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Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach

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  • Rubén Albeiro Loaiza Maya
  • Luis Fernando Melo Velandia

Abstract

This study implements a regular vine copula methodology to evaluate the level of contagion among the exchange rates of six Latin American countries (Argentina, Brazil, Chile, Colombia, Mexico and Peru) from June 2005 to April 2012. We measure contagion in terms of tail dependence coefficients, following Fratzscher´s [1999] definition of contagion as interdependence.Our results indicate that these countries are divided into two blocs. The first bloc consists of Brazil, Colombia, Chile and Mexico, whose exchange rates exhibit the largest dependence coefficients, and the second bloc consists of Argentina and Peru, whose exchange rate dependence coefficients with other Latin American countries are low. We also found that most of the Latin American exchange rate pairs exhibit asymmetric behaviors characterized by non-significant upper tail dependence and significant lower tail dependence. These results imply that there exists contagion in Latin American exchange rates in periods of large appreciations

Suggested Citation

  • Rubén Albeiro Loaiza Maya & Luis Fernando Melo Velandia, 2012. "Latin American Exchange Rate Dependencies: A Regular Vine Copula Approach," Borradores de Economia 9902, Banco de la Republica.
  • Handle: RePEc:col:000094:009902
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    Cited by:

    1. Luis V. Bejarano-Bejarano & Jose E. Gomez-Gonzalez & Luis F. Melo-Velandia & Jhon E. Torres-Gorron, 2015. "Financial Contagion in Latin America," Borradores de Economia 884, Banco de la Republica de Colombia.
    2. Loaiza-Maya, Rubén Albeiro & Gómez-González, José Eduardo & Melo-Velandia, Luis Fernando, 2015. "Exchange rate contagion in Latin America," Research in International Business and Finance, Elsevier, vol. 34(C), pages 355-367.
    3. Juan J. Echavarría & Luis F. Melo-Velandia & Mauricio Villamizar-Villegas, 2018. "The impact of pre-announced day-to-day interventions on the Colombian exchange rate," Empirical Economics, Springer, vol. 55(3), pages 1319-1336, November.
    4. Mauricio Villamizar-Villegas, 2016. "Identifying The Effects Of Simultaneous Monetary Policy Shocks," Contemporary Economic Policy, Western Economic Association International, vol. 34(2), pages 268-296, April.
    5. Çekin, Semih Emre & Pradhan, Ashis Kumar & Tiwari, Aviral Kumar & Gupta, Rangan, 2020. "Measuring co-dependencies of economic policy uncertainty in Latin American countries using vine copulas," The Quarterly Review of Economics and Finance, Elsevier, vol. 76(C), pages 207-217.
    6. Muhammad Mar’i & Turgut Tursoy, 2021. "Exchange Rate Dependency Between Emerging Countries-Case of Black Sea Countries," Capital Markets Review, Malaysian Finance Association, vol. 29(2), pages 43-54.
    7. Gong, Yuting & Ma, Chao & Chen, Qiang, 2022. "Exchange rate dependence and economic fundamentals: A Copula-MIDAS approach," Journal of International Money and Finance, Elsevier, vol. 123(C).
    8. Gomez-Gonzalez, Jose E. & Rojas-Espinosa, Wilmer, 2019. "Detecting contagion in Asian exchange rate markets using asymmetric DCC-GARCH and R-vine copulas," Economic Systems, Elsevier, vol. 43(3).
    9. Himchan Jeong & Dipak Dey, 2020. "Application of a Vine Copula for Multi-Line Insurance Reserving," Risks, MDPI, vol. 8(4), pages 1-23, October.
    10. Kunlapath Sukcharoen & David Leatham, 2018. "Analyzing Extreme Comovements in Agricultural and Energy Commodity Markets Using a Regular Vine Copula Method," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 193-201.
    11. Sandoval Paucar, Giovanny, 2018. "Efectos de desbordamiento sobre los mercados financieros de Colombia. Identificación a través de la heterocedasticidad [Spillovers effects on financial markets of Colombia. Identification through h," MPRA Paper 90422, University Library of Munich, Germany.
    12. Das, Suman & Roy, Saikat Sinha, 2023. "Following the leaders? A study of co-movement and volatility spillover in BRICS currencies," Economic Systems, Elsevier, vol. 47(2).
    13. Cubillos-Rocha, Juan S. & Gomez-Gonzalez, Jose E. & Melo-Velandia, Luis F., 2019. "Detecting exchange rate contagion using copula functions," The North American Journal of Economics and Finance, Elsevier, vol. 47(C), pages 13-22.
    14. Gomez-Gonzalez, Jose & Rojas-Espinosa, Wilmer, 2018. "Detecting exchange rate contagion in Asian exchange rate markets using asymmetric DDC-GARCH and R-vine copulas," MPRA Paper 88578, University Library of Munich, Germany.
    15. Huang, Wanling & Mollick, André Varella & Nguyen, Khoa Huu, 2016. "U.S. stock markets and the role of real interest rates," The Quarterly Review of Economics and Finance, Elsevier, vol. 59(C), pages 231-242.
    16. Kjersti Aas, 2016. "Pair-Copula Constructions for Financial Applications: A Review," Econometrics, MDPI, vol. 4(4), pages 1-15, October.
    17. Cyprian Omari & Peter Mwita & Anthony Waititu, 2019. "Conditional Dependence Modelling with Regular Vine Copulas," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 8(1), pages 1-5.
    18. Peng, Wei & Hu, Shichao & Chen, Wang & Zeng, Yu-feng & Yang, Lu, 2019. "Modeling the joint dynamic value at risk of the volatility index, oil price, and exchange rate," International Review of Economics & Finance, Elsevier, vol. 59(C), pages 137-149.

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    More about this item

    Keywords

    Copula; Regular Vine; Exchange Rates; Tail Dependence Coefficients.;
    All these keywords.

    JEL classification:

    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • E42 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Monetary Sytsems; Standards; Regimes; Government and the Monetary System

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