Abstract
This paper illustrates how to compare different agent-based models and how to compare an agent-based model with real data. As examples we investigate ARFIMA models, the probability density function, and the spectral density function. We illustrate the methodology in an analysis of the agent-based model developed by Levy, Levy, Solomon (2000), and confront it with the S&P 500 for a comparison with real life data.
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References
Alfarano, S., Lux, T., Wagner, F.: Estimation of agent-based models: The case of an asymmetric herding model. Computational Economics 26, 19–49 (2005)
Barberis, N., Huang, M., Santos, T.: Prospect theory and asset prices. Quarterly Journal of Economics 116, 1–54 (2001)
Boswijk, H.P., Hommes, C., Manzan, S.: Behavioral heterogeneity in stock prices. Journal of Economic Dynamics and Control 31, 1938–1970 (2007)
Cochrane, J.H.: Asset pricing. Princeton University Press, Princeton (2001)
Diebold, F.X., Ohanian, L., Berkwitz, J.: Dynamic equilibrium economies: A framework for comparing models and data. Review of Economic Studies 65, 433–452 (1998)
Franke, J., Härdle, W.: On bootstrapping kernel spectral estimates. The Annals of Statistics 20, 121–145 (1992)
Hall, P.: Effect of bias estimation on converage accuracy of bootstrap confidence intervals for a probability density. The Annals of Statistics 20, 675–694 (1992)
Hall, P.: On Edgeworth expansion and bootstrap confidence bands in nonparametric curve estimation. J. R. Statist. Soc. B 55, 291–304 (1993)
He, X., Li, Y.: Heterogeneity, convergence, and autocorrelations. Quantitative Finance (to appear, 2007a)
He, X., Li, Y.: Power-law behaviour, heterogeneity, and trend chasing. Journal of Economic Dynamics and Control 31, 3396–3426 (2007b)
Hommes, C.: Heterogeneous agent models in economics and finance. In: Judd, K.L., Tesfatsion, L. (eds.) Handbook of Computational Economics, vol. 2, Elsevier Science, Amsterdam (2006)
LeBaron, B.: Agent-based computational finance. In: Judd, K.L., Tesfatsion, L. (eds.) Handbook of Computational Economics, vol. 2, Elsevier Science, Amsterdam (2006)
Levy, M., Levy, H., Solomon, S.: Microscopic simulation of financial markets. Academic Press, New York (2000)
Li, Y., Donkers, B., Melenberg, B.: Econometric analysis of microscopic simulation models. Tilburg University, CentER Discussion Papers 2006-99 (2006a), Available at: http://ssrn.com/abstract=939518
Li, Y., Donkers, B., Melenberg, B.: The nonparametric and semiparametric analysis of microscopic simulation models. Tilburg University, CentER Discussion Papers 2006-95 (2006b), Available at: http://ssrn.com/abstract=939510
Lux, T., Marchesi, M.: Scaling and criticality in a stochastic multi-agent model of financial markets. Nature 397, 498–500 (1999)
Pagan, A., Ullah, A.: Nonparametric econometrics. Cambridge University Press, Cambridge (1999)
Swanepoel, J.W.H., van Wyk, J.W.J.: The bootstrap applied to power spectral density function estimation. Biometrika 73, 135–141 (1986)
Zschischang, E., Lux, T.: Some new results on the Levy, Levy and Solomon microscopic stock market model. Physica A 291, 563–573 (2001)
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Li, Y., Donkers, B., Melenberg, B. (2007). The Econometric Analysis of Agent-Based Models in Finance: An Application. In: Yin, H., Tino, P., Corchado, E., Byrne, W., Yao, X. (eds) Intelligent Data Engineering and Automated Learning - IDEAL 2007. IDEAL 2007. Lecture Notes in Computer Science, vol 4881. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77226-2_108
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DOI: https://doi.org/10.1007/978-3-540-77226-2_108
Publisher Name: Springer, Berlin, Heidelberg
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