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An Objective Function for Simulation Based Inference on Exchange Rate Data

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Author Info

  • Peter Winker

    (Department of Economics, University of Giessen)

  • Manfred Gilli

    (University of Geneva and Swiss Finance Institute)

  • Vahidin Jeleskovic

    (Department of Economics, University of Giessen)

Abstract

The assessment of models of financial market behavior requires evaluation tools. When complexity hinders a direct estimation approach, e.g., for agent basedmicrosimulationmodels or complex multifractal models, simulation based estimators might provide an alternative. In order to apply such techniques, an objective function is required, which should be based on robust statistics of the time series under consideration. Based on the identification of robust statistics of foreign exchange rate time series in previous research, an objective function is derived. This function takes into account stylized facts about the unconditional distribution of exchange rate returns and properties of the conditional distribution, in particular, autoregressive conditional heteroscedasticity and long memory. A bootstrap procedure is used to obtain an estimate of the variance-covariancematrix of the different moments included in the objective function, which is used as a base for the weighting matrix. Finally, the properties of the objective function are analyzed for two different agent based models of the foreign exchange market, a simple GARCH-model and a stochastic volatility model using the DM/US-$ exchange rate as a benchmark. It is also discussed how the results might be used for inference purposes.

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Bibliographic Info

Paper provided by Swiss Finance Institute in its series Swiss Finance Institute Research Paper Series with number 07-01.

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Length: 20 pages
Date of creation: Feb 2007
Date of revision:
Handle: RePEc:chf:rpseri:rp0701

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Web page: http://www.SwissFinanceInstitute.ch
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Keywords: Indirect estimation; simulation based estimation; exchange rate returns;

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References

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  1. 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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  4. Lux, T. & M. Marchesi, . "Scaling and Criticality in a Stochastic Multi-Agent Model of a Financial Market," Discussion Paper Serie B 438, University of Bonn, Germany, revised Jul 1998.
  5. M. Angeles Carnero, 2004. "Persistence and Kurtosis in GARCH and Stochastic Volatility Models," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 2(2), pages 319-342.
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  8. Tesfatsion, Leigh & Judd, Kenneth L., 2006. "Handbook of Computational Economics, Vol. 2: Agent-Based Computational Economics," Staff General Research Papers 10368, Iowa State University, Department of Economics.
  9. Kalaba, Robert & Tesfatsion, Leigh, 1996. "A multicriteria approach to model specification and estimation," Computational Statistics & Data Analysis, Elsevier, vol. 21(2), pages 193-214, February.
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  11. Heij, Christiaan & de Boer, Paul & Franses, Philip Hans & Kloek, Teun & van Dijk, Herman K., 2004. "Econometric Methods with Applications in Business and Economics," OUP Catalogue, Oxford University Press, number 9780199268016.
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Cited by:
  1. Fischer, Thomas & Riedler, Jesper, 2013. "Prices, debt and market structure in an agent-based model of the financial market," ZEW Discussion Papers 12-045 [rev.], ZEW - Zentrum für Europäische Wirtschaftsforschung / Center for European Economic Research.
  2. Frank H. Westerhoff, 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(2+3), pages 195-227, June.
  3. Blake LeBaron & Peter Winker, 2008. "Introduction to the Special Issue on Agent-Based Models for Economic Policy Advice," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(2+3), pages 141-148, June.
  4. 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.
  5. 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.
  6. Giorgio Fagiolo & Andrea Roventini, 2012. "Macroeconomic Policy in DSGE and Agent-Based Models," Working Papers 07/2012, University of Verona, Department of Economics.
  7. Manfred Gilli & Enrico Schumann, 2009. "Heuristic Optimisation in Financial Modelling," Working Papers 007, COMISEF.
  8. 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.
  9. Jakob Grazzini, 2011. "Consistent Estimation of Agent Based Models," LABORatorio R. Revelli Working Papers Series 110, LABORatorio R. Revelli, Centre for Employment Studies.
  10. Gottfried Haber, 2008. "Monetary and Fiscal Policy Analysis With an Agent-Based Macroeconomic Model," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), Justus-Liebig University Giessen, Department of Statistics and Economics, vol. 228(2+3), pages 276-295, June.
  11. Demary, Markus, 2010. "Transaction taxes and traders with heterogeneous investment horizons in an agent-based financial market model," Economics - The Open-Access, Open-Assessment E-Journal, Kiel Institute for the World Economy, vol. 4(8), pages 1-44.
  12. Markus Demary, 2011. "Transaction taxes, greed and risk aversion in an agent-based financial market model," Journal of Economic Interaction and Coordination, Springer, vol. 6(1), pages 1-28, May.
  13. Franke, Reiner, 2009. "Applying the method of simulated moments to estimate a small agent-based asset pricing model," Journal of Empirical Finance, Elsevier, vol. 16(5), pages 804-815, December.
  14. Marianna Lyra, 2010. "Heuristic Strategies in Finance – An Overview," Working Papers 045, COMISEF.
  15. Annalisa Fabretti, 2013. "On the problem of calibrating an agent based model for financial markets," Journal of Economic Interaction and Coordination, Springer, vol. 8(2), pages 277-293, October.

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