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The Shape of Australian Real Estate Return Distributions and Comparisons to the United States

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Abstract
Investment risk models with variance provide a better description of distribution of individual property returns in the Property Council of Australia data base from 1985 to 1996 than normally distributed risk models. The shape of the distribution of Australian property returns is virtually indistinguishable from the shape of United States property returns in the NCREIF Property Index for the years 1980 to 1992. Australian real estate investment risk is heteroscedastic, like its US counterpart, but the characteristic exponent of the investment risk function is constant across time and property type. It follows that portfolio management and asset diversification techniques that rely upon finite-variance statistics are as ineffectual for the Australian real estate market as they have been found to be for the United States.

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  • Richard A. Graff & Adrian Harrington & Michael S. Young, 1997. "The Shape of Australian Real Estate Return Distributions and Comparisons to the United States," Journal of Real Estate Research, American Real Estate Society, vol. 14(3), pages 291-308.
    • Handle: RePEc:jre:issued:v:14:n:3:1997:p:291-308
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    1. Young, Michael S & Graff, Richard A, 1995. "Real Estate Is Not Normal: A Fresh Look at Real Estate Return Distributions," The Journal of Real Estate Finance and Economics, Springer, vol. 10(3), pages 225-259, May.
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    Cited by:

    1. Michael Young, 2008. "Revisiting Non-normal Real Estate Return Distributions by Property Type in the U.S," The Journal of Real Estate Finance and Economics, Springer, vol. 36(2), pages 233-248, February.
    2. Tamás Kiss & Hoang Nguyen & Pär Österholm, 2021. "Modelling Returns in US Housing Prices—You’re the One for Me, Fat Tails," JRFM, MDPI, vol. 14(11), pages 1-17, October.
    3. Carsten Lausberg & Stephen Lee & Moritz Müller & Cay Oertel & Tobias Schultheiß, 2020. "Risk measures for direct real estate investments with non-normal or unknown return distributions," Zeitschrift für Immobilienökonomie (German Journal of Real Estate Research), Springer;Gesellschaft für Immobilienwirtschaftliche Forschung e. V., vol. 6(1), pages 3-27, April.
    4. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    5. 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.
    6. Ming-Chu Chiang & I-Chun Tsai, 2016. "Ripple effect and contagious effect in the US regional housing markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 55-82, January.
    7. Richard A. Graff, 2001. "Off-Balance-Sheet Corporate Finance with Synthetic Leases: Shortcomings and How to Avoid Them with Synthetic Debt," Journal of Real Estate Research, American Real Estate Society, vol. 22(1/2), pages 213-242.
    8. Ming-Chu Chiang & I-Chun Tsai, 2016. "Ripple effect and contagious effect in the US regional housing markets," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 56(1), pages 55-82, January.
    9. Michael S. Young, 2000. "REIT Property-Type Sector Integration," Journal of Real Estate Research, American Real Estate Society, vol. 19(1), pages 3-21.
    10. Zhan Liu & Gang-Zhi Fan & Kian Lim, 2009. "Extreme Events and the Copula Pricing of Commercial Mortgage-Backed Securities," The Journal of Real Estate Finance and Economics, Springer, vol. 38(3), pages 327-349, April.

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    JEL classification:

    • L85 - Industrial Organization - - Industry Studies: Services - - - Real Estate Services

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