A method to generate multivariate data with moments arbitrary close to the desired moments
AbstractWe show how it is possible to generate multivariate data which have moments arbitrary close to the desired ones. They are generated as linear combinations of variables with known theoretical moments. It is shown how to derive the weights of the linear combinations in both the univariate and the multivariate setting. The use in bootstrapping is discussed and examplified with an Monte Carlo simulation where the importance of the ability of generating data with control of higher moments is shown.
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Bibliographic InfoPaper provided by Stockholm School of Economics in its series Working Paper Series in Economics and Finance with number 481.
Length: 13 pages
Date of creation: 18 Dec 2001
Date of revision:
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Monte Carlo; skewness;
Find related papers by JEL classification:
- C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
This paper has been announced in the following NEP Reports:
- NEP-ALL-2001-12-26 (All new papers)
- NEP-CMP-2001-12-26 (Computational Economics)
- NEP-ECM-2001-12-26 (Econometrics)
- NEP-ETS-2001-12-26 (Econometric Time Series)
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