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...

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...

The purpose of this study is to extend the current understanding of business divestiture by investigating its potential for triggering strategic reorientation. A divestiture involving strategic reorientation is here denoted as a strategic business exit, otherwise it is a status...

State price density (SPD) contains important information concerning market expectations. In existing literature, a constrained estimator of the SPD is found by nonlinear least squares in a suitable Sobolev space...

Due to its ability to allow and account for similarities between pairs of alternatives, the nested logit model is increasingly used in practical applications. However the fact that there are two different specifications of the nested logit model has not received adequate attention. The utility...

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...

Motivated by the recurrent Neural Networks, this paper proposes a recurrent Support Vector Regression (SVR) procedure to forecast nonlinear ARMA model based simulated data and real data of financial returns. The forecasting ability of the recurrent SVR is compared with three competing methods,...

Exploratory factor analysis (EFA) is an important tool in data analyses,particularly in social science. Usually four steps are carried out which contain alarge number of options. One important option is the number of factors and theassociation of variables with a factor. Our tools aim to...

In the era of Basel II a powerful tool for bankruptcy prognosis isvital for banks. The tool must be precise but also easily adaptable tothe bank's objections regarding the relation of false acceptances (TypeI error) and false rejections (Type II error). We explore the suitabil-ity of Smooth...

We propose a new nonlinear classification method based on a Bayesian "sum-of-trees" model, the Bayesian Additive Classification Tree (BACT), whichextends the Bayesian Additive Regression Tree (BART) method into the classification context. Like BART, the BACT is a Bayesian nonparametric...