Barucca, P;
Mazzarisi, P;
Tantari, D;
Lillo, F;
(2018)
A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market.
In:
Proceedings of CCS2018.
Complex Systems Society: Thessaloniki, Greece.
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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 ExpectationMaximization 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 recognize 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.
| Type: | Proceedings paper |
|---|---|
| Title: | A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market |
| Event: | CCS2018 |
| Open access status: | An open access version is available from UCL Discovery |
| Publisher version: | http://ccs2018.web.auth.gr/dynamic-network-model-p... |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10110953 |
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