IDEAS home Printed from https://ideas.repec.org/a/lde/journl/y2020i92p67-100.html

Market dynamics and integration of the financial markets of the NAFTA countries

Author

Listed:
  • Javier Emmanuel Anguiano Pita

    (Universidad de Guadalajara)

  • Antonio Ruiz Porras

    (Universidad de Guadalajara)

Abstract

The aim of this paper is to study the dynamics of the integration process of the bond, interbank, currency and stock markets of the NAFTA region. For this purpose, we use the generalized dynamic factor model originally proposed by Forni, Hallin, Lippi and Reichlin (2005) and representative series of monthly returns of the analyzed markets for the period from January 1995 to December 2017. The main results suggest that: 1) There are asymmetries in the size of the markets; 2) there is evidence of structural breaks; 3) common factors exist among the financial markets; 4) the markets have differentiated levels of integration; and 5) the currency and stock markets are the most sensitive to the common components. These findings may be useful to analyze the evolution of NAFTA and to propose economic and financial regional policies

Suggested Citation

  • Javier Emmanuel Anguiano Pita & Antonio Ruiz Porras, 2020. "Market dynamics and integration of the financial markets of the NAFTA countries," Lecturas de Economía, Universidad de Antioquia, Departamento de Economía, issue 92, pages 67-100, Enero-Jun.
    • Handle: RePEc:lde:journl:y:2020:i:92:p:67-100
    DOI: 10.17533/udea.le.n92a03
    as

