The development of shadow banking system in China catalyzes the expansion of banks' off-balance-sheet activities, resulting in a distortion of China's traditional credit expansion and underestimation of its commercial banks' overall risk. This paper is the first to incorporate banks' overall...

We develop a composite indicator measuring the performance of national innovation systems. The indicator takes into account both "hard" factors that are quantifiable (such as R&D spending, number of patents) and "soft" factors like the assessment of preconditions for innovation by managers. We...

The implied volatility became one of the key issues in modern quantitative finance, since the plain vanilla option prices contain vital information for pricing and hedging of exotic and illiquid options. European plain vanilla options are nowadays widely traded, which results in a great amount...

A primary goal in modelling the implied volatility surface (IVS) for pricing and hedging aims at reducing complexity. For this purpose one fits the IVS each day and applies a principal component analysis using a functional norm. This approach, however, neglects the degenerated string structure...

After 20 years of transition from an economy integrated in an exchange scheme of planned economies towards an open market economy based on the ideas of competition, we ask whether East German firms succeeded in finding their place in the international division of labour. We concentrate on the...

This paper studies polar sets of anisotropic Gaussian random elds, i.e. sets which a Gaussian random eld does not hit almost surely. The main assumptions are that the eigenvalues of the covariance matrix are bounded from below and that the canonical metric associated with the Gaussian random eld...

In this article, we present new ideas concerning Non-Gaussian Component Analysis (NGCA). We use the structural assumption that a high-dimensional random vector X can be represented as a sum of two components - a lowdimensional signal S and a noise component N. We show that this assumption...

In many economic applications it is desirable to make future predictions about the financial status of a company. The focus of predictions is mainly if a company will default or not. A support vector machine (SVM) is one learning method which uses historical data to establish a classification...

Let a high-dimensional random vector ⃗X can be represented as a sum of two components - a signal ⃗S , which belongs to some low-dimensional subspace S, and a noise component ⃗N . This paper presents a new approach for estimating the subspace S based on the ideas of the Non-Gaussian...