COVID-19 Coronavirus Pandemic Influence on Crude Oil Prices A Preliminary Statistical Analysis

Avtandil  Silagadze  Alexander Tvalchrelidze

Journal number 2 ∘ Avtandil Silagadze ∘ Alexander Tvalchrelidze ∘
COVID-19 Coronavirus Pandemic Influence on Crude Oil Prices A Preliminary Statistical Analysis

World economy rapidly recovered after the 2009 global economic crisis, and starting from 2010 fast increase of the world GDP was fixed. In 2018 the world GDP was as high as US$ 85,909.816 billion [1]. The world economic growth was unexpectedly hampered by COVID-19 coronavirus pandemic. Within one month the world economy has frozen, industries and budgetary incomes fall down to a critical level, employment collapsed, investor activities distorted and so on. Future prospects are vague. The current framework brings back to memory the period of the Great Depression, when the liberal economic doctrines failed, and governmental interventions became necessary [2]. It is obvious that after the pandemic breakthrough, a lot of fundamental principles will change in the world, including social & economic development doctrines: a bet seems to be placed on maximal involvement of national resources, and such a policy will both be basement of national economic strategies [3-7] and a precondition of regional economic relations [8]. Of course, there is a node of huge and crucial problems to be studied, but in this article, we will present a preliminary statistical analysis of crude oil prices within the framework of COVID-19 coronavirus pandemic.

Keywords: Pandemy, oil price, correlation coefficient, quadratic regression equation, statistical model.

JEL Codes: C10, C40, H12

There is a huge number of publications in the world mass media where influence of coronavirus pandemic on crude oil prices is discussed, however, we have found only a single scientific article, where an econometric model of such an influence is explored [9]. The author concludes that pandemic influence is minor, and oil price trend follows its immanent regularities. However, in March 2020 available statistical material was minor, and econometric equations’ coefficients were not correctly proven. Even now, at our opinion, time for correct econometric analysis has not came yet. Only after cancelling the pandemic sanctions and dully registration of new infection cases such an analysis will have a scientific value.

In a lot of publicist articles [see, for instance, 10] dramatic decrease of oil prices in spring 2020 is explained by decline of demand on fuel due to pandemic sanctions, which have canceled almost all international flights and theatrically diminished automobile traffic in the great majority of developed countries. Hence, as it was proven in a number of fundamental researches [11, 12, etc.], crude oil prices do not follow the main rule of economy and do not obey to supply vs demand ratio. As it has been explored earlier [13], oil prices are driven by the world commodity futures markets. For instance, in 2018 at the world stock, mercantile and commodity exchanges 30.28 billion futures, options and derivative contracts were signed [14], and 30.68% of them or 9.29 billion were oil contracts. Their total nominal cost exceeded three times the world oil consumption.

That is why we have processed available by May 4, 2020 data. Information on world coronavirus infection rate were borrowed from the Worldometers data base [15], and on crude oil weekly prices – from U.S. Statistics Agency [16]. Average weighted weekly world crude oil prices were calculated as a mean value between the OPEC Basket, Brent Blend and Western Texas Intermediate (WTI) benchmark oil prices. World coronavirus infection cases were recalculated on the weekly basis.

Fig. 1 demonstrates correlation between world oil prices and world coronavirus infection cases weekly. Extremely high negative value of the correlation coefficient r (critical value of Pearson’s correlation for 0.001equals 0.693 [17]) allowed us to perform statistical modelling of interdependence between weekly world coronavirus infection cases and crude oil price according to the methodology elaborated [5] and updated [18] earlier. Modelling was performed in the SPSS computer software using ANOVA (Analysis of Variance) technology [19].

Interrelation Between Weekly World Coronavirus Infection Cases and Average Weighted Crude Oil Price.

Fig. 1.

Fig. 2 displays the quadratic equation of this interdependence whereas Tables 1 and 2 provide basic parameters and coefficients of the quadratic regression equation. Comparison of the real and the model (calculated as a function of weekly world coronavirus infection cases) crude oil price graphs are provided on Fig. 3. Tables demonstrate an admissible confidence value of the equation, proven also by good coincidence of the real and model oil price curves.

