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Volatility Clustering in U.S. Home Prices

Author

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  • William Miles

    () (Wichita State University Wichita, KS 67260-0078)

Abstract

Generalized autoregressive conditional heteroscedasticity (GARCH) effects imply the probability of large losses is greater than standard mean-variance analysis suggests. Accurately capturing GARCH for housing markets is vital for portfolio management. Previous investigations of GARCH in housing have focused on narrow regions or aggregated effects of GARCH across markets, imposing one nationwide effect. This paper tests fifty state housing markets for GARCH, and develops individual GARCH models for those states, allowing for different effects in each. Results indicate there are GARCH effects in over half the states, and the signs and magnitudes vary widely, highlighting the importance of estimating separate GARCH models for each market.

Suggested Citation

  • William Miles, 2008. "Volatility Clustering in U.S. Home Prices," Journal of Real Estate Research, American Real Estate Society, vol. 30(1), pages 73-90.
  • Handle: RePEc:jre:issued:v:30:n:1:2008:p:73-90
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    Citations

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    Cited by:

    1. Bruce Morley & Dennis Thomas, 2016. "An Empirical Analysis of UK House Price Risk Variation by Property Type," Review of Economics & Finance, Better Advances Press, Canada, vol. 6, pages 45-56, May.
    2. Maria Christidou & Stilianos Fountas, 2017. "Uncertainty in the housing market: Evidence from the US states," Discussion Paper Series 2017_08, Department of Economics, University of Macedonia, revised Aug 2017.
    3. Chyi Lin Lee, 2009. "Housing price volatility and its determinants," International Journal of Housing Markets and Analysis, Emerald Group Publishing, vol. 2(3), pages 293-308, August.
    4. Yongheng Deng & Eric Girardin & Roselyne Joyeux, 2015. "Fundamentals and the Volatility of Real Estate Prices in China: A Sequential Modelling Strategy," Working Papers 222015, Hong Kong Institute for Monetary Research.
    5. Kishor, N. Kundan & Kumari, Swati & Song, Suyong, 2015. "Time variation in the relative importance of permanent and transitory components in the U.S. housing market," Finance Research Letters, Elsevier, vol. 12(C), pages 92-99.
    6. Azimi, Mohammad Naim, 2015. "Modelling the Clustering Volatility of India's Wholesales Price Index and the Factors Affecting it," MPRA Paper 70267, University Library of Munich, Germany.
    7. Hong Miao & Sanjay Ramchander & Marc W. Simpson, 2011. "Return and Volatility Transmission in U.S. Housing Markets," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 39(4), pages 701-741, December.
    8. Sheung-Chi Chow & Juncal Cunado & Rangan Gupta & Wing-Keung Wong, 2016. "Causal Relationships between Economic Policy Uncertainty and Housing Market Returns in China and India: Evidence from Linear and Nonlinear Panel and Time Series Models," Working Papers 201674, University of Pretoria, Department of Economics.
    9. Chang, Kuang-Liang, 2010. "House price dynamics, conditional higher-order moments, and density forecasts," Economic Modelling, Elsevier, vol. 27(5), pages 1029-1039, September.

    More about this item

    JEL classification:

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

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