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dc.contributor.authorDhesi, Gurjeet-
dc.contributor.authorShakeel, Bilal-
dc.contributor.authorAusloos, Marcel-
dc.identifier.citationAnnals of Operations Research, 2019en
dc.description.abstractThis paper reports a new methodology and results on the forecast of the numerical value of the fat tail(s) in asset returns distributions using the irrational fractional Brownian motion model. Optimal model parameter values are obtained from fits to consecutive daily 2-year period returns of S&P500 index over [1950–2016], generating 33-time series estimations. Through an econometric model, the kurtosis of returns distributions is modelled as a function of these parameters. Subsequently an auto-regressive analysis on these parameters advances the modelling and forecasting of kurtosis and returns distributions, providing the accurate shape of returns distributions and measurement of Value at Risk.en
dc.publisherSpringer (part of Springer Nature)en
dc.rightsCopyright © the authors, 2019. This is an open-access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.en
dc.subjectFinancial forecasting and simulation (G12)en
dc.subjectAsset pricing (G17)en
dc.subjectSimulation modelling (C63)en
dc.subjectFinancial econometrics (C58)en
dc.titleModelling and forecasting the kurtosis and returns distributions of financial markets: irrational fractional Brownian motion model approachen
dc.typeJournal Articleen
dc.description.versionPublisher Versionen
dc.type.subtypeJournal Article-
pubs.organisational-group/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIESen
pubs.organisational-group/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Businessen
Appears in Collections:Published Articles, School of Management

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