IDEAS home Printed from https://ideas.repec.org/p/bdm/wpaper/2009-17.html
   My bibliography  Save this paper

High and Low Frequency Correlations in Global Equity Markets

Author

Listed:
  • Engle Robert F.
  • Rangel José Gonzalo

Abstract

This study models high and low frequency variation in global equity correlations using a comprehensive sample of 43 countries that includes developed and emerging markets, during the period 1995-2008. These two types of variations are modeled following the semi-parametric Factor-Spline-GARCH approach of Rangel and Engle (2008). This framework is extended and modified to incorporate the effect of multiple factors and to address the issue of non-synchronicity in international markets. Our empirical analysis suggests that the slow-moving dynamics of global correlations can be described by the Factor-Spline-GARCH specifications using either weekly or daily data. The analysis shows that the low frequency component of global correlations increased in the current financial turmoil; however, this increase was not equally distributed across countries. The countries that experienced the largest increase in correlations were mainly emerging markets.

Suggested Citation

  • Engle Robert F. & Rangel José Gonzalo, 2009. "High and Low Frequency Correlations in Global Equity Markets," Working Papers 2009-17, Banco de México.
    • Handle: RePEc:bdm:wpaper:2009-17
    as

    Download full text from publisher

    File URL: https://www.banxico.org.mx/publications-and-press/banco-de-mexico-working-papers/%7B4F6CEDB3-2AED-1A68-D1FF-7ABCB9693C63%7D.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andrew Ang & Geert Bekaert, 2002. "International Asset Allocation With Regime Shifts," The Review of Financial Studies, Society for Financial Studies, vol. 15(4), pages 1137-1187.
    2. Stephen A. Ross, 2013. "The Arbitrage Theory of Capital Asset Pricing," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 1, pages 11-30, World Scientific Publishing Co. Pte. Ltd..
    3. Cavit Pakel & Neil Shephard & Kevin Sheppard & Robert F. Engle, 2021. "Fitting Vast Dimensional Time-Varying Covariance Models," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 39(3), pages 652-668, July.
    4. Dumas, Bernard & Harvey, Campbell R. & Ruiz, Pierre, 2003. "Are correlations of stock returns justified by subsequent changes in national outputs?," Journal of International Money and Finance, Elsevier, vol. 22(6), pages 777-811, November.
    5. Robert F. Engle & Jose Gonzalo Rangel, 2008. "The Spline-GARCH Model for Low-Frequency Volatility and Its Global Macroeconomic Causes," The Review of Financial Studies, Society for Financial Studies, vol. 21(3), pages 1187-1222, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José Rangel & Robert Engle, 2012. "The Factor–Spline–GARCH Model for High and Low Frequency Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 109-124.
    2. Manuel A. Hernandez & Raul Ibarra & Danilo R. Trupkin, 2014. "How far do shocks move across borders? Examining volatility transmission in major agricultural futures markets," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 41(2), pages 301-325.
    3. Clark Lundberg, 2019. "Identifying horizon-based heterogeneity in the cross section of portfolio returns," Economics Bulletin, AccessEcon, vol. 39(2), pages 1163-1175.
    4. Asako, Kazumi & Liu, Zhentao, 2013. "A statistical model of speculative bubbles, with applications to the stock markets of the United States, Japan, and China," Journal of Banking & Finance, Elsevier, vol. 37(7), pages 2639-2651.
    5. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2015. "Many a little makes a mickle: Macro portfolio stress test for small and medium-sized German banks," Discussion Papers 23/2015, Deutsche Bundesbank.
    6. Tolga Cenesizoglu & Jonathan J. Reeves, 2013. "CAPM, Components of Beta and the Cross Section of Expected Returns," CIRANO Working Papers 2013s-09, CIRANO.
    7. Contessi, Silvio & De Pace, Pierangelo & Guidolin, Massimo, 2014. "How did the financial crisis alter the correlations of U.S. yield spreads?," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 362-385.
    8. Busch, Ramona & Koziol, Philipp & Mitrovic, Marc, 2018. "Many a little makes a mickle: Stress testing small and medium-sized German banks," The Quarterly Review of Economics and Finance, Elsevier, vol. 68(C), pages 237-253.

