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A Measure of Fundamental Volatility in the Commercial Property Market

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  • Shaun A. Bond
  • Soosung Hwang

Abstract

The low level of volatility observed in appraisal‐based commercial property indices relative to other asset classes has been frequently noted and extensively commented on in the real estate finance literature. However, the volatility of such commercial property indices is only one source of information on the second moment of commercial property returns. The volatility of securitized property returns forms another potential source of information, though there is some uncertainty about how closely the volatility of securitized returns may match the volatility of the underlying asset. Each measure of volatility has a potential source of noise associated with it. This paper proposes a fundamental measure of volatility for the commercial property market by using a stochastic volatility model to filter out the signal in the different sources of volatility information. This allows for different measures of volatility to be decomposed into transitory noise and unobserved fundamental volatility. The suitability of such an approach and the properties of the underlying fundamental volatility series are analyzed using data from the U.K. property market.

Suggested Citation

  • Shaun A. Bond & Soosung Hwang, 2003. "A Measure of Fundamental Volatility in the Commercial Property Market," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 31(4), pages 577-600, December.
  • Handle: RePEc:bla:reesec:v:31:y:2003:i:4:p:577-600
    DOI: 10.1046/j.1080-8620.2003.00077.x
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    Cited by:

    1. John Cotter & Simon Stevenson, 2006. "Multivariate Modeling of Daily REIT Volatility," The Journal of Real Estate Finance and Economics, Springer, vol. 32(3), pages 305-325, May.
    2. Kim Liow & Muhammad Ibrahim, 2010. "Volatility Decomposition and Correlation in International Securitized Real Estate Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 40(2), pages 221-243, February.
    3. S. Wong & K. Chau & C. Yiu, 2007. "Volatility Transmission in the Real Estate Spot and Forward Markets," The Journal of Real Estate Finance and Economics, Springer, vol. 35(3), pages 281-293, October.
    4. Kim Liow & Wei Chen, 2013. "Is There Volatility Convergence in Asia-Pacific Securitized Real Estate Markets?," The Journal of Real Estate Finance and Economics, Springer, vol. 47(2), pages 370-390, August.
    5. Shaun Bond & Soosung Hwang & Zhenguo Lin & Kerry Vandell, 2007. "Marketing Period Risk in a Portfolio Context: Theory and Empirical Estimates from the UK Commercial Real Estate Market," The Journal of Real Estate Finance and Economics, Springer, vol. 34(4), pages 447-461, May.
    6. Ting, Sai Hung Marten & Ewald, Christian-Oliver & Wang, Wen-Kai, 2013. "On the investment–uncertainty relationship in a real option model with stochastic volatility," Mathematical Social Sciences, Elsevier, vol. 66(1), pages 22-32.
    7. Martin Hoesli & Eva Liljeblom & Anders Loflund, 2014. "The Effect of Lock-Ups on the Suggested Real Estate Portfolio Weight," International Real Estate Review, Global Social Science Institute, vol. 17(1), pages 1-22.
    8. 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.
    9. Youngha Cho & Soosung Hwang & Yong-ki Lee, 2014. "The Dynamics of Appraisal Smoothing," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 42(2), pages 497-529, June.
    10. Kim, Jeong-Hoon & Lee, Min-Ku & Sohn, So Young, 2014. "Investment timing under hybrid stochastic and local volatility," Chaos, Solitons & Fractals, Elsevier, vol. 67(C), pages 58-72.
    11. Shaun A. Bond & Soosung Hwang & Gianluca Marcato, 2006. "An Analysis of Commercial Real Estate Returns: Is there a Smoothing Puzzle?," Real Estate & Planning Working Papers rep-wp2006-17, Henley Business School, University of Reading.

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