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2014-07-08Diskussionspapier DOI: 10.18452/4522
Adaptive Order FlowForecasting withMultiplicativeError Models
dc.contributor.authorHärdle, Wolfgang Karl
dc.contributor.authorMihoci, Andrija
dc.contributor.authorTing, Christopher Hian-Ann
dc.date.accessioned2017-06-16T01:02:48Z
dc.date.available2017-06-16T01:02:48Z
dc.date.created2014-09-11
dc.date.issued2014-07-08
dc.date.submitted2014-07-08
dc.identifier.issn1860-5664
dc.identifier.urihttp://edoc.hu-berlin.de/18452/5174
dc.description.abstractA flexible statistical approach for the analysis of time-varying dynamics of transaction data on financial markets is here applied to intra-day trading strategies. A local adaptive technique is used to successfully predict financial time series, i.e., the buyer and the seller-initiated trading volumes and the order flow dynamics. Analysing order flow series and its information content of mini Nikkei 225 index futures traded at the Osaka Securities Exchange in 2012 and 2013, a data-driven optimal length of local windows up to approximately 1-2 hours is reasonable to capture parameter variations and is suitable for short-term prediction. Our proposed trading strategies achieve statistical arbitrage opportunities and are therefore beneficial for quantitative finance practice.eng
dc.language.isoeng
dc.publisherHumboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectforecastingeng
dc.subjecttrading volumeeng
dc.subjectorder floweng
dc.subjectmultiplicative error modelseng
dc.subject.ddc310 Sammlungen allgemeiner Statistiken
dc.subject.ddc330 Wirtschaft
dc.titleAdaptive Order FlowForecasting withMultiplicativeError Models
dc.typeworkingPaper
dc.identifier.urnurn:nbn:de:kobv:11-100220135
dc.identifier.doihttp://dx.doi.org/10.18452/4522
local.edoc.pages28
local.edoc.type-nameDiskussionspapier
local.edoc.container-typeseries
local.edoc.container-type-nameSchriftenreihe
local.edoc.container-year2014
dc.identifier.zdb2195055-6
bua.series.nameSonderforschungsbereich 649: Ökonomisches Risiko
bua.series.issuenumber2014,35

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