| 正文 | This article presents a new class of realized stochastic volatility model based on realized volatilities and
returns jointly. We generalize the traditionally used logarithm transformation of realized volatility to the
Box–Cox transformation, a more flexible parametric family of transformations. A two-step maximum
likelihood estimation procedure is introduced to estimate this model on the basis of Koopman and Scharth
(2013). Simulation results show that the two-step estimator performs well, and the misspecified log
transformation may lead to inaccurate parameter estimation and certain excessive skewness and kurtosis.
Finally, an empirical investigation on realized volatility measures and daily returns is carried out for several
stock indices. |
