Edited by
Peter Rossi, University of Massachusetts, Amherst, U.S.A.
Description
This essay collection focuses on the relationship between continuous time models and Autoregressive Conditionally Heteroskedastic (ARCH)
models and applications. For the first time,
Modelling Stock Market Volatility provides new insights about the links
between these two models and new work on practical estimation methods for continuous time models. Featuring the pioneering scholarship
of Daniel Nelson, the text presents research about the discrete time model, continuous time limits and optimal filtering of ARCH models,
and the specification and estimation of continuous time processes. This work will lead to a rapid growth in their empirical application
as they are increasingly subjected to routine specification testing.
