alternative for modelling financial data exhibiting skewness and fat tails. In this paper we explore the Bayesian estimation of …

We establish a relation between stochastic volatility models and the class of generalized hyperbolic distributions …

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

find that the volatility depends on either the interest rate level or information shocks but not on both. Finally, we … propose to describe the short term interest rate's dynamics by means of an AR(1) model with stochastic volatility. -- Term … Structure Models ; Stochastic Volatility ; ARCH …

, and the Deutschmark-US dollar. The estimation results for both models show: (i) that the unrestricted model outperforms …

- 1998, namely FX-rates measured against the US dollar (USD) and the Japanese yen (JPY). Ta account for volatility e1ustering … prices. Having identified subperiods of homogeneous volatility dynamics we concentrate on stylized facts to distinguish these … volatility regimes. The bottom level of estimated volatility turns out be considerably higher during the second part of the …

Multivariate Volatility Models belong to the class of nonlinear models for financial data. Here we want to focus on …

prices caused by stochastic volatility. -- option pricing ; autoregression ; heteroskedasticity ; GARCH ; leverage effect …

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 …