Authors
Massimiliano Zanin, David Papo, Miguel Romance, Regino Criado, Santiago Moral
Journal Paper
https://doi.org/10.1016/j.physa.2016.06.091
Publisher URL
https://www.sciencedirect.com/
Publication date
November 2016
Money flow models are essential tools to understand different economical phenomena, like saving propensities and wealth distributions. In spite of their importance, most of them are based on synthetic transaction networks with simple topologies, e.g. random or scale-free ones, as the characterisation of real networks is made difficult by the confidentiality and sensitivity of money transaction data. Here we present an analysis of the topology created by real credit card transactions from one of the biggest world banks, and show how different distributions, e.g. number of transactions per card or amount, have nontrivial characteristics. We further describe a stochastic model to create transactions data sets, feeding from the obtained distributions, which will allow researchers to create more realistic money flow models.