IDEAS home Printed from https://ideas.repec.org/a/rnd/arjebs/v11y2019i1p152-165.html
   My bibliography  Save this article

Efficiency in BRICS Currency Markets Using Long-Spans of Data: Evidence from Model-Free Tests of Directional Predictability

Author

Listed:
  • Rangan Gupta
  • Vasilios Plakandaras

Abstract

We analyze the directional predictability in foreign exchange markets of Brazil, Russia, India, China and South Africa (BRICS) using the quantilogram, based on long-spans of monthly historical data, at times covering over a century. We find that the efficient market hypothesis (EMH) holds at the extreme phases of the currency markets (and around the median for India and South Africa). Since predictability holds at certain parts of the unconditional distribution of exchange rate returns, we find support for the Adaptive Market Hypothesis (AMH). AMH, based on the idea of bounded rationality, suggests that currency return predictability will be intermittent, due to changing market conditions and institutional factors.

Suggested Citation

  • Rangan Gupta & Vasilios Plakandaras, 2019. "Efficiency in BRICS Currency Markets Using Long-Spans of Data: Evidence from Model-Free Tests of Directional Predictability," Journal of Economics and Behavioral Studies, AMH International, vol. 11(1), pages 152-165.
  • Handle: RePEc:rnd:arjebs:v:11:y:2019:i:1:p:152-165
    DOI: 10.22610/jebs.v11i1(J).2756
    as

    Download full text from publisher

    File URL: https://ojs.amhinternational.com/index.php/jebs/article/view/2756/1816
    Download Restriction: no

    File URL: https://ojs.amhinternational.com/index.php/jebs/article/view/2756
    Download Restriction: no

    File URL: https://libkey.io/10.22610/jebs.v11i1(J).2756?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
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Mehmet Balcilar & Rangan Gupta & Clement Kyei & Mark E. Wohar, 2016. "Does Economic Policy Uncertainty Predict Exchange Rate Returns and Volatility? Evidence from a Nonparametric Causality-in-Quantiles Test," Open Economies Review, Springer, vol. 27(2), pages 229-250, April.
    2. Charfeddine, Lanouar & Khediri, Karim Ben & Aye, Goodness C. & Gupta, Rangan, 2018. "Time-varying efficiency of developed and emerging bond markets: Evidence from long-spans of historical data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 505(C), pages 632-647.
    3. Vasilios Plakandaras & Theophilos Papadimitriou & Periklis Gogas, 2015. "Forecasting Daily and Monthly Exchange Rates with Machine Learning Techniques," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 34(7), pages 560-573, November.
    4. Sarno,Lucio & Taylor,Mark P., 2003. "The Economics of Exchange Rates," Cambridge Books, Cambridge University Press, number 9780521485845.
    5. Charles, Amélie & Darné, Olivier & Kim, Jae H., 2012. "Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1607-1626.
    6. Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras, 2013. "Forecasting the NOK/USD Exchange Rate with Machine Learning Techniques," Working Paper series 59_13, Rimini Centre for Economic Analysis.
    7. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis, 2012. "Directional forecasting in financial time series using support vector machines: The USD/Euro exchange rate," DUTH Research Papers in Economics 5-2012, Democritus University of Thrace, Department of Economics.
    8. Anoop S. KUMAR & Bandi KAMAIAH, 2016. "Efficiency, non-linearity and chaos: evidences from BRICS foreign exchange markets," Theoretical and Applied Economics, Asociatia Generala a Economistilor din Romania - AGER, vol. 0(1(606), S), pages 103-118, Spring.
    9. Aye, Goodness C. & Gil-Alana, Luis A. & Gupta, Rangan & Wohar, Mark E., 2017. "The efficiency of the art market: Evidence from variance ratio tests, linear and nonlinear fractional integration approaches," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 283-294.
    10. Theophilos Papadimitriou & Periklis Gogas & Vasilios Plakandaras, 2016. "Testing Exchange Rate Models in a Small Open Economy: an SVR Approach," Bulletin of Applied Economics, Risk Market Journals, vol. 3(2), pages 9-29.
    11. Meese, Richard A. & Rogoff, Kenneth, 1983. "Empirical exchange rate models of the seventies : Do they fit out of sample?," Journal of International Economics, Elsevier, vol. 14(1-2), pages 3-24, February.
    12. Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2019. "Are BRICS exchange rates chaotic?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(13), pages 1104-1110, July.
    13. Nikolaos Antonakakis & Mehmet Balcilar & Rangan Gupta & Clement Kyei, 2016. "Components of Economic Policy Uncertainty and Predictability of US Stock Returns and Volatility: Evidence from a Nonparametric Causality-in-Quantile Approach," Working Papers 201639, University of Pretoria, Department of Economics.
    14. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    15. Plakandaras, Vasilios & Papadimitriou, Theophilos & Gogas, Periklis & Diamantaras, Konstantinos, 2015. "Market sentiment and exchange rate directional forecasting," Algorithmic Finance, IOS Press, vol. 4(1-2), pages 69-79.
    16. Jaehun Chung & Yongmiao Hong, 2007. "Model-free evaluation of directional predictability in foreign exchange markets," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(5), pages 855-889.
    17. Ali Almail & Fahad Almudhaf, 2017. "Adaptive Market Hypothesis: Evidence from three centuries of UK data," Economics and Business Letters, Oviedo University Press, vol. 6(2), pages 48-53.
    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. Aviral Kumar Tiwari & Rangan Gupta & Juncal Cunado & Xin Sheng, 2020. "Testing the white noise hypothesis in high-frequency housing returns of the United States," Economics and Business Letters, Oviedo University Press, vol. 9(3), pages 178-188.
    2. Lin Liu, 2022. "Economic Uncertainty and Exchange Market Pressure: Evidence From China," SAGE Open, , vol. 12(1), pages 21582440211, January.

