Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/79504
Authors: 
Koo, Bonsoo
Linton, Oliver
Year of Publication: 
2013
Series/Report no.: 
cemmap working paper, Centre for Microdata Methods and Practice CWP11/13
Abstract: 
We investigate a model in which we connect slowly time varying unconditional long-run volatility with short-run conditional volatility whose representation is given as a semi-strong GARCH (1,1) process with heavy tailed errors. We focus on robust estimation of both long-run and short-run volatilities. Our estimation is semiparametric since the long-run volatility is totally unspeci.ed whereas the short-run conditional volatility is a parametric semi-strong GARCH (1,1) process. We propose different robust estimation methods for nonstationary and strictly stationary GARCH parameters with nonparametric long run volatility function. Our estimation is based on a two-step LAD procedure. We establish the relevant asymptotic theory of the proposed estimators. Numerical results lend support to our theoretical results.
Subjects: 
semiparametric
heavy-tailed errors
time varying
nonstationary multiplicative GARCH
JEL: 
C13
C14
C22
G12
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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