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The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis

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  • Das, Sonali
  • Demirer, Riza
  • Gupta, Rangan
  • Mangisa, Siphumlile

Abstract

This paper presents a novel, mixed-frequency based regression approach, derived from functional data analysis (FDA), to analyze the effect of global crises on stock market correlations, using a long span of data, dating as far back as early 1800s, thus covering a wide range of global crises that have not yet been examined in the literature in this context. Focusing on the advanced nations in the G7 group, we observe heterogeneous effects of global crises on the convergence patterns across developed stock markets. While the post World War II period experienced a general rise in the level of correlations among developed stock market returns, we find that global crises in general have led to a stronger association of stock market returns in the US, UK and Canada, whereas the opposite holds when it comes to how European and Japanese stock markets co-move with the US. Overall, our results suggest that crises that are global in nature generally contribute to the convergence of global stock markets, while the effect largely depends on the context and nature of the crises that possibly drive the perception of risk and/or contagion in financial markets. From an investment perspective, our findings suggest that, in the wake of global crises, diversification benefits will be limited by moving funds across the US and UK stock markets whereas possible diversification benefits would have been possible during the crises-ridden period of the early twentieth century by holding positions in equities in the remaining G7 nations to supplement positions in the US. However, these diversification benefits seem to have frittered away in the post World War II period, highlighting the role of emerging markets and alternative assets to improve diversification benefits in the modern era.

