Name
Title | ||
|---|---|---|
A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market. |
Abstract | ||
|---|---|---|
•We model temporal networks driven by latent node variables and link persistence.•Maximum a Posteriori approach allows unbiased inference and short term link prediction.•The method allows to quantify the role of persistence for each link.•In interbank markets latent variables explain the network more than link persistence.•Latent node variables are correlated with banks’ aggregate exposures. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1016/j.ejor.2019.07.024 | European Journal of Operational Research |
Keywords | Field | DocType |
Temporal networks,Markov processes,Expectation-Maximization,Interbank market,Link prediction | Dynamic network analysis,Network formation,Interbank network,Data mining,Interbank lending market,Computer science,Inference,Markov chain,Latent variable,Network topology | Journal |
Volume | Issue | ISSN |
281 | 1 | 0377-2217 |
Citations | PageRank | References |
1 | 0.35 | 5 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Piero Mazzarisi | 1 | 1 | 0.69 |
| Paolo Barucca | 2 | 11 | 3.76 |
| Fabrizio Lillo | 3 | 41 | 10.66 |
| Daniele Tantari | 4 | 15 | 2.78 |