IDEAS home Printed from https://ideas.repec.org/a/eee/reveco/v40y2015icp72-89.html
   My bibliography  Save this article

A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates

Author

Listed:
  • Balcilar, Mehmet
  • Hammoudeh, Shawkat
  • Asaba, Nwin-Anefo Fru

Abstract

We use the Bayesian Markov-switching vector error correction (MS-VEC) model and the regime-dependent impulse response functions (RDIRFs) to examine the transmission dynamics between oil spot prices, precious metals (gold, silver, platinum, and palladium) spot prices and the US dollar/euro exchange rate. Using daily data from 1987 to 2012, two regimes (low and high volatility regimes) appear to be prevalent for this system. We find evidence that among the five commodity prices the gold prices are the most informative in the group in the high volatility regime, while gold, palladium, and platinum are the most informative in the low volatility regime. Though the platinum and palladium prices impact each other, the impacts in the high volatility regime are asymmetric. In addition to its low correlation in the group, palladium's negative impact on the exchange rate and gold makes it a reliable hedge asset for investors. Gold is the least volatile variable, thus affirming its use as a “safe haven” asset, while silver and oil are the most volatile in the group. Understanding the dynamics of these commodity prices should help investors decide how to invest during periods of low vs. highly volatile regimes.

Suggested Citation

  • Balcilar, Mehmet & Hammoudeh, Shawkat & Asaba, Nwin-Anefo Fru, 2015. "A regime-dependent assessment of the information transmission dynamics between oil prices, precious metal prices and exchange rates," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 72-89.
  • Handle: RePEc:eee:reveco:v:40:y:2015:i:c:p:72-89
    DOI: 10.1016/j.iref.2015.02.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1059056015000271
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.iref.2015.02.005?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pierre Perron & Serena Ng, 1996. "Useful Modifications to some Unit Root Tests with Dependent Errors and their Local Asymptotic Properties," Review of Economic Studies, Oxford University Press, vol. 63(3), pages 435-463.
    2. Schwert, G. William, 1989. "Business cycles, financial crises, and stock volatility," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 83-125, January.
    3. Hammoudeh, Shawkat M. & Yuan, Yuan & McAleer, Michael & Thompson, Mark A., 2010. "Precious metals-exchange rate volatility transmissions and hedging strategies," International Review of Economics & Finance, Elsevier, vol. 19(4), pages 633-647, October.
    4. Saikkonen, Pentti & Lütkepohl, Helmut, 2000. "Testing For The Cointegrating Rank Of A Var Process With An Intercept," Econometric Theory, Cambridge University Press, vol. 16(3), pages 373-406, June.
    5. Awokuse, Titus O. & Yang, Jian, 2003. "The informational role of commodity prices in formulating monetary policy: a reexamination," Economics Letters, Elsevier, vol. 79(2), pages 219-224, May.
    6. Ehrmann, Michael & Ellison, Martin & Valla, Natacha, 2003. "Regime-dependent impulse response functions in a Markov-switching vector autoregression model," Economics Letters, Elsevier, vol. 78(3), pages 295-299, March.
    7. Pagan, Adrian R. & Schwert, G. William, 1990. "Alternative models for conditional stock volatility," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 267-290.
    8. Ghysels, Eric, 1994. "On the Periodic Structure of the Business Cycle," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 289-298, July.
    9. Saikkonen, Pentti, 1992. "Estimation and Testing of Cointegrated Systems by an Autoregressive Approximation," Econometric Theory, Cambridge University Press, vol. 8(1), pages 1-27, March.
    10. Johansen, Soren & Juselius, Katarina, 1990. "Maximum Likelihood Estimation and Inference on Cointegration--With Applications to the Demand for Money," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 52(2), pages 169-210, May.
    11. Krolzig, H., 1996. "Statistical Analysis of Cointegrated VAR Processes with Markovian Regime Shifts," SFB 373 Discussion Papers 1996,25, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
    12. Beckmann, Joscha & Czudaj, Robert, 2013. "Oil prices and effective dollar exchange rates," International Review of Economics & Finance, Elsevier, vol. 27(C), pages 621-636.
    13. Deb, Partha & Trivedi, Pravin K & Varangis, Panayotis, 1996. "The Excess Co-movement of Commodity Prices Reconsidered," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(3), pages 275-291, May-June.
