AI artificial intelligence brings about new quantitative techniques to assess the state of an economy. Here we describe a new measure for systemic risk: the Financial Risk Meter (FRM). This measure is based on the penalization parameter (λ) of a linear quantile lasso regression. The FRM is...

The management of universities demands data on teaching and research performance. While teaching parameters can be measured via student performance and teacher evaluation programs, the connection of research outputs and their grant antecedents is much harder to check, test and understand. This...

More and more companies start offering digital payment systems. Smartphones evolve to a digital wallet such that it seems like we are about to enter the era of digital finance. In fact we are already inside an digital economy. The market of e-x (x = "finance", "money", "book", you name it ...)...

New Public Management helps universities and research institutions to perform in a highly competitive research environment. Evaluating publicly financed research results improves transparency, helps in reflection and self-assessment, and provides information for strategic decision making. In...

New Public Management helps universities and research institutions to perform in a highly competitive research environment. Evaluating publicly financed research results improves transparency, helps in reflection and self-assessment, and provides information for strategic decision making. In...

The EU Emission Trading System (EU ETS) was created to reduce the CO2 and other greenhouse gas emissions at the lowest economic cost. In reality market participants are faced with considerable uncertainty due to price changes and require price and volatility estimates and forecasts for...

For change-point analysis of high dimensional time series, we consider a semiparametric model with dynamic structural break factors. The observations are described by a few low dimensional factors with time-invariate loading functions of covariates. The unknown structural break in time models...

High-frequency data can provide us with a quantity of informa- tion for forecasting, help to calculate and prevent the future risk based on extremes. This tail behaviour is very often driven by ex- ogenous components and may be modelled conditional on other vari- ables. However, many of these...

The management of universities demands data on teaching and research performance. While teaching parameters can be measured via student performance and teacher evaluation programs, the connection of research outputs and their grant antecedents is much harder to check, test and understand. This...

Why do investors entrust active mutual fund managers with large sums of money while receiving negative excess returns on average? Our explanation is that investors have a coarser information set than fund managers which leads them to systematically misinterpret managers' skill. When investors...