Exploratory factor analysis (EFA) is an important tool in data analyses, particularly in social science. Usually four steps are carried out which contain an large number of options. One important option is the number of factors and the association of variables with a factor. Our tools aim to...

Exploratory factor analysis (EFA) is an important tool in data analyses, particularly in social science. Usually four steps are carried out which contain an large number of options. One important option is the number of factors and the association of variables with a factor. Our tools aim to...

Exploratory factor analysis (EFA) is an important tool in data analyses, particularly in social science. Usually four steps are carried out which contain a large number of options. One important option is the number of factors and the association of variables with a factor. Our tools aim to...

The paper investigates the sellers' ratings of e-commerce platforms. E-commerce platforms require a robust rating system for the sellers to build their credibility and establish trust in the procurement process. We combine the transaction-level data and feedback scores to develop a model for the...

The article investigates the use of adaptive learning algorithms in constructing dynamic portfolios replicating the return characteristics of a given hedge fund. The emphasis is on out of sample conditional predictive capabilites as necessary to serve as a valuable risk management tool, rather...

One of the main principles to build portfolios of financial assets is to achieve stable long-term performance and avoid large drawdowns. This article describes how a method of Machine Learning, Kohonen's Self-Organising Maps (SOM), can be applied to visualise risk and to build robust portfolios...