{"id":1079,"date":"2018-01-08T18:24:11","date_gmt":"2018-01-08T17:24:11","guid":{"rendered":"http:\/\/mathfinance.sns.it\/?p=1079"},"modified":"2018-02-27T12:18:53","modified_gmt":"2018-02-27T11:18:53","slug":"a-dynamic-network-model-with-persistent-links-and-node-specific-latent-variables-with-an-application-to-the-interbank-market","status":"publish","type":"post","link":"http:\/\/mathfinance.sns.it\/index.php\/a-dynamic-network-model-with-persistent-links-and-node-specific-latent-variables-with-an-application-to-the-interbank-market\/","title":{"rendered":"P.Mazzarisi, P.Barucca, F.Lillo, D.Tantari, <em>A dynamic network model with persistent links and node-specific latent variables, with an application to the interbank market<\/em>"},"content":{"rendered":"<p>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.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>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 [&hellip;]<\/p>\n","protected":false},"author":16,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[11],"tags":[],"_links":{"self":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/1079"}],"collection":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/users\/16"}],"replies":[{"embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/comments?post=1079"}],"version-history":[{"count":4,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/1079\/revisions"}],"predecessor-version":[{"id":1125,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/posts\/1079\/revisions\/1125"}],"wp:attachment":[{"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/media?parent=1079"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/categories?post=1079"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/mathfinance.sns.it\/index.php\/wp-json\/wp\/v2\/tags?post=1079"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}