Efficient posterior simulators for two GARCH models with generalized hyperbolic disturbances are presented. The first model, GHt-GARCH, is a threshold GARCH with a skewed and heavy-tailed error distribution; in this model, the latent variables that account for skewness and heavy tails are...

In this paper we explore some crude approximation, calibration and estimation procedures for Normal Inverse Gaussian (NIG) variates of potential use in risk management. Among others we treat in some detail the calibration of bivariate NIG consistent with marginal NIG.

In this paper we explore some crude approximation, calibration and estimation procedures for Normal Inverse Gaussian (NIG) variates of potential use in risk management. Among others we treat in some detail the calibration of bivariate NIG consistent with marginal NIG.

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods.

The Normal Inverse Gaussian (NIG) distribution recently introduced by Barndorff-Nielsen (1997) is a promising alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of NIG-parameters by Markov Chain Monte Carlo Methods.

In recent years, with the availability of high-frequency financial market data modeling realized volatility has become a new and innovative research direction. The construction of “observable” or realized volatility series from intra-day transaction data and the use of standard time-series...