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Real Estate Risk Management with Copulas

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  • Anish Goorah

Abstract

Real estate risk management tools are traditionally based on mean‐variance analysis. The non‐normal behaviour of financial asset returns including real estate securities is a violation of one of the fundamental assumptions of mean‐variance analysis. In this paper, the pitfalls of using the correlation coefficient as a measure of dependency are discussed first. The use of copulas as an alternative to modelling the dependence structure and more generally as a risk‐management tool is then proposed. Copula‐based value‐at‐risk computations are also carried out. The results confirm that the linear correlation measure is unable to capture the dependence between the US and the UK publicly listed real estate securities. The limitations of the joint multivariate normal distribution are also shown.

Suggested Citation

  • Anish Goorah, 2007. "Real Estate Risk Management with Copulas," Journal of Property Research, Taylor & Francis Journals, vol. 24(4), pages 289-311, December.
    • Handle: RePEc:taf:jpropr:v:24:y:2007:i:4:p:289-311
    DOI: 10.1080/09599910801916162
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    References listed on IDEAS

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    1. Frederick C. Mills, 1927. "Introduction to "The Behavior of Prices"," NBER Chapters, in: The Behavior of Prices, pages 31-36, National Bureau of Economic Research, Inc.
    2. Frederick C. Mills, 1927. "The Behavior of Prices," NBER Books, National Bureau of Economic Research, Inc, number mill27-1.
    3. Robert F. Engle & Kevin Sheppard, 2001. "Theoretical and Empirical properties of Dynamic Conditional Correlation Multivariate GARCH," NBER Working Papers 8554, National Bureau of Economic Research, Inc.
    4. Frederick C. Mills, 1927. "Appendix to "The Behavior of Prices"," NBER Chapters, in: The Behavior of Prices, pages 441-586, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Jian Zhou & Yanmin Gao, 2012. "Tail Dependence in International Real Estate Securities Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 45(1), pages 128-151, June.
    2. Wang, Gang-Jin & Xie, Chi, 2015. "Correlation structure and dynamics of international real estate securities markets: A network perspective," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 424(C), pages 176-193.
    3. Andrey Pavlov & Eva Steiner & Susan Wachter, 2018. "The Consequences of REIT Index Membership for Return Patterns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 46(1), pages 210-250, March.
    4. Martin Hoesli & Kustrim Reka, 2013. "Volatility Spillovers, Comovements and Contagion in Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 47(1), pages 1-35, July.
    5. Walter I. Boudry & Robert A. Connolly & Eva Steiner, 2022. "What happens during flight to safety: Evidence from public and private real estate markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 50(1), pages 147-172, March.
    6. Louis Chakkalakal & Ulrich Hommel & Wenwei Li, 2018. "Transport infrastructure equities in mixed-asset portfolios: estimating risk with a Garch-Copula CVaR model," Journal of Property Research, Taylor & Francis Journals, vol. 35(2), pages 117-138, April.
    7. Andréas Heinen & James B. Kau & Donald C. Keenan & Mi Lim Kim, 2021. "Spatial Dependence in Subprime Mortgage Defaults," The Journal of Real Estate Finance and Economics, Springer, vol. 62(1), pages 1-24, January.
    8. Anderson, Randy I. & Chen, Yi-Chi & Wang, Li-Min, 2015. "A range-based volatility approach to measuring volatility contagion in securitized real estate markets," Economic Modelling, Elsevier, vol. 45(C), pages 223-235.
    9. Jamie Alcock & Eva Steiner, 2018. "Fundamental Drivers of Dependence in REIT Returns," The Journal of Real Estate Finance and Economics, Springer, vol. 57(1), pages 4-42, July.

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