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Short - and long-run relationship between oil price and exchange rate: evidence from Malaysia based on Markov regime switching approach

Author

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  • Hoe, Foong Chee
  • Masih, Mansur

Abstract

There has been an increase in irregularities in fluctuation of oil price globally with high unpredictability that have badly hit oil-producing countries including Malaysia as well as oil and gas companies that remains unresolved. We attempt to examine the short-and long run relationship between crude oil price and exchange rate using a combination of vector auto regression and Markov regime switching techniques. Malaysia is used as a case study. The findings tend to indicate that there is a short run impact on exchange rate when price of oil fluctuates, whereby oil price fluctuation has negative impact on MYR and it takes a long time for the impact to taper off. It is recommended that policy makers, investors and oil companies to take note of the impact on MYR with peaks in the 4th month after oil price changes and prepare accordingly using the right tools to manage and minimise risk of the impact.

Suggested Citation

  • Hoe, Foong Chee & Masih, Mansur, 2017. "Short - and long-run relationship between oil price and exchange rate: evidence from Malaysia based on Markov regime switching approach," MPRA Paper 112105, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:112105
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    References listed on IDEAS

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    1. 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.
    2. van Amano, Robert A & Norden, Simon, 1998. "Exchange Rates and Oil Prices," Review of International Economics, Wiley Blackwell, vol. 6(4), pages 683-694, November.
    3. Johansen, Soren, 1991. "Estimation and Hypothesis Testing of Cointegration Vectors in Gaussian Vector Autoregressive Models," Econometrica, Econometric Society, vol. 59(6), pages 1551-1580, November.
    4. Mandilaras, Alex & Bird, Graham, 2010. "A Markov switching analysis of contagion in the EMS," Journal of International Money and Finance, Elsevier, vol. 29(6), pages 1062-1075, October.
    5. Brahmasrene, Tantatape & Huang, Jui-Chi & Sissoko, Yaya, 2014. "Crude oil prices and exchange rates: Causality, variance decomposition and impulse response," Energy Economics, Elsevier, vol. 44(C), pages 407-412.
    6. Jones, Charles M & Kaul, Gautam, 1996. "Oil and the Stock Markets," Journal of Finance, American Finance Association, vol. 51(2), pages 463-491, June.
    7. Atems, Bebonchu & Kapper, Devin & Lam, Eddery, 2015. "Do exchange rates respond asymmetrically to shocks in the crude oil market?," Energy Economics, Elsevier, vol. 49(C), pages 227-238.
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    More about this item

    Keywords

    oil price; exchange rate; Markov regime switching; Malaysia;
    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
    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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