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dc.contributor.authorCazenave, Tristan
dc.contributor.authorBen Hamida, Sana
dc.date.accessioned2019-04-08T13:27:00Z
dc.date.available2019-04-08T13:27:00Z
dc.date.issued2015
dc.identifier.urihttps://basepub.dauphine.fr/handle/123456789/18613
dc.language.isoenen
dc.subjectMonte Carlo methodsen
dc.subjectForecastingen
dc.subjectGenetic programmingen
dc.subjectTime series analysisen
dc.subject.ddc006.3en
dc.titleForecasting Financial Volatility Using Nested Monte Carlo Expression Discoveryen
dc.typeCommunication / Conférence
dc.description.abstractenWe are interested in discovering expressions for financial prediction using Nested Monte Carlo Search and Genetic Programming. Both methods are applied to learn from financial time series to generate non linear functions for market volatility prediction. The input data, that is a series of daily prices of European S&P500 index, is filtered and sampled in order to improve the training process. Using some assessment metrics, the best generated models given by both approaches for each training sub sample, are evaluated and compared. Results show that Nested Monte Carlo is able to generate better forecasting models than Genetic Programming for the majority of learning samples.en
dc.identifier.citationpages726-733en
dc.relation.ispartoftitle2015 IEEE Symposium Series on Computational Intelligenceen
dc.relation.ispartofeditorIEEE
dc.relation.ispartofpublnameIEEE - Institute of Electrical and Electronics Engineersen
dc.relation.ispartofpublcityPiscataway, NJen
dc.relation.ispartofdate2015-12
dc.subject.ddclabelIntelligence artificielleen
dc.relation.ispartofisbn978-1-4799-7560-0en
dc.relation.conftitle2015 IEEE Symposium Series on Computational Intelligenceen
dc.relation.confdate2015-12
dc.relation.confcityCape Townen
dc.relation.confcountrySouth Africaen
dc.relation.forthcomingnonen
dc.identifier.doi10.1109/SSCI.2015.110en
dc.description.ssrncandidatenonen
dc.description.halcandidateouien
dc.description.readershiprechercheen
dc.description.audienceInternationalen
dc.relation.Isversionofjnlpeerreviewednonen
dc.relation.Isversionofjnlpeerreviewednonen
dc.date.updated2019-03-22T09:54:59Z
hal.person.labIds989
hal.person.labIds989
hal.identifierhal-02092940*


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