Publication:
Forecasting daily return densities from intraday data: a multifractal approach

dc.contributor.coauthorOlmo, Jose
dc.contributor.departmentDepartment of Economics
dc.contributor.kuauthorHallam, Mark
dc.contributor.schoolcollegeinstituteCollege of Administrative Sciences and Economics
dc.date.accessioned2024-11-09T23:09:24Z
dc.date.issued2014
dc.description.abstractThis paper proposes a new approach for estimating and forecasting the moments and probability density function of daily financial returns from intraday data. This is achieved through a new application of the distributional scaling laws for the class of multifractal processes. Density forecasts from the new multifractal approach are typically found to provide substantial improvements in predictive ability over existing forecasting methods for the EUR/USD exchange rate, and are also competitive with existing methods when forecasting the daily return density of the S&P500 and NASDAQ-100 equity index.
dc.description.indexedbyWOS
dc.description.indexedbyScopus
dc.description.issue4
dc.description.openaccessYES
dc.description.publisherscopeInternational
dc.description.sponsoredbyTubitakEuN/A
dc.description.volume30
dc.identifier.doi10.1016/j.ijforecast.2014.01.007
dc.identifier.eissn1872-8200
dc.identifier.issn0169-2070
dc.identifier.quartileQ1
dc.identifier.scopus2-s2.0-84904599922
dc.identifier.urihttps://doi.org/10.1016/j.ijforecast.2014.01.007
dc.identifier.urihttps://hdl.handle.net/20.500.14288/9292
dc.identifier.wos345060200002
dc.keywordsDensity forecasts
dc.keywordsVolatility forecasting
dc.keywordsMultifractal
dc.keywordsUnifractal
dc.keywordsIntraday
dc.keywordsFinance
dc.keywordsConditional volatility
dc.keywordsMoving average
dc.keywordsSkewness
dc.keywordsKurtosis
dc.keywordsFluctuations
dc.keywordsStock
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofInternational Journal of Forecasting
dc.subjectEconomics
dc.subjectManagement
dc.titleForecasting daily return densities from intraday data: a multifractal approach
dc.typeJournal Article
dspace.entity.typePublication
local.contributor.kuauthorHallam, Mark
local.publication.orgunit1College of Administrative Sciences and Economics
local.publication.orgunit2Department of Economics
relation.isOrgUnitOfPublication7ad2a3bb-d8d9-4cbd-a6a3-3ca4b30b40c3
relation.isOrgUnitOfPublication.latestForDiscovery7ad2a3bb-d8d9-4cbd-a6a3-3ca4b30b40c3
relation.isParentOrgUnitOfPublication972aa199-81e2-499f-908e-6fa3deca434a
relation.isParentOrgUnitOfPublication.latestForDiscovery972aa199-81e2-499f-908e-6fa3deca434a

Files