REAL ESTATE DEVELOPMENT DECISIONS UNDER THE RISK AND
UNCERTAINTY
Raimonda Martinkutė, Aleksandras V. Rutkauskas
Vilnius Gediminas technical university, Lithuania
Produced real estate forms almost the half of Lithuanian national worth, and tangible asset
(produced and non-produced real estate) forms almost 90% from the whole national worth. It is
obvious, that management of tangible asset is the basis of country’s economy management, and
economy development strategy must be related with strategies of real estate development. In
addition, modern risk management theory insists that successful risk management may increase the
effectiveness of country’s financial and other resources by 15-20%. So the real estate development
strategy, supported by economical risk management mechanism, should become the main factor of
stabile economical growth of country.
In this article development possibilities of the real estate investment strategy as the main real
estate management mean under risk and uncertainty will be investigated. Possibilities of risk
evaluation in the processes of investment strategy preparation and realisation are revealed through
analysis of concrete situations.
1. About the necessity to deal with uncertainty
John Kenneth Galbraith writing in the 1970s called the latter part of the twentieth century The
Age of Uncertainty (Galbraith, 1977). His theme was to “contrast the great certainties in economic
thought in the last century with the great uncertainty that problems are faced in our time”. Once this
uncertainty is accepted as being, as it were, in the nature of things, it is easily seen that those who
enter into ventures that depend upon future outcomes have to come to terms with it. One such group
of people are those who control business ventures. Consequently it is not surprising to find that it is
in this area of activity where attempts have been made to develop a theory of decision-making that
copes with uncertainty. Decision analysis has now become well established part of the curricula of
business schools and the like, although it is fair to say that to date the basis of that theory has tended
to support a mostly rational/quantitative methodology. These ideas are only beginning to gain more
general acceptance, particularly with the development of techniques such as scenario analysis and
more recently and still controversially, fuzzy analysis.
At first sight it might be supposed that this body of theory and practice would have been taken
up enthusiastically by those concerned with the development of land and buildings. After all,
uncertainty lies at the root of the process of property development, which is essentially concerned,
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with the manufacture of a product in anticipation of an unknown future demand. Indeed, if it were
not for the constraint upon supply imposed by the system of town planning, it would rank as one of
the most speculative of activities, involving as it does the investment of relatively large amounts of
capital into a product that is fixed both in time and space. Yet the property development industry
has largely ignored the methods of formal decision analysis adopted extensively in other industries
(see for example Marshall and Kennedy, 1992).
2. Understanding the process of property development
Even when related specifically to property, “the development process” means different things to
different people. To some it is simply the construction of buildings, a physical process of
production. To others it is essentially a part of a social and political process, involving the
distribution and control of resources.
Although there is no model of the development process that can be applied universally, for the
purpose of our study, which is principally the investigation of uncertainty and risk, we can divide
the process into three parts as follows:
1. Acquisition
2. Production
3. Disposal
The first part of the process comprises the acquisition of the land upon which the development
is to take place and the acquisition of the appropriate planning permission. The second part
comprises the construction of the building or buildings and the third part comprises their disposal
both for occupation and investment. As the process takes place, the developer's knowledge of the
likely outcome increases but at the same time, the room for manoeuvre decreases. Thus, while at the
start of the process developers have maximum uncertainty and manoeuvrability, at the end they
know all but can do nothing to change their product, which has been manufactured on an essentially
once and for all basis. The process is especially susceptible to risk and uncertainty because, once
started, it is relatively fixed in time and place and because it aims at a very narrow consumer
market.
During the first part of the process, the period of acquisition, the uncertainties are of three main
types: the physical characteristics of the land, the characteristics of tenure, including restrictive
covenants and casements both in favour of and against the land, and the nature and extent of use
that the local planning authority will permit. Most developers will attempt to identify and determine
all these factors before committing themselves to the purchase of the land. Land acquisition cost is
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often the first major commitment of capital and as it comes at the start of the development process it
is then like a snowball, accumulating interest throughout the remainder of the development.
During the second part of the process, the period of production, the main element of uncertainty
is the cost of construction. This factor, which represents the second major capital commitment, is
substantially determined at the start of the building contract with the builder. However, nearly in all
cases there will be some element of fluctuation allowed in the contract and, in any event, the
phasing of the construction and the length of the building period can never be fully determined at
the outset.
The third part of the process, the period of disposal, can be seen as comprising both the disposal of
the building to one or more occupiers and its disposal as an investment.
The process that transfixes all the components of real estate development is investing. More
over, effective investment strategy is the main instrument for the successive real estate
development. And finally, investing is the most widely exposed to risk development activity.
Further we discus some possibilities how to prepare and realise investment strategy under the risk.
3. Preparation and realisation of investment strategy under the risk
3.1. The real estate investment process as jumping-of investment strategy preparation
In management engineering the category of strategy is used for both to impress the importance
of analysed purposes, criterions, assumptions and means and to designate the function, that depends
on current information and gains the means from set of possible alternatives. So if we treat strategy
as the whole of rules for achievement of system’s strategic purposes using strategic means, then the
real estate investment strategy should be perceived as the achievement of strategic investment
purpose. This purpose consists of the maximisation of investment value, choosing between
alternative investment sources and utility maximisation.
The real estate investment process (Figure 1) is the main mean for strategy preparation and
should be analysed using probabilistically arranged information.
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Figure 1. Real estate investment process
Step 1: Identify investor’s objectives, goals, and constraints
Risk-return
preferences
Wealth
Step 2: Analyze investment climate and market conditions
Market analysis
Legal environment
Sociopolitical
analysis
Step 3: Develop financial analysis
Operating
decisions
Financing
decisions
Reversion
decisions
Income taxation
Tax planing
Wealth taxation
Step 4: Apply decision – making criteria
Rules of thumb
techniques
Discounted cash
Traditional
flow techniques
appraisal methods
Step 5: Investment decision
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Data, characterising the realisation of chosen real estate development strategy is presented in
Table 1: the price of investment, indicators of exploitation of investment, sources and conditions of
finance, selling price of investment, indicators of dependence and interaction between factors and
indicators of investment efficiency. In many cases the presumption is made that data, presented in
Table 1, is sufficient for description of strategy. Indeed, this data is the result of consistent and
comprehensive research of external and internal environments. A lot of information about various
factor’s impact on investment process and about results of interaction between investment purposes,
possibilities, means and consequences after choosing the strategy is accumulated in this research.
Really, a traditional point of view into investment process as deterministic doesn’t create
presumptions for taking into account some strategic factors of investment process such as risk and
uncertainty. The purpose of this article is to take into consideration the impact of uncertainty of
separate parameters, dependencies and restrictions on the results of investment strategy realisation.
As we can see from Table 1, the data in Columns 2-4 is arranged differently than the data in the
first column. The data, presented in Columns 2-4, which can’t be described in deterministic manner
(the rent, the change of operating costs, the interest rate of first mortgage, selling price of
investment, discount rate of expected incomes) is defined as probability distributions. Such way of
definition of possible meanings reflects the fact, that investment process is perceived as
probabilistic process. This fact must be taken into account.
3.2. The real estate investment strategy, based on probabilistic standpoint at investment
process
In the traditional description of strategy, where investment process is understood as
deterministic process, there are three possibilities: pessimistic, realistic and optimistic. After
making the assumption that each of these three possibilities may occur with determined
probabilities, it is affirmed that probabilistic case of strategy realisation is chