Risk Measurement, Econometrics and Neural Networks

This text presents articles taken from the 6th Econometric Workshop, held in Karlsruhe. In the first part of the text, approaches from traditional econometrics and innovative methods from machine learning such as neural nets are applied to financial issues. Neural networks are successfully applied to different areas such as debtor analysis, forecasting and corporate finance. The second part of the text deals with various aspects from value-at-risk. The proceedings describe the legal framework, review the basics and discuss approaches such as shortfall measures and credit risk.