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Finance and Credit
 

Macroeconomic determinants of earnings on shares: Evidence from Rosneft oil company

Vol. 26, Iss. 6, JUNE 2020

Received: 20 April 2020

Received in revised form: 4 May 2020

Accepted: 18 May 2020

Available online: 29 June 2020

Subject Heading: Securities market

JEL Classification: G11, G12, C32, C58

Pages: 1352–1372

https://doi.org/10.24891/fc.26.6.1352

Ignatenko E.A. Financial University under Government of Russian Federation, Moscow, Russian Federation
ignatenkoegor19@gmail.com

ORCID id: not available

Krinichanskii K.V. Financial University under Government of Russian Federation, Moscow, Russian Federation
kkrin@ya.ru

https://orcid.org/0000-0002-1225-7263

Subject. The article investigates how macroeconomic variables influence the pricing for common stocks of Rosneft Oil Company.
Objectives. The study identifies principal macroeconomic factors and evaluates their impact on the dynamism of stock exchange rates in the oil and gas sector.
Methods. We rely upon econometric modeling and linear regression based on the least square method. The regression is tested for autocorrelation in residues, heteroskedasticity and non-strict multicollinearity. To arrive at correct standard errors of coefficients given the autocorrelation, we do the robust estimation of covariance matrix.
Results. The dynamics of earnings on shares of Rosneft Oil Company was found to correlate with macroeconomic factors as follows. It has the linear dependency on the Brent price trend, real effective exchange rate of RUB, market risk premium. However, it is inverse to the price index of industrial producers. The earnings on shares were found to be most dependent on fluctuations of the price index of producers, foreign exchange rate and market risk premium.
Conclusions and Relevance. Earnings on shares of the analyzable company and the group of macroeconomic factors reveal the relationship that is statistically considerable. The high determination coefficient and significance in large confidence intervals of regression coefficients are indicative of the high quality of the model. Hence, using macroeconomic variables as regressors, the model may be effective for evaluating and predicting earnings on shares in the oil and gas sector. The findings can be used for further research on macroeconomic shocks and their impact on prices for financial assets issued by the Russian oil and gas companies. The model can be applied to the fundamental analysis and prediction of stock exchange rates of identical companies.

Keywords: stock market, pricing theory, common stock, price determinant, econometric models

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