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  • Das, Sonali & Demirer, Riza & Gupta, Rangan & Mangisa, Siphumlile, 2019. "The effect of global crises on stock market correlations: Evidence from scalar regressions via functional data analysis," Structural Change and Economic Dynamics, Elsevier, vol. 50(C), pages 132-147.
  • Handle: RePEc:eee:streco:v:50:y:2019:i:c:p:132-147
    DOI: 10.1016/j.strueco.2019.05.007
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    as
    1. Claudia Foroni & Massimiliano Marcellino, 2013. "A survey of econometric methods for mixed-frequency data," Working Paper 2013/06, Norges Bank.
    2. Fang, Libing & Bouri, Elie & Gupta, Rangan & Roubaud, David, 2019. "Does global economic uncertainty matter for the volatility and hedging effectiveness of Bitcoin?," International Review of Financial Analysis, Elsevier, vol. 61(C), pages 29-36.
    3. Kizys, Renatas & Pierdzioch, Christian, 2006. "Business-cycle fluctuations and international equity correlations," Global Finance Journal, Elsevier, vol. 17(2), pages 252-270, December.
    4. John Y. Campbell & Martin Lettau & Burton G. Malkiel & Yexiao Xu, 2001. "Have Individual Stocks Become More Volatile? An Empirical Exploration of Idiosyncratic Risk," Journal of Finance, American Finance Association, vol. 56(1), pages 1-43, February.
    5. Balcilar, Mehmet & Katzke, Nico & Gupta, Rangan, 2017. "Do precious metal prices help in forecasting South African inflation?," The North American Journal of Economics and Finance, Elsevier, vol. 40(C), pages 63-72.
    6. Rey, Hélène, 2015. "Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence," CEPR Discussion Papers 10591, C.E.P.R. Discussion Papers.
    7. Rıza Demirer & Shrikant P. Jategaonkar, 2013. "The conditional relation between dispersion and return," Review of Financial Economics, John Wiley & Sons, vol. 22(3), pages 125-134, September.
    8. Ľuboš Pástor & Pietro Veronesi, 2020. "Political Cycles and Stock Returns," Journal of Political Economy, University of Chicago Press, vol. 128(11), pages 4011-4045.
    9. Gregory R. Duffee, 2001. "Asymmetric cross-sectional dispersion in stock returns: evidence and implications," Working Paper Series 2000-18, Federal Reserve Bank of San Francisco.
    10. Foroni, Claudia & Guérin, Pierre & Marcellino, Massimiliano, 2018. "Using low frequency information for predicting high frequency variables," International Journal of Forecasting, Elsevier, vol. 34(4), pages 774-787.
    11. Adams, Zeno & Füss, Roland & Glück, Thorsten, 2017. "Are correlations constant? Empirical and theoretical results on popular correlation models in finance," Journal of Banking & Finance, Elsevier, vol. 84(C), pages 9-24.
    12. Carmen M. Reinhart & Kenneth S. Rogoff, 2014. "This Time is Different: A Panoramic View of Eight Centuries of Financial Crises," Annals of Economics and Finance, Society for AEF, vol. 15(2), pages 215-268, November.
    13. Goodness C. Aye & Mehmet Balcilar & Rangan Gupta, 2017. "International stock return predictability: Is the role of U.S. time-varying?," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 44(1), pages 121-146, February.
    14. Muteba Mwamba, John W. & Hammoudeh, Shawkat & Gupta, Rangan, 2017. "Financial tail risks in conventional and Islamic stock markets: A comparative analysis," Pacific-Basin Finance Journal, Elsevier, vol. 42(C), pages 60-82.
    15. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2005. "There is a risk-return trade-off after all," Journal of Financial Economics, Elsevier, vol. 76(3), pages 509-548, June.
    16. Geert Bekaert & Eric C. Engstrom & Nancy R. Xu, 2022. "The Time Variation in Risk Appetite and Uncertainty," Management Science, INFORMS, vol. 68(6), pages 3975-4004, June.
    17. Stivers, Christopher T., 2003. "Firm-level return dispersion and the future volatility of aggregate stock market returns," Journal of Financial Markets, Elsevier, vol. 6(3), pages 389-411, May.
    18. Yonghong Jiang & Mengmeng Yu & Shabir Mohsin Hashmi, 2017. "The Financial Crisis and Co-Movement of Global Stock Markets—A Case of Six Major Economies," Sustainability, MDPI, vol. 9(2), pages 1-18, February.
    19. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity, and (Non-) Asymptotic Properties of the Dynamic Conditional Correlation (DCC) Model," JRFM, MDPI, vol. 12(2), pages 1-9, April.
    20. Carmen M. Reinhart & Kenneth S. Rogoff, 2009. "Varieties of Crises and Their Dates," Introductory Chapters, in: This Time Is Different: Eight Centuries of Financial Folly, Princeton University Press.
    21. 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.
    22. Longin, Francois & Solnik, Bruno, 1995. "Is the correlation in international equity returns constant: 1960-1990?," Journal of International Money and Finance, Elsevier, vol. 14(1), pages 3-26, February.
    23. Lieven Baele & Pilar Soriano, 2010. "The determinants of increasing equity market comovement: economic or financial integration?," Review of World Economics (Weltwirtschaftliches Archiv), Springer;Institut für Weltwirtschaft (Kiel Institute for the World Economy), vol. 146(3), pages 573-589, September.
    24. Bouri, Elie & Gupta, Rangan & Wong, Wing-Keung & Zhu, Zhenzhen, 2018. "Is wine a good choice for investment?," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 171-183.
