A bipartite graph, in which the nodes (or actors in a social network) are partitioned into two sets, can be studied using recent statistical models for dyadic interactions. These models, which are loglinear for the probabilities of dyadic choices or interactions, allow not only arcs or...

The aim of the paper is to provide an analysis of news and financial data using their network representation. The formation of network structures from data sources is carried out using two different approaches: by building the so-called market graph in which nodes represent financial assets...

A time series can often be characterized using machine learning techniques, which require feature vectors as input. The quality of the feature vectors reflects the accuracy of the utilized machine learning techniques. We propose a method for combining features extracted from two popular...

Transport constraints limit competition and arbitrageurs' possibilities of exploiting price differences between goods in neighbouring markets, especially when storage capacity is negligible. We analyse this in markets where strategic producers compete with supply functions, as in wholesale...