Todd, Prono (2009): Using skewness to estimate the semistrong GARCH(1,1) model.
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Abstract
IV estimators with an instrument vector composed only of past squared residuals, while applicable to the semistrong ARCH(1) model, do not extend to the semistrong GARCH(1,1) case because of underidentification. Augmenting the instrument vector with past residuals, however, renders traditional IV estimation feasible, if the residuals are skewed. The proposed estimators are much simpler to implement than efficient IV estimators, yet they retain improved finite sample performance over QMLE. Jackknife versions of these estimators deal with the issues caused by many (potentially weak) instruments. A Monte Carlo study is included, as is an empirical application involving foreign currency spot returns.
Item Type:  MPRA Paper 

Original Title:  Using skewness to estimate 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:  30995 
Depositing User:  Todd Prono 
Date Deposited:  19. May 2011 20:44 
Last Modified:  04. Jan 2016 16:09 
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URI:  https://mpra.ub.unimuenchen.de/id/eprint/30995 
Available Versions of this Item

Simple, SkewnessBased GMM Estimation of the SemiStrong GARCH(1,1) Model. (deposited 01. Aug 2011 17:13)
 Using skewness to estimate the semistrong GARCH(1,1) model. (deposited 19. May 2011 20:44) [Currently Displayed]