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dc.contributor.advisorAndreou, Elenaen
dc.contributor.authorIoakeim, Ariaen
dc.creatorIoakeim, Ariaen
dc.date.accessioned2024-06-07T06:23:30Z
dc.date.available2024-06-07T06:23:30Z
dc.date.issued2024-05
dc.identifier.urihttp://gnosis.library.ucy.ac.cy/handle/7/66242en
dc.description.abstractThis dissertation was produced as a component of the "Monetary and Finance Economics" postgraduate program at the University of Cyprus. Its primary objective is to examine the time series data of weekly returns on crude oil prices to forecast their future fluctuations. The study proposes a methodology for predicting oil returns movements utilizing the Box-Jenkins approach, a widely recognized method in time series analysis. The Box-Jenkins methodology involves the identification, estimation, and diagnostic checking of a suitable autoregressive integrated moving average model for the time series data. In addition to the theoretical framework, the study will also include empirical validation of the forecasting model using historical crude oil price data. A theoretical overview is presented, elucidating the crude oil concept and its significance within the global market and financial domain. Subsequent chapters delve into empirical analysis, employing suitable methods to effectively model and forecast crude oil returns. Specifically, autoregressive moving average (ARMA) models and hybrid models within the Generalized Autoregressive Conditional Heteroscedasticity (GARCH) family are constructed utilizing the statistical software EViews 9. By comparing the forecasted values with actual returns movements, the model's performance will be evaluated, thereby contributing to the practical applicability of the Box-Jenkins methodology in the context of crude oil returns forecasting. By shedding light on the predictability of oil returns and the factors driving their movements, this study aims to provide valuable insights that can aid in risk management and strategic planning in the energy and financial sectors.en
dc.language.isoengen
dc.publisherΠανεπιστήμιο Κύπρου, Σχολή Οικονομικών Επιστημών και Διοίκησης / University of Cyprus, Faculty of Economics and Management
dc.rightsinfo:eu-repo/semantics/openAccessen
dc.rightsOpen Accessen
dc.titleModelling and Forecasting Brent Crude Oil Returnsen
dc.typeinfo:eu-repo/semantics/masterThesisen
dc.contributor.committeememberFlori Lyssiotou, Panayiotaen
dc.contributor.departmentΠανεπιστήμιο Κύπρου, Σχολή Οικονομικών Επιστημών και Διοίκησης, Τμήμα Οικονομικώνel
dc.contributor.departmentUniversity of Cyprus, Faculty of Economics and Management, Department of Economicsen
dc.subject.uncontrolledtermBRENTen
dc.subject.uncontrolledtermCRUDE OILen
dc.subject.uncontrolledtermPRICESen
dc.subject.uncontrolledtermRETURNSen
dc.subject.uncontrolledtermTIME-SERIESen
dc.subject.uncontrolledtermBOX-JENKINSen
dc.subject.uncontrolledtermEVIEWS 9en
dc.subject.uncontrolledtermHYBRID MODELSen
dc.subject.uncontrolledtermMODELLINGen
dc.subject.uncontrolledtermFORECASTINGen
dc.author.facultyΣχολή Οικονομικών Επιστημών και Διοίκησης / Faculty of Economics and Management
dc.author.departmentΤμήμα Οικονομικών / Department of Economics
dc.type.uhtypeMaster Thesisen
dc.contributor.orcidFlori Lyssiotou, Panayiota [0000-0001-6007-3023]
dc.gnosis.orcid0000-0001-6007-3023


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