系统性风险
新颖性
大数据
金融市场
财务建模
风险管理
计算机科学
财务风险
估计
市场数据
财务风险管理
金融服务
贝叶斯概率
财务
数据科学
业务
经济
数据挖掘
金融危机
人工智能
哲学
神学
管理
宏观经济学
作者
Paola Cerchiello,Paolo Giudici
标识
DOI:10.1186/s40537-016-0053-4
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.
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