This paper develops an early warning system for predicting distress for large European banks. Using a novel definition of distress derived from banks' headroom above regulatory requirements, we investigate the performance of three machine learning techniques against the traditional logistic...

In this paper we design a simple trading strategy to exploit the hypothesized distinct informational content of the arithmetic and geometric mean. The rejection of cointegration between the two stock market indicators supports this conjecture. The profits generated by this cheaply replicable...

Several approaches for subset recovery and improved forecasting accuracy have been proposed and studied. One way is to apply a regularization strategy and solve the model selection task as a continuous optimization problem. One of the most popular approaches in this research field is given by...

Business tendency survey indicators are widely recognized as a key instrument for business cycle forecasting. Their leading indicator property is assessed with regard to forecasting industrial production in Russia and Germany. For this purpose, vector autoregressive (VAR) models are specified...

Banks are concerned with the assessment of the risk of financial distress before giving out a loan. Many researchers proposed the use of models based on the Neural Networks in order to help the banker better make a decision. The objective of this paper is to explore a new practical way based on...

Credit risk is defined as the risk that borrowers will fail to pay its loan obligations. In recent years, a large number of banks have developed sophisticated systems and models to help bankers in quantifying, aggregating and managing risk. The outputs of these models also play increasingly...

A reflection on the lackluster growth over the decade since the Global Financial Crisis has renewed interest in preventative measures for a long-standing problem. Advances in machine learning algorithms during this period present promising forecasting solutions. In this context, the paper...

We use a long history of global temperature and atmospheric carbon dioxide (CO2) concentration to estimate the conditional joint evolution of temperature and CO2 at a millennial frequency. We document three basic facts. First, the temperature-CO2 dynamics are non-linear, so that large deviations...

This study explores the redundancy of the value premium by conducting a Fourier analysis. The results illustrate periodicity in the value premium and merges the Adaptive Market Hypothesis with the Efficient Market hypothesis. The value premium is considered to be redundant due to structural...

Anwendung der Extremwerttheorie zur Quantifizierung von Marktpreisrisiken – Test der Relevanz anhand vergangener Extrembelastungen von DAX und MSCI Europe Ein Verfahren, das gezielt entwickelt wurde, um Risiken mit sehr geringen Eintrittswahrscheinlichkeiten zu quantifizieren, stellt die...