A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market
Abstract
We propose a dynamic network model where two mechanisms control the probability of a link between two nodes: (i) the existence or absence of this link in the past, and (ii) node-specific latent variables (dynamic fitnesses) describing the propensity of each node to create links. Assuming a Markov dynamics for both mechanisms, we propose an Expectation-Maximization algorithm for model estimation and inference of the latent variables. The estimated parameters and fitnesses can be used to forecast the presence of a link in the future. We apply our methodology to the e-MID interbank network for which the two linkage mechanisms are associated with two different trading behaviors in the process of network formation, namely preferential trading and trading driven by node-specific characteristics. The empirical results allow to recognise preferential lending in the interbank market and indicate how a method that does not account for time-varying network topologies tends to overestimate preferential linkage.
Keywords
Cite
@article{arxiv.1801.00185,
title = {A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market},
author = {Piero Mazzarisi and Paolo Barucca and Fabrizio Lillo and Daniele Tantari},
journal= {arXiv preprint arXiv:1801.00185},
year = {2018}
}
Comments
19 pages, 6 figures