The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index,...

The Value-at-Risk calculation reduces the dimensionality of the risk factor space. The main reasons for such simplifications are, e.g., technical efficiency, the logic and statistical appropriateness of the model. In Chapter 2 we present three simple mappings: the mapping on the market index,...

This book offers a detailed application guide to XploRe - the interactive statistical computing environment - with case studies of real data analysis situations. It helps the beginner in statistical data analysis to learn in gradual steps how XploRe works in real life applications. Many examples...

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...

Applied Quantitative Finance presents solutions, theoretical developments and method proliferation for many practical problems in quantitative finance. The combination of practice and theory supported by computational tools is reflected in the selection of topics as well as in a finely tuned...