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The Non- and Semiparametric Analysis of MS Models: Some Applications

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  • Li, Y.
  • Donkers, A.C.D.
  • Melenberg, B.

    (Tilburg University, Center for Economic Research)

Abstract

This paper illustrates how to compare different microscopic simulation (MS) models and how to compare a MS model with real data in case the parameters of interest are estimated non- or semiparametrically.As examples we investigate the marginal single-period probability density function of stock returns, and the corresponding spectral density function and memory parameters.We illustrate the methodology by the MS models developed by Levy, Levy, Solomon (2000) and the market fraction model developed by He and Li (2005a, b), and confront the resulting return data with the S&P 500 stock index data.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2006-95.

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Date of creation: 2006
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Handle: RePEc:dgr:kubcen:200695

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Related research

Keywords: Microscopic simulation models; Probability density function; Spectral density function; Memory parameters;

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References

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  1. Lobato, I.N. & Savin, N.E., 1996. "Real and Spurious Long Memory Properties of Stock Market Data," Working Papers 96-07, University of Iowa, Department of Economics.
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  11. Franke,J. & Haerdle,W., 1987. "On bootstrapping Kernel spectral estimates," Discussion Paper Serie A 121, University of Bonn, Germany.
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Cited by:
  1. He, Xue-Zhong & Li, Youwei, 2007. "Power-law behaviour, heterogeneity, and trend chasing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(10), pages 3396-3426, October.

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