    25. Bekaert, Geert & Wu, Guojun, 2000. "Asymmetric Volatility and Risk in Equity Markets," The Review of Financial Studies, Society for Financial Studies, vol. 13(1), pages 1-42.
    26. Michael McAleer, 2019. "What They Did Not Tell You about Algebraic (Non-) Existence, Mathematical (IR-)Regularity and (Non-) Asymptotic Properties of the Full BEKK Dynamic Conditional Covariance Model," JRFM, MDPI, vol. 12(2), pages 1-7, April.
    27. Loungani, Prakash & Rush, Mark & Tave, William, 1990. "Stock market dispersion and unemployment," Journal of Monetary Economics, Elsevier, vol. 25(3), pages 367-388, June.
    28. Kizys, Renatas & Pierdzioch, Christian, 2009. "Changes in the international comovement of stock returns and asymmetric macroeconomic shocks," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(2), pages 289-305, April.
    29. Ramsay, James O. & Ramsey, James B., 2002. "Functional data analysis of the dynamics of the monthly index of nondurable goods production," Journal of Econometrics, Elsevier, vol. 107(1-2), pages 327-344, March.
    30. Han Shang, 2014. "A survey of functional principal component analysis," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 98(2), pages 121-142, April.
    31. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2006. "Predicting volatility: getting the most out of return data sampled at different frequencies," Journal of Econometrics, Elsevier, vol. 131(1-2), pages 59-95.
    32. Suits, Daniel B & Mason, Andrew & Chan, Louis, 1978. "Spline Functions Fitted by Standard Regression Methods," The Review of Economics and Statistics, MIT Press, vol. 60(1), pages 132-139, February.
    33. Roman Horvath & Petr Poldauf, 2012. "International Stock Market Comovements: What Happened during the Financial Crisis?," Global Economy Journal (GEJ), World Scientific Publishing Co. Pte. Ltd., vol. 12(1), pages 1-21, March.
    34. Clements, Michael P & Galvão, Ana Beatriz, 2008. "Macroeconomic Forecasting With Mixed-Frequency Data," Journal of Business & Economic Statistics, American Statistical Association, vol. 26, pages 546-554.
    35. Yarovaya, Larisa & Lau, Marco Chi Keung, 2016. "Stock market comovements around the Global Financial Crisis: Evidence from the UK, BRICS and MIST markets," Research in International Business and Finance, Elsevier, vol. 37(C), pages 605-619.
    36. Eric Ghysels & Arthur Sinko & Rossen Valkanov, 2007. "MIDAS Regressions: Further Results and New Directions," Econometric Reviews, Taylor & Francis Journals, vol. 26(1), pages 53-90.
    37. Kristin J. Forbes & Roberto Rigobon, 2002. "No Contagion, Only Interdependence: Measuring Stock Market Comovements," Journal of Finance, American Finance Association, vol. 57(5), pages 2223-2261, October.
    38. François Longin & Bruno Solnik, 2001. "Extreme Correlation of International Equity Markets," Journal of Finance, American Finance Association, vol. 56(2), pages 649-676, April.
    39. Hwang, Eugene & Min, Hong-Ghi & Kim, Bong-Han & Kim, Hyeongwoo, 2013. "Determinants of stock market comovements among US and emerging economies during the US financial crisis," Economic Modelling, Elsevier, vol. 35(C), pages 338-348.
    40. Balcilar, Mehmet & Ozdemir, Zeynel Abidin & Arslanturk, Yalcin, 2010. "Economic growth and energy consumption causal nexus viewed through a bootstrap rolling window," Energy Economics, Elsevier, vol. 32(6), pages 1398-1410, November.
    41. Adnen Ben Nasr & Matteo Bonato & Riza Demirer & Rangan Gupta, 2019. "Investor Sentiment and Crash Risk in Safe Havens," Journal of Economics and Behavioral Studies, AMH International, vol. 10(6), pages 97-108.
    42. Colacito, Riccardo & Engle, Robert F. & Ghysels, Eric, 2011. "A component model for dynamic correlations," Journal of Econometrics, Elsevier, vol. 164(1), pages 45-59, September.
    43. Ang, Andrew & Chen, Joseph, 2002. "Asymmetric correlations of equity portfolios," Journal of Financial Economics, Elsevier, vol. 63(3), pages 443-494, March.
    44. Ghysels, Eric & Santa-Clara, Pedro & Valkanov, Rossen, 2004. "The MIDAS Touch: Mixed Data Sampling Regression Models," University of California at Los Angeles, Anderson Graduate School of Management qt9mf223rs, Anderson Graduate School of Management, UCLA.
    45. David E. Rapach & Jack K. Strauss & Guofu Zhou, 2013. "International Stock Return Predictability: What Is the Role of the United States?," Journal of Finance, American Finance Association, vol. 68(4), pages 1633-1662, August.
    46. Rey, Hélène & Miranda-Agrippino, Silvia, 2015. "World Asset Markets and the Global Financial Cycle," CEPR Discussion Papers 10936, C.E.P.R. Discussion Papers.
    47. Kofman, Paul & Koedijk, Kees & Campbell, Rachel, 2002. "Increased Correlation in Bear markets: A Downside Risk Perspective," CEPR Discussion Papers 3172, C.E.P.R. Discussion Papers.
    48. Demirer, Riza & Omay, Tolga & Yuksel, Asli & Yuksel, Aydin, 2018. "Global risk aversion and emerging market return comovements," Economics Letters, Elsevier, vol. 173(C), pages 118-121.
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    More about this item

    Keywords

    Functional data analysis; Global crises; Stock markets; Correlation;
    All these keywords.

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • G01 - Financial Economics - - General - - - Financial Crises
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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