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A Test of Weak‐Form Efficiency in Residential Real Estate Returns

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  • William Rayburn
  • Michael Devaney
  • Richard Evans

Abstract

This paper tests weak‐form efficiency of residential real estate returns for the city of Memphis, Tennessee. The database for the study is comprised of the population of all sales of single‐unit residential property over a fifteen‐year period, 1970–1984. The city was divided into ten submarkets based on Memphis City Planning Commission planning districts. An analysis of variance procedure was utilized to stabilize the variance both within and across submarkets and nonmarket financing was partially controlled by eliminating transactions with loan‐to‐value ratios greater than 95%. The remaining transactions were then used to generate a mean return series. The advantage of the mean over the single transaction series used by Gau is that it represents the most likely outcome for the investor trying to duplicate investment performance since “property unique” features would be expected to cancel. Seven of the ten submarkets exhibited time patterns; however, after adjusting for transaction costs, all ten submarkets were determined weak‐form efficient for the period 1970–1984. This was not true for the short horizon holding period, 1970–1975. In four sub‐markets an asymmetric version of Alexander's filter rule was able to outperform a buy‐and‐hold, even for round‐ trip transaction costs as high as 10%.

Suggested Citation

  • William Rayburn & Michael Devaney & Richard Evans, 1987. "A Test of Weak‐Form Efficiency in Residential Real Estate Returns," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 15(3), pages 220-233, September.
    • Handle: RePEc:bla:reesec:v:15:y:1987:i:3:p:220-233
    DOI: 10.1111/1540-6229.00429
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    Cited by:

    1. Maier, Gunther & Herath, Shanaka, 2009. "Real Estate Market Efficiency. A Survey of Literature," SRE-Discussion Papers 2009/07, WU Vienna University of Economics and Business.
    2. Cohen, Jeffrey P. & Ioannides, Yannis M. & (Wirathip) Thanapisitikul, Win, 2016. "Spatial effects and house price dynamics in the USA," Journal of Housing Economics, Elsevier, vol. 31(C), pages 1-13.
    3. Caporale, Guglielmo Maria & Sousa, Ricardo M., 2016. "Consumption, wealth, stock and housing returns: Evidence from emerging markets," Research in International Business and Finance, Elsevier, vol. 36(C), pages 562-578.
    4. El-Jahel, Lina & MacCulloch, Robert, 2021. "Trading in the housing market: A model with transaction costs," Mathematical Social Sciences, Elsevier, vol. 113(C), pages 89-96.
    5. Ghysels, Eric & Plazzi, Alberto & Valkanov, Rossen & Torous, Walter, 2013. "Forecasting Real Estate Prices," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 509-580, Elsevier.
    6. Richard D. Evans & William Rayburn, 1991. "The Effect of School Desegregation Decisions on Single-Family Housing Prices," Journal of Real Estate Research, American Real Estate Society, vol. 6(2), pages 107-216.
    7. William L. Attebery & Ronald C. Rutherford & Mark E. Eakin, 1993. "Industrial Real Estate Prices and Market Efficiency," Journal of Real Estate Research, American Real Estate Society, vol. 8(3), pages 377-386.
    8. Esra ALP & Ünal SEVEN, 2019. "Türkiye Konut Piyasasında Etkinlik Analizi," Istanbul Business Research, Istanbul University Business School, vol. 48(1), pages 84-112, May.
    9. Alan W. Evans, 1995. "The Property Market: Ninety Per Cent Efficient?," Urban Studies, Urban Studies Journal Limited, vol. 32(1), pages 5-29, February.

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