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...

The goal of this work is to introduce one of the most successful among recently developed statistical techniques - the support vector machine (SVM) - to the field of corporate bankruptcy analysis. The main emphasis is done on implementing SVMs for analysing predictors in the form of financial...

This study analyses credit default risk for firms in the Asian and Pacific region by applying two methodologies: a Support Vector Machine (SVM) and a logistic regression (Logit). Among different financial ratios suggested as predictors of default, leverage ratios and the company size display a...

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 moving...

Financial theory creates a puzzle. Some authors argue that high-risk entrepreneurs choose debt contracts instead of equity contracts since risky but high returns are of relatively more value for a loan-financed firm. On the contrary, authors who focus explicitly on start-up finance predict that...

This paper investigates the link between the optimal level of non-financial firms' liquid assets and industry-level uncertainty. We develop a structural model of a firm's value maximization problem that predicts that as industry-level uncertainty increases the firm will increase its optimal...

The paper investigates young firms' choice of capital source. Our theoretical model hypothesizes a positive (negative) relation between riskiness of the project (price of venture capital) and receiving informed equity. We test our predictions by employing a unique data set collected by KfW...

A good description of the dynamics of interest rates is crucial to price derivatives and to hedge corresponding risk. Interest rate modelling in an unstable macroeconomic context motivates one factor models with time varying parameters. In this paper, the local parameter approach is introduced...

Financial theory creates a puzzle. Some authors argue that high-risk entrepreneurs choose debt contracts instead of equity contracts since risky but high returns are of relatively more value for a loan-financed firm. On the contrary, authors who focus explicitly on start-up finance predict that...

We examine what are common factors that determine systematic credit risk and estimate and interpret the common risk factors. We also compare the contributions of common factors in explaining the changes of credit default swap (CDS) spreads during the pre-crisis, crisis and post-crisis period....