作者：Hamilton, James D., and Raul Susmel

杂志全称或缩写：Journal of Econometrics

年份，卷（期），起止页码：1994,(64) 307-333.

Abstract
ARCH models often impute a lot of persistence to stock volatility and yet give
relatively poor forecasts. One explanation is that extremely large shocks, such as the
October 1987 crash. arise from quite different causes and have different consequences for
subsequent volatility than do small shocks. We explore this possibility with U.S. weekly
stock returns, allowing the parameters of an ARCH process to come from one of several
different regimes, with transitions between regimes governed by an unobserved Markov
chain. We estimate models with two to four regimes in which the latent innovations come
from Gaussian and Student f distributions.