The study of natural catastrophe models plays an important role in the prevention and mitigation of disasters. After the occurrence of a natural disaster, the reconstruction can be financed with catastrophe bonds (CAT bonds) or reinsurance. This paper examines the calibration of a real...

Along with many others, we agree that a modern education in statistics needs toincorporate the practical analysis of real datasets, which are usually more complex than the common examples found in standard textbooks. The software used in the teaching of statistics includes standard spreadsheet...

This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of...

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...

The volatility implied by observed market prices as a function of the strikeand time to maturity form an Implied Volatility Surface (IV S). Practicalapplications require reducing the dimension and characterize its dynamicsthrough a small number of factors. Such dimension reduction is...

Option prices are a valuable source of information concerning risk assessments from investors about future financial payoffs. The information is summarized in the state price densities (SPD), the continuous counterpart (normalized by a constant) from Arrow-Debreu security prices. Under no...

We consider two semiparametric models for the weight function in a biased sample model. The object of our interest parametrizes the weight function, and it is either Euclidean or non Euclidean. One of the models discussed in this paper is motivated by the estimation the mixing distribution of...

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...

We propose a general class of Markov-switching-ARFIMA processes in order to combine strands of long memory and Markov-switching literature. Although the coverage of this class of models is broad, we show that these models can be easily estimated with the DLV algorithm proposed. This algorithm...

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...