good on the present set of measures as the stochastic volatility models, with or without dynamic correlation. …The focus of this article is using dynamic correlation models for the calculation of minimum variance hedge ratios …. Modelling the correlation explicitly is shown to produce the best hedges when applied to the simulated data. For financial time …

We develop a new simultaneous time series model for volatility and dependence with long memory (fractionally integrated … volatility and dependence measures. The forecast accuracy is overall higher compared to those from some well-known competing …

distribution specifications or historical and Monte Carlo simulation methods. Although these approaches to overall VaR estimation …, component VaR and incremental VaR readily follow. The proposed estimation approach pairs intuitive appeal with computational … efficiency. We evaluate various alternative estimation methods in an application example and conclude that the proposed approach …

conditions: in particular it allows for parameter estimation uncertainty and for the copulas to be nested or non-nested. Monte …

volatility processes. This is called a GSSF-SV model. We show that conventional MCMC algorithms for this type of model are …

volatility in the disturbances. The risk of a liquidity trap in the U.S.A. and Japan is evaluated. Although this risk found to be …

considered for the modelling of economic time series. The focus of this paper is on the simultaneous estimation of parameters … related to the stochastic processes of the mean part and the variance part of the model. The estimation method is based on … carried out to investigate the small-sample properties of the estimation procedure. We present two illustrations which are …