatorio R. Revelli, Centre for Employment Studies.
    21. Monira Essa Aloud, 2016. "Profitability of Directional Change Based Trading Strategies: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 87-95.
    22. de Jong, Eelke & Verschoor, Willem F.C. & Zwinkels, Remco C.J., 2010. "Heterogeneity of agents and exchange rate dynamics: Evidence from the EMS," Journal of International Money and Finance, Elsevier, vol. 29(8), pages 1652-1669, December.
    23. Thorsten Lehnert & Bart Frijns & Remco Zwinkels, 2009. "A Volatility Targeting GARCH model with Time-Varying Coefficients," LSF Research Working Paper Series 09-08, Luxembourg School of Finance, University of Luxembourg.
    24. Baur, Dirk G. & Glover, Kristoffer J., 2014. "Heterogeneous expectations in the gold market: Specification and estimation," Journal of Economic Dynamics and Control, Elsevier, vol. 40(C), pages 116-133.

    More about this item

    Keywords

    Artificial markets; agent based models; indirect estimation; optimization;

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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