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Real estate returns predictability revisited: novel evidence from the US REITs market

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An Erratum to this article was published on 27 February 2016

Abstract

In this paper, we examine the real estate returns predictability employing US real estate investment trusts (REITs) and a set of possible predictors for the period January 1991–December 2014. To this end, we employ several forecasting models to test for REITs predictability under a flexible framework that captures parameter instability. Apart from the traditional factors examined in relevant studies, we also account for a series of sentiment and uncertainty indicators that may be significant predictors of REITs returns, especially during turbulent times when sentiment determines investment decisions to a greater extent. The empirical results indicate that the good predictors of REITs returns vary over time and over the forecast horizons. Our results suggest that economy-wide indicators, monetary policy instruments and sentiment indicators are among the most powerful predictors of REITs returns. In economic terms, an investment strategy that is based on our forecasts outperforms a buy and hold strategy. The issue of the most suitable forecasting method is also discussed in detail. Our results might entail implications for investors and market authorities.

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Notes

  1. Researchers have also focused on investor behavior in the real estate market trying to identify herd behavior in real estate market (Lan 2014; Philippas et al. 2013; Zhou and Anderson 2013), especially after the recent global financial crisis.

  2. http://www.reit.com/investing/industry-data-research/us-reit-industry-equity-market-cap.

  3. See Gatzlaff and Tirtiroglu (1995), Cho (1996), Maier and Herath (2009) and Ghysels et al. (2013) for a comprehensive review on the real estate market efficiency.

  4. See Koop and Korobilis (2012) for technical details on conditional prediction for both single and multi-model cases.

  5. Further details on the DMA and DMS methods and implementation can be obtained from Koop and Korobilis (2011, 2012).

  6. See http://www.reit.com/investing/index-data/ftse-nareit-us-real-estate-index-historical-values-returns.

  7. http://www.econ.yale.edu/~shiller/data.htm.

  8. The CP factor was calculated based on the method described in the paper by Cochrane and Piazzesi (2005) using the 1–5 years Fama-Bliss Discount Bond Yields, with these series being obtained from the Center for Research in Security Prices (CRSP).

  9. Data derived from the official Web site of the Federal Reserve Bank of the Kansas City, available at http://www.kc.frb.org/research/indicatorsdata/kcfsi/.

  10. Data available at http://www.sca.isr.umich.edu/tables.php.

  11. Data available at http://www.policyuncertainty.com/.

  12. In addition to these 13 predictors, we also analyzed the predictive ability of the four components (news-based, federal-state local expenditure disagreement, CPI disagreement and tax expiration) of the UPUN instead of the aggregate index itself; the debt ceiling and government shutdown indexes; all of which are available from www.policyuncertainty.com. Barring the news-based component of UPUN, none of the other indices had any predictive ability. Further, we also looked at eight (six on moving average-based rules and 2 on momentum-based rules) technical indicators, which too did not have any predictive ability. In light of this, we decided to drop these additional predictors to keep the analysis tractable in terms of the number of predictors. However, details of these results are available upon request from the authors.

  13. We would like to thank an anonymous referee for his suggestion to perform a trading strategy.

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Authors and Affiliations

  1. School of Construction Economics and Management, University of Witwatersrand, Johannesburg, South Africa

    Omokolade Akinsomi

  2. Department of Economics, University of Pretoria, Pretoria, 0002, South Africa

    Goodness C. Aye & Rangan Gupta

  3. Department of Accounting and Finance, Technological Educational Institute of Peloponnese, Kalamata, Greece

    Vassilios Babalos

  4. Department of Banking and Financial Management, University of Piraeus, Piraeus, Greece

    Vassilios Babalos

  5. Centre of Planning and Economic Research, Athens, Greece

    Fotini Economou

Authors
  1. Omokolade Akinsomi
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  2. Goodness C. Aye
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  3. Vassilios Babalos
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  4. Fotini Economou
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  5. Rangan Gupta
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Corresponding author

Correspondence to Vassilios Babalos.

Additional information

Authors are grateful to two anonymous reviewers and to the editor for their constructive comments that helped improve the paper.

An erratum to this article can be found at http://dx.doi.org/10.1007/s00181-016-1066-8.

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Akinsomi, O., Aye, G.C., Babalos, V. et al. Real estate returns predictability revisited: novel evidence from the US REITs market. Empir Econ 51, 1165–1190 (2016). https://doi.org/10.1007/s00181-015-1037-5

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  • DOI: https://doi.org/10.1007/s00181-015-1037-5

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