Show simple item record

dc.contributor.authorNyangarika, Anthony
dc.contributor.authorUlf Henning, Richter
dc.contributor.authorAlexey, Mikhaylov
dc.date.accessioned2024-11-25T07:32:28Z
dc.date.available2024-11-25T07:32:28Z
dc.date.issued2018-11
dc.identifier.urihttps://doi.org/10.32479/ijeep.6812
dc.identifier.urihttps://dspace.nm-aist.ac.tz/handle/20.500.12479/2813
dc.descriptionThis research article was published by International Journal of Energy Economics and Policy, 2019, 9(1), 149-159.en_US
dc.description.abstractThe paper proposes modification of auto-regressive integrated moving average model for finding the parameters of estimation and forecasts using exponential smoothing. The study use data Brent crude oil price and gas prices in the period from January 1991 to December 2016. The result of the study showed an improvement in the accuracy of the predicted values, while the emissions occurred near the end of the time series. It has minimal or no effect on other emissions of this data series. The study suggests that investors can predict prices analyzing the possible risks in oil futures markets.en_US
dc.language.isoenen_US
dc.publisherInternational Journal of Energy Economics and Policy (IJEEP)en_US
dc.subjectOil Price Forecasten_US
dc.subjectEconometric Modelen_US
dc.subjectAuto-regressive Integrated Moving Average Modelen_US
dc.titleOil price factors : forecasting on the base of modified auto-regressive integrated moving average modelen_US
dc.typeArticleen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record