In semiparametric models it is a common approach to under-smooth the nonparametric functions inorder that estimators of the finite dimensional parameters can achieve root-n consistency. The requirementof under-smoothing may result as we show from inefficient estimation methods or technical...

In this paper we provide a review of copula theory with applications to finance. We illustrate the idea on the bivariate framework and discuss the simple, elliptical and Archimedean classes of copulae. Since the copulae model the dependency structure between random variables, next we explain the...

Let (X1, Y1), . . ., (Xn, Yn) be i.i.d. rvs and let l(x) be the unknownp-quantile regression curve of Y on X. A quantile-smootherln(x) is a localised, nonlinear estimator of l(x). The strong uniformconsistency rate is established under general conditions. In many applicationsit is necessary to...

Normal distribution of the residuals is the traditional assumption in the classicalmultivariate time series models. Nevertheless it is not very often consistent with the real data.Copulae allows for an extension of the classical time series models to nonelliptically distributedresiduals. In this...

This book is the third volume of the Handbook of Computational Statisticsand covers the field of Data Visualization. In line with the companion volumes,it contains a collection of chapters by experts in the field to present readerswith an up-to-date and comprehensive overview of the state of the...

This paper analyzes empirical market utility functions and pricing kernelsderived from the DAX and DAX option data for three market regimes. Aconsistent parametric framework of stochastic volatility is used. All empiricalmarket utility functions show a region of risk proclivity that is...

With the recent availability of high-frequency nancial data the longrange dependence of volatility regained researchers' interest and has leadto the consideration of long memory models for realized volatility. Thelong range diagnosis of volatility, however, is usually stated for long...

Systemic weather risk is a major obstacle for the formation of private (non-subsidized) crop insurance. This paper explores the possibility of spatial diversication ofinsurance by estimating the joint occurrence of unfavorable weather conditions in dierentlocations. For that purpose copula...

Measuring and modeling financial volatility is the key to derivative pricing, asset allocation and risk management. The recent availability of high-frequency data allows for refined methods in this field. In particular, more precise measures for the daily or lower frequency volatility can be...

Dimension reduction techniques for functional data analysis model and approximate smooth random functions by lower dimensional objects. In many applications the focus of interest lies not only in dimension reduction but also in the dynamic behaviour of the lower dimensional objects. The most...