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Persistence Characteristics of Latin American Financial Markets

Author

Listed:
  • Sijing Zong

    (Kent State University)

  • Cornelis A. Los

    (Kent State University)

  • Nyonyo Kyaw

    (Kent State University)

Abstract

The financial rates of return from Latin American stock and currency markets are found to be non-normal, non-stationary, non-ergodic and long-term dependent, i.e., they have long memory. The degree of long- term dependence is measured by monofractal (global) Hurst exponents from wavelet multiresolution analysis (MRA). Scalograms and scalegrams provide the respective visualizations of these wavelet coefficients and the power spectrum of the rates of return. The slope of the power spectrum identifies the Hurst exponent and thereby the degree of scaling dependence that cannot be determined by Box-Jenkins type time series analysis. Our dependency and time and frequency scaling results are consistent with similar empirical findings from American, European, and Asian financial markets, extending the domain of the empirical investigation of the dynamics and risk characteristics of financial markets and refuting the hypothesis of perfectly efficient markets.

Suggested Citation

  • Sijing Zong & Cornelis A. Los & Nyonyo Kyaw, 2004. "Persistence Characteristics of Latin American Financial Markets," Finance 0411013, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpfi:0411013
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    Cited by:

    1. Los, Cornelis A. & Yu, Bing, 2008. "Persistence characteristics of the Chinese stock markets," International Review of Financial Analysis, Elsevier, vol. 17(1), pages 64-82.
    2. Fernandez, Viviana, 2007. "A postcard from the past: The behavior of U.S. stock markets during 1871–1938," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 386(1), pages 267-282.
    3. Francis In & Sangbae Kim, 2012. "An Introduction to Wavelet Theory in Finance:A Wavelet Multiscale Approach," World Scientific Books, World Scientific Publishing Co. Pte. Ltd., number 8431, August.
    4. Jamdee, Sutthisit & Los, Cornelis A., 2007. "Long memory options: LM evidence and simulations," Research in International Business and Finance, Elsevier, vol. 21(2), pages 260-280, June.
    5. Espinosa Méndez, Christian, 2005. "Evidencia De Comportamiento Caótico En Indices Bursátiles Americanos [Evidence Of Chaotic Behavior In American Stock Markets]," MPRA Paper 2794, University Library of Munich, Germany, revised 30 Jun 2006.
    6. Cerqueti, Roy & Fanelli, Viviana & Rotundo, Giulia, 2019. "Long run analysis of crude oil portfolios," Energy Economics, Elsevier, vol. 79(C), pages 183-205.
    7. Sensoy, Ahmet & Tabak, Benjamin M., 2016. "Dynamic efficiency of stock markets and exchange rates," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 353-371.
    8. Erdinc Akyildirim & Ahmet Goncu & Ahmet Sensoy, 2021. "Prediction of cryptocurrency returns using machine learning," Annals of Operations Research, Springer, vol. 297(1), pages 3-36, February.
    9. Vogl, Markus, 2023. "Hurst exponent dynamics of S&P 500 returns: Implications for market efficiency, long memory, multifractality and financial crises predictability by application of a nonlinear dynamics analysis framewo," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    10. Karuppiah, Jeyanthi & Los, Cornelis A., 2005. "Wavelet multiresolution analysis of high-frequency Asian FX rates, Summer 1997," International Review of Financial Analysis, Elsevier, vol. 14(2), pages 211-246.
    11. Chaker Aloui & Duc Khuong Nguyen, 2014. "On the detection of extreme movements and persistent behaviour in Mediterranean stock markets: a wavelet-based approach," Applied Economics, Taylor & Francis Journals, vol. 46(22), pages 2611-2622, August.
    12. Harbir Lamba & Tim Seaman, 2008. "Market Statistics Of A Psychology-Based Heterogeneous Agent Model," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 11(07), pages 717-737.
    13. Roy Cerqueti & Viviana Fanelli, 2021. "Long memory and crude oil’s price predictability," Annals of Operations Research, Springer, vol. 299(1), pages 895-906, April.

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    More about this item

    Keywords

    financial markets; long memory; Hurst exponent; scalegram; wavelets; multiresolution analysis; measurement accuracy;
    All these keywords.

    JEL classification:

    • G - Financial Economics

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