    14. Stanley R. Thompson & Donggyu Sul & Martin T. Bohl, 2002. "Spatial Market Efficiency and Policy Regime Change: Seemingly Unrelated Error Correction Model Estimation," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 84(4), pages 1042-1053.
    15. Saikkonen, Pentti & Lutkepohl, Helmut, 2000. "Testing for the Cointegrating Rank of a VAR Process with Structural Shifts," Journal of Business & Economic Statistics, American Statistical Association, vol. 18(4), pages 451-464, October.
    16. Saikkonen, Pentti & Luukkonen, Ritva, 1997. "Testing cointegration in infinite order vector autoregressive processes," Journal of Econometrics, Elsevier, vol. 81(1), pages 93-126, November.
    17. Benassy-Quere, Agnes & Mignon, Valerie & Penot, Alexis, 2007. "China and the relationship between the oil price and the dollar," Energy Policy, Elsevier, vol. 35(11), pages 5795-5805, November.
    18. Sims, Christopher A, 1980. "Macroeconomics and Reality," Econometrica, Econometric Society, vol. 48(1), pages 1-48, January.
    19. Kim, Chang-Jin & Nelson, Charles R., 1998. "Testing for mean reversion in heteroskedastic data II: Autoregression tests based on Gibbs-sampling-augmented randomization1," Journal of Empirical Finance, Elsevier, vol. 5(4), pages 385-396, October.
    20. Barkoulas, John T. & Chakraborty, Atreya & Ouandlous, Arav, 2012. "A metric and topological analysis of determinism in the crude oil spot market," Energy Economics, Elsevier, vol. 34(2), pages 584-591.
    21. M. R. Barassi & A. Ghoshray, 2007. "Structural Change and Long-run Relationships between US and EU Wheat Export Prices," Journal of Agricultural Economics, Wiley Blackwell, vol. 58(1), pages 76-90, February.
    22. Camacho, Maximo, 2005. "Markov-switching stochastic trends and economic fluctuations," Journal of Economic Dynamics and Control, Elsevier, vol. 29(1-2), pages 135-158, January.
    23. Elliott, Graham & Rothenberg, Thomas J & Stock, James H, 1996. "Efficient Tests for an Autoregressive Unit Root," Econometrica, Econometric Society, vol. 64(4), pages 813-836, July.
    24. Kim, Chang-Jin & Nelson, Charles R. & Startz, Richard, 1998. "Testing for mean reversion in heteroskedastic data based on Gibbs-sampling-augmented randomization1," Journal of Empirical Finance, Elsevier, vol. 5(2), pages 131-154, June.
    25. Palaskas, Theodosios B. & Varangis, Panos N., 1991. "Is there excess co-movement of primary commodity prices? A co-integration test," Policy Research Working Paper Series 758, The World Bank.
    26. Bhar, Ramaprasad & Hammoudeh, Shawkat, 2011. "Commodities and financial variables: Analyzing relationships in a changing regime environment," International Review of Economics & Finance, Elsevier, vol. 20(4), pages 469-484, October.
    27. Massimiliano Marcellino & Grayham E. Mizon & Hans-Martin Krolzig, 2002. "A Markov-switching vector equilibrium correction model of the UK labour market," Empirical Economics, Springer, vol. 27(2), pages 233-254.
    28. Pindyck, Robert S & Rotemberg, Julio J, 1990. "The Excess Co-movement of Commodity Prices," Economic Journal, Royal Economic Society, vol. 100(403), pages 1173-1189, December.
    29. Ang, Andrew & Bekaert, Geert, 2002. "Regime Switches in Interest Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(2), pages 163-182, April.
    30. 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.
    31. Ni, Shawn & Sun, Dongchu & Sun, Xiaoqian, 2007. "Intrinsic Bayesian Estimation of Vector Autoregression Impulse Responses," Journal of Business & Economic Statistics, American Statistical Association, vol. 25, pages 163-176, April.
    32. Massimo Guidolin & Allan Timmermann, 2008. "International asset allocation under regime switching, skew, and kurtosis preferences," Review of Financial Studies, Society for Financial Studies, vol. 21(2), pages 889-935, April.
    33. Ihle, Rico & von Cramon-Taubadel, Stephan, 2008. "A Comparison of Threshold Cointegration and Markov-Switching Vector Error Correction Models in Price Transmission Analysis," 2008 Conference, April 21-22, 2008, St. Louis, Missouri 37603, NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management.
    34. Filardo, Andrew J, 1994. "Business-Cycle Phases and Their Transitional Dynamics," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 299-308, July.
    35. Ciner Cetin, 2001. "Energy Shocks and Financial Markets: Nonlinear Linkages," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 5(3), pages 1-11, October.
