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

Petra Ristau

2019

Abstract

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.

Paper Citation

in Harvard Style

Ristau P. (2019). Implementing Value-at-Risk and Expected Shortfall for Real Time Risk Monitoring.In Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: ADITCA, ISBN 978-989-758-377-3, pages 459-464. DOI: 10.5220/0008318704590464

in Bibtex Style

@conference{aditca19,
author={Petra Ristau},
title={Implementing Value-at-Risk and Expected Shortfall for Real Time Risk Monitoring},
booktitle={Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: ADITCA,},
year={2019},
pages={459-464},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0008318704590464},
isbn={978-989-758-377-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 8th International Conference on Data Science, Technology and Applications - Volume 1: ADITCA,
TI - Implementing Value-at-Risk and Expected Shortfall for Real Time Risk Monitoring
SN - 978-989-758-377-3
AU - Ristau P.
PY - 2019
SP - 459
EP - 464
DO - 10.5220/0008318704590464