This paper is concerned with modelling time series by single hidden layer feedforward neural network models. A coherent modelling strategy based on statistical inference is presented. Variable selection is carried out using existing techniques. The problem of selecting the number of hidden units...

The current financial market crisis has impressively demonstrated the importance of an effective credit risk management for financial institutions. At the same time, the use and the valuation of credit derivatives has been widely criticised as a result of the crisis. Over the past decade, credit...

The current financial market crisis has impressively demonstrated the importance of an effective credit risk management for financial institutions. At the same time, the use and the valuation of credit derivatives has been widely criticised as a result of the crisis. Over the past decade, credit...

We study the implications of the value at risk concept for the bank's optimum amount of equity capital under credit risk. The market value of loans is risky and lognormally distributed. We show that the required equity capital depends upon managerial and market factors. Furthermore, the bank's...

[...] The objective of this study is to analyse - relying on 2006 data - FX settlement risk that may arise in the domestic banking system under its current operations, and to chart the changes which took place after 2000, covering improvements and, if necessary, formulating (new) recommendations...

The paper presents a new approach to optimizing automatic transactional systems. We propose a multi-stage technique which enables us to find investment strategies beating the market. Additionally, new measures of combined risk and returns are applied in the process of optimization. Moreover, we...

This short paper is a comment on ``Testing for Nonlinear Structure and Chaos in Economic Time Series'' by Catherine Kyrtsou and Apostolos Serletis. We summarize their main results and discuss some of their conclusions concerning the role of outliers and noisy chaos. In particular, we include...

We closely examine and compare two promising techniques helpful in estimating the moment an asset bubble bursts. Namely, the Log-Periodic Power Law model and Generalized Hurst Exponent approaches are considered. Sequential LPPL fitting to empirical financial time series exhibiting evident bubble...

This study was prepared by Beate Schirwitz while she was working at the Ifo Institute’s Dresden Branch. It was completed in February 2012 and accepted as a doctoral thesis by the Faculty of Law, Management, and Economics at the Johannes Gutenberg University Mainz in July 2012. It focuses on a...

In this paper modelling time series by single hidden layer feedforward neural network models is considered. A coherent modelling strategy based on statistical inference is discussed. The problems of selecting the variables and the number of hidden units are solved by using statistical model...