This paper applies a non- and a semiparametric copula-based approach to analyze the first-order autocorrelation of returns in high frequency financial time series. Using the EUREX D3047 tick data from the German stock index, it can be shown that the temporal dependence structure of price...

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...

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...

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...

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...

Stock picking is the field of financial analysis that is of particular interest for many professional investors and researchers. In this study stock picking is implemented via binary classification trees. Optimal tree size is believed to be the crucial factor in forecasting performance of 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...

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...