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We propose a dynamic network model where two mechanisms control theprobability of a link between two nodes: (i) the existence or absence of thislink in the past, and (ii) node-specific latent variables (dynamic fitnesses)describing the propensity of each node to create links. Assuming a Markovdynamics for both mechanisms, we propose an Expectation-Maximization algorithmfor model estimation and inference of the latent variables. The estimatedparameters and fitnesses can be used to forecast the presence of a link in thefuture. We apply our methodology to the e-MID interbank network for which thetwo linkage mechanisms are associated with two different trading behaviors inthe process of network formation, namely preferential trading and tradingdriven by node-specific characteristics. The empirical results allow torecognise preferential lending in the interbank market and indicate how amethod that does not account for time-varying network topologies tends tooverestimate preferential linkage.

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