Exponential GARCH Modeling With Realized Measures of Volatility

By P. R. Hansen, Zhuo Huang. 2016

197 citations recorded by the source corpus.

We introduce the realized exponential GARCH model that can use multiple realized volatility measures for the modeling of a return series. The model specifies the dynamic properties of both returns and realized measures, and is characterized by a flexible modeling of the dependence between returns and volatility. We apply the model to 27 stocks and an exchange traded fund that tracks the S&P 500 index and find specifications with multiple realized measures that dominate those that rely on a single realized measure. The empirical analysis suggests some convenient simplifications and highlights the advantages of the new specification.

Subfields: Economics and Econometrics, Finance, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/73468aff228b54b28921127408f32759fb7a362a

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Citations in the corpus

REALIZED BETA GARCH: A MULTIVARIATE GARCH MODEL WITH REALIZED MEASURES OF VOLATILITY (2012, methodology): “The marginal model we use for the market-specific time series is the Realized EGARCH model by Hansen and Huang (2012), see also Hansen et al. (2012, section 6.3), which shares certain features with the EGARCH model by Nelson (1991).”
Volatility and Quantile Forecasts by Realized Stochastic Volatility Models with Generalized Hyperbolic Distribution (2016, background): “In fact, Hansen and Huang (2012) introduce the realized exponential GARCH model which can utilize multiple RV measures and show that the model with multiple measures dominates the one with a single measure.”