Basic Parameters of the Equation

Table 1

Coefficients of the Equation

Table 2

The performed analysis leads to some principal and important conclusions as follows:

Dramatic failure of crude oil prices in January-April 2020 was not determined by the diminished world demand on crude oil. It may be proven by data of April 20 – May 4, when the demand has not been increased as far as coronavirus sanctions were not canceled yet but prices have started to grow at the background of diminishing infection cases and announcement of step-by-step sanctions canceling.
Coronavirus infection rate analysis provides to investors tangible guidelines to assess sustainability of futures markets in the medium term and, therefore, to elaborate investment strategy.
The quadratic function has, of course, a parabolic shape, and this means that the oil prices are driven by the coronavirus infection rate rather than by the absolute number of infection cases. In other words, the decisive driver for oil prices in medium term run are pandemic development tendencies instead of real epidemiologic situation.
Relevancy of these conclusions is proven by the model oil pricing curve, which coincides with an admissible accuracy with empiric data.

Will amount of weekly infected people diminish, crude oil futures contract prices will grow.

Quadratic Model of Interdependence Between Weekly World Coronavirus Infection Cases and Crude Oil Price

Fig. 2

Real and Model Crude Oil Prices in January-April 2020

Fig. 3

By the end of 2020 we will present the final model of the interdependence between the coronavirus pandemic and oil prices and compare it with the preliminary analysis hereto.

References:

World Development Indicators. The World Bank. https://databank.worldbank.org/source/world-development-indicators. Accessed on May 4, 2020.
Jordà Ò., Singh S.R., Taylor A.M. (2020). Longer-run Economic Consequences of Pandemics. Working Paper 2020-09. San Francisco: Federal Reserve Bank of San Francisco, 17 pp.
Mekvabishvili E., Atanelishvili T. (2017). Personal Remittances in Post-Soviet Countries (comparative analysis). Bull. Georg. Natl. Acad. Sci., Vol. 11, No 3, pp. 157-163.
Papava V., Silagadze, A. (2019). How the Term the Gross Domestic Product Should be Translated into Georgian. Journal “Globalization & Business”, Vol. 7, pp. 203-204.
Papava V., Charaia V. (2020). The Coronomic Crisis and Some Challenges for the Georgian Economy. GFSIS, Expert Opinion, No. 136. https://www.gfsis.org/files/library/opinion-papers/136-expert-opinion-eng.pdf. Accessed on May 4, 2020.
Silagadze A., Atanelishvili T., Silagadze N. (2019). Economic Doctrines. The Origins. New York: Nova Science Publshers Inc., 58 pp.
Zubiashvili T. (2017) Aspects of Post-Soviet Economy Against the Background of the Associate Agreement with the European Union. Ecoforum, Vol. 6, Issue 1 (10).
Tvalchrelidze A.G., Kervalishvili P.J. (2019). Economic Security of the Southern Caucasus: Opportunities and Shallenges. Nanotechnology Perceptions, Vol. 15, pp. 21-47.
C.T. Albulescu, C.T. (2020). Coronavirus and oil price crash. ResearchGate, March, pp. 1-13.
McCormick M., Raval A., H. Foy, Rocco M. (2020). Oil Prices Take a New Dive as Coronavirus Wipes out Demand .The Financial Times, April 21.
Happonen J. (2009). A Review of Factors Determining Crude Oil Prices. Helsinki: Helsinki School of Economics, 84 p.
Newell R. (2011). Energy and Financial Markets Overview: Crude Oil Price Formation. Washington DC: U.S. Energy Information Administration, 39 p.
Tvalchrelidze A.G.(2011). Economics of Commodities and Commodity Markets. New York: Nova Science Publisher, Inc., 908 p.
WFE IOMA 2018 Derivatives Report (2019). London: World Federation of Exchanges, 53 p.
CoVid-19 Coronavirus Pandemic. https://www.worldometers.info/coronavirus/. Accessed on May 9, 2020.
Weekly Brent, OPEC Basket, and WTI Crude Oil rices from December 30, 2019 to May 4, 2020 (in U.S. dollars per barrel). https://www.statista.com/statistics/326017/weekly-crude-oil-prices/. Accessed on May 9, 2020.
Table of Critical Values for Pearson’s r. https://www.radford.edu/~jaspelme/statsbook/Chapter%20files/Table_of_Critical_Values_for_r.pdf. Accessed on May 9, 2020.
Tvalchrelidze A., A. Silagadze A. (2013). Macroeconomic Model for Oil-Exporting Countries. Central Asia and the Caucasus, Vol. 14, Issue 4, pp. 118-144.
Levine D.M., Berenson M.L., Krehbiel T.C., Stephan D.F. (2010). Statistics for Managers Using Microsoft Excel. 6^th Edition. London: Pearson PLC, 840 pp.

