T
Tiziano Squartini
Researcher at IMT Institute for Advanced Studies Lucca
Publications - 137
Citations - 3824
Tiziano Squartini is an academic researcher from IMT Institute for Advanced Studies Lucca. The author has contributed to research in topics: Complex network & Financial networks. The author has an hindex of 29, co-authored 126 publications receiving 2947 citations. Previous affiliations of Tiziano Squartini include Leiden University & Sapienza University of Rome.
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Detecting early signs of the 2007–2008 crisis in the world trade
TL;DR: The present paper uses the theoretical tools of network theory to shed light on the response of world trade to the financial crisis of 2007 and the economic recession of 2008–2009, suggesting the emerging economies as being the most sensitive ones to the global economic cycles.
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Reconstruction methods for networks: The case of economic and financial systems
Tiziano Squartini,Guido Caldarelli,Giulio Cimini,Andrea Gabrielli,Diego Garlaschelli,Diego Garlaschelli +5 more
TL;DR: In this article, the authors present a review of network reconstruction methods for economic and financial networks, mainly focusing on their application to economic networks, and provide a unifying framework to present all these studies.
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Breaking of Ensemble Equivalence in Networks.
TL;DR: It is shown that ensemble nonequivalence can manifest itself also in random graphs with topological constraints, and it is found that, while graphs with a given number of links are ensemble equivalent, graphsWith a given degree sequence are not.
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The Physics of Financial Networks
Marco Bardoscia,Paolo Barucca,Stefano Battiston,Fabio Caccioli,Giulio Cimini,Diego Garlaschelli,Fabio Saracco,Tiziano Squartini,Guido Caldarelli +8 more
TL;DR: This analysis is particularly timely since financial stability as well as recent innovations in climate finance, once properly analysed and understood in terms of complex network theory, can play a pivotal role in the transformation of the authors' society towards a more sustainable world.
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Estimating topological properties of weighted networks from limited information.
TL;DR: This work develops a reconstruction method, based on statistical mechanics concepts, that makes use of the empirical link density in a highly nontrivial way and represents a valuable tool for gaining insights on privacy-protected or partially accessible systems.