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Persistence characteristics of Latin American financial markets

  • Kyaw, NyoNyo A.
  • Los, Cornelis A.
  • Zong, Sijing

Static time series models usually assume stationarity, normality, and independence for the increments of financial rates of return. This paper investigates the empirical characteristics of financial rates of return from Latin American stock and currency markets and documents that their empirical rates of return are non-normal, non- stationary and non-ergodic, and that they exhibit long-term dependence. This paper measures the degree of long-term dependence of these financial time series by calculating their global, or homogeneous, Hurst exponents from their wavelet multiresolution analyses (MRA), i.e. from the wavelet resonance coefficients. Visualizations of these resonance coefficients and their power spectra are provided by scalograms and scalegrams, respectively. These visualizations help to identify the long-term dependence characteristics, which cannot be identified by the classical time series analysis, which is based on the stationarity and independence assumptions. Our findings are consistent with some empirical findings from financial market data in the USA, in Europe and in Asia, but extend their domain of empirical investigation.

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Article provided by Elsevier in its journal Journal of Multinational Financial Management.

Volume (Year): 16 (2006)
Issue (Month): 3 (July)
Pages: 269-290

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Handle: RePEc:eee:mulfin:v:16:y:2006:i:3:p:269-290
Contact details of provider: Web page: http://www.elsevier.com/locate/mulfin

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  1. Benoit Mandelbrot & Adlai Fisher & Laurent Calvet, 1997. "A Multifractal Model of Asset Returns," Cowles Foundation Discussion Papers 1164, Cowles Foundation for Research in Economics, Yale University.
  2. Laurent Calvet & Adlai Fisher, 2002. "Multifractality In Asset Returns: Theory And Evidence," The Review of Economics and Statistics, MIT Press, vol. 84(3), pages 381-406, August.
  3. Cheung, Yin-Wong, 1993. "Long Memory in Foreign-Exchange Rates," Journal of Business & Economic Statistics, American Statistical Association, vol. 11(1), pages 93-101, January.
  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. Mandelbrot, Benoit, 1969. "Long-Run Linearity, Locally Gaussian Process, H-Spectra and Infinite Variances," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(1), pages 82-111, February.
  6. GHYSELS, Eric & HARVEY, Andrew & RENAULT, Eric, 1995. "Stochastic Volatility," CORE Discussion Papers 1995069, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
  7. Greene, Myron T. & Fielitz, Bruce D., 1977. "Long-term dependence in common stock returns," Journal of Financial Economics, Elsevier, vol. 4(3), pages 339-349, May.
  8. Crato, Nuno & de Lima, Pedro J. F., 1994. "Long-range dependence in the conditional variance of stock returns," Economics Letters, Elsevier, vol. 45(3), pages 281-285.
  9. Cheung, Yin-Wong & Lai, Kon S., 1995. "A search for long memory in international stock market returns," Journal of International Money and Finance, Elsevier, vol. 14(4), pages 597-615, August.
  10. Sebastian Edwards, 1998. "Capital Inflows into Latin America: A Stop-Go Story?," NBER Working Papers 6441, National Bureau of Economic Research, Inc.
  11. Sadique, Shibley & Silvapulle, Param, 2001. "Long-Term Memory in Stock Market Returns: International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 6(1), pages 59-67, January.
  12. Cornelis A. Los & Jeyanthi Karuppiah, 2004. "Wavelet Multiresolution Analysis of High-Frequency Asian FX Rates, Summer 1997," Finance 0409037, EconWPA.
  13. Marco Corazza & A. G. Malliaris, 2002. "Multi-Fractality in Foreign Currency Markets," Multinational Finance Journal, Multinational Finance Journal, vol. 6(2), pages 65-98, June.
  14. Cochrane, John H, 1988. "How Big Is the Random Walk in GNP?," Journal of Political Economy, University of Chicago Press, vol. 96(5), pages 893-920, October.
  15. Cornelis A. Los, 2004. "Nonparametric Testing of the High-Frequency Efficiency of the 1997 Asian Foreign Exchange Markets," Finance 0409040, EconWPA.
  16. Bollerslev, Tim & Ole Mikkelsen, Hans, 1996. "Modeling and pricing long memory in stock market volatility," Journal of Econometrics, Elsevier, vol. 73(1), pages 151-184, July.
  17. Baillie, Richard T. & Bollerslev, Tim & Mikkelsen, Hans Ole, 1996. "Fractionally integrated generalized autoregressive conditional heteroskedasticity," Journal of Econometrics, Elsevier, vol. 74(1), pages 3-30, September.
  18. Lo, Andrew W. (Andrew Wen-Chuan), 1989. "Long-term memory in stock market prices," Working papers 3014-89., Massachusetts Institute of Technology (MIT), Sloan School of Management.
  19. Fama, Eugene F, 1970. "Efficient Capital Markets: A Review of Theory and Empirical Work," Journal of Finance, American Finance Association, vol. 25(2), pages 383-417, May.
  20. repec:att:wimass:9208 is not listed on IDEAS
  21. Baillie, Richard T., 1996. "Long memory processes and fractional integration in econometrics," Journal of Econometrics, Elsevier, vol. 73(1), pages 5-59, July.
  22. Loretan, Mico & Phillips, Peter C. B., 1994. "Testing the covariance stationarity of heavy-tailed time series: An overview of the theory with applications to several financial datasets," Journal of Empirical Finance, Elsevier, vol. 1(2), pages 211-248, January.
  23. Robert J. Elliott & John van der Hoek, 2003. "A General Fractional White Noise Theory And Applications To Finance," Mathematical Finance, Wiley Blackwell, vol. 13(2), pages 301-330.
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