Economics and Business Referential and Reviewed International Scientific-Analytical Journal of Ivane Javakhishvili Tbilisi State University, Faculty of Economics and Business

ISSN 1987-5789 ESSN 2587-5426 doi 10.52340	Journal number 2 ∘ Avtandil Silagadze ∘ Alexander Tvalchrelidze ∘ COVID-19 Coronavirus Pandemic Influence on Crude Oil Prices A Preliminary Statistical Analysis World economy rapidly recovered after the 2009 global economic crisis, and starting from 2010 fast increase of the world GDP was fixed. In 2018 the world GDP was as high as US$ 85,909.816 billion [1]. The world economic growth was unexpectedly hampered by COVID-19 coronavirus pandemic. Within one month the world economy has frozen, industries and budgetary incomes fall down to a critical level, employment collapsed, investor activities distorted and so on. Future prospects are vague. The current framework brings back to memory the period of the Great Depression, when the liberal economic doctrines failed, and governmental interventions became necessary [2]. It is obvious that after the pandemic breakthrough, a lot of fundamental principles will change in the world, including social & economic development doctrines: a bet seems to be placed on maximal involvement of national resources, and such a policy will both be basement of national economic strategies [3-7] and a precondition of regional economic relations [8]. Of course, there is a node of huge and crucial problems to be studied, but in this article, we will present a preliminary statistical analysis of crude oil prices within the framework of COVID-19 coronavirus pandemic. Keywords: Pandemy, oil price, correlation coefficient, quadratic regression equation, statistical model. JEL Codes: C10, C40, H12 There is a huge number of publications in the world mass media where influence of coronavirus pandemic on crude oil prices is discussed, however, we have found only a single scientific article, where an econometric model of such an influence is explored [9]. The author concludes that pandemic influence is minor, and oil price trend follows its immanent regularities. However, in March 2020 available statistical material was minor, and econometric equations’ coefficients were not correctly proven. Even now, at our opinion, time for correct econometric analysis has not came yet. Only after cancelling the pandemic sanctions and dully registration of new infection cases such an analysis will have a scientific value. In a lot of publicist articles [see, for instance, 10] dramatic decrease of oil prices in spring 2020 is explained by decline of demand on fuel due to pandemic sanctions, which have canceled almost all international flights and theatrically diminished automobile traffic in the great majority of developed countries. Hence, as it was proven in a number of fundamental researches [11, 12, etc.], crude oil prices do not follow the main rule of economy and do not obey to supply vs demand ratio. As it has been explored earlier [13], oil prices are driven by the world commodity futures markets. For instance, in 2018 at the world stock, mercantile and commodity exchanges 30.28 billion futures, options and derivative contracts were signed [14], and 30.68% of them or 9.29 billion were oil contracts. Their total nominal cost exceeded three times the world oil consumption. That is why we have processed available by May 4, 2020 data. Information on world coronavirus infection rate were borrowed from the Worldometers data base [15], and on crude oil weekly prices – from U.S. Statistics Agency [16]. Average weighted weekly world crude oil prices were calculated as a mean value between the OPEC Basket, Brent Blend and Western Texas Intermediate (WTI) benchmark oil prices. World coronavirus infection cases were recalculated on the weekly basis. Fig. 1 demonstrates correlation between world oil prices and world coronavirus infection cases weekly. Extremely high negative value of the correlation coefficient r (critical value of Pearson’s correlation for 0.001equals 0.693 [17]) allowed us to perform statistical modelling of interdependence between weekly world coronavirus infection cases and crude oil price according to the methodology elaborated [5] and updated [18] earlier. Modelling was performed in the SPSS computer software using ANOVA (Analysis of Variance) technology [19]. Interrelation Between Weekly World Coronavirus Infection Cases and Average Weighted Crude Oil Price. Fig. 1. Fig. 2 displays the quadratic equation of this interdependence whereas Tables 1 and 2 provide basic parameters and coefficients of the quadratic regression equation. Comparison of the real and the model (calculated as a function of weekly world