Financial big data analysis for the estimation of systemic risks

Paola Cerchiello () and Paolo Giudici

No 86, DEM Working Papers Series from University of Pavia, Department of Economics and Management

Abstract: Systemic risk modelling concerns the estimation of the interrelationships between financial institutions, with the aim of establishing which of them are more central and, therefore, more contagious/subject to contagion. The aim of this paper is to develop a novel systemic risk model. A model that, differently from existing ones, employs not only the information contained in financial market prices, but also big data coming from financial tweets. From a methodological viewpoint, the novelty of our paper is the estimation of systemic risk models using two different data sources: financial markets and financial tweets, and a proposal to combine them, using a Bayesian approach. From an applied viewpoint, we present the first systemic risk model based on big data, and show that such a model can shed further light on the interrelationships between financial institutions.

Keywords: Twitter data analysis; Graphical Gaussian models; Graphical Model selection; Banking and Finance applications; Risk Management (search for similar items in EconPapers)
Pages: 19 pages
Date: 2014-09
New Economics Papers: this item is included in nep-ecm, nep-hme and nep-rmg
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Persistent link: https://EconPapers.repec.org/RePEc:pav:demwpp:086

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