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Realized GARCH: a joint model for returns and realized measures of volatility
by
Hansen, Peter Reinhard
, Shek, Howard Howan
, Huang, Zhuo
in
Economic models
/ Forecasting models
/ GARCH models
/ Kurtosis
/ Linear models
/ Measurement
/ Measures
/ Microelectromechanical systems
/ Modeling
/ Rates of return
/ Securities markets
/ Skewed distribution
/ Specification
/ Standard error
/ Statistical variance
/ Statistics
/ Stochastic models
/ Stock exchanges
/ Stock returns
/ Stocks
/ Studies
/ Variance
/ Volatility
2012
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Realized GARCH: a joint model for returns and realized measures of volatility
by
Hansen, Peter Reinhard
, Shek, Howard Howan
, Huang, Zhuo
in
Economic models
/ Forecasting models
/ GARCH models
/ Kurtosis
/ Linear models
/ Measurement
/ Measures
/ Microelectromechanical systems
/ Modeling
/ Rates of return
/ Securities markets
/ Skewed distribution
/ Specification
/ Standard error
/ Statistical variance
/ Statistics
/ Stochastic models
/ Stock exchanges
/ Stock returns
/ Stocks
/ Studies
/ Variance
/ Volatility
2012
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Do you wish to request the book?
Realized GARCH: a joint model for returns and realized measures of volatility
by
Hansen, Peter Reinhard
, Shek, Howard Howan
, Huang, Zhuo
in
Economic models
/ Forecasting models
/ GARCH models
/ Kurtosis
/ Linear models
/ Measurement
/ Measures
/ Microelectromechanical systems
/ Modeling
/ Rates of return
/ Securities markets
/ Skewed distribution
/ Specification
/ Standard error
/ Statistical variance
/ Statistics
/ Stochastic models
/ Stock exchanges
/ Stock returns
/ Stocks
/ Studies
/ Variance
/ Volatility
2012
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Realized GARCH: a joint model for returns and realized measures of volatility
Journal Article
Realized GARCH: a joint model for returns and realized measures of volatility
2012
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Overview
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.
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