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Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach

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  • Susanne Cannon
  • Norman G. Miller
  • Gurupdesh S. Pandher

Abstract

This article carries out an asset-pricing analysis of the U.S. metropolitan housing market. We use ZIP code-level housing data to study the cross-sectional role of volatility, price level, stock market risk and idiosyncratic volatility in explaining housing returns. While the related literature tends to focus on the dynamic role of volatility and housing returns within submarkets over time, our risk-return analysis is cross-sectional and covers the national U.S. metropolitan housing market. The study provides a number of important findings on the asset-pricing features of the U.S. housing market. Specifically, we find (i) a positive relation between housing returns and volatility, with returns rising by 2.48% annually for a 10% rise in volatility, (ii) a positive but diminishing price effect on returns and (iii) that stock market risk is priced directionally in the housing market. Our results on the return-volatility-price relation are robust to (i) metropolitan statistical area clustering effects and (ii) differences in socioeconomic characteristics among submarkets related to income, employment rate, managerial employment, owner-occupied housing, gross rent and population density. Copyright 2006 American Real Estate and Urban Economics Association

Suggested Citation

  • Susanne Cannon & Norman G. Miller & Gurupdesh S. Pandher, 2006. "Risk and Return in the U.S. Housing Market: A Cross-Sectional Asset-Pricing Approach," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 34(4), pages 519-552, December.
  • Handle: RePEc:bla:reesec:v:34:y:2006:i:4:p:519-552
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    Citations

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    Cited by:

    1. MeiChi Huang, 2013. "The Role of People’s Expectation in the Recent US Housing Boom and Bust," The Journal of Real Estate Finance and Economics, Springer, vol. 46(3), pages 452-479, April.
    2. Ebrahim, M. Shahid, 2009. "Can an Islamic model of housing finance cooperative elevate the economic status of the underprivileged?," Journal of Economic Behavior & Organization, Elsevier, vol. 72(3), pages 864-883, December.
    3. repec:eme:ijhmap:ijhma-07-2016-0052 is not listed on IDEAS
    4. Brent Smith, 2012. "Lending Through the Cycle: The Federal Housing Administration’s Evolving Risk in the Primary Market," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 40(3), pages 253-271, September.
    5. repec:gam:jecomi:v:5:y:2017:i:4:p:38-:d:115667 is not listed on IDEAS
    6. repec:eme:sefpps:v:33:y:2016:i:4:p:735-754 is not listed on IDEAS
    7. Eli Beracha & Hilla Skiba, 2013. "Findings from a Cross-Sectional Housing Risk-Factor Model," The Journal of Real Estate Finance and Economics, Springer, vol. 47(2), pages 289-309, August.
    8. Christopher Anderson & Eli Beracha, 2012. "Frothy Housing Markets and Local Stock-Price Movements," The Journal of Real Estate Finance and Economics, Springer, vol. 45(2), pages 326-346, August.
    9. Chun-Kei Tsang & Wing-Keung Wong & Ira Horowitz, 2016. "Arbitrage opportunities, efficiency, and the role of risk preferences in the Hong Kong property market," Studies in Economics and Finance, Emerald Group Publishing, vol. 33(4), pages 735-754, October.
    10. MeiChi Huang & Tzu-Chien Wang, 2015. "Housing-bubble vulnerability and diversification opportunities during housing boom–bust cycles: evidence from decomposition of asset price returns," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 54(2), pages 605-637, March.
    11. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.
    12. Tsang, Chun-Kei & Wong, Wing-Keung & Horowitz, Ira, 2016. "A stochastic-dominance approach to determining the optimal home-size purchase: The case of Hong Kong," MPRA Paper 69175, University Library of Munich, Germany.

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