Our research project analyses the suitability of social responsible investments (SRI) and alternative asset classes (in particular commodities, hedge fund in-vestments, high-yield bonds) for the portfolio management of German Pension Insurance Funds (Pensionskassen), the largest external...

This paper introduces a new approach to modelling the conditional variance in a multivariate setting. It is essentially a combination of the popular GARCH model class with a spatial component, inspired by generalized space-time models. The resulting spatial GARCH model takes into account both...

Electricity price forecasting has become an area of increasing relevance in recent years. Despite the growing interest in predictive algorithms, the challenges are difficult to overcome given the restricted access to relevant data series and the lack of accurate metrics. Multiple models have...

The empirical joint distribution of return-pairs on stock indices displays high tail-dependence in the lower tail and low tail-dependence in the upper tail. The presence of tail-dependence is not compatible with the assumption of (conditional) joint normality. The presence of asymmetric-tail...

An explication of the key ideas behind the Cointegrated Vector Autoregression Approach. The CVAR approach is related to Haavelmo's famous quot;Probability Approach in Econometricsquot; (1944). It insists on careful stochastic specification as a necessary groundwork for econometric inference and...

This study presents a multivariate analysis of the stability of long-run relationships between variables that influence the conduct and transmission process of the German monetary policy. The initial VAR comprises the variables real money M3, real GNP, the inflation rate, a long-term and a...

This paper investigates the dependence structure between the equity market and the foreign exchange market by using copulas. In particular, several copulas with different dependence structure are compared and used to directly model the underlying dependence structure. We find that there exists...

The paper discusses different methods to deal with unobservable variables: Kalman-Filtering, principal components, factor analysis, LISREL, MIMIC, DYMIMIC, PLS with respect to parameter estimation and forecasting. We got very good results by an extension of Kalman-Filtering called AS (general...