Risk management and the thorough understanding of the relations betweenfinancial markets and the standard theory of macroeconomics have always been among the topics most addressed by researchers, both financial mathematicians and economists. This work aims at explaining investors behavior from a...

Graphical data representation is an important tool for model selection in bankruptcy analysis since the problem is highly non-linear and its numericalrepresentation is much less transparent. In classical rating models a convenientrepresentation of ratings in a closed form is possible reducing...

The calibration of option pricing models leads to the minimization of an error functional. We show that its usual specification as a root mean squared error implies fluctuating exotics prices and possibly wrong prices...

In this paper we analyse the properties of hierarchical Archimedean copulas. This classis a generalisation of the Archimedean copulas and allows for general non-exchangeable dependencystructures. We show that the structure of the copula can be uniquely recovered from all bivariate margins.We...

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...

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,...

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...

In this paper we adopt a principal components analysis (PCA) to reduce the dimensionality of the term structure and employ autoregressive models (AR) to forecast principal components which, in turn, are used to forecast swap rates. Arguing in favor of structural variation, we propose data...

A huge body of empirical and theoretical literature has emerged on the relationship between foreign exchange (FX) uncertainty and international trade. Empirical findings about the impact of FX uncertainty on trade figures are at best weak and often ambiguous with respect to its direction. Almost...

Predicting default probabilities is important for firms and banks to operate successfully and to estimate their specific risks. There are many reasons to use nonlinear techniques for predicting bankruptcy from financial ratios. Here we propose the so called Support Vector Machine (SVM) to...