In this paper an in-depth analysis of the estimation of the realized volatility Wishart Autoregressive model is … the estimated degrees of freedom result sensitively lower when extremely high values in the volatility process are present …

We propose exible models for multivariate realized volatility dynamics which involve generalizations of the Box …

We develop a nonparametric estimator of the stochastic volatility density of a discretely-observed Ito semimartingale … underlying volatility Laplace transform. The second step is using a regularized kernel to invert the realized Laplace transform … important cases such as level jumps and possible dependencies between volatility moves and either diffusive or jump moves in the …

implied volatility smile and the risk neutral density function is tested on SPX options …

by proposing an exponential weighted moving average model that jointly estimates volatility, skewness and kurtosis over …

volatility density estimator in discrete-time stochastic volatility models. …

volatility. In this sense, we extend recent papers by Andersen, Bollerslev, Diebold and Labys (2003), and by Andersen, Bollerslev … and Meddahi (2004, 2005), who address the issue of pointwise prediction of volatility via ARMA models, based on the use of … realized volatility. Our approach is to use a realized volatility measure to construct a non parametric (kernel) estimator of …

-frequency data, in line with IT developments, enables the use of more information to estimate not only the variance (volatility), but …

volatility. In this sense, we extend recent papers by Andersen, Bollerslev, Diebold and Labys (2003), and by Andersen, Bollerslev … and Meddahi (2004, 2005), who address the issue of pointwise prediction of volatility via ARMA models, based on the use of … realized volatility. Our approach is to use a realized volatility measure to construct a non parametric (kernel) estimator of …