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How to geographically allocate a pan-European logistics real

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					How to geographically allocate a
pan-European logistics real estate fund
An analytical study assessing the principles
of a country allocation decision model




T.R. ten Bokum BSc
MSRE Master Thesis

Amsterdam School of Real Estate
Amsterdam, September 2008
Graduate lecturers:
drs. R.M. Weisz RA MRICS
A.G.M. Tielens LL.M. MRE FRICS




 The author is held responsible for the content of the thesis; the copyright of this thesis rests with the author and no quotation from it or
                      information derived from it may be published without the prior written consent of the author.
                                                          Executive summary
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Executive summary

This thesis has attempted to design a methodology for establishing a geographical allocation
for a pan-European logistics non-listed real estate fund. The research and development of a
methodology was needed because currently, the scientific knowledge on geographical
(country) allocation is mainly provided by broad theories that don’t cover the allocation
sufficiently and thoroughly enough. Therefore most country allocations of non-listed real
estate funds are based upon macro-economic data and a small quantity of (available) data on
the drivers of the specific property sector, but no scientific method is used in order to
compose the actual geographical allocation. Furthermore, although the familiarity of logistics
real estate as a property asset class is steadily increasing amongst European institutional
investors, a lot can still be done in order to accelerate the knowledge on this asset class in
order for it to become a mature asset class like for example the office or retail sector.
          The objective of this thesis is twofold; firstly the research study aims to qualify the
factors and criteria of investing in logistics markets in different pan-European countries in
order to provide real estate professionals with an insight into how logistics portfolios can be
geographically allocated from a risk and return point of view. In addition, the research reviews
the differences within the logistics real estate sectors as well as the differences in non-listed
fund strategies which can sometimes become intertwined with the specific choice of these
different asset types. Secondly, a methodology for establishing a geographical allocation for a
pan-European logistics non-listed real estate fund is developed in order to provide logistics
real estate fund managers with a scientific method which can aid them with the process of
composing a country allocation and the decisions that are associated with it.
          In order to develop the country allocation decision model (CADM) the thesis first
elaborates on the logistics real estate and investment market and its main drivers. The most
important conclusion of the theoretical research on the logistics markets is that both the
factors and criteria that influence the location choice of tenants - as well as factors and criteria
that influence the country allocation process of fund managers and investors - should be
implemented in the decision model. The reason being that both viewpoints are important in
order to successfully manage a fund strategy that is sustainable over a long period of time.
          As far as the author was aware there were no appropriate scientific methods
available that elaborated on the geographical allocation process - that’s why this thesis has
studied theories and models that came closest to the allocation problem. Although the
reviewed methods and models could not be used in their entirety, they did however form a
solid basis for the CADM. Additionally they helped in understanding how risk and returns
could be managed and how implementing certain basic investment strategies could help
optimizing a portfolio. Although most models and theories were grounded and derived from
the stock markets (listed funds) the main principle could be applied in the real estate market
for non-listed funds as well, if only to a lesser extent.




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An analytical study assessing the principles of a country allocation decision model              2
                                                          Executive summary
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          In order to develop the CADM, the weighted factor score method was selected and
then modified so that it consisted of two sets of criteria (country and feasibility) to which a
country must comply in order to form part of the in the country allocation. By constructing the
CADM in such an order, an allocation can be constructed which is based on theoretical as
well as practical understanding. By means of testing the model by comprising two sample
country allocations for two opposite fund strategies the validity of the CADM could be
determined. After performing the two country allocations it was concluded that the validity of
the CADM was achieved, because it demonstrated that the CADM can be applied for funds
with different fund characteristics and strategies and that the final geographical allocation is
based on this input. The strengths of the CADM lie in the fact that all steps of the decision
process that ultimately lead to a geographical allocation are visible and comprehensible to
both the decision makers (i.e. the fund management) as well as external parties (e.g. fund
investors and analysts.) With these results the country allocation decision model was judged
as valid.
          The approach of intertwining the knowledge of the institutional investment market and
the logistics and real estate industry turned out to be incredibly valuable. Not only did the
combination of these factors make the selection process more accurate, it also made it more
robust since it incorporate both the supply and demand side of both the investment world and
the logistics real estate industry. As far as the usefulness of the outcome of the CADM, it
should always be perceived as a tool that can facilitate the allocation process rather then
providing the factual allocation. Because the results of the CADM are based on assumptions
regarding correlations and historical and future data, an allocation range was added to the
CADM in order to nullify these factors. Another advantage of adding a range to the final
allocation is that is provides leeway during the execution of the allocation, therefore allowing
the fund to utilise the most beneficial circumstances in each country in a specific period of
time.
          As more data becomes available over time due to the increasing professionalism of
the real estate markets, quantitative analyses will be less difficult to perform and the CADM
will become increasingly accurate.




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An analytical study assessing the principles of a country allocation decision model          3

				
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