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An econometric analysis of factors affecting the stock price of Russian companies

Vol. 25, Iss. 4, APRIL 2019

Received: 12 February 2019

Received in revised form: 26 February 2019

Accepted: 12 March 2019

Available online: 26 April 2019

Subject Heading: Securities market

JEL Classification: C38, G11

Pages: 912–924

Malkina M.Yu. National Research Lobachevsky State University of Nizhny Novgorod (UNN), Nizhny Novgorod, Russian Federation

Yakovleva E.K. Nizhny Novgorod Institute of Management of Russian Presidential Academy of National Economy and Public Administration (RANEPA), Nizhny Novgorod, Russian Federation

ORCID id: not available

Subject This paper considers the factors affecting the dynamics of stock market value of the Russian share market.
Objectives The paper aims to identify factors determining the stock prices of Russian emitters and to assess the degree of their influence. We are to build a regression model for shares of the Acron Company as well as examine the resulting model for compliance with quality criteria and explain the obtained results.
Methods We conduct a correlation-regression analysis with the elimination of the seasonal component and bringing the time series to a stationary state. The work uses the least squares method with robust standard errors applying the Cochrane–Orcutt autoregressive transformation, and the Prais–Winsten amendment.
Results The research identifies nine industry and macroeconomic factors affecting the market value of the shares of the company under consideration. We built three alternative models that met all the quality criteria.
Conclusions and Relevance The study reveals the most significant factors for Acron's shares prices: the RTS index, the dollar exchange rate, the volume of commercial transportation of goods by transport etc. The constructed regression equations enable to predict the future stock price of the considered companies.

Keywords: stock market value, correlation-regression analysis, least squares method, autoregressive transformation, Cochrane–Orcutt model


  1. Gorbunova N.A. [Methods of integral evaluation of investment attractiveness of equity securities]. Vestnik Volzhskogo universiteta imeni V.N. Tatishcheva = Vestnik of Volzhsky University after V.N. Tatishchev, 2016, vol. 2, iss. 2, pp. 47–54. URL: Link (In Russ.)
  2. Aleninskaya E.I., Ryabov Yu.P. [Application of comparative approach to estimation of cost of actions on the basis of the fundamental analysis: search of the actions most attractive to investment in oil and gas sector of Russia]. Sotsial'no-ekonomicheskie yavleniya i protsessy = Social and Economic Phenomena and Processes, 2013, no. 5, pp. 23–30. URL: Link (In Russ.)
  3. Kogdenko V.G. [Fundamental analysis of a company: features and key indicators]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2014, no. 33, pp. 2–16. URL: Link (In Russ.)
  4. Trifonov A.Yu., Kritskii O.L., Bel'sner O.A. [Model of dynamic correlations: common application to study of financial markets]. Ekonomicheskii analiz: teoriya i praktika = Economic Analysis: Theory and Practice, 2012, no. 39, pp. 58–62. URL: Link (In Russ.)
  5. Loktionova E.A. [Peculiarities of applying stock valuation methods to various groups of stocks]. Izvestiya Irkutskoi gosudarstvennoi ekonomicheskoi akademii (Baikal'skii gosudarstvennyi universitet ekonomiki i prava) = Baikal Research Journal, 2013, no. 1, 7 p. (In Russ.) URL: Link
  6. Musin A.R. [Economic-mathematical model for predicting financial market dynamics]. Statistika i ekonomika = Statistics and Economics, 2018, vol. 15, iss. 4, pp. 61–69. (In Russ.) URL: Link
  7. Kurochkina I.P., Chudinova T.V. [About the method of estimating and forecasting of value of securities in the stock market]. Statistika i ekonomika = Statistics and Economics, 2012, no. 2, pp. 144–147. URL: Link (In Russ.)
  8. Zabolotnii A.A. [Factor model as a tool for predicting the course of the stock index]. Transportnoe delo Rossii = Transport Business of Russia, 2013, no. 5, pp. 205–208. URL: Link (In Russ.)
  9. Fedorova E.A., Pankratov K.A. [Volatility modeling of the stock market during the crisis]. Finansovaya analitika: problemy i resheniya = Financial Analytics: Science and Experience, 2011, no. 37, pp. 21–30. URL: Link (In Russ.)
  10. Ankudinov A.B., Ibragimov R.M., Lebedev O.V. [Extreme movements of the Russian stock market and their consequences for management and economic modeling]. Prikladnaya ekonometrika = Applied Econometrics, 2017, no. 1, pp. 75–92. URL: Link (In Russ.)
  11. Ivanchenko I.S. [Methods for testing the efficiency of the financial market]. Finansovaya analitika problemy i resheniya = Financial Analytics: Science and Experience, 2015, no. 21, pp. 58–68. URL: Link (In Russ.)
  12. Buyanova E.A., Sarkisov A.R. [Formation of the investment portfolio in the Russian stock market using the nonparametric method of artificial neural network]. Korporativnye finansy = Journal of Corporate Finance Research, 2017, vol. 11, iss. 3, pp. 100–110. (In Russ.) URL: Link
  13. Krasnov M.A. [Method of predicting the dynamics of financial time series in investing]. Terra Economicus, 2009, vol. 7, iss. 1-2, pp. 93–98. URL: Link (In Russ.)
  14. Malkina M.Yu., Yakovleva E.K. [An analysis of growth drivers of prices for the Russian companies' shares]. Regional'naya ekonomika: teoriya i praktika = Regional Economics: Theory and Practice, 2019, vol. 17, iss. 1, pp. 183–200. (In Russ.) URL: Link

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