High-dimensional regression problems which reveal dynamic behavior are typicallyanalyzed by time propagation of a few number of factors. The inference on thewhole system is then based on the low-dimensional time series analysis. Such highdimensional problems occur frequently in many different...

A primary goal in modelling the implied volatility surface (IVS) for pricing andhedging aims at reducing complexity. For this purpose one fits the IVS each dayand applies a principal component analysis using a functional norm. This approach, however, neglects the degenerated string structure of...

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...

Market option prices in last 20 years confirmed deviations from the Black and Scholes (BS) models assumptions, especially on the BS implied volatility. Implied binomialtrees (IBT) models capture the variations of the implied volatility known as \volatility smile". They provide a discrete...

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...

E-learning plays an important role in education as it supports online education viacomputer networks and provides educational services by utilising information technologies. We present a case study describing the development of an Arabic language elearning course in statistics. Discussed are...

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...

In recent years, support vector regression (SVR), a novel neural network (NN) technique, has been successfully used for financial forecasting. This paper deals with the application of SVR in volatility forecasting. Based on a recurrent SVR, a GARCH method is proposed and is compared with a...

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...