Exponential GARCH Modeling With Realized Measures of Volatility
提出一种能利用多个已实现波动率测度来建模收益率序列的指数GARCH模型，应用于27只股票和一只跟踪标普500指数的ETF，发现多测度模型优于单测度模型。
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.