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Estimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning

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dc.contributor.authorForesti, Andrea
dc.date.accessioned2019-03-27T14:54:07Z
dc.date.available2019-03-27T14:54:07Z
dc.date.issued2019-03
dc.description.abstractThis paper presents different deep neural network architectures designed to forecast the distribution of returns on a portfolio of U.S. Treasury securities. A long short-term memory model and a convolutional neural network are tested as the main building blocks of each architecture. The models are then augmented by cross-sectional data and the portfolio's empirical distribution. The paper also presents the fit and generalization potential of each approach.en
dc.identifierhttp://documents.worldbank.org/curated/en/433791553192242300/Estimation-of-the-ex-ante-Distribution-of-Returns-for-a-Portfolio-of-U-S-Treasury-Securities-via-Deep-Learning
dc.identifier.doi10.1596/1813-9450-8790
dc.identifier.urihttps://hdl.handle.net/10986/31449
dc.languageEnglish
dc.publisherWorld Bank, Washington, DC
dc.relation.ispartofseriesPolicy Research Working Paper;No. 8790
dc.rightsCC BY 3.0 IGO
dc.rights.holderWorld Bank
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/igo
dc.subjectMACHINE LEARNING
dc.subjectNEURAL NETWORKS
dc.subjectCONVOLUTION
dc.subjectLSTM
dc.subjectMARKET RISK
dc.subjectSECURITIES PORTFOLIO
dc.titleEstimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learningen
dc.typeWorking Paperen
dc.typeDocument de travailfr
dc.typeDocumento de trabajoes
dspace.entity.typePublication
okr.crossref.titleEstimation of the ex ante Distribution of Returns for a Portfolio of U.S. Treasury Securities via Deep Learning
okr.date.disclosure2019-03-21
okr.doctypePublications & Research
okr.doctypePublications & Research::Policy Research Working Paper
okr.docurlhttp://documents.worldbank.org/curated/en/433791553192242300/Estimation-of-the-ex-ante-Distribution-of-Returns-for-a-Portfolio-of-U-S-Treasury-Securities-via-Deep-Learning
okr.guid433791553192242300
okr.identifier.doi10.1596/1813-9450-8790
okr.identifier.doihttps://doi.org/10.1596/1813-9450-8790
okr.identifier.externaldocumentum090224b086ac2842_2_0
okr.identifier.internaldocumentum30921728
okr.identifier.reportWPS8790
okr.importedtrueen
okr.language.supporteden
okr.pdfurlhttp://documents.worldbank.org/curated/en/433791553192242300/pdf/WPS8790.pdfen
okr.region.countryUnited States
okr.statistics.combined1047
okr.statistics.dr433791553192242300
okr.statistics.drstats825
okr.topicMacroeconomics and Economic Growth::Economic Theory & Research
okr.topicScience and Technology Development::Science Mathematics and Technology
okr.unitMarket and Counterparty Risk Team
relation.isSeriesOfPublication26e071dc-b0bf-409c-b982-df2970295c87
relation.isSeriesOfPublication.latestForDiscovery26e071dc-b0bf-409c-b982-df2970295c87
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