Network connectivity, systematic and systemic risk

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dc.contributor.advisor Pelizzon, Loriana it_IT
dc.contributor.author Panzica, Roberto Calogero <1984> it_IT
dc.date.accessioned 2017-09-08 it_IT
dc.date.accessioned 2019-04-06T05:56:33Z
dc.date.available 2019-04-06T05:56:33Z
dc.date.issued 2018-03-01 it_IT
dc.identifier.uri http://hdl.handle.net/10579/14091
dc.description.abstract The thesis collects five papers, each of them, except the last one, treats a different topics related to the asset interconnections and asset pricing. The first paper extends the classic factor-based asset pricing model by including network linkages, leading to a network-augmented linear factor models. The contribution of the paper is to show that the network presence affects the exposure on the common factor, the power of the diversification and the expected returns. The second paper generalizes the model used in the first work by allowing the number of network greater than one. This work has two contributions: how to use a linear factor model as a device for estimating a combination of several networks that monitor the links across variables from different viewpoints; and to demonstrate that Granger causality should be combined with quantile-based causality when the focus is on risk propagation. The third paper investigates on the determinants of the idiosyncratic volatility puzzle by allowing the contemporaneous linkages across asset returns. The first contribution is to show that the puzzle found by ang et al 2006, where stocks with high (low)idiosyncratic volatility relative to the FamaFrench1993 model have low (high) average returns, falls if the idiosyncratic volatility is filtered out from the impact coming from the network. The purpose of the fourth paper is to assert the different informative content between quantile based network measures and quantile based loss measures such as ΔCoVaR. Globally Systemically Important Banks and Insurers and several Hedge Fund indices are considered. The contribution of the paper is to show that quantile regression based on network measures capture the indirect effect of risk spillovers that is instead ignored by quantile based loss measures. Finally, the comparison between quantile based network measures and quantile based losses measures highlights the predicting power of the former during the global systemic crisis of 2007/2008. The fifth paper is a not network related topic, it analyses which are the causes to make a contract eligible to be cleared, by using probit analysis. it_IT
dc.language.iso en it_IT
dc.publisher Università Ca' Foscari Venezia it_IT
dc.rights © Roberto Calogero Panzica, 2017 it_IT
dc.title Network connectivity, systematic and systemic risk it_IT
dc.title.alternative it_IT
dc.type Doctoral Thesis it_IT
dc.degree.name Economia it_IT
dc.degree.level Dottorato di ricerca it_IT
dc.degree.grantor Dipartimento di Economia it_IT
dc.description.academicyear 30 CICLO + PROLUNGAMENTI E SOSPENSIONI 29 CICLO it_IT
dc.description.cycle 29 it_IT
dc.degree.coordinator Pasini, Giacomo <1976> it_IT
dc.location.shelfmark D001846 it_IT
dc.location Venezia, Archivio Università Ca' Foscari, Tesi Dottorato it_IT
dc.rights.accessrights openAccess it_IT
dc.thesis.matricno 963322 it_IT
dc.format.pagenumber XVI, 265 p.
dc.subject.miur SECS-P/02 POLITICA ECONOMICA it_IT
dc.description.note Cotutela con Johann Wolfgang Goethe Universität, Francoforte it_IT
dc.degree.discipline it_IT
dc.contributor.co-advisor Billio, Monica it_IT
dc.provenance.upload Roberto Calogero Panzica (963322@stud.unive.it) it_IT
dc.provenance.plagiarycheck Monica Billio (billio@unive.it) it_IT


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