    36. Durland, J Michael & McCurdy, Thomas H, 1994. "Duration-Dependent Transitions in a Markov Model of U.S. GNP Growth," Journal of Business & Economic Statistics, American Statistical Association, vol. 12(3), pages 279-288, July.
    37. Cheung, Yin-Wong & Ng, Lilian K., 1996. "A causality-in-variance test and its application to financial market prices," Journal of Econometrics, Elsevier, vol. 72(1-2), pages 33-48.
    38. William Schwert, G., 1989. "Business cycles, financial crises, and stock volatility : Reply to Shiller," Carnegie-Rochester Conference Series on Public Policy, Elsevier, vol. 31(1), pages 133-137, January.
    39. Filardo, Andrew J. & Gordon, Stephen F., 1998. "Business cycle durations," Journal of Econometrics, Elsevier, vol. 85(1), pages 99-123, July.
    40. Djuric, Ivan & Gotz, Linde & Glauben, Thomas, 2012. "Global commodity price peaks and governmental interventions: The case of the wheat-to-bread supply chain in Serbia – Did consumers really benefit?," 52nd Annual Conference, Stuttgart, Germany, September 26-28, 2012 133023, German Association of Agricultural Economists (GEWISOLA).
    41. Serena Ng & Pierre Perron, 2001. "LAG Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, Econometric Society, vol. 69(6), pages 1519-1554, November.
    42. Granger, Clive W J, 1996. "Can We Improve the Perceived Quality of Economic Forecasts?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 11(5), pages 455-473, Sept.-Oct.
    43. Param Silvapulle & Imad A. Moosa, 1999. "The relationship between spot and futures prices: Evidence from the crude oil market," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 19(2), pages 175-193, April.
    44. Bruce E. Hansen, 2001. "The New Econometrics of Structural Change: Dating Breaks in U.S. Labour Productivity," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 117-128, Fall.
    45. Ewing, Bradley T. & Malik, Farooq, 2013. "Volatility transmission between gold and oil futures under structural breaks," International Review of Economics & Finance, Elsevier, vol. 25(C), pages 113-121.
    46. Mr. Paul Cashin & Mr. C. John McDermott & Mr. Alasdair Scott, 1999. "The Myth of Comoving Commodity Prices," IMF Working Papers 1999/169, International Monetary Fund.
    47. Lutkepohl, Helmut & Saikkonen, Pentti, 2000. "Testing for the cointegrating rank of a VAR process with a time trend," Journal of Econometrics, Elsevier, vol. 95(1), pages 177-198, March.
    48. Hua, Ping, 1998. "On Primary Commodity Prices: The Impact of Macroeconomic/Monetary Shocks," Journal of Policy Modeling, Elsevier, vol. 20(6), pages 767-790, December.
    49. Mahdavi, Saeid & Zhou, Su, 1997. "Gold and commodity prices as leading indicators of inflation: Tests of long-run relationship and predictive performance," Journal of Economics and Business, Elsevier, vol. 49(5), pages 475-489.
    50. Robert Savit, 1988. "When random is not random: An introduction to chaos in market prices," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 8(3), pages 271-290, June.
    51. Chang-Jin Kim & Charles R. Nelson, 1998. "Business Cycle Turning Points, A New Coincident Index, And Tests Of Duration Dependence Based On A Dynamic Factor Model With Regime Switching," The Review of Economics and Statistics, MIT Press, vol. 80(2), pages 188-201, May.
    52. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
    53. Zacharias Psaradakis & Nicola Spagnolo, 2003. "On The Determination Of The Number Of Regimes In Markov‐Switching Autoregressive Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 24(2), pages 237-252, March.
    54. 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.
    55. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
    56. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    57. Listorti, Giulia & Esposti, Roberto, 2012. "Horizontal Price Transmission in Agricultural Markets: Fundamental Concepts and Open Empirical Issues," Bio-based and Applied Economics Journal, Italian Association of Agricultural and Applied Economics (AIEAA), vol. 1(1), pages 1-28, April.
    58. Zacharias Psaradakis & Martin Sola & Fabio Spagnolo, 2004. "On Markov error-correction models, with an application to stock prices and dividends," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(1), pages 69-88.
    59. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    60. Cody, Brian J & Mills, Leonard O, 1991. "The Role of Commodity Prices in Formulating Monetary Policy," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 358-365, May.
    Full references (including those not matched with items on IDEAS)

