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. -- Normal Inverse Gaussian distribution ; Bayesian Analysis ; Markov …

exchange the paper compares estimation results of parametric and nonparametric autoregressive models with respect to possible …

We establish a relation between stochastic volatility models and the class of generalized hyperbolic distributions …. These distributions have been found to fit exceptionally well to the empirical distribution of stock returns. We review the …

behaviour and asset prices. We give sufficient conditions for the distribution of equilibrium prices to converge to a unique …

Stochastic Volatility (SV) models are widely used in financial applications. To decide whether standard parametric …

tool for options portfolios using the "Maximum Loss" methodology based on Principal Components. -- Implied Volatility ; DAX …

is the volatility coefficient which in turn obeys an autoregression type equation log v t = w + a S t- l + nt with an … problem of online estimation of current values of w = w(T) and a = a(T) from the observations SI , ... ,ST. We propose an … adaptive method of estimation which does not use any information about time homogeneity of the obscured process. We apply this …