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Time Variation in Diversification Benefits of Commodity, REITs, and TIPS

Abstract

Diversification benefits of three “hot” asset classes—Commodity, Real Estate Investment Trusts (REITs), and Treasury Inflation-Protected Securities (TIPS)—are well-studied on an individual basis and in a static setting. Using data from 1970 to 2010, this paper documents both that the three asset classes are in general not substitutes for each other, and that diversification benefits of each asset class change substantially over time. Therefore, all three asset classes ought to be included in investors’ portfolios. Furthermore, we show that the observed time variation in diversification benefits can be explained by time-varying return correlations. To see the implications of these findings for asset allocation in practice, we examine the out-of-sample performance of portfolio strategies, based on a variety of correlation structures. We find that the Dynamic Conditional Correlation (DCC) model (Engle, J Bus Econ Stat 20(3):339–350, 2002) outperforms other correlation structures, such as rolling-window, historical, and constant correlations. Our findings suggest that diversification benefits of the three asset classes should be examined in a dynamic setting, and that investors need to use appropriate correlation estimates to adjust for such time variation.

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Notes

  1. 1.

    Gorton and Rouwenhorst (2006) find negative correlations only in low frequency data (quarterly and annually) but not in monthly data. Our result here is based on daily data, and, to some extent, complements their finding.

  2. 2.

    See Ferson et al. (1993), De Santis (1994, 1995), Harvey (1995), Bekaert and Urias (1996) and De Roon et al. (2001) for different implementations of spanning tests.

  3. 3.

    We also try alternative lags from 1 to 24 and find that our results are robust to the choice of different lags.

  4. 4.

    This is because all the intermediate value of v between \(v_\textrm{min}\) and \(v_\textrm{max}\) will satisfy Eq. 4 as long as both \(v_\textrm{min}\) and \(v_\textrm{max}\) do. The proof of this statement is straightforward.

  5. 5.

    The DCC model is estimated using the UCSD GARCH Toolbox provided by Kelvin Sheppard. See http://www.kevinsheppard.com/research/.

  6. 6.

    The constant correlation is studied in Elton and Gruber (1973) and Elton et al. (1978, 2006).

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Acknowledgements

We thank Charles Cao, Ian Cooper, Zekeriya Eser, Bill Kracaw, C.F. Lee, Jiang Wang, Fan Yu, Hao Zhou, and seminar participants at the 2006 FMA Annual Meeting in Salt Lake City, the 2006 Journal of Banking and Finance 30th Anniversary Conference in Beijing, and the 2006 China International Conference in Finance in Xi’an for their helpful comments and suggestions. Special thanks go to an anonymous referee and James B. Kau (the Editor) for their valuable suggestions that significantly improved the focus of our paper.

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Correspondence to Zhaodong (Ken) Zhong.

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Huang, J., Zhong, Z.(. Time Variation in Diversification Benefits of Commodity, REITs, and TIPS. J Real Estate Finan Econ 46, 152–192 (2013). https://doi.org/10.1007/s11146-011-9311-6

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Keywords

  • Diversification
  • Commodity
  • REITs
  • TIPS
  • DCC