    Download full text from publisher

    File URL: http://aprendeenlinea.udea.edu.co/revistas/index.php/lecturasdeeconomia/article/view/331442
    Download Restriction: no
    File URL: https://libkey.io/10.17533/udea.le.n92a03?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Boysen-Hogrefe, Jens, 2013. "A dynamic factor model with time-varying loadings for euro area bond markets during the debt crisis," Economics Letters, Elsevier, vol. 118(1), pages 50-54.
    2. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 2005. "The Generalized Dynamic Factor Model: One-Sided Estimation and Forecasting," Journal of the American Statistical Association, American Statistical Association, vol. 100, pages 830-840, September.
    3. Mr. Luc Eyraud & Ms. Diva Singh & Mr. Bennett W Sutton, 2017. "Benefits of Global and Regional Financial Integration in Latin America," IMF Working Papers 2017/001, International Monetary Fund.
    4. Chambet, Anthony & Gibson, Rajna, 2008. "Financial integration, economic instability and trade structure in emerging markets," Journal of International Money and Finance, Elsevier, vol. 27(4), pages 654-675, June.
    5. Mario Forni & Marc Hallin & Marco Lippi & Lucrezia Reichlin, 2000. "The Generalized Dynamic-Factor Model: Identification And Estimation," The Review of Economics and Statistics, MIT Press, vol. 82(4), pages 540-554, November.
    6. Lieven Baele, 2010. "The Determinants of Stock and Bond Return Comovements," The Review of Financial Studies, Society for Financial Studies, vol. 23(6), pages 2374-2428, June.
    7. Tibor F. Liska, 2007. "The Liska model," Society and Economy, Akadémiai Kiadó, Hungary, vol. 29(3), pages 363-381, December.
    8. Sosa, Miriam & Ortiz, Edgar, 2017. "Global Financial Crisis Volatility Impact and Contagion Effect on NAFTA Equity Markets / Impacto de la volatilidad y efecto de contagio de la crisis global financiera en los mercados bursátiles del TLCAN," Estocástica: finanzas y riesgo, Departamento de Administración de la Universidad Autónoma Metropolitana Unidad Azcapotzalco, vol. 7(1), pages 67-88, enero-jun.
    9. Lahrech, Abdelmounaim & Sylwester, Kevin, 2013. "The impact of NAFTA on North American stock market linkages," The North American Journal of Economics and Finance, Elsevier, vol. 25(C), pages 94-108.
    10. Aggarwal, Raj & Kyaw, NyoNyo A., 2005. "Equity market integration in the NAFTA region: Evidence from unit root and cointegration tests," International Review of Financial Analysis, Elsevier, vol. 14(4), pages 393-406.
    11. Ryan Greenaway‐McGrevy & Nelson C. Mark & Donggyu Sul & Jyh‐Lin Wu, 2018. "Identifying Exchange Rate Common Factors," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 59(4), pages 2193-2218, November.
    12. Alessi, Lucia & Barigozzi, Matteo & Capasso, Marco, 2010. "Improved penalization for determining the number of factors in approximate factor models," Statistics & Probability Letters, Elsevier, vol. 80(23-24), pages 1806-1813, December.
    13. Hallin, Marc & Liska, Roman, 2007. "Determining the Number of Factors in the General Dynamic Factor Model," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 603-617, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Poncela, Pilar & Ruiz, Esther & Miranda, Karen, 2021. "Factor extraction using Kalman filter and smoothing: This is not just another survey," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1399-1425.
    2. Aramonte, Sirio & Giudice Rodriguez, Marius del & Wu, Jason, 2013. "Dynamic factor Value-at-Risk for large heteroskedastic portfolios," Journal of Banking & Finance, Elsevier, vol. 37(11), pages 4299-4309.
    3. Pilar Poncela & Esther Ruiz, 2016. "Small- Versus Big-Data Factor Extraction in Dynamic Factor Models: An Empirical Assessment," Advances in Econometrics, in: Dynamic Factor Models, volume 35, pages 401-434, Emerald Group Publishing Limited.
    4. Matteo Luciani & David Veredas, 2012. "A model for vast panels of volatilities," Working Papers 1230, Banco de España.
    5. Matteo Luciani & David Veredas, "undated". "A simple model for vast panels of volatilities," ULB Institutional Repository 2013/136239, ULB -- Universite Libre de Bruxelles.
    6. Xisong Jin, 2018. "How much does book value data tell us about systemic risk and its interactions with the macroeconomy? A Luxembourg empirical evaluation," BCL working papers 118, Central Bank of Luxembourg.
    7. Kabundi, Alain & De Simone, Francisco Nadal, 2020. "Monetary policy and systemic risk-taking in the euro area banking sector," Economic Modelling, Elsevier, vol. 91(C), pages 736-758.
    8. Trucíos, Carlos & Mazzeu, João H.G. & Hotta, Luiz K. & Valls Pereira, Pedro L. & Hallin, Marc, 2021. "Robustness and the general dynamic factor model with infinite-dimensional space: Identification, estimation, and forecasting," International Journal of Forecasting, Elsevier, vol. 37(4), pages 1520-1534.
    9. Tommaso Proietti, 2008. "Estimation of Common Factors Under Cross-Sectional and Temporal Aggregation Constraints: Nowcasting Monthly GDP and Its Main Components," Springer Books, in: Paula Brito (ed.), Compstat 2008, pages 547-558, Springer.
    10. Mario Forni & Alessandro Giovannelli & Marco Lippi & Stefano Soccorsi, 2018. "Dynamic factor model with infinite‐dimensional factor space: Forecasting," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 33(5), pages 625-642, August.
    11. Richard D. F. Harris & Anh T. H. Nguyen, 2017. "Dynamic factor long memory volatility," Quantitative Finance, Taylor & Francis Journals, vol. 17(8), pages 1205-1221, August.
    12. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2016. "Non-Stationary Dynamic Factor Models for Large Datasets," Finance and Economics Discussion Series 2016-024, Board of Governors of the Federal Reserve System (U.S.).
    13. Xia, Qiang & Liang, Rubing & Wu, Jianhong, 2017. "Transformed contribution ratio test for the number of factors in static approximate factor models," Computational Statistics & Data Analysis, Elsevier, vol. 112(C), pages 235-241.
    14. Mario Forni & Marc Hallin & Marco Lippi & Paolo Zaffaroni, 2011. "One-Sided Representations of Generalized Dynamic Factor Models," Working Papers ECARES ECARES 2011-019, ULB -- Universite Libre de Bruxelles.
    15. Forni, Mario & Di Bonaventura, Luca & Pattarin, Francesco, 2018. "The Forcasting Performance of Dynamic Factor Models with Vintage Data," CEPR Discussion Papers 13034, C.E.P.R. Discussion Papers.
    16. Bai, Jushan & Liao, Yuan, 2016. "Efficient estimation of approximate factor models via penalized maximum likelihood," Journal of Econometrics, Elsevier, vol. 191(1), pages 1-18.
    17. Forni, Mario & Hallin, Marc & Lippi, Marco & Zaffaroni, Paolo, 2017. "Dynamic factor models with infinite-dimensional factor space: Asymptotic analysis," Journal of Econometrics, Elsevier, vol. 199(1), pages 74-92.
    18. Luca Gambetti, 2010. "Fiscal Policy, Foresight and the Trade Balance in the U.S," UFAE and IAE Working Papers 852.10, Unitat de Fonaments de l'Anàlisi Econòmica (UAB) and Institut d'Anàlisi Econòmica (CSIC).
    19. Carlos Cesar Trucios-Maza & João H. G Mazzeu & Luis K. Hotta & Pedro L. Valls Pereira & Marc Hallin, 2019. "On the robustness of the general dynamic factor model with infinite-dimensional space: identification, estimation, and forecasting," Working Papers ECARES 2019-32, ULB -- Universite Libre de Bruxelles.
    20. Barigozzi, Matteo & Hallin, Marc, 2017. "Generalized dynamic factor models and volatilities: estimation and forecasting," Journal of Econometrics, Elsevier, vol. 201(2), pages 307-321.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • C58 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Financial Econometrics
    • F36 - International Economics - - International Finance - - - Financial Aspects of Economic Integration
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:lde:journl:y:2020:i:92:p:67-100. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Carlos Andrés Vasco Correa (email available below). General contact details of provider: https://edirc.repec.org/data/deantco.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.