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Long-term memories of developed and emerging markets: Using the scaling analysis to characterize their stage of development

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  • Matteo, T. Di
  • Aste, T.
  • Dacorogna, Michel M.

Abstract

The scaling properties encompass in a simple analysis many of the volatility characteristics of financial markets. That is why we use them to probe the different degree of markets development. We empirically study the scaling properties of daily Foreign Exchange rates, Stock Market indices and fixed income instruments by using the generalized Hurst approach. We show that the scaling exponents are associated with characteristics of the specific markets and can be used to differentiate markets in their stage of development. The robustness of the results is tested by both Monte-Carlo studies and a computation of the scaling in the frequency-domain.

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Bibliographic Info

Article provided by Elsevier in its journal Journal of Banking & Finance.

Volume (Year): 29 (2005)
Issue (Month): 4 (April)
Pages: 827-851
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Handle: RePEc:eee:jbfina:v:29:y:2005:i:4:p:827-851

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For corrections or technical questions regarding this item, or to correct its listing, contact: (Jeroen Loos).

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Citations

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Cited by:
  1. Cornelis A. Los & Bing Yu, 2005. "Persistence Characteristics of the Chinese Stock Markets," Finance 0508008, EconWPA.
  2. Cajueiro, Daniel O. & Tabak, Benjamin M., 2010. "Fluctuation dynamics in US interest rates and the role of monetary policy," Finance Research Letters, Elsevier, vol. 7(3), pages 163-169, September.
  3. Ladislav Kristoufek, 2012. "Fractal Markets Hypothesis and the Global Financial Crisis: Scaling, Investment Horizons and Liquidity," Quantitative Finance Papers 1203.4979, arXiv.org.
  4. Espinosa Méndez, Christian, 2007. "Efecto Fin De Semana Y Fin De Mes En El Mercado Bursatil Chileno
    [Effect Weekend And Effect Month End In The Chilean Stock Market]    ," MPRA Paper 3252, University Library of Munich, Germany.
  5. Raffaello Morales & T. Di Matteo & Ruggero Gramatica & Tomaso Aste, 2011. "Dynamical Hurst exponent as a tool to monitor unstable periods in financial time series," Quantitative Finance Papers 1109.0465, arXiv.org.
  6. Jozef Barunik & Ladislav Kristoufek, 2012. "On Hurst exponent estimation under heavy-tailed distributions," Quantitative Finance Papers 1201.4786, arXiv.org.
  7. Kristoufek, Ladislav, 2009. "Distinguishing between short and long range dependence: Finite sample properties of rescaled range and modified rescaled range," MPRA Paper 16424, University Library of Munich, Germany.
  8. Kristoufek, Ladislav, 2009. "R/S analysis and DFA: finite sample properties and confidence intervals," MPRA Paper 16446, University Library of Munich, Germany.
  9. Jérôme Coulon & Yannick Malevergne, 2010. "Heterogeneous expectations and long range correlation of the volatility of asset returns," Working Papers halshs-00541953, HAL.
  10. Ladislav Krištoufek, 2010. "Rescaled Range Analysis and Detrended Fluctuation Analysis: Finite Sample Properties and Confidence Intervals," Czech Economic Review, Charles University Prague, Faculty of Social Sciences, Institute of Economic Studies, vol. 4(3), pages 315-329, November.
  11. Jozef Barunik & Tomaso Aste & Tiziana Di Matteo & Ruipeng Liu, 2012. "Understanding the source of multifractality in financial markets," Quantitative Finance Papers 1201.1535, arXiv.org, revised Jan 2012.

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