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.