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An analysis of long horizon exchange rate predictability

datacite.subject.fosCiências Sociais::Economia e Gestãopt_PT
dc.contributor.advisorRodrigues, Paulo Manuel Marques
dc.contributor.authorSantos, Patrícia Vicente Lopes Da Silva
dc.date.accessioned2020-10-15T13:01:43Z
dc.date.available2020-10-15T13:01:43Z
dc.date.issued2020-01-21
dc.date.submitted2020-01-03
dc.description.abstractExchange rate predictability in long-horizons has turned into a debatable topic. Many were the ones achieving evidence of higher predictive power by economic models as larger periods were considered, while others argued against this premise. The main problem resides in the data properties that the regressors used exhibit, more specifically, overlapping observations, high ly persistent regressors, and endogeneity, which affect the statistical inference. Consequently, if the biases are wrongfully corrected, invalid conclusions will be reached. Bearing this in mind, this analysis applies suitable tests aimed at overcoming these issues, after which it is in ferred that mean-based regressions present weak statistical evidence on larger predictability in longer horizons. Lastly, a quantile regression is implemented, contemplating all potential biases. This innovative procedure finally provides results favoring long-horizon predictability.pt_PT
dc.identifier.tid202493784pt_PT
dc.identifier.urihttp://hdl.handle.net/10362/105633
dc.language.isoengpt_PT
dc.relationNova School of Business and Economics
dc.subjectPredictabilitypt_PT
dc.subjectExchange ratespt_PT
dc.subjectQuantile regressionpt_PT
dc.titleAn analysis of long horizon exchange rate predictabilitypt_PT
dc.typemaster thesis
dspace.entity.typePublication
oaire.awardNumberUID/ECO/00124/2013
oaire.awardTitleNova School of Business and Economics
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UID%2FECO%2F00124%2F2013/PT
oaire.fundingStream6817 - DCRRNI ID
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typemasterThesispt_PT
relation.isProjectOfPublication644a3f4f-817b-4d0d-aba6-f98cdca28bc7
relation.isProjectOfPublication.latestForDiscovery644a3f4f-817b-4d0d-aba6-f98cdca28bc7
thesis.degree.nameA Work Project, presented as part of the requirements for the Award of a Masters Degree in Finance from the NOVA – School of Business and Economicspt_PT

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