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Physical real estate in long-term asset allocation: The case of France

 

The essential

The available historical data and how to interpret it

  • CBRE
  • IPD
  • EDHEC IEIF

Long-term risk

Correlation with other asset classes

Consequences for portfolio allocation

  • An example
  • Diversifying power of physical real estate depending on the initial portfolio

      

This paper analyses for France, indices that represent physical real estate and shows that they differ from one another in terms of assets which are included or their valuation methods. They are constructed in such a way that comparisons with listed asset indices must be done with care. In particular, they exhibit smoothing and time lag. We investigate the hierarchy of risks and we show that residential is less risky than offices, prime real estate in Paris’s “Golden Triangle” is the riskiest.

The long-term risk is greater than what a simplistic calculation would show, and may be as high as the risk level of equities. Over the long term, there is a positive correlation with equities and a negative correlation with government bonds. Again, the phenomenon may be concealed through careless work on series with too high a frequency.

Consequently, the diversifying power of physical real estate is very attractive in the long term for bond-heavy portfolios, but less so for equity-heavy portfolios. The smoothed valuation method, however, has a favourable optical effect on short-term risk.

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Introduction

The benefit of an asset class is explained by the expected return given its risk, as well as its impact on the total risk of the portfolio via diversification. It is hard to extrapolate from past returns, but observing historical series is helpful for quantifying risk and correlations. Here, we are interested in the risk of physical real estate and its correlation with the listed assets to be taken into account for long-term allocation in the case of France.

[...]

Alessandro RUSSO, CFA, Head of Equity Quant Research at Amundi
Sylvie de LAGUICHE, Head of Quantitative Research at Amundi

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