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Gains From Diversifying Into Real Estate: Three Decades of Portfolio Returns Based on the Dynamic Investment Model
Author(s) -
Grauer Robert R.,
Hakansson Nils H.
Publication year - 1995
Publication title -
real estate economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.064
H-Index - 61
eISSN - 1540-6229
pISSN - 1080-8620
DOI - 10.1111/1540-6229.00661
Subject(s) - real estate , portfolio , economics , econometrics , leverage (statistics) , smoothing , capitalization rate , financial economics , real estate investment trust , bond , investment (military) , investment strategy , finance , actuarial science , mathematics , market liquidity , statistics , politics , political science , law
This paper compares the investment policies and returns for portfolios of stocks and bonds with and without up to three categories of real estate. Both domestic and global settings are examined, with and without the possibility of leverage. The portfolios were generated via the dynamic investment model based on the empirical probability assessment approach applied to past (joint) realizations of returns, both with and without correction for “smoothing” in the real estate data series. Our principal findings are: (1) the gains from adding real estate, on a semi‐passive (equal‐weighted) basis, to portfolios of either U.S. or global financial assets were relatively modest; in contrast, (2) the gains from adding real estate to the universe of U.S. financial assets under an active strategy were rather large (in some cases highly statistically significant), especially for the very risk‐averse strategies; (3) the gains from adding U.S. real estate to a universe of global financial assets under an active strategy were mixed, although generally favorable for the highly risk‐averse strategies; (4) correcting for second‐moment smoothing in the real estate returns series had a relatively small impact for the more risk‐tolerant strategies; and (5) there was some evidence that desmoothing resulted in improved probability estimates.