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A wavelet analysis of capital markets' integration in Latin America

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  • B. Dima
  • Ş.M. Dima
  • F. Barna

Abstract

The continuous wavelet transform analysis may provide a rich and flexible framework for the analysis of time series which exhibit less stable statistical properties, such as the ones describing the dynamic trajectory of capital markets. In contrast to the Fourier analysis, wavelet transform preserves information on both time and frequency. We provide a summary of the most important features of this framework. By involving the concept of coherence as well as its partial and multiple forms, we analyse the connections between Santiago Stock Exchange, Mexican Stock Exchange and BM&FBOVESPA São Paulo Stock Exchange, for a time span which covers the 23 September 2003-12 March 2014 period. We highlight the existence of several significant forces of regional integration and of a short- to medium-run synchronization process between these markets. We conclude that deeper structural and institutional reforms are required in order to enhance the sustainable development and more profound integration of these markets.

Suggested Citation

  • B. Dima & Ş.M. Dima & F. Barna, 2015. "A wavelet analysis of capital markets' integration in Latin America," Applied Economics, Taylor & Francis Journals, vol. 47(10), pages 1019-1036, February.
    • Handle: RePEc:taf:applec:v:47:y:2015:i:10:p:1019-1036
    DOI: 10.1080/00036846.2014.987917
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    References listed on IDEAS

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    1. International Monetary Fund, 2012. "Brazil: Financial System Stability Assessment," IMF Staff Country Reports 2012/206, International Monetary Fund.
    2. International Monetary Fund, 2012. "Mexico: Financial System Stability Assessment," IMF Staff Country Reports 2012/065, International Monetary Fund.
    3. International Monetary Fund, 2011. "Chile: Financial System Stability Assessment," IMF Staff Country Reports 2011/261, International Monetary Fund.
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    Cited by:

    1. Kim Hiang Liow & Xiaoxia Zhou & Qiang Li & Yuting Huang, 2019. "Time–Scale Relationship between Securitized Real Estate and Local Stock Markets: Some Wavelet Evidence," JRFM, MDPI, vol. 12(1), pages 1-23, January.
    2. Shekhar Mishra & Avik Sinha & Arshian Sharif & Norazah Mohd Suki, 2020. "Dynamic linkages between tourism, transportation, growth and carbon emission in the USA: evidence from partial and multiple wavelet coherence," Current Issues in Tourism, Taylor & Francis Journals, vol. 23(21), pages 2733-2755, November.
    3. Funashima, Yoshito, 2017. "Time-varying leads and lags across frequencies using a continuous wavelet transform approach," Economic Modelling, Elsevier, vol. 60(C), pages 24-28.
    4. Xing, Jieli & Zhang, Yongjie & Chu, Gang & Pan, Qi & Zhang, Xiaotao, 2021. "Detection and reconstruction of catastrophic breaks of high-frequency financial data with local linear scaling approximation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 561(C).
    5. M. Kannadhasan & Debojyoti Das, 2019. "Has Co-Movement Dynamics in Brazil, Russia, India, China and South Africa (BRICS) Markets Changed After Global Financial Crisis? New Evidence from Wavelet Analysis," Asian Academy of Management Journal of Accounting and Finance (AAMJAF), Penerbit Universiti Sains Malaysia, vol. 15(1), pages 1-26.
    6. Bhattacherjee, Purba & Mishra, Sibanjan & Kang, Sang Hoon, 2023. "Does market sentiment and global uncertainties influence ESG-oil nexus? A time-frequency analysis," Resources Policy, Elsevier, vol. 86(PA).

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