IDEAS home Printed from https://ideas.repec.org/p/pra/mprapa/102450.html
   My bibliography  Save this paper

Модель Зависимости Обменного Курса Рубля От Цен На Нефть С Марковскими Переключениями Режимов
[Modeling the relationship between the Russian ruble exchange rate and oil prices: A Markov regime switching approach]

Author

Listed:
  • Polbin, Andrey
  • Shumilov, Andrei

Abstract

This paper examines the relationship between the Russian ruble/US dollar exchange rate and global oil prices using autoregressive model with Markovian regime shifts. Empirical analysis on daily data for 2009–2019 shows that exchange rate dynamics is best described by three regimes, characterized as follows: 1) weak exchange rate reaction to oil price shocks – low conditional volatility of exchange rate changes; 2) strong reaction – moderate volatility; 3) strong reaction – high volatility. Regime 3 covers crisis periods, when ruble depreciated substantially. Regime 1 prevailed during the period of managed exchange rate arrangement lasted until November 2014. After adoption of a floating exchange rate and inflation targeting policy, regime 1 became regularly identified since mid-2017. This result can be attributed to the introduction in 2017 of a new budget rule, aimed to reduce dependence of exchange rate on oil price fluctuations. Switches between regimes could also be due to fluctuations in the uncertainty measured by the indices of geopolitical risk and economic policy uncertainty for Russia. It is also shown that the model with three regimes outperforms the random walk and linear models of the ruble exchange rate in an out-of-sample fit exercise. The proposed model can be used for identifying the current exchange rate regime in real time, scenario analysis of the consequences for the ruble exchange rate under alternative oil price trajectories, as well as in developing strategies for hedging currency risks by the private sector.

Suggested Citation

  • Polbin, Andrey & Shumilov, Andrei, 2020. "Модель Зависимости Обменного Курса Рубля От Цен На Нефть С Марковскими Переключениями Режимов [Modeling the relationship between the Russian ruble exchange rate and oil prices: A Markov regime swit," MPRA Paper 102450, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:102450
    as

