Estimating GARCH volatility in the presence of outliers
AbstractGARCH volatilities depend on the unconditional variance, which is a non-linear function of the parameters. Consequently, they can have larger biases than estimated parameters. Using robust methods to estimate both parameters and volatilities is shown to outperform Maximum Likelihood procedures.
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Bibliographic InfoPaper provided by Universidad Carlos III de Madrid in its series Open Access publications from Universidad Carlos III de Madrid with number info:hdl:10016/15744.
Length: 92 p.
Date of creation: 2012
Date of revision:
Publication status: Published in Economics Letters (2012) v.v. 114, p.86-90
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Financial markets; Heteroscedasticity; QML estimator; Robustness;
Other versions of this item:
- Carnero, M. Angeles & Peña, Daniel & Ruiz, Esther, 2012. "Estimating GARCH volatility in the presence of outliers," Economics Letters, Elsevier, vol. 114(1), pages 86-90.
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models
This paper has been announced in the following NEP Reports:
- NEP-ALL-2012-11-03 (All new papers)
- NEP-ECM-2012-11-03 (Econometrics)
- NEP-ETS-2012-11-03 (Econometric Time Series)
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