Statistics is often difficult for students, since it requires coordination of quantitative and graphical insights with mathematical ability. Furthermore, ever-increasing special knowledge of statistics is demanded, since data of increasing complexity and size need to be understood and analyzed....

Newly developed and advanced methods for nonlinear time series analysis are in general not available in standard software packages. Moreover, their implementation requires substantial time, computing power as well as programming skills. The recent results on lag and bandwidth selection methods...

VaR models are related to statistical forecast systems. Within that framework different forecast tasks including Value-at-Risk and shortfall are discussed and motivated. A backtesting method based on the shortfall is developed and applied to VaR forecasts of areal portfolio. The analysis shows...