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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-4052
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dc.contributor.authorStockinger, Kurt-
dc.contributor.authorHeitz, Jonas-
dc.contributor.authorBundi, Nils Andri-
dc.contributor.authorBreymann, Wolfgang-
dc.date.accessioned2018-11-23T08:58:27Z-
dc.date.available2018-11-23T08:58:27Z-
dc.date.issued2018-
dc.identifier.isbn978-1-5386-5502-3de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/13175-
dc.description.abstractReal-time financial risk analytics is very challenging due to heterogeneous data sets within and across banks world-wide and highly volatile financial markets. Moreover, large financial organizations have hundreds of millions of financial contracts on their balance sheets. Since there is no standard for modelling financial data, current financial risk algorithms are typically inconsistent and non-scalable. In this paper, we present a novel implementation of a real-world use case for performing large-scale financial risk analytics leveraging Big Data technology. Our performance evaluation demonstrates almost linear scalability.de_CH
dc.language.isoende_CH
dc.publisherIEEEde_CH
dc.rightsNot specifiedde_CH
dc.subjectBig datade_CH
dc.subjectData modelingde_CH
dc.subjectParallel processingde_CH
dc.subjectComputational financede_CH
dc.subject.ddc332.6: Investitionde_CH
dc.titleLarge-scale data-driven financial risk modeling using big data technologyde_CH
dc.typeKonferenz: Paperde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
zhaw.organisationalunitInstitut für Datenanalyse und Prozessdesign (IDP)de_CH
dc.identifier.doi10.1109/BDCAT.2018.00033de_CH
dc.identifier.doi10.21256/zhaw-4052-
zhaw.conference.details5th International Conference on Big Data Computing, Applications and Technologies (BDCAT), Zurich, Switzerland, 17-20 December 2018de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end207de_CH
zhaw.pages.start206de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
zhaw.title.proceedings2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT)de_CH
zhaw.webfeedDatalabde_CH
zhaw.webfeedInformation Engineeringde_CH
zhaw.funding.zhawLarge Scale Data-Driven Financial Risk Modellingde_CH
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Stockinger, K., Heitz, J., Bundi, N. A., & Breymann, W. (2018). Large-scale data-driven financial risk modeling using big data technology [Conference paper]. 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), 206–207. https://doi.org/10.1109/BDCAT.2018.00033
Stockinger, K. et al. (2018) ‘Large-scale data-driven financial risk modeling using big data technology’, in 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT). IEEE, pp. 206–207. Available at: https://doi.org/10.1109/BDCAT.2018.00033.
K. Stockinger, J. Heitz, N. A. Bundi, and W. Breymann, “Large-scale data-driven financial risk modeling using big data technology,” in 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), 2018, pp. 206–207. doi: 10.1109/BDCAT.2018.00033.
STOCKINGER, Kurt, Jonas HEITZ, Nils Andri BUNDI und Wolfgang BREYMANN, 2018. Large-scale data-driven financial risk modeling using big data technology. In: 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT). Conference paper. IEEE. 2018. S. 206–207. ISBN 978-1-5386-5502-3
Stockinger, Kurt, Jonas Heitz, Nils Andri Bundi, and Wolfgang Breymann. 2018. “Large-Scale Data-Driven Financial Risk Modeling Using Big Data Technology.” Conference paper. In 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), 206–7. IEEE. https://doi.org/10.1109/BDCAT.2018.00033.
Stockinger, Kurt, et al. “Large-Scale Data-Driven Financial Risk Modeling Using Big Data Technology.” 2018 IEEE/ACM 5th International Conference on Big Data Computing Applications and Technologies (BDCAT), IEEE, 2018, pp. 206–7, https://doi.org/10.1109/BDCAT.2018.00033.


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