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Re-thinking commercial real estate market segmentation

Fuerst, F. and Marcato, G., (2010) Re-thinking commercial real estate market segmentation. Working Papers in Real Estate & Planning. 12/10. Working Paper. University of Reading, Reading. pp21.

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Investments in direct real estate are inherently difficult to segment compared to other asset classes due to the complex and heterogeneous nature of the asset. The most common segmentation in real estate investment analysis relies on property sector and geographical region. In this paper, we compare the predictive power of existing industry classifications with a new type of segmentation using cluster analysis on a number of relevant property attributes including the equivalent yield and size of the property as well as information on lease terms, number of tenants and tenant concentration. The new segments are shown to be distinct and relatively stable over time. In a second stage of the analysis, we test whether the newly generated segments are able to better predict the resulting financial performance of the assets than the old dichotomous segments. Applying both discriminant and neural network analysis we find mixed evidence for this hypothesis. Overall, we conclude from our analysis that each of the two approaches to segmenting the market has its strengths and weaknesses so that both might be applied gainfully in real estate investment analysis and fund management.

Item Type:Report (Working Paper)
Divisions:Henley Business School > Real Estate and Planning
ID Code:22729
Uncontrolled Keywords:market segmentation, commercial real estate, financial performance measurement, cluster analysis, neural network analysis, risk diversification
Publisher:University of Reading
Publisher Statement:The copyright of each working paper remains with the author. If you wish to quote from or cite any paper please contact the appropriate author; in some cases a more recent version of the paper may have been published elsewhere.


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