Research article

On macroeconomic determinants of co-movements among international stock markets: evidence from DCC-MIDAS approach

  • Received: 07 October 2020 Accepted: 05 January 2021 Published: 08 January 2021
  • JEL Codes: C33, C58, E44, G15

  • This study aims to examine the macro-financial dynamics of the time-varying co-movements between the daily stock market returns of G7 and BRICS-T countries using a two-step procedure. Firstly, we decompose the dynamic conditional correlations between the daily stock market returns into the short-term (daily) and the long-term (quarterly) components using the DCC-MIDAS (Dynamic Conditional Correlation-Mixed Data Sampling) method for the period from 2002 to 2018. Then, we estimate the relationship between the quarterly DCC-MIDAS correlations and quarterly macroeconomic variables that represent the economic-financial proximity between country pairs using the System GMM (Generalized Method of Moments) method. Empirical results suggest that the most important factors which explain the long-term dynamic conditional correlations between the stock market returns of G7 and BRICS-T countries are the differences in GDP growth rates, five-year CDS risk premiums, and EPU (Economy Policy Uncertainty) indices between the country pairs.

    Citation: Arifenur Güngör, Hüseyin Taştan. On macroeconomic determinants of co-movements among international stock markets: evidence from DCC-MIDAS approach[J]. Quantitative Finance and Economics, 2021, 5(1): 19-39. doi: 10.3934/QFE.2021002

    Related Papers:

  • This study aims to examine the macro-financial dynamics of the time-varying co-movements between the daily stock market returns of G7 and BRICS-T countries using a two-step procedure. Firstly, we decompose the dynamic conditional correlations between the daily stock market returns into the short-term (daily) and the long-term (quarterly) components using the DCC-MIDAS (Dynamic Conditional Correlation-Mixed Data Sampling) method for the period from 2002 to 2018. Then, we estimate the relationship between the quarterly DCC-MIDAS correlations and quarterly macroeconomic variables that represent the economic-financial proximity between country pairs using the System GMM (Generalized Method of Moments) method. Empirical results suggest that the most important factors which explain the long-term dynamic conditional correlations between the stock market returns of G7 and BRICS-T countries are the differences in GDP growth rates, five-year CDS risk premiums, and EPU (Economy Policy Uncertainty) indices between the country pairs.



