Todd, Prono (2009): Simple GMM Estimation of the SemiStrong GARCH(1,1) Model.
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Abstract
IV estimators for the semistrong ARCH(1) model that rely on past squared residuals alone as instruments do not extend to the GARCH case. Efficient IV estimators of the semistrong GARCH(1,1) model require the derivative of the conditional variance as well as both the third and fourth conditional moments to be included within the instrument vector. This paper proposes IV estimators for the semistrong GARCH(1,1) model that only rely on past residuals and past squared residuals as instruments. These estimators are based on the autocovariances of squared residuals, as in the ARCH(1) case described above, as well as on the covariances between squared residuals and past residuals. These latter covariances are nonzero if the residuals are skewed. Jackknife GMM estimators and jackknife continuous updating estimators (CUE) eliminate the bias caused by many (weak) instruments. The jackknife CUE is new and applies to cases where the optimal weighting matrix is unavailable out of a concern over the existence of higher moments. In these cases, a robust analog to the variancecovariance matrix determines the weighting matrix. A Monte Carlo study shows that a CUE based on the optimal weighting matrix as well as the jackknife CUE outperforms QMLE in finite samples. An empirical application involving Australian Dollar and Japanese Yen spot returns is also included.
Item Type:  MPRA Paper 

Original Title:  Simple GMM Estimation of the SemiStrong GARCH(1,1) Model 
Language:  English 
Keywords:  GARCH; GMM; instrumental variables; continuous updating; many moments; robust estimation 
Subjects:  C  Mathematical and Quantitative Methods > C1  Econometric and Statistical Methods and Methodology: General > C13  Estimation: General C  Mathematical and Quantitative Methods > C5  Econometric Modeling > C53  Forecasting and Prediction Methods ; Simulation Methods 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:  28540 
Depositing User:  Todd Prono 
Date Deposited:  02. Feb 2011 14:30 
Last Modified:  02. Mar 2013 15:42 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/28540 
Available Versions of this Item

Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 15. Jan 2010 14:10)

Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 13. Nov 2010 14:51)

Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 20. Dec 2010 03:47)
 Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 02. Feb 2011 14:30) [Currently Displayed]

Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 20. Dec 2010 03:47)

Simple GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 13. Nov 2010 14:51)