Forecasting oil market balance and its components using an additive model

UDK: 330.105:622.276
DOI: 10.24887/0028-2448-2018-9-76-80
Key words: decomposition, additive model, forecasting, market balance, oil, price, supply, demand
Authors: A.G. Malanichev (Rosneft Oil Company, RF, Moscow)

The paper studies the dynamics of the balance of the global oil market for the period 2016-2017. It is shown that the balance of the world oil market is one of the key factors determining oil price. The market balance is the difference in supply and demand, which are analyzed separately. For the analysis and forecast of time series of supply and demand, their decomposition into trend, seasonality and oscillations is used. For the supply the fourth component is used - supply interruptions.

The analysis showed that the seasonal components of demand and supply are similar to each other. They make a negative contribution in the first two quarters and a positive contribution in the last two quarters. A significant excess of the seasonal component of demand in the third quarter over the supply component can regularly lead to a decrease in the surplus (or deficit growth) in the global oil market and an increase in prices at that time. In the fourth quarter, there is an inverse relationship between the seasonal components of supply and demand, which negatively affects the price of oil. The component of "oscillations" outstripped other components in terms of size, both for demand and for supply. The maximum amplitude of supply oscillations arose due to a reduction in OPEC+ production in the first quarter of 2017, and demand - due to its volatility in the Middle East.

A hypothesis was formulated that the world oil market will remain balanced throughout 2018, and this will allow the world oil price to rise relative to the previous year and its average annual value may be above $70/bbl (Brent). Among the key risks that can affect the price are geopolitical tensions, trade wars, economic instability and a change in the policies of OPEC and its allies.

References

1. Polbin A., Econometric estimation of the impact of oil prices shock on the Russian economy in VECM model (In Russ.), Voprosy ekonomiki, 2017, no. 10, pp. 27–49.

2. Gurvich E.T., Prilepskiy I.V., Analysis of expert and official oil price forecasts (In Russ.), Voprosy ekonomiki, 2018, no. 4, pp. 26–48.

3. What drives crude oil prices, EIA, 2018, April, 23 p.

4. Short-term Energy outlook, EIA, 2018, April.

5. Medlock K.B., Energy demand theory. In International handbook on the economics of energy, Edvard Elgar Publishing, 2009, 848 p.

6. Hyndman R.J., Athanasopoulos G., Forecasting: principles and practice, Pert: University of Western Australia, 2013, 520 p.

7. Svetun'kov I.S., Svetun'kov S.G., Metody i modeli sotsial'no-ekonomicheskogo prognozirovaniya (Methods and models of socio-economic forecasting), Part 2. Modeli i metody (Models and methods), Moscow: Yurayt Publ., 2014, 447 p.8. Malanichev A.G., Modelling of economic oscillations of shale oil production on the basis of analytical solutions of a differentiation equation with a retarded argument (In Russ.), Zhurnal Novoy ekonomicheskoy assotsiatsii, 2018, no. 2 (38), pp. 54–74.

9. https://www.goldmansachs.com/insights/pages/outlook-2016/?playlist=0&video=0


Attention!
To buy the complete text of article (Russian version a format - PDF) or to read the material which is in open access only the authorized visitors of the website can. .