Fourier--type estimation of the power garch model with stable--paretian innovations
AbstractWe consider estimation for general power GARCH models under stable--Paretian innovations. Exploiting the simple structure of the conditional characteristic function of the observations driven by these models we propose minimum distance estimation based on the empirical characteristic function of corresponding residuals. Consistency of the estimators is proved, and we obtain a singular asymptotic distribution which is concentrated on a hyperplane. Efficiency issues are explored and finite--sample results are presented as well as applications of the proposed procedures to real data from the financial markets. A multivariate extension is also considered.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 41667.
Date of creation: 01 Oct 2012
Date of revision:
GARCH model; Minimum distance estimation; Heavy--tailed distribution; Empirical characteristic function;
Find related papers by JEL classification:
- C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models &bull Diffusion Processes
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-10-13 (All new papers)
- NEP-ECM-2012-10-13 (Econometrics)
- NEP-ETS-2012-10-13 (Econometric Time Series)
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