| Summary: | When faced with an investment opportunity in commercial real estate, the investor
requires knowledge of the discount rate since it can be used to convert expected future
cash flows from the property in today's terms and in doing so, place a value on the
property. The so-called required rate of return would be the appropriate conversion rate
since it compensates the investor for risk and, if attainable, will induce the investor to
invest. An inaccurate assessment of the discount rate could, depending on the direction
of the error, lead to a potential over or under estimation of the property value.
A number of single or multiple variable frameworks for required return have been
derived by other researchers for the US, UK and EU property markets. Each of the
variables encountered in these frameworks acts as a proxy for some aspect of
systematic risk associated with the investment. However, locally, such models are either
not extensively published or well described and are limited to single explanatory
variables. Some professionals prefer to avoid frameworks and simply divert to
qualitative, gut-feel and experienced based considerations in order to derive at required
return rate.
This dissertation addressed the possible local need for an explanatory framework of
required return on commercial property. The scope of work entailed: (i) a review of the
literature to establish the theoretical determinants of return and (ii) an empirical study to
test a short-list of parameters for Retail, Offices and Industrial sites in Cape Town,
Pretoria, Bloemfontein and Durban, respectively.
Three categories of explanatory variables were identified: (i) Capital market variables
and alternative investment opportunities in the form of stocks on the JSE, (ii) economic
activity indicators and (iii) property market fundamental parameters. The empirical study
entailed a three-phase methodology, which included the following steps: (i) data
sampling and processing, (ii) screening variables through the simple regression and
correlation coefficients and (iii) multiple regression complemented by statistical
significance testing. Between 69% and 98.2 % (alpha=O.1) of the variation in returns
could be explained in terms of the variation by the explanatory variables that passed the
rigorous screening process. The relative good results are likely to be related to the
higher explanatory power of the multi-factor approach. The remaining unexplained
portion of return can potentially be decreased by using larger samples and pursuing
some of the other recommendations for additional research. === Thesis (M.B.A.)--North-West University, Potchefstroom Campus, 2006.
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