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Coherent risk measures in real estate investment

Author

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  • Roger Brown
  • Michael Young

Abstract

Purpose - The purpose of this paper is to propose a new way to measure risk in real estate investment, which departs from traditional statistical methodology borrowed from finance. Design/methodology/approach - An argument is advanced for the use of so‐called coherent risk measures for real estate investment decisions. Central to this class of measure is the computation of spectral risk, a measure that covers the spectrum of an individual's risk aversion function. Intuition being hard to observe, empirical data from two large databases are presented as support. Findings - At the heart of the controversy is a discussion of the nature of risk and how it should be measured. This paper seeks common ground where peace may be made between these two warring factions. Scenarios are tested wherein different risk aversion functions are used to compute spectral risk for different sectors. Ex‐post analysis shows that reasoning of this nature can lead to improved risk‐adjusted investment results. Practical implications - The route to finding an appropriate risk measure for real estate investment has been tortuous. It is not certain that the destination has been reached. Complicating the task is a considerable gap between academic and practitioner methodology, the former relying on the mathematics of objective probability, the latter dwelling quite successfully in a habitat of subjective risk measures. Social implications - It is widely accepted that risk represents a cost to society. Real estate, as a repository of roughly half the world's wealth, can be viewed as having risk of a structurally different nature. The better understanding of this risk reduces the cost to society. Originality/value - For practitioners, spectral measures offer formal support for something they have been doing their entire careers: evaluating risk subjectively. The simple dot product of weights and ordered outcomes is an extension of the widely used “Best case – Worse case – Most likely” methodology that has served professionals well for decades. Perhaps a by‐product of spectral measures is to bring academics and field gladiators closer together. If there is merit to a new way of thinking about risk independent of its implementation, real estate investment could benefit from that thinking. Among those who doubt that everything is “normal” are those who believe that previous attempts to explain risk in real estate have fallen far short of the mark. The challenge to those still not satisfied by the spectral approach is to offer an alternative that represents both a departure from and an improvement of the old methods.

Suggested Citation

  • Roger Brown & Michael Young, 2011. "Coherent risk measures in real estate investment," Journal of Property Investment & Finance, Emerald Group Publishing Limited, vol. 29(4/5), pages 479-493, July.
  • Handle: RePEc:eme:jpifpp:v:29:y:2011:i:4/5:p:479-493
    DOI: 10.1108/14635781111150358
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    Citations

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    Cited by:

    1. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy, 2018. "Ex-ante real estate Value at Risk calculation method," Annals of Operations Research, Springer, vol. 262(2), pages 257-285, March.
    2. Zouheir Mighri & Raouf Jaziri, 2023. "Long-Memory, Asymmetry and Fat-Tailed GARCH Models in Value-at-Risk Estimation: Empirical Evidence from the Global Real Estate Markets," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 21(1), pages 41-97, March.
    3. Charles-Olivier Amedee-Manesme & Fabrice Barthélémy, 2012. "Cornish-Fisher expansion for real estate value at risk," ERES eres2012_044, European Real Estate Society (ERES).
    4. Charles-Olivier Amédée-Manesme & Fabrice Barthélémy & Jean-Luc Prigent & Donald Keenan & Mahdi Mokrane, 2017. "Modified Sharpe Ratios in Real Estate Performance Measurement: Beyond the Standard Cornish Fisher Expansion," THEMA Working Papers 2017-20, THEMA (THéorie Economique, Modélisation et Applications), Université de Cergy-Pontoise.

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