Big data models of bank risk contagion

Paola Cerchiello (), Paolo Giudici and Giancarlo Nicola
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Giancarlo Nicola: Department of Economics and Management, University of Pavia

No 117, DEM Working Papers Series from University of Pavia, Department of Economics and Management

Abstract: A very important area of financial risk management is systemic risk modelling,which 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 systemic risk model which, 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, we propose a new framework, based on graphical models, that can estimate systemic risks with models based on two different sources: financial markets and financial tweets, and suggest a way 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. This can help predicting the level of returns of a bank, conditionally on the others, for example when a shock occurs in another bank, or exogeneously.

Keywords: Financial Risk Management; Graphical models; Systemic risks; Twitter data analysis (search for similar items in EconPapers)
Pages: 18 pages
Date: 2016-02
New Economics Papers: this item is included in nep-ecm and nep-rmg
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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