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Realized GARCH: a joint model for returns and realized measures of volatility
Author(s) -
Hansen Peter Reinhard,
Huang Zhuo,
Shek Howard Howan
Publication year - 2011
Publication title -
journal of applied econometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.878
H-Index - 99
eISSN - 1099-1255
pISSN - 0883-7252
DOI - 10.1002/jae.1234
Subject(s) - autoregressive conditional heteroskedasticity , econometrics , volatility (finance) , realized variance , conditional variance , economics , index (typography) , measure (data warehouse) , variance (accounting) , computer science , accounting , data mining , world wide web
SUMMARY We introduce a new framework, Realized GARCH, for the joint modeling of returns and realized measures of volatility. A key feature is a measurement equation that relates the realized measure to the conditional variance of returns. The measurement equation facilitates a simple modeling of the dependence between returns and future volatility. Realized GARCH models with a linear or log‐linear specification have many attractive features. They are parsimonious, simple to estimate, and imply an ARMA structure for the conditional variance and the realized measure. An empirical application with Dow Jones Industrial Average stocks and an exchange traded index fund shows that a simple Realized GARCH structure leads to substantial improvements in the empirical fit over standard GARCH models that only use daily returns. Copyright © 2011 John Wiley & Sons, Ltd.