Πρόβλεψη τιμών αργού πετρελαίου
![Thumbnail](/xmlui/bitstream/handle/unipi/16057/Tsouklas_1721.pdf.jpg?sequence=4&isAllowed=y)
View/ Open
Keywords
Πετρέλαιο ; Μη ανανεώσιμες πηγές ενέργειας ; Περιβαλλοντικές επιπτώσεις ; Μοντέλα ARIMA ; Box-Jenkins ; Statgraphics ; Προβλέψεις ; Μελλοντική τιμή ; ΧρονοσειρέςAbstract
The following work attempts to analyze the oil market of the time and by using the time series and the statistical package Statgraphics to dare to predict the price of oil soon.
Oil affects both the financial market and the world economy and rightly bears the name of "black gold". Many researchers agree that there is a direct and indirect relationship between the price of oil and economic fundamentals, such as Gross National Product (GDP), unemployment and inflation. [Kilian & Vigfusson, 2011]
Countries that import or export oil are affected differently by the price of oil. For example, when the country imports oil which shows a sharp rise in price, this will have a negative impact on economic growth and inflation. Equally negatively, however, a sharp fall in their price will have an effect, when otherwise the country exports oil since it will have to deal with serious state budget issues.
Despite the oil crises of recent years and the negative and burdened effects on the environment from the extensive use of oil as an energy good (greenhouse effect, climate change), the global energy shift towards renewable energy sources (RES) to reverse this unhealthy situation is not yet at a high level of efficiency so that it can exclusively meet the planet's energy needs. Dependence on "black gold" continues to chastise countries, people, and the environment.
With the help of time series, this paper investigates real crude oil price data as extracted from the reliable source Thomson Reuters (Europe Brent Spot Price FOB) for the period from January 20 10 to December 2022, while with the help of an appropriate model through the statistical tool Statgraphics, important conclusions are drawn, and predictions are given for future prices of this good. [Papadakis et al., 1997]