Implementing Value-at-Risk and Expected Shortfall for Real Time Risk Monitoring

被引：0
|
作者：
Ristau, Petra [1 ]
机构：
[1] JRC Capital Management & Res GmbH, Kurfurstendamm 186, D-10707 Berlin, Germany
来源：
PROCEEDINGS OF THE 8TH INTERNATIONAL CONFERENCE ON DATA SCIENCE, TECHNOLOGY AND APPLICATIONS (DATA) | 2019年
关键词：
Cloud Appliance; Financial Risk Measures; Value-at-Risk; Expected Shortfall; Monte-Carlo Simulations;
D O I：
10.5220/0008318704590464
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
Regulatory standards require financial service providers and banks to calculate certain risk figures, such as Value at Risk (VaR) and Expected Shortfall (ES). If properly calculated, their formulas are based on a Monte-Carlo simulation, which is computationally complex. This paper describes architecture and development considerations of a use case building a demonstrator for a big data analytics cloud platform developed in the project CloudDBAppliance (CDBA). The chosen approach will allow for real time risk monitoring using cloud computing and a fast analytical processing platform and data base.
引用
收藏
页码：459 / 464
页数：6
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