    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. José Rangel & Robert Engle, 2012. "The Factor–Spline–GARCH Model for High and Low Frequency Correlations," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 30(1), pages 109-124.
    2. Peter Christoffersen & Vihang Errunza & Kris Jacobs & Hugues Langlois, 2012. "Is the Potential for International Diversification Disappearing? A Dynamic Copula Approach," The Review of Financial Studies, Society for Financial Studies, vol. 25(12), pages 3711-3751.
    3. Anne Opschoor & Dick van Dijk & Michel van der Wel, 2013. "Predicting Covariance Matrices with Financial Conditions Indexes," Tinbergen Institute Discussion Papers 13-113/III, Tinbergen Institute.
    4. Andersen, Torben G. & Bollerslev, Tim & Christoffersen, Peter F. & Diebold, Francis X., 2013. "Financial Risk Measurement for Financial Risk Management," Handbook of the Economics of Finance, in: G.M. Constantinides & M. Harris & R. M. Stulz (ed.), Handbook of the Economics of Finance, volume 2, chapter 0, pages 1127-1220, Elsevier.
    5. Shi, Huai-Long & Zhou, Wei-Xing, 2022. "Factor volatility spillover and its implications on factor premia," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    6. Polanski, Arnold & Stoja, Evarist, 2017. "Forecasting multidimensional tail risk at short and long horizons," International Journal of Forecasting, Elsevier, vol. 33(4), pages 958-969.
    7. Boudt, Kris & Cornilly, Dries & Verdonck, Tim, 2020. "Nearest comoment estimation with unobserved factors," Journal of Econometrics, Elsevier, vol. 217(2), pages 381-397.
    8. Arouri, Mohamed El Hedi & Nguyen, Duc Khuong & Pukthuanthong, Kuntara, 2012. "An international CAPM for partially integrated markets: Theory and empirical evidence," Journal of Banking & Finance, Elsevier, vol. 36(9), pages 2473-2493.
    9. Gianluca De Nard & Olivier Ledoit & Michael Wolf, 2018. "Factor models for portfolio selection in large dimensions: the good, the better and the ugly," ECON - Working Papers 290, Department of Economics - University of Zurich, revised Dec 2018.
    10. Christoffersen, Peter & Langlois, Hugues, 2013. "The Joint Dynamics of Equity Market Factors," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(5), pages 1371-1404, October.
    11. Mensah, Jones Odei & Premaratne, Gamini, 2014. "Dependence patterns among Banking Sectors in Asia: A Copula Approach," MPRA Paper 60119, University Library of Munich, Germany.
    12. Fernando Moraes & Rodrigo De-Losso, 2020. "Risk Factor Centrality and the Cross-Section of Expected Returns," Working Papers, Department of Economics 2020_17, University of São Paulo (FEA-USP).
    13. Barigozzi, Matteo & Brownlees, Christian & Gallo, Giampiero M. & Veredas, David, 2014. "Disentangling systematic and idiosyncratic dynamics in panels of volatility measures," Journal of Econometrics, Elsevier, vol. 182(2), pages 364-384.
    14. Hautsch, Nikolaus & Kyj, Lada M. & Malec, Peter, 2011. "The merit of high-frequency data in portfolio allocation," CFS Working Paper Series 2011/24, Center for Financial Studies (CFS).
    15. Okimoto, Tatsuyoshi, 2014. "Asymmetric increasing trends in dependence in international equity markets," Journal of Banking & Finance, Elsevier, vol. 46(C), pages 219-232.
    16. Thomas Conlon & John Cotter & Iason Kynigakis, 2021. "Machine Learning and Factor-Based Portfolio Optimization," Papers 2107.13866, arXiv.org.
    17. Lee, Eun-Joo, 2017. "Intra- and inter-regional portfolio diversification strategies under regional market integration: Evidence from U.S. global banks," International Review of Financial Analysis, Elsevier, vol. 54(C), pages 1-22.
    18. Cakici, Nusret & Zaremba, Adam, 2023. "Misery on Main Street, victory on Wall Street: Economic discomfort and the cross-section of global stock returns," Journal of Banking & Finance, Elsevier, vol. 149(C).
    19. Chen, Peng, 2018. "Understanding international stock market comovements: A comparison of developed and emerging markets," International Review of Economics & Finance, Elsevier, vol. 56(C), pages 451-464.
    20. De Nard, Gianluca & Zhao, Zhao, 2023. "Using, taming or avoiding the factor zoo? A double-shrinkage estimator for covariance matrices," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 23-35.

    More about this item

    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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bdm:wpaper:2009-17. 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: Subgerencia de desarrollo de sistemas (email available below). General contact details of provider: https://edirc.repec.org/data/bangvmx.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.