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...

In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

This paper investigates how media coverage in°uences macroeconomic information processing at the bond market. I provide evidence that a high media coverage of an economic topic increases investor attention prior to the release of the corresponding economic indicator: High media coverage of the...

Observing prices of European put and call options, we calibrate exponential Lévy models nonparametrically. We discuss the implementation of the spectral estimation procedures for Lévy models of finite jump activity as well as for self-decomposable Lévy models and improve these methods....

This paper employs a new and comprehensive data set to investigate short-term herding behavior of institutional investors. Using data of all transactions made by financial institutions in the German stock market, we show that herding behavior occurs on a daily basis. However, in contrast to...