| This dissertation produces two strategic tools for use by institutional real estate investors. Both tools combine theory and facts in a manner that is intuitively plausible, expand the investable universe, and provide a structure for strengthening the available data. The first tool optimally diversifies the real estate portfolio. The optimizer tool provides weights for groups of real estate assets, which minimize risk for a given level of return.;The dissertation compared thirteen "within real estate" portfolio diversification strategies. In support of the main body of real estate research, economic diversification was found to be superior to geographic diversification. The findings also indicate that more dimensions of diversification are better than fewer dimensions and property types should be segregated. Property type is a critical characteristic, explaining nearly a third of the differences in real estate returns. The best diversification method overall among the thirteen tested sorted assets by geographic region/property type. This method provided the best MPT-efficient frontier and should be easier for portfolio managers to implement than economic diversification.;Once the weight of each regional/property type (for example, east offices) has been determined, the second tool is used to provide further direction for investment. The second tool is a recursive econometric model that forecasts the implied market returns for 200 metropolitan area/property types (for example, Boston offices). By ranking the forecasted market returns, the investor decides where in the region to acquire individual assets. "REEFM"--the Real Estate Econometric Forecast Model pooled an unbalanced panel to estimate six equations for each of four property type (apartment, office, retail, and warehouse) markets. These six equations predicted occupancy, real rents, cap rate, market value per square foot, net change in stock, and real construction cost. REEFM also employs a unique equation for determining the change in the stock of space. This equation links the space and capital markets and the short- and long-run by combining both price and quantity signals. Methods for implementing the two tools are also discussed in the dissertation. |
