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.
Papers
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Journal ArticleDOI
Complexity in Neural and Financial Systems: From Time-Series to Networks
Tiziano Squartini,Andrea Gabrielli,Diego Garlaschelli,Tommaso Gili,Angelo Bifone,Fabio Caccioli +5 more
TL;DR: This special issue aims at contributing to this ongoing discussion by collecting a number of studies tackling two aspects of complexity that have recently gained increasing attention: the temporal one and the structural one.
Journal ArticleDOI
Information recovery in behavioral networks.
TL;DR: This work focuses on the problem of recovering behavior-related choice information from origin-destination type data, and considers the Cressie-Read family of entropic functionals, enlarging the set of estimators commonly employed to make optimal use of the available information.
Breaking of ensemble equivalence in networks
TL;DR: In this article, it is shown that for discrete systems, ensemble equivalence reduces to equivalence of the large deviation properties of microcanonical and canonical probabilities of a single microstate.
Journal ArticleDOI
Uncovering the mesoscale structure of the credit default swap market to improve portfolio risk modelling
Ioannis Anagnostou,Ioannis Anagnostou,Tiziano Squartini,Drona Kandhai,Drona Kandhai,Diego Garlaschelli,Diego Garlaschelli +6 more
TL;DR: The mesoscopic structure of the CDS market is resolved and this decomposition is used to introduce a novel default risk model that is shown to outperform more traditional alternatives.
Book ChapterDOI
Reconstructing Topological Properties of Complex Networks Using the Fitness Model
Giulio Cimini,Tiziano Squartini,Nicoló Musmeci,Michelangelo Puliga,Andrea Gabrielli,Diego Garlaschelli,Stefano Battiston,Guido Caldarelli +7 more
TL;DR: In this paper, the knowledge of an intrinsic property of the nodes and the number of connections of only a limited subset of nodes is used to generate an ensemble of exponential random graphs that are representative of the real systems and that can be used to estimate its topological properties.