coronavirus infection cases) crude oil price graphs are provided on Fig. 3. Tables demonstrate an admissible confidence value of the equation, proven also by good coincidence of the real and model oil price curves. Basic Parameters of the Equation Table 1 Coefficients of the Equation Table 2 The performed analysis leads to some principal and important conclusions as follows: Dramatic failure of crude oil prices in January-April 2020 was not determined by the diminished world demand on crude oil. It may be proven by data of April 20 – May 4, when the demand has not been increased as far as coronavirus sanctions were not canceled yet but prices have started to grow at the background of diminishing infection cases and announcement of step-by-step sanctions canceling. Coronavirus infection rate analysis provides to investors tangible guidelines to assess sustainability of futures markets in the medium term and, therefore, to elaborate investment strategy. The quadratic function has, of course, a parabolic shape, and this means that the oil prices are driven by the coronavirus infection rate rather than by the absolute number of infection cases. In other words, the decisive driver for oil prices in medium term run are pandemic development tendencies instead of real epidemiologic situation. Relevancy of these conclusions is proven by the model oil pricing curve, which coincides with an admissible accuracy with empiric data. Will amount of weekly infected people diminish, crude oil futures contract prices will grow. Quadratic Model of Interdependence Between Weekly World Coronavirus Infection Cases and Crude Oil Price Fig. 2 Real and Model Crude Oil Prices in January-April 2020 Fig. 3 By the end of 2020 we will present the final model of the interdependence between the coronavirus pandemic and oil prices and compare it with the preliminary analysis hereto. References: World Development Indicators. The World Bank. https://databank.worldbank.org/source/world-development-indicators. Accessed on May 4, 2020. Jordà Ò., Singh S.R., Taylor A.M. (2020). Longer-run Economic Consequences of Pandemics. Working Paper 2020-09. San Francisco: Federal Reserve Bank of San Francisco, 17 pp. Mekvabishvili E., Atanelishvili T. (2017). Personal Remittances in Post-Soviet Countries (comparative analysis). Bull. Georg. Natl. Acad. Sci., Vol. 11, No 3, pp. 157-163. Papava V., Silagadze, A. (2019). How the Term the Gross Domestic Product Should be Translated into Georgian. Journal “Globalization & Business”, Vol. 7, pp. 203-204. Papava V., Charaia V. (2020). The Coronomic Crisis and Some Challenges for the Georgian Economy. GFSIS, Expert Opinion, No. 136. https://www.gfsis.org/files/library/opinion-papers/136-expert-opinion-eng.pdf. Accessed on May 4, 2020. Silagadze A., Atanelishvili T., Silagadze N. (2019). Economic Doctrines. The Origins. New York: Nova Science Publshers Inc., 58 pp. Zubiashvili T. (2017) Aspects of Post-Soviet Economy Against the Background of the Associate Agreement with the European Union. Ecoforum, Vol. 6, Issue 1 (10). Tvalchrelidze A.G., Kervalishvili P.J. (2019). Economic Security of the Southern Caucasus: Opportunities and Shallenges. Nanotechnology Perceptions, Vol. 15, pp. 21-47. C.T. Albulescu, C.T. (2020). Coronavirus and oil price crash. ResearchGate, March, pp. 1-13. McCormick M., Raval A., H. Foy, Rocco M. (2020). Oil Prices Take a New Dive as Coronavirus Wipes out Demand .The Financial Times, April 21. Happonen J. (2009). A Review of Factors Determining Crude Oil Prices. Helsinki: Helsinki School of Economics, 84 p. Newell R. (2011). Energy and Financial Markets Overview: Crude Oil Price Formation. Washington DC: U.S. Energy Information Administration, 39 p. Tvalchrelidze A.G.(2011). Economics of Commodities and Commodity Markets. New York: Nova Science Publisher, Inc., 908 p. WFE IOMA 2018 Derivatives Report (2019). London: World Federation of Exchanges, 53 p. CoVid-19 Coronavirus Pandemic. https://www.worldometers.info/coronavirus/. Accessed on May 9, 2020. Weekly Brent, OPEC Basket, and WTI Crude Oil rices from December 30, 2019 to May 4, 2020 (in U.S. dollars per barrel). https://www.statista.com/statistics/326017/weekly-crude-oil-prices/. Accessed on May 9, 2020. Table of Critical Values for Pearson’s r. https://www.radford.edu/~jaspelme/statsbook/Chapter%20files/Table_of_Critical_Values_for_r.pdf. Accessed on May 9, 2020. Tvalchrelidze A., A. Silagadze A. (2013). Macroeconomic Model for Oil-Exporting Countries. Central Asia and the Caucasus, Vol. 14, Issue 4, pp. 118-144. Levine D.M., Berenson M.L., Krehbiel T.C., Stephan D.F. (2010). Statistics for Managers Using Microsoft Excel. 6^th Edition. London: Pearson PLC, 840 pp.