SMS scnews item created by John Robinson at Fri 14 Nov 2008 1609
Type: Seminar
Distribution: World
Expiry: 21 Nov 2008
Calendar1: 21 Nov 2008 1400-1500
CalLoc1: Carslaw 173
Auth: johnr(.ststaff;3005.3001)@p8224.pc.maths.usyd.edu.au

Statistics Seminar: Thavaneswaran -- Inference for Volatility Models

Accurate estimates of volatility parameters are needed in option pricing.  Generalized
Autoregressive Conditional Heteroscedastic (GARCH) models and Random Coefficient
Autoregressive (RCA) models have been used for volatility modelling.  Following Thompson
and Thavaneswaran(1999) combined estimating functions are used to estimate the
parameters in the volatility models.  It turns out that the combined estimating function
is more informative for autoregressive processes with GARCH errors and for RCA models.
The combination of the least squares (LS) estimating function and the least absolute
deviation (LAD) estimating function with application to GARCH model error identification
is discussed as an application.Recursive estimation for stochastic volatility models and
GARCH models are also discussed in some detail.


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