    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. Christina Christou & Rangan Gupta & Christis Hassapis & Tahir Suleman, 2018. "The role of economic uncertainty in forecasting exchange rate returns and realized volatility: Evidence from quantile predictive regressions," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 37(7), pages 705-719, November.
    2. 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.
    3. Tasadduq Imam, 2021. "Model selection for one‐day‐ahead AUD/USD, AUD/EUR forecasts," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(2), pages 1808-1824, April.
    4. Abid, Abir & Rault, Christophe, 2020. "On the Exchange Rate and Economic Policy Uncertainty Nexus: A Panel VAR Approach for Emerging Markets," IZA Discussion Papers 13365, Institute of Labor Economics (IZA).
    5. Aviral Kumar Tiwari & Rangan Gupta & Juncal Cunado & Xin Sheng, 2020. "Testing the white noise hypothesis in high-frequency housing returns of the United States," Economics and Business Letters, Oviedo University Press, vol. 9(3), pages 178-188.
    6. Narayan, Paresh Kumar & Sharma, Susan Sunila & Phan, Dinh Hoang Bach & Liu, Guangqiang, 2020. "Predicting exchange rate returns," Emerging Markets Review, Elsevier, vol. 42(C).
    7. Plakandaras, Vasilios & Gupta, Rangan & Wohar, Mark E., 2017. "The depreciation of the pound post-Brexit: Could it have been predicted?," Finance Research Letters, Elsevier, vol. 21(C), pages 206-213.
    8. Abir ABID & Christophe RAULT, 2020. "On the Exchange Rates Volatility and Economic Policy Uncertainty Nexus: A Panel VAR Approach for Emerging Markets," LEO Working Papers / DR LEO 2816, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
    9. Bonato, Matteo & Cepni, Oguzhan & Gupta, Rangan & Pierdzioch, Christian, 2023. "Climate risks and realized volatility of major commodity currency exchange rates," Journal of Financial Markets, Elsevier, vol. 62(C).
    10. 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.
    11. Khyati Kathuria & Nand Kumar, 2022. "Pandemic‐induced fear and government policy response as a measure of uncertainty in the foreign exchange market: Evidence from (a)symmetric wild bootstrap likelihood ratio test," Pacific Economic Review, Wiley Blackwell, vol. 27(4), pages 361-379, October.
    12. Carlo Altavilla & Paul De Grauwe, 2010. "Forecasting and combining competing models of exchange rate determination," Applied Economics, Taylor & Francis Journals, vol. 42(27), pages 3455-3480.
    13. Valeria Bejarano-Salcedo & William Iván Moreno-Jimenez & Juan Manuel Julio-Román, 2020. "La Magnitud y Duración del Efecto de la Intervención por Subastas sobre el Mercado Cambiario: El caso Colombiano," Borradores de Economia 1142, Banco de la Republica de Colombia.
    14. Barbara Rossi, 2013. "Exchange Rate Predictability," Journal of Economic Literature, American Economic Association, vol. 51(4), pages 1063-1119, December.
    15. Sager, Michael & Taylor, Mark P., 2014. "Generating currency trading rules from the term structure of forward foreign exchange premia," Journal of International Money and Finance, Elsevier, vol. 44(C), pages 230-250.
    16. Papaioannou, Elias & Portes, Richard & Siourounis, Gregorios, 2006. "Optimal currency shares in international reserves: The impact of the euro and the prospects for the dollar," Journal of the Japanese and International Economies, Elsevier, vol. 20(4), pages 508-547, December.
    17. Wollmershauser, Timo, 2006. "Should central banks react to exchange rate movements? An analysis of the robustness of simple policy rules under exchange rate uncertainty," Journal of Macroeconomics, Elsevier, vol. 28(3), pages 493-519, September.
    18. U. Michael Bergman & Shakill Hassan, 2008. "Currency Crises and Monetary Policy in an Economy with Credit Constraints: The No Interest Parity Case," EPRU Working Paper Series 08-01, Economic Policy Research Unit (EPRU), University of Copenhagen. Department of Economics.
    19. David Gruen & Tro Kortian, 1996. "Why Does the Australian Dollar Move so Closely with the Terms of Trade?," RBA Research Discussion Papers rdp9601, Reserve Bank of Australia.
    20. Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2019. "Are BRICS exchange rates chaotic?," Applied Economics Letters, Taylor & Francis Journals, vol. 26(13), pages 1104-1110, July.

    More about this item

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • F31 - International Economics - - International Finance - - - Foreign Exchange
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:rnd:arjebs:v:11:y:2019:i:1:p:152-165. 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: Muhammad Tayyab (email available below). General contact details of provider: https://ojs.amhinternational.com/index.php/jebs .

    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.