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Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets


This paper analyzes the relationships between local and global securitized real estate markets, but also between securitized real estate and common stock markets. First, the volatility transmissions across markets are examined using an asymmetric t-BEKK (Baba-Engle-Kraft-Kroner) specification of their covariance matrix. Second, correlations from that model and tail dependences estimated using a time-varying copula framework are analyzed to assess whether different dynamics underlie the comovements in the whole distribution and those in the tails. Third, we investigate market contagion by testing for structural changes in the tail dependences. We use data for the U.S., the U.K. and Australia for the period 1990–2010 as a basis for our analyses. Spillover effects are found to be the largest in the U.S., both domestically and internationally. Further, comovements in tail distributions between markets appear to be quite important. We also document different dynamics between the conditional tail dependences and correlations. Finally, we find evidence of market contagion between the U.S. and the U.K. markets following the subprime crisis.

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  1. 1.

    European Public Real Estate Association (EPRA), Monthly Statistical Bulletin of July 2010.

  2. 2.

    See, for instance, Embrechts et al. (2002).

  3. 3.

    Bae et al. (2003, p. 718–719).

  4. 4.

    See Ling and Naranjo (2002) for a study finding evidence of a worldwide factor driving securitized real estate returns.

  5. 5.

    For further studies on volatility spillovers involving the equity market, see Karolyi and Stulz (1996), King et al. (1994), and Susmel and Engle (1994).

  6. 6.

    Miao et al. (2011), and Wong et al. (2007) also use the symmetric BEKK model for volatility spillover purposes, but analyze the housing markets, and the real estate spot and forward markets, respectively.

  7. 7.

    European Public Real Estate Association/National Association of Real Estate Investment Trusts.

  8. 8.

    The univariate version of the ARCH and GARCH models were first established by Engle (1982) and Bollerslev (1986), respectively.

  9. 9.

    The Student’s t distribution partially captures the leptokurtosis of the innovations. Besides, the BEKK model coupled with a bivariate Student’s t distribution represents one of the most flexible multivariate models available (Ang and Bekaert 2002).

  10. 10.

    For further details on the development of this methodology, see Patton (2006).

  11. 11.

    For further details, see Dias and Embrechts (2004) and Csörgő and Horvàth (1997).

  12. 12.

    The results of this test are not reported. They can be obtained upon request.

  13. 13.

    The results are not reported in this paper. They can be obtained upon request.

  14. 14.

    The results are not reported in this paper. They can be obtained upon request.

  15. 15.

    The indices are expressed in local currency in order to avoid any impact of exchange rate factors on the analysis of financial contagion.

  16. 16.

    As we filtered our returns with an AR(1)-GJR-t-GARCH(1,1) model, we can assume that we have independent bivariate vectors with no structural break in the margins; therefore the conditions for applying the test of Dias and Embrechts (2004) are satisfied.

  17. 17.

    Longstaff (2010) reviews two other mechanisms of shock transmission: Contagion trough the liquidity channel and contagion through the time-varying risk premiums. These mechanisms are not discussed in this paper as they do not constitute the purpose of our study.

  18. 18.

    The significant change could have occurred only to the upper tail dependence as we test for a change in one parameter only or in both parameters.


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Correspondence to Martin Hoesli.

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Hoesli, M., Reka, K. Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets. J Real Estate Finan Econ 47, 1–35 (2013).

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  • Volatility spillovers
  • Financial contagion
  • Asymmetric BEKK model
  • Copulas
  • Structural breaks
  • Real estate securities

JEL classification

  • G11
  • G15
  • C32