How can we measure and compare the relative performance of production units?If input and output variables are one dimensional, then the simplest way is tocompute efficiency by calculating and comparing the ratio of output and inputfor each production unit. This idea is inappropriate though, when...

Trading, hedging and risk analysis of complex option portfolios depend on accurate pricing models. The modelling of implied volatilities (IV) plays an important role, since volatility is the crucial parameter in the Black-Scholes (BS) pricing formula. It is well known from empirical studies that...

The Black-Scholes formula, one of the major breakthroughs of modern finance,allows for an easy and fast computation of option prices. But some of its assumptions, like constant volatility or log-normal distribution of asset prices,do not find justification in the markets. More complex models,...

An enormous number of statistical methods have been developed in quantitivefinance during the last decades. Nonparametric methods, bootstrapping timeseries, wavelets, estimation of diffusion coefficients are now almost standard instatistical applications. To implement these new methods the...

The purpose of this work is to introduce one of the most promising among recentlydeveloped statistical techniques – the support vector machine (SVM) –to corporate bankruptcy analysis. An SVM is implemented for analysing suchpredictors as financial ratios. A method of adapting it to default...

Many of the concepts in theoretical and empirical finance developed over thepast decades - including the classical portfolio theory, the Black-Scholes-Mertonoption pricing model and the RiskMetrics variance-covariance approach toValue at Risk (VaR) - rest upon the assumption that asset returns...

Value-at-Risk (VaR) of a portfolio is determined by the multivariate distribution of the risk factors increments. This distribution can be modelled through copulae, where the copulae parameters are not necessarily constant over time. For an exchange rate portfolio, copulae with time varying...

In this paper we propose the GHADA risk management model that is based on the generalized hyperbolic (GH) distribution and on a nonparametric adaptive methodology. Compared to the normal distribution, the GH distribution possesses semi-heavy tails and represents the financial risk factors more...

With the increase of e-learning by universities and educational institutes in the worldthrough more electronic platforms, come the questions to researchers, educators anddesigners of electronic platforms about feasibility and using this method of learning.Are we achieving the desired goals and...

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...