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Structural Conditional Correlation

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  • Enzo Weber

Abstract

A small strand of recent literature is occupied with identifying simultaneity in multiple equation systems through autoregressive conditional heteroscedasticity. Since this approach assumes that the structural innovations are uncorrelated, any contemporaneous connection of the endogenous variables needs to be exclusively explained by mutual spillover effects. In contrast, this paper allows for instantaneous covariances, which become identifiable by imposing the constraint of structural constant/dynamic conditional correlation (SCCC/SDCC). In this, common driving forces can be modeled in addition to simultaneous transmission effects. The methodology is applied to the Dow Jones and Nasdaq Composite indexes, illuminating scope and functioning of the new models. Copyright The Author 2009. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oupjournals.org, Oxford University Press.

Suggested Citation

  • Enzo Weber, 2010. "Structural Conditional Correlation," Journal of Financial Econometrics, Society for Financial Econometrics, vol. 8(3), pages 392-407, Summer.
  • Handle: RePEc:oup:jfinec:v:8:y:2010:i:3:p:392-407
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    File URL: http://hdl.handle.net/10.1093/jjfinec/nbp025
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    Cited by:

    1. Numan Ülkü & Enzo Weber, 2014. "Identifying the Interaction between Foreign Investor Flows and Emerging Stock Market Returns," Review of Finance, European Finance Association, vol. 18(4), pages 1541-1581.
    2. Till Strohsal & Enzo Weber, 2012. "The Signal of Volatility," SFB 649 Discussion Papers SFB649DP2012-043, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    3. Lütkepohl, Helmut & Netšunajev, Aleksei, 2017. "Structural vector autoregressions with heteroskedasticity: A review of different volatility models," Econometrics and Statistics, Elsevier, vol. 1(C), pages 2-18.
    4. Helmut Luetkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticity - A Comparison of Different Volatility Models," CESifo Working Paper Series 5308, CESifo Group Munich.
    5. Weber, Enzo & Zhang, Yanqun, 2012. "Common influences, spillover and integration in Chinese stock markets," Journal of Empirical Finance, Elsevier, vol. 19(3), pages 382-394.
    6. Jahn, Elke & Weber, Enzo, 2016. "Identifying The Substitution Effect Of Temporary Agency Employment," Macroeconomic Dynamics, Cambridge University Press, vol. 20(05), pages 1264-1281, July.
    7. Choe, Kwang-il & Choi, Pilsun & Nam, Kiseok & Vahid, Farshid, 2012. "Testing financial contagion on heteroskedastic asset returns in time-varying conditional correlation," Pacific-Basin Finance Journal, Elsevier, vol. 20(2), pages 271-291.
    8. Numan Ülkü, 2011. "Modeling Comovement among Emerging Stock Markets: The Case of Budapest and Istanbul," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(3), pages 277-304, July.
    9. Weber, Enzo, 2013. "Simultaneous stochastic volatility transmission across American equity markets," The Quarterly Review of Economics and Finance, Elsevier, vol. 53(1), pages 53-60.
    10. repec:zbw:espost:180833 is not listed on IDEAS
    11. repec:bla:ecorec:v:93:y:2017:i:302:p:465-483 is not listed on IDEAS
    12. Weber, Enzo, 2013. "Decomposing U.S. Stock Market Comovement into spillovers and common factors," The North American Journal of Economics and Finance, Elsevier, vol. 26(C), pages 106-118.
    13. Conrad, Christian & Weber, Enzo, 2013. "Measuring Persistence in Volatility Spillovers," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79850, Verein für Socialpolitik / German Economic Association.
    14. Herwartz, Helmut & Roestel, Jan, 2018. "A structural approach to identify financial transmission in distinguished scenarios of crises," Economics Working Papers 2018-08, Christian-Albrechts-University of Kiel, Department of Economics.
    15. Ülkü, Numan & Weber, Enzo, 2013. "Identifying the interaction between stock market returns and trading flows of investor types: Looking into the day using daily data," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 2733-2749.
    16. Lütkepohl, Helmut & Velinov, Anton, 2016. "Structural Vector Autoregressions : Checking Identifying Long-Run Restrictions via Heteroskedasticity," EconStor Open Access Articles, ZBW - German National Library of Economics, pages 377-392.
    17. Strohsal, Till & Weber, Enzo, 2015. "Time-varying international stock market interaction and the identification of volatility signals," Journal of Banking & Finance, Elsevier, vol. 56(C), pages 28-36.
    18. Helmut Lütkepohl & Aleksei Netšunajev, 2015. "Structural Vector Autoregressions with Heteroskedasticy," SFB 649 Discussion Papers SFB649DP2015-015, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    19. Strohsal, Till & Weber, Enzo, 2013. "Identifying Volatility Signals from Time-Varying Simultaneous Stock Market Interaction," Annual Conference 2013 (Duesseldorf): Competition Policy and Regulation in a Global Economic Order 79903, Verein für Socialpolitik / German Economic Association.

    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
    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

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