Financial Analytics: Science and Experience

A roller coaster ride for the Russian ruble. Part 2

Vol. 11, Iss. 2, MAY 2018

Received: 5 December 2017

Received in revised form: 8 January 2018

Accepted: 15 January 2018

Available online: 31 May 2018


JEL Classification: E31, F31, F33

Pages: 154–169

Alekhin B.I. Russian State University for Humanities, Moscow, Russian Federation

ORCID id: not available

Importance This article considers the relationships between the Brent crude oil price and the Russian ruble/dollar rate.
Objectives The article aims to empirically check the statements on loosening the dependence of the ruble on the price of Brent crude oil, using Russian data for the period from 16 June, 2014 to 27 November, 2017 (181 weekly values).
Methods The study uses econometric tools, which include tests for changes in the data structure, unit root, weak exogeneity, and a model of correction of equilibrium errors.
Results The article presents the results of the analysis of structural changes corresponding to the three regimes of the ruble exchange rate and Brent oil price.
Conclusions Various rate formation factors, such as low inflation and high key interest rate of the Bank of Russia, have stimulated the influx of foreign investments. The demand for rubles to purchase Russian assets, primarily government bonds, is rising, and the ruble exchange rate is rising as well. As a result, the ruble exchange rate loses its cointegration with Brent crude oil price.

Keywords: oil, ruble, cointegration


  1. Hacker R.S. The Effectiveness of Information Criteria in Determining Unit Root and Trend Stratus. CESIS Electronic Working Paper Series, February 2010, no. 213, pp. 1–33. URL: Link
  2. Hamilton J. A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle. Econometrica, 1989, vol. 57, iss. 2, pp. 357–384. URL: Link
  3. Bai J., Perron P. Estimating and Testing Linear Models with Multiple Structural Changes. Econometrica, 1998, vol. 66, no. 1, pp. 47–78.
  4. Nelson C.R., Plosser C.I. Trends and Random Walks in Macroeconomic Time Series: Some Evidence and Implications. Journal of Monetary Economics, 1982, vol. 10, iss. 2, pp. 139–162. URL: Link90012-5
  5. Dickey D., Fuller W. Distribution of the Estimators for Autoregressive Time Series with a Unit Root. Journal of the American Statistical Association, 1979, vol. 74, iss. 366, pp. 427–431. URL: Link
  6. MacKinnon J.G. Critical Values for Cointegration Tests. Queen's Economics Department Working Paper, 2010, no. 1227, pp. 1–19. URL: Link
  7. Kwiatkowski D., Phillips P., Schmidt P. et al. Testing the Null Hypothesis of Stationarity Against the Alternative of a Unit Root. Journal of Econometrics, 1992, vol. 54, iss. 1-3, pp. 159–178. URL: Link90104-Y
  8. Granger C. Some Properties of Time Series Data and Their Use in Econometric Model Specification. Journal of Econometrics, 1981, vol. 16, iss. 1, pp. 121–130. URL: Link90079-8
  9. Engle R., Granger C. Co-Integration and Error Correction: Representation, Estimation, and Testing. Econometrica, 1987, vol. 55, iss. 2, pp. 251–276. URL: Link
  10. Keele L., De Boef S. Not Just for Cointergration: Error Correction Models with Stationary Data. Department of Politics and International Relations Nuffield College and Oxford University, 2004, pp. 1–19. URL: Link
  11. Fama E. Efficient Capital Markets: A Review of Theory and Empirical Work. Journal of Finance, 1970, vol. 25, iss. 2, pp. 385–386, 403. URL: Link
  12. Cashin P., Céspedes L., Sahay R. Commodity Currencies and the Real Exchange Rate, Central Bank of Chile. Journal of Development Economics, 2004, vol. 75, iss. 1, pp. 239–268. URL: Link
  13. Chen Y., Rogoff K. Commodity Currencies. Journal of International Economics, 2003, vol. 59, iss. 2, pp. 133–160. URL: Link00072-7
  14. Chen Y., Rogoff K., Rossi B. Can Exchange Rates Forecast Commodity Prices? NBER Working Paper, 2008, no. 13901, pp. 1–49. URL: Link
  15. Gonsalo J. Five Alternative Methods of Estimating Long-run Equilibrium Relationship. Journal of Econometrics, 1999, vol. 60, iss. 1-2, pp. 200–223. URL: Link90044-2
  16. Hubrich K. Estimation of a German Money Demand System – A Long-run Analysis. Empirical Economics, 1999, vol. 24, iss. 1, pp. 77–99.
  17. Muller Ch. A Note on the Interpretation of Error Correction Coefficients. Swiss Federal Institute of Technology. Zurich Swiss Institute for Business Cycle Research. 2004, September 23.
  18. Gregory A., Hansen B. Residual-based Tests for Co-integration in Models with Regime Shifts. Journal of Econometrics, 1996, vol. 70, iss. 1, pp. 99–126. URL: Link41685-7
  19. Morales L., Gassie E. Structural Breaks and Financial Volatility: Lessons from BRIC Countries. Will the BRIC Decade Continue? – Prospects for Trade and Growth. IAMO Forum 2011, no. 13, pp. 1–35. URL: Link
  20. Schwert G.W. Tests for Unit Roots: A Monte Carlo Investigation. Journal of Business and Economic Statistics, 2002, vol. 20, iss. 1, pp. 5–17. URL: Link

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