The year 2018 was characterized by an increased demand, continuing the pricing uptrend from 2017, though experiencing a sharp drop by the end of the year. This study aims to provide a careful projection for next year's average oil pricing, utilizing predictive analysis methods. Evidently, predictive analysis cannot provide accurate answers, since we are only speaking of statistical probability, but we can define a high probability range with fair accuracy. Combining predictive analysis models of 10-year and 15-year pricing trends we should expect an average pricing of 65 to 95 USD per oil barrel during 2019.

The conventional crude oil sector is an enormous market, with a daily turnover of nearly 4 billion US Dollars, not including investments and indirect expenses and excluding non-conventional resources. Annual crude oil sales revenue surpassed 2.5 trillion US Dollars throughout 2018, which is nearly 2.9% of global GDP. Despite decreasing importance of conventional crude oil, it is still making up a lion share of the global energy market. Conventional crude oil is currently supplied at about 73-74 million bpd, which is about 76-77% out of total 96 million bpd of liquid fuels, whereas liquid fuels compose some 30% of the primary energy market. Thus, conventional crude oil has significantly dropped from its peak primary energy market share of 50% in the 1970s, but is still critical for global economy. Conventional crude oil is primarily important for the transportation sector, though there is a wide use of oil products for backup power, industrial heating and for electricity production in non-OECD countries. Conventional crude oil is also widely utilized as a source for oils and polymers in the plastics and cosmetics industries.

The year 2018 has been characterized by an increased oil demand for most of the year, continuing the pricing uptrend from 2017, though experiencing a sharp drop of price by the end of the year. With global oil supply and demand closely corresponding, the sharp drop of oil price at the end of 2018 may be an indication of parallel bearish sentiment at the stock market, implying that future prices of commodities will greatly be influenced by the global economic atmosphere.

This study aims to provide a careful projection for next year's average oil pricing utilizing predictive analysis methods. The herewith described price projection is based on the mathematical extrapolation model, which is derived from 15-year long and 10-year long OPEC basket oil price trends. It is of course an assumption that polynomial trend extrapolation of first, second, third and fourth degree is sufficiently accurate to predict oil pricing in the short term of one year . Such a model can be defined as "non-linear predictive analysis", and in case the assumption is correct - it allows us to provide reasonable projections for a limited time range. This is not a perfect method for financial predictions and is in fact rarely utilized by economists, but is much more objective compared with fundamental analysis and is certainly much more reliable than a simple "business-as-usual" scenario (zero or first degree polynomial fit), which is the dominant, but mostly imprecise, tool in many economic models.

In regard to the previous projection for 2018 based on the 15-year price trend, the most precise result was derived from the 1st polynomial fit, which had a good correlation with the actual average annual oil price. However, 2017 projection was fair with 1st and 2nd polynomial fits, 2016 projection was most accurate with the 3rd polynomial fit and none of the 15-year price trend based projections was close in 2015. Somewhat better results can be derived from the 10-year price trend model. Using the above assumptions, the same polynomial fits can be applied for average annual oil price data series, in order to produce projections for average annual oil price in 2019.

Using the 15-year price trend model - with the 1st polynomial fit, the 2019 result for annual average price is 78 USD per barrel; with 2nd polynomial fit, the 2019 result for annual average price is 30 USD per barrel; with 3rd polynomial fit, the 2019 result for annual average price is 44 USD per barrel. Higher polynomial fits can also be utilized, but may not sufficiently add to prediction accuracy with this 15-year price trend model. However, combining polynomial fir projections based on 10-year price trend, the model could provide us with more precise tools for estimating future oil pricing.

*Figure 1. Annual average OPEC basket oil price during 2004-2018, with mathematical predictive analysis fits of first polynomial, second polynomial and third polynomial degrees to the 15-year
price trend of oil.*

With such relatively simple mathematical analysis, there is a wide selection of results, ranging from strongly positive direction per first polynomial fit to collapse per second and third polynomial fit with the 15-year price trend model. Evidently, predictive analysis cannot provide accurate answers, since we are only speaking of statistical probability, but we can speak of a high probability range. With predictive analysis models of 10-year and 15-year pricing trends we should expect an average oil pricing in the range of 65-95 USD per barrel during 2019. The projection is referring to the average oil basket pricing of OPEC countries, thus not directly relevant to Brent oil pricing, though there is of course a strong correlation between the two. This projection implies some uncertainty, which makes much sense in light of general instability in global economy.

**Disclaimer**

The above presented data is a general informative survey and is not to be considered as a consulting in any way in relevance to capital investment, securities or any other financial instrument. For the avoidance of doubt, the author of this survey is not a certified investment consultant and hence the content of this document is not inclining the readers towards any financial action. It should be emphasized that the reader is recommended to check and verify the content of the above survey prior to obtaining any conclusions of it, since misunderstanding of written material might occur and that there could be unintentional data errors and resulting errors in the analysis. The content of this survey, including every part of it, as well as charts and analyses, are protected by the 2007 Copyright Act of the State of Israel and are not to be used in any way without the explicit approval of LNRG Technology. Charts and images from external sources are utilized in the survey with appropriate licenses; any use of such external charts and images by reader is under the direct responsibility of the reader and under the explicit conditions of the relevant author.

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