The Non- and Semiparametric Analysis of MS Models: Some Applications
AbstractThis 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 InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2006-95.
Date of creation: 2006
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Microscopic simulation models; Probability density function; Spectral density function; Memory parameters;
Find related papers by JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
This paper has been announced in the following NEP Reports:
- NEP-ALL-2006-10-28 (All new papers)
- NEP-CMP-2006-10-28 (Computational Economics)
- NEP-ECM-2006-10-28 (Econometrics)
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