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Efficiency, non-linearity and chaos: evidences from BRICS foreign exchange markets

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  • Anoop S. KUMAR

    (BITS Pilani KK Birla Goa Campus, Goa, India)

  • Bandi KAMAIAH

    (University of Hyderabad, Hyderabad, India)

Abstract

This study examines the presence of possible weak form of market efficiency, non-linearity and chaotic behaviour in the foreign exchange markets of Brazil, Russia, India, China and South Africa(commonly known together as BRICS) using various tests. Monthly Nominal Effective Exchange Rate (NEER) data for the said countries, ranging from April 1994 to September 2014 were examined. The analysis was carried out using variance ratio (VR) tests, BDS test, Hinich Bispectrum test, Teräsvirta Neural Network test and estimation of Largest Lyapunov exponents (LLE’s). The first stage consisted of testing for weak-form market efficiency using VR tests, which rejected the Weak-form Efficient Market Hypothesis for all the five series. The next step was to analyze the possible presence of non-linearity, and this was carried out using BDS test, Hinich Bispectrum test, and Teräsvirta Neural Network test. All the tests confirmed the presence of non-linearity in the five series under study. The last step of the study was to analyze the structure of nonlinearity. LLE’s were estimated for all series in order to examine the possible presence of chaos. LLE’s for all the 5 series returned positive values, and thus confirmed the presence of an underlying chaotic structure for all markets.

Suggested Citation

  • 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.
    • Handle: RePEc:agr:journl:v:xxiii:y:2016:i:1(606):p:103-118
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    Cited by:

    1. 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.
    2. Goodness C. Aye & Rangan Gupta & Chi Keung Marco Lau & Xin Sheng, 2019. "Is there a role for uncertainty in forecasting output growth in OECD countries? Evidence from a time-varying parameter-panel vector autoregressive model," Applied Economics, Taylor & Francis Journals, vol. 51(33), pages 3624-3631, July.
    3. Nils Bundi & Marc Wildi, 2019. "Bitcoin and market-(in)efficiency: a systematic time series approach," Digital Finance, Springer, vol. 1(1), pages 47-65, November.
    4. 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.
    5. Marinakis, Yorgos D. & White, Reilly & Walsh, Steven T., 2020. "Lotka–Volterra signals in ASEAN currency exchange rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).

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