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 …

We forecast the term structure of U.S. Treasury zero-coupon bond yields by analyzing a range of models that have been … inference compared to frequentist estimation techniques, and model uncertainty by combining forecasts from individual models …

suggested by the ‘financial accelerator’ theory. Multivariate Markov-switching models that allow for phase shifts between the …

This article presents a bifurcation theory of smooth stochastic dynamical systems that are governed by everywhere … of the system. By introducing a weak equivalence notion of these dependence ratios, we arrive at a bifurcation theory for … which in the compact case, the set of stable (non-bifurcating) systems is open and dense. The theory is illustrated with …

We consider likelihood inference and state estimation by means of importance sampling for state space models with a … is given for the stochastic volatility model with leverage. …