A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market

DOI10.1016/j.ejor.2019.07.024zbMath1430.90176arXiv1801.00185OpenAlexW2962798205WikidataQ127478262 ScholiaQ127478262MaRDI QIDQ2329477

Fabrizio Lillo, Piero Mazzarisi, Daniele Tantari, Paolo Barucca

Publication date: 17 October 2019

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1801.00185

zbMATH Keywords

Markov processesexpectation-maximizationlink predictioninterbank markettemporal networks

Mathematics Subject Classification ID

Markov processes: estimation; hidden Markov models (62M05) Stochastic network models in operations research (90B15) Applications of Markov chains and discrete-time Markov processes on general state spaces (social mobility, learning theory, industrial processes, etc.) (60J20) Financial applications of other theories (91G80)

Related Items (8)

Do banks change their liquidity ratios based on network characteristics? ⋮ Analytical formulation for explaining the variations in traffic states: a fundamental diagram modeling perspective with stochastic parameters ⋮ New reliability model for complex systems based on stochastic processes and survival signature ⋮ On the analysis of fitness change: fitness-popularity dynamic network model with varying fitness ⋮ Tail Granger causalities and where to find them: extreme risk spillovers vs spurious linkages ⋮ Memory effects on link formation in temporal networks: a fractional calculus approach ⋮ The construction of multilayer stock network model ⋮ On the equivalence between the kinetic Ising model and discrete autoregressive processes

Uses Software

• BayesLogit
• FinTS

Cites Work

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