According to housing investment models, house prices and replacement costshould have an equilibrating relationship. Previous empirical work|mainlybased on aggregate-level data|has found only little evidence of such a relationship.By using a unique data set, covering transactions of...

The higher our aspirations, the higher the probability that we have to adjust them downwards when forming more realistic expectations later on. This paper shows that the costs induced by high aspirations are not trivial. We first develop a theoretical framework to identify the factors that...

This paper analyzes dynamic equilibrium risk sharing contracts between profit-maximizing intermediaries and a large pool of ex-ante identical agents that face idiosyncratic income uncertainty that makes them heterogeneous ex-post. In any given period, after having observed her income, the agent...

We consider the problem of optimal consumption for an investor who is risk and uncertainty avers. We model these preferences of the investor with the help of a convex risk-measure...

A great proportion of stock dynamics can be explained using publicly availableinformation. The relationship between dynamics and public information may be ofnonlinear character. In this paper we offer an approach to stock picking by employing so-called decision trees and applying them to XETRA...

Empirical studies have shown that a large number of financial asset returns exhibit fat tails and are often characterized by volatility clustering and asymmetry. Also revealed as a stylized fact is Long memory or long range dependence in market volatility, with significant impact on pricing and...

In the era of Basel II a powerful tool for bankruptcy prognosis isvital for banks. The tool must be precise but also easily adaptable tothe bank's objections regarding the relation of false acceptances (TypeI error) and false rejections (Type II error). We explore the suitabil-ity of Smooth...

Independent component analysis (ICA) is a modern factor analysis tool developed in the last two decades. Given p-dimensional data, we search for that linear combination of data which creates (almost) independent components. Here copulae are used to model the p-dimensional data and then...

We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), whichextends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric...

This paper offers a new method for estimation and forecasting of the linear and nonlinear time series when the stationarity assumption is violated. Our general local parametric approach particularly applies to general varying-coefficient parametric models, such as AR or GARCH, whose coefficients...