Motivated by increment process modeling for two correlated random and non-random systems from a discrete-time asset pricing with both risk free asset and risky security, we propose a class of semiparametric regressions for a combination of a non-random and a random system. Unlike classical...

We consider theoretical bootstrap coupling techniques for nonparametric robust smoothers and quantile regression, and verify the bootstrap improvement. To cope with curse of dimensionality, a variant of coupling bootstrap techniques are developed for additive models with both symmetric error...

East German wages have been below the West German wage level since unification. Moreover, the East-West wage gap implied by the contractual wages specified in collective wage agreements is drifting ever further apart from the wage gap in terms of effective wages. This paper looks at the role of...

"Bodenrichtwerte" reflect the average location value of land plots within a specific area. They constitute an important source of information that contributes to price transparency on land markets. In Germany, "Bodenrichtwerte" are provided by publicly appointed expert groups...

We use Adaptive Weights Smoothing (AWS) of Polzehl and Spokoiny (2000, 2003, 2006) to estimate a map of land values for Berlin, Germany. Our data are prices of undeveloped land that was transacted between 1996-2009. Even though the observed land price is an indicator of the respective land...

Generalized single-index models are natural extensions of linear models and circumvent the so-called curse of dimensionality. They are becoming increasingly popular in many scientific fields including biostatistics, medicine, economics and financial econometrics. Estimating and testing the model...

In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals. It is known that the approximation error...

Financial risk control has always been challenging and becomes now an even harder problem as joint extreme events occur more frequently. For decision makers and government regulators, it is therefore important to obtain accurate information on the interdependency of risk factors. Given a...

Most dimension reduction methods based on nonparametric smoothing are highly sensitive to outliers and to data coming from heavy-tailed distributions. We show that the recently proposed methods by Xia et al. (2002) can be made robust in such a way that preserves all advantages of the original...

Market value predictions for residential properties are important for investment decisions and the risk management of households, banks, and real estate developers. The increased access to market data has spurred the development and application of Automated Valuation Models (AVMs), which can...