    Download full text from publisher

    File URL: https://mpra.ub.uni-muenchen.de/102450/1/MPRA_paper_102450.pdf
    File Function: original version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:bla:scandj:v:78:y:1976:i:2:p:200-224 is not listed on IDEAS
    2. Michael B. Devereux & Philip R. Lane & Juanyi Xu, 2006. "Exchange Rates and Monetary Policy in Emerging Market Economies," Economic Journal, Royal Economic Society, vol. 116(511), pages 478-506, April.
    3. Domenico Ferraro & Kenneth S. Rogoff & Barbara Rossi, 2011. "Can oil prices forecast exchange rates?," Working Papers 11-34, Federal Reserve Bank of Philadelphia.
    4. Mussa, Michael, 1982. "A Model of Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 90(1), pages 74-104, February.
    5. Ferraro, Domenico & Rogoff, Kenneth & Rossi, Barbara, 2015. "Can oil prices forecast exchange rates? An empirical analysis of the relationship between commodity prices and exchange rates," Journal of International Money and Finance, Elsevier, vol. 54(C), pages 116-141.
    6. Jordi Galí & Tommaso Monacelli, 2005. "Monetary Policy and Exchange Rate Volatility in a Small Open Economy," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 72(3), pages 707-734.
    7. Scott R. Baker & Nicholas Bloom & Steven J. Davis, 2016. "Measuring Economic Policy Uncertainty," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(4), pages 1593-1636.
    8. Nicholas Bloom, 2009. "The Impact of Uncertainty Shocks," Econometrica, Econometric Society, vol. 77(3), pages 623-685, May.
    9. Bartsch, Zachary, 2019. "Economic policy uncertainty and dollar-pound exchange rate return volatility," Journal of International Money and Finance, Elsevier, vol. 98(C), pages 1-1.
    10. Kuang, Pei & Mitra, Kaushik, 2016. "Long-run growth uncertainty," Journal of Monetary Economics, Elsevier, vol. 79(C), pages 67-80.
    11. Obstfeld, Maurice & Rogoff, Kenneth, 1995. "Exchange Rate Dynamics Redux," Journal of Political Economy, University of Chicago Press, vol. 103(3), pages 624-660, June.
    12. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    13. Golub, Stephen S, 1983. "Oil Prices and Exchange Rates," Economic Journal, Royal Economic Society, vol. 93(371), pages 576-593, September.
    14. Kenneth Rogoff, 2009. "Exchange rates in the modern floating era: what do we really know?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 145(1), pages 1-12, April.
    15. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-384, March.
    16. Dornbusch, Rudiger, 1976. "Expectations and Exchange Rate Dynamics," Journal of Political Economy, University of Chicago Press, vol. 84(6), pages 1161-1176, December.
    17. Robert Krol, 2014. "Economic Policy Uncertainty and Exchange Rate Volatility," International Finance, Wiley Blackwell, vol. 17(2), pages 241-256, June.
    18. Polbin, Andrey & Shumilov, Andrei & Bedin, Andrei & Kulikov, Alexander, 2019. "Modeling real exchange rate of the Russian ruble using Markov regime switching approach," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 55, pages 32-50.
    19. Goldfeld, Stephen M. & Quandt, Richard E., 1973. "A Markov model for switching regressions," Journal of Econometrics, Elsevier, vol. 1(1), pages 3-15, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Daniil Lomonosov & Andrey Polbin & Nikita Fokin, 2021. "The Impact of Global Economic Activity, Oil Supply and Speculative Oil Shocks on the Russian Economy," HSE Economic Journal, National Research University Higher School of Economics, vol. 25(2), pages 227-262.
    2. Lomonosov, Daniil & Polbin, Andrey & Fokin, Nikita, 2020. "Влияние Шоков Мировой Деловой Активности, Предложения Нефти И Спекулятивных Нефтяных Шоков На Экономику Рф [The impact of global economic activity, oil supply and speculative oil shocks on the Russ," MPRA Paper 106019, University Library of Munich, Germany.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bermpei, Theodora & Ferrara, Laurent & Karadimitropoulou, Aikaterini & Triantafyllou, Athanasios, 2024. "Commodity currencies revisited: The role of global commodity price uncertainty," Journal of International Money and Finance, Elsevier, vol. 145(C).
    2. Stijn Claessens & M Ayhan Kose, 2017. "Asset prices and macroeconomic outcomes: a survey," BIS Working Papers 676, Bank for International Settlements.
    3. Takamitsu Kurita & Patrick James, 2022. "The Canadian–US dollar exchange rate over the four decades of the post‐Bretton Woods float: An econometric study allowing for structural breaks," Metroeconomica, Wiley Blackwell, vol. 73(3), pages 856-883, July.
    4. Song, Lu & Tian, Gengyu & Jiang, Yonghong, 2022. "Connectedness of commodity, exchange rate and categorical economic policy uncertainties — Evidence from China," The North American Journal of Economics and Finance, Elsevier, vol. 60(C).
    5. Zhou, Zhongbao & Fu, Zhangyan & Jiang, Yong & Zeng, Ximei & Lin, Ling, 2020. "Can economic policy uncertainty predict exchange rate volatility? New evidence from the GARCH-MIDAS model," Finance Research Letters, Elsevier, vol. 34(C).
    6. Stijn Claessens & M Ayhan Kose, 2018. "Frontiers of macrofinancial linkages," BIS Papers, Bank for International Settlements, number 95.
    7. Bush, Georgia & López Noria, Gabriela, 2021. "Uncertainty and exchange rate volatility: Evidence from Mexico," International Review of Economics & Finance, Elsevier, vol. 75(C), pages 704-722.
    8. Beckmann, Joscha & Czudaj, Robert L. & Arora, Vipin, 2020. "The relationship between oil prices and exchange rates: Revisiting theory and evidence," Energy Economics, Elsevier, vol. 88(C).
    9. Magnus Reif, 2020. "Macroeconomics, Nonlinearities, and the Business Cycle," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 87.
    10. Abir Abid & Christophe Rault, 2021. "On the Exchange Rates Volatility and Economic Policy Uncertainty Nexus: A Panel VAR Approach for Emerging Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(3), pages 403-425, September.
    11. Laurent Ferrara & Pierre Guérin, 2018. "What are the macroeconomic effects of high‐frequency uncertainty shocks?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 662-679, August.
    12. Roman Frydman & Michael D. Goldberg & Søren Johansen & Katarina Juselius, 2008. "A Resolution of the Purchasing Power Parity Puzzle: Imperfect Knowledge and Long Swings," Discussion Papers 08-31, University of Copenhagen. Department of Economics.
    13. Stefan Sauer & Klaus Wohlrabe, 2020. "ifo Handbuch der Konjunkturumfragen," ifo Beiträge zur Wirtschaftsforschung, ifo Institute - Leibniz Institute for Economic Research at the University of Munich, number 88.
    14. Balcilar, Mehmet & Gupta, Rangan & Segnon, Mawuli, 2016. "The role of economic policy uncertainty in predicting U.S. recessions: A mixed-frequency Markov-switching vector autoregressive approach," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 10, pages 1-20.
    15. Salisu, Afees A. & Olaniran, Abeeb & Tchankam, Jean Paul, 2022. "Oil tail risk and the tail risk of the US Dollar exchange rates," Energy Economics, Elsevier, vol. 109(C).
    16. Bisharat Hussain Chang & Omer Faruk Derindag & Nuri Hacievliyagil & Mehmet Canakci, 2022. "Exchange rate response to economic policy uncertainty: evidence beyond asymmetry," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-14, December.
    17. Athanasios Triantafyllou & Dimitrios Bakas & Marilou Ioakimidis, 2023. "Commodity price uncertainty as a leading indicator of economic activity," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(4), pages 4194-4219, October.
    18. S. M. Woahid Murad, 2022. "The role of domestic and foreign economic uncertainties in determining the foreign exchange rates: an extended monetary approach," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(4), pages 666-677, October.
    19. Utkarsh Kumar & Wasim Ahmad & Gazi Salah Uddin, 2024. "Bayesian Markov switching model for BRICS currencies' exchange rates," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2322-2340, September.
    20. Albulescu, Claudiu Tiberiu & Demirer, Riza & Raheem, Ibrahim D. & Tiwari, Aviral Kumar, 2019. "Does the U.S. economic policy uncertainty connect financial markets? Evidence from oil and commodity currencies," Energy Economics, Elsevier, vol. 83(C), pages 375-388.

    More about this item

    Keywords

    exchange rate; Russian ruble; oil prices; autoregressive Markov regime switching model; out-of-sample fit;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E58 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Central Banks and Their Policies
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:102450. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Joachim Winter (email available below). General contact details of provider: https://edirc.repec.org/data/vfmunde.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.