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    [1] Alotaibi A, Mishra A (2015) Global and regional volatility spillovers to GCC stock markets. Econ Modell 45: 38–49. doi: 10.1016/j.econmod.2014.10.052
    [2] Arellano M, Bover O (1995) Another look at the instrumental variable estimation of error-components models. J Econometrics 68: 29–51. doi: 10.1016/0304-4076(94)01642-D
    [3] Arouri M, Bellalah M, Nguyen D (2010) The comovements in international stock markets: new evidence from Latin American emerging countries. Appl Econ Lett 17: 1323–1328. doi: 10.1080/13504850902967449
    [4] Asgharian H, Hess W, Liu L (2013) A spatial analysis of international stock market linkages. J Bank Financ 37: 4738–4754. doi: 10.1016/j.jbankfin.2013.08.015
    [5] Beine M, Candelon B (2011) Liberalisation and stock market co-movement between Emerging Economies. Quant Financ 11: 299–312. doi: 10.1080/14697680903213815
    [6] Blundell R, Bond S (1998) Initial conditions and moment restrictions in dynamic panel data models. J Econometrics 87: 115–143. doi: 10.1016/S0304-4076(98)00009-8
    [7] Bracker K, Docking D, Koch P (1999) Economic determinants of evolution in international stock market integration. J Empir Financ 6: 1–27. doi: 10.1016/S0927-5398(98)00007-3
    [8] Colacito R, Engle R, Ghysels E (2011) A component model for dynamic correlations. J Econometrics 164: 45–59. doi: 10.1016/j.jeconom.2011.02.013
    [9] Das D, Bhowmik P, Jana R (2018) A multiscale analysis of stock return co-movements and spillovers: evidence from Pacific developed markets. Phys A 502: 379–393. doi: 10.1016/j.physa.2018.02.143
    [10] Didier T, Love I, Peria M (2012) What explains comovement in stock market returns during the 2007–2008 crisis? Int J Financ Econ 17: 182–202.
    [11] Dimitriou D, Kenourgios D, Simos T (2013) Global financial crisis and emerging stock market contagion: a multivariate FIAPARCH-DCC approach. Int Rev Financ Anal 30: 46–56. doi: 10.1016/j.irfa.2013.05.008
    [12] Engle R, Ghysels E, Sohn B (2006) Stock market volatility and macroeconomic fundamentals. Rev Econ Stat 95: 776–797. doi: 10.1162/REST_a_00300
    [13] Güngör A, Güngör M (2020) Macroeconomic fundamentals of the long-run time varying correlations between Turkish and European stock markets. Empir Econ Lett 19: 903–912.
    [14] Hamao Y, Masulis R, Ng V (1990) Corelation in price changes and volatility across international stock markets. Rev Financ Stud 3: 281–307. doi: 10.1093/rfs/3.2.281
    [15] Johnson R, Soenen L (2002) Asian economic integration and stock market comovement. J Financ Res 25: 141–157. doi: 10.1111/1475-6803.00009
    [16] Jung R, Maderitsch R (2014) Structural breaks in volatility spillovers between international financial markets: contagion or mere interdependence? J Bank Financ 47: 331–342.
    [17] Kim B, Kim H, Lee B (2015) Spillover effects of the U.S. financial crisis on financial markets in emerging Asian countries. Int Rev Econ Financ 39: 192–210. doi: 10.1016/j.iref.2015.04.005
    [18] Liu X, An H, Li H, et al. (2017) Features of spillover networks in international financial markets: evidence from the G20 countries. Phys A 479: 265–278. doi: 10.1016/j.physa.2017.03.016
    [19] Lucey B, Zhang Q (2010) Does cultural distance matter in international stock market comovement? evidence from emerging economies around the World. Emerging Mark Rev 11: 62–78. doi: 10.1016/j.ememar.2009.11.003
    [20] Luchtenberg K, Vu Q (2015) The 2008 financial crisis: stock market contagion and its determinants. Res Int Bus Financ 33: 178–203. doi: 10.1016/j.ribaf.2014.09.007
    [21] Min H, Hwang Y (2012) Dynamic correlation analysis of US financial crisis and contagion: evidence from four OECD countries. Appl Financ Econ 22: 2063–2074. doi: 10.1080/09603107.2012.698161
    [22] Mobarek A, Muradoglu G, Mollah S, et al. (2016) Determinants of time varying co-movements among international stock markets during crisis and non-crisis periods. J Financ Stab 24: 1–11. doi: 10.1016/j.jfs.2016.03.003
    [23] Naifar N (2012) Modeling the dependence structure between default risk premium, equity return volatility and the jump risk: evidence from a financial crisis. Econ Modell 29: 119–131. doi: 10.1016/j.econmod.2011.08.026
    [24] Narayan S, Sriananthakumar S, Islam S (2014) Stock market integration of emerging Asian economies: patterns and causes. Econ Modell 39: 19–31. doi: 10.1016/j.econmod.2014.02.012
    [25] Nitoi M, Pochea M (2019) What drives European Union stock market co-movements? J Int Money Financ 97: 57–69.
    [26] Peng G, Huiming Z, Wanhai Y (2018) Asymmetric dependence between economic policy uncertainty and stock market returns in G7 and BRIC: a quantile regression approach. Financ Res Lett 25: 251–258. doi: 10.1016/j.frl.2017.11.001
    [27] Pretorius E (2002) Economic determinants of emerging stock market interdependence. Emerging Mark Rev 3: 84–105. doi: 10.1016/S1566-0141(01)00032-2
    [28] Romer D (2012) Advanced macroeconomics, The McGraw-Hill Companies, USA.
    [29] Tavares J (2009) Economic integration and the comovement of stock returns. Econ Lett 103: 65–67. doi: 10.1016/j.econlet.2009.01.016
    [30] Thomas N, Kashiramka S, Yadav S (2019) The nature and determinants of comovement between developed, emerging and frontier equity markets: Europe versus Asia-Pacific. Thunderbird Int Bus Rev 61: 291–307. doi: 10.1002/tie.22015
    [31] Vithessonthi C, Kumarasinghe S (2016) Financial development, international trade integration, and stock market integration: evidence from Asia. J Multinatl Financ Manage 35: 79–92. doi: 10.1016/j.mulfin.2016.03.001
    [32] Walti S (2005) The macroeconomic determinants of stock market synchronization. J Int Bank Law 11: 436–441.
    [33] Walti S (2011) Stock market synchronization and monetary integration. J Int Money Financ 30: 96–110. doi: 10.1016/j.jimonfin.2010.07.004
    [34] Wang S, Guo Z (2020) A study on the co-movement and influencing factors of stock markets between China and the other G20 members. Int J Financ Econ 25: 43–62. doi: 10.1002/ijfe.1727
    [35] Zhou X, Zhang W, Zhang J (2012) Volatility spillovers between the Chinese and World equity markets. Pacific-Basin Financ J 20: 247–270. doi: 10.1016/j.pacfin.2011.08.002
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