Francq, Christian and Meintanis, Simos (2012): Fouriertype estimation of the power garch model with stableparetian innovations.

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Abstract
We consider estimation for general power GARCH models under stableParetian 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 finitesample results are presented as well as applications of the proposed procedures to real data from the financial markets. A multivariate extension is also considered.
Item Type:  MPRA Paper 

Original Title:  Fouriertype estimation of the power garch model with stableparetian innovations 
Language:  English 
Keywords:  GARCH model; Minimum distance estimation; Heavytailed distribution; Empirical characteristic function 
Subjects:  C  Mathematical and Quantitative Methods > C3  Multiple or Simultaneous Equation Models ; Multiple Variables > C32  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes ; State Space Models C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C2  Single Equation Models ; Single Variables > C22  TimeSeries Models ; Dynamic Quantile Regressions ; Dynamic Treatment Effect Models ; Diffusion Processes 
Item ID:  41667 
Depositing User:  Christian Francq 
Date Deposited:  01. Oct 2012 18:24 
Last Modified:  22. Aug 2015 20:29 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/41667 