Big data analysis for financial risk management

被引：44

作者：

Cerchiello P. ^{[1
]}

Giudici P. ^{[1
]}

机构：

[1] Department of Economics and Management Science, Universita degli Studi di Pavia, Via San Felice, 5, Pavia

来源：

Journal of Big Data | / 3卷 / 1期

关键词：

Banking and finance applications; Graphical Gaussian models; Graphical model selection; Risk management; Twitter data analysis;

D O I：

10.1186/s40537-016-0053-4

中图分类号：

学科分类号：

摘要：

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 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. © 2016, The Author(s).

引用

共 17 条

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