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Are BRICS Exchange Rates Chaotic?

Author

Listed:
  • Vasilios Plakandaras

    (Department of Economics, Democritus University of Thrace, Komotini, Greece)

  • Rangan Gupta

    (Department of Economics, University of Pretoria, Pretoria, South Africa)

  • Luis A. Gil-Alana

    (Department of Economics, University of Navarra, Spain)

  • Mark E. Wohar

    (College of Business Administration, University of Nebraska at Omaha USA, and School of Business and Economics, Loughborough University, UK.)

Abstract

In this paper, we focus on the stochastic (chaotic) attributes of the US dollar-based exchange rates for Brazil, Russia, India, China and South Africa (BRICS) using a long-run monthly dataset covering 1812M01-2017M12, 1814M01-2017M12, 1822M07-2017M12, 1948M08-2017M12, and 1844M01-2017M12, respectively. For our purpose, we consider the Lyapunov exponents, robust to nonlinear and stochastic systems, in both full—samples and in rolling windows. For comparative purposes, we also evaluate a long-run dataset of a developed currency market, namely British pound over the period of 1791M01-2017M12. Our empirical findings detect chaotic behavior only episodically for all countries before the dissolution of the Bretton Woods system, with the exception of the Russian ruble. Overall, our findings suggest that the establishment of the free floating exchange rate system have altered the path of exchange rates removing chaotic dynamics from the phenomenon, and hence, the need for policymakers to intervene in the currency markets for the most important emerging market bloc, should be carefully examined.

Suggested Citation

  • Vasilios Plakandaras & Rangan Gupta & Luis A. Gil-Alana & Mark E. Wohar, 2018. "Are BRICS Exchange Rates Chaotic?," Working Papers 201822, University of Pretoria, Department of Economics.
    • Handle: RePEc:pre:wpaper:201822
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    References listed on IDEAS

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    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. Serletis, Apostolos & Gogas, Periklis, 1997. "Chaos in East European black market exchange rates," Research in Economics, Elsevier, vol. 51(4), pages 359-385, December.
    3. 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 / Editura Economica, vol. 0(1(606), S), pages 103-118, Spring.
    4. Cristescu, C.P. & Stan, C. & Scarlat, E.I., 2009. "The dynamics of exchange rate time series and the chaos game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(23), pages 4845-4855.
    5. Lahmiri, Salim, 2017. "Investigating existence of chaos in short and long term dynamics of Moroccan exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 465(C), pages 655-661.
    6. BenSaïda, Ahmed & Litimi, Houda, 2013. "High level chaos in the exchange and index markets," Chaos, Solitons & Fractals, Elsevier, vol. 54(C), pages 90-95.
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    Citations

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    Cited by:

    1. Omane-Adjepong, Maurice & Alagidede, Imhotep Paul, 2020. "High- and low-level chaos in the time and frequency market returns of leading cryptocurrencies and emerging assets," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    2. 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.
    3. Elie Bouri & Riza Demirer & Rangan Gupta & Xiaojin Sun, 2020. "The predictability of stock market volatility in emerging economies: Relative roles of local, regional, and global business cycles," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(6), pages 957-965, September.
    4. João Frois Caldeira & Rangan Gupta & Muhammad Tahir Suleman & Hudson S. Torrent, 2021. "Forecasting the Term Structure of Interest Rates of the BRICS: Evidence from a Nonparametric Functional Data Analysis," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 57(15), pages 4312-4329, December.
    5. Oguzhan Cepni & David Gabauer & Rangan Gupta & Khuliso Ramabulana, 2020. "Time-Varying Spillover of US Trade War on the Growth of Emerging Economies," Working Papers 202002, University of Pretoria, Department of Economics.
    6. 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.
    7. Tiwari, Aviral Kumar & Aye, Goodness C. & Gupta, Rangan, 2019. "Stock market efficiency analysis using long spans of Data: A multifractal detrended fluctuation approach," Finance Research Letters, Elsevier, vol. 28(C), pages 398-411.
    8. Suman Das & Saikat Sinha Roy, 2021. "Predicting regime switching in BRICS currency volatility: a Markov switching autoregressive approach," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 48(2), pages 165-180, June.

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    More about this item

    Keywords

    Exchange rate; chaos; Lyapunov exponent;
    All these keywords.

    JEL classification:

    • C46 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Specific Distributions
    • E52 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - Monetary Policy

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