Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

We generalize the score test for time-varying copula parameters proposed by [Abegaz & Naik-Nimbalkar, 2008] to a setting where more than one-parametric copulas can be tested for time variation in at least one parameter. In a next step we model the daily log returns of the Commerzbank stock using...

Although building operating charges have turned out to be a major determinant of profitability for real estate investments, there is a noticeable lack of reports or studies that analyze these costs with state-of-the-art statistical techniques. Specifically, past studies usually assume linear...

The paper discusses the question of whether financial participation of multilateral development banks does prompt private investors to inject more risky equity capital in emerging market banks. Using a theoretical model, it is stipulated that the presence of an official lender in a project gives...

Multinational labor demand responds to wage differentials at the extensive margin, when a multinational enterprise (MNE) expands into foreign locations, and at the intensive margin, when an MNE operates existing affiliates across locations. We derive conditions for parametric and nonparametric...

This paper discusses methods to quantify risk and uncertainty in macroeconomic forecasts. Both, parametric and non-parametric procedures are developed. The former are based on a class of asymmetrically weighted normal distributions whereas the latter employ asymmetric bootstrap simulations. Both...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

We consider the problem of ex-ante forecasting conditional correlation patterns using ultra high frequency data. Flexible semiparametric predictors referring to the class of dynamic panel and dynamic factor models are adopted for daily forecasts. The parsimonious set up of our approach allows to...