We study the interplay between scientific progress and culture through text analysis on a corpus of about eight million books, with the use of techniques and algorithms from machine learning. We focus on a specific scientific breakthrough, the theory of evolution through natural selection by...

In US-amerikanischen Studien verschiedener Disziplinen hat sich zur Analyse der sprachlichen Komplexität von Vornamen seit einigen Jahren die so genannte Scrabble-Score-Analyse etabliert. Wie im bekannten Scrabble-Spiel Wörtern nach bestimmten Regeln Punktewerte zugeordnet werden, wird bei...

In this paper, we investigate the temporal dynamics of correlations between sentiment indices worldwide. Employing the tools of Random Matrix Theory (RMT) and Principal Component Analysis (PCA), our paper aims to extract latent information embedded in the interactions between economic and...

We model 1927-1997 U.S. business failure rates using a time series approach based on unobserved components. Clear evidence is found of cyclical behavior in default rates. The cycle has a period of around 10 years. We also detect longer term movements in default probabilities and default...

Causal inference in the empirical sciences is based on counterfactuals. This paper presents the counterfactual account of causation in terms of Lewis's possible-world semantics, and reformulates the statistical potential outcome framework and its underlying assumptions using counterfactual...

In this study we combine clustering techniques with a moving window algorithm in order to filter financial market data outliers. We apply the algorithm to a set of financial market data which consists of 25 series selected from a larger dataset using a cluster analysis technique taking into...

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

The paper offers an alternative approach to analyzing stock market time series data. The purpose is to develop descriptive, more intuitive, and closer to reality analogs of the behavior of US stock market prices, as indexed by the S&P500 stock price index covering the period October 2003 to...

Using the statistical technique of fuzzy clustering, regimes of inflation and unemployment are explored for the United States, the United Kingdom and Germany between 1871 and 2009. We identify for each country three distinct regimes in inflation/unemployment space. There is considerable...

In terms of regulatory and economic capital, credit risk is the most significant risk faced by banks. We implement a credit risk model - based on publicly available information . with the aim of developing a tool to monitor credit risk in a sample of large and complex banking groups (LCBGs) in...