    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. Balcilar, Mehmet & Gupta, Rangan & Miller, Stephen M., 2015. "Regime switching model of US crude oil and stock market prices: 1859 to 2013," Energy Economics, Elsevier, vol. 49(C), pages 317-327.
    2. Mehmet Balcilar & Reneé van Eyden & Josine Uwilingiye & Rangan Gupta, 2017. "The Impact of Oil Price on South African GDP Growth: A Bayesian Markov Switching-VAR Analysis," African Development Review, African Development Bank, vol. 29(2), pages 319-336, June.
    3. Beckmann, Joscha & Czudaj, Robert, 2013. "Gold as an inflation hedge in a time-varying coefficient framework," The North American Journal of Economics and Finance, Elsevier, vol. 24(C), pages 208-222.
    4. Balcilar, Mehmet & Gungor, Hasan & Hammoudeh, Shawkat, 2015. "The time-varying causality between spot and futures crude oil prices: A regime switching approach," International Review of Economics & Finance, Elsevier, vol. 40(C), pages 51-71.
    5. Yuan, Chunming, 2011. "The exchange rate and macroeconomic determinants: Time-varying transitional dynamics," The North American Journal of Economics and Finance, Elsevier, vol. 22(2), pages 197-220, August.
    6. Beckmann, Joscha & Czudaj, Robert, 2013. "Is there a homogeneous causality pattern between oil prices and currencies of oil importers and exporters?," Energy Economics, Elsevier, vol. 40(C), pages 665-678.
    7. Joscha Beckmann & Robert Czudaj, 2017. "Effective Exchange Rates, Current Accounts and Global Imbalances," Review of International Economics, Wiley Blackwell, vol. 25(3), pages 500-533, August.
    8. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2012. "Was the Recent Downturn in US GDP Predictable?," Working Papers 1210, University of Nevada, Las Vegas , Department of Economics.
    9. John D. Levendis, 2018. "Time Series Econometrics," Springer Texts in Business and Economics, Springer, number 978-3-319-98282-3, September.
    10. Mehmet Balcilar & Rangan Gupta & Anandamayee Majumdar & Stephen M. Miller, 2015. "Was the recent downturn in US real GDP predictable?," Applied Economics, Taylor & Francis Journals, vol. 47(28), pages 2985-3007, June.
    11. Balcılar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2015. "Regional and global spillovers and diversification opportunities in the GCC equity sectors," Emerging Markets Review, Elsevier, vol. 24(C), pages 160-187.
    12. Sari, Ramazan & Hammoudeh, Shawkat & Soytas, Ugur, 2010. "Dynamics of oil price, precious metal prices, and exchange rate," Energy Economics, Elsevier, vol. 32(2), pages 351-362, March.
    13. Balcilar, Mehmet & Demirer, Rıza & Hammoudeh, Shawkat, 2013. "Investor herds and regime-switching: Evidence from Gulf Arab stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 23(C), pages 295-321.
    14. Chevallier, Julien, 2011. "Evaluating the carbon-macroeconomy relationship: Evidence from threshold vector error-correction and Markov-switching VAR models," Economic Modelling, Elsevier, vol. 28(6), pages 2634-2656.
    15. Zulquar Nain & Bandi Kamaiah, 2020. "Uncertainty and Effectiveness of Monetary Policy: A Bayesian Markov Switching-VAR Analysis," Journal of Central Banking Theory and Practice, Central bank of Montenegro, vol. 9(special i), pages 237-265.
    16. Joscha Beckmann & Robert Czudaj, 2012. "Gold as an Infl ation Hedge in a Time-Varying Coeffi cient Framework," Ruhr Economic Papers 0362, Rheinisch-Westfälisches Institut für Wirtschaftsforschung, Ruhr-Universität Bochum, Universität Dortmund, Universität Duisburg-Essen.
    17. Yong Song & Tomasz Wo'zniak, 2020. "Markov Switching," Papers 2002.03598, arXiv.org.
    18. repec:zbw:rwirep:0362 is not listed on IDEAS
    19. M. Portugal & I.A. de Morais, 2004. "STRUCTURAL CHANGE IN THE BRAZILIAN DEMAND FOR IMPORTS: A regime switching approach," Econometric Society 2004 Latin American Meetings 346, Econometric Society.
    20. Fischer, Henning & Stolper, Oscar, 2019. "The nonlinear dynamics of corporate bond spreads: Regime-dependent effects of their determinants," Discussion Papers 08/2019, Deutsche Bundesbank.
    21. Richard H. Clarida & Lucio Sarno & Mark P. Taylor & Giorgio Valente, 2006. "The Role of Asymmetries and Regime Shifts in the Term Structure of Interest Rates," The Journal of Business, University of Chicago Press, vol. 79(3), pages 1193-1224, May.

    More about this item

    Keywords

    Markov-switching VEC model; Oil prices; Precious metal prices; Regime-dependent impulse response function; Information transmission;
    All these keywords.

    JEL classification:

    • Q30 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation - - - General
    • Q40 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - General
    • Q43 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy - - - Energy and the Macroeconomy

    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:eee:reveco:v:40:y:2015:i:c:p:72-89. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

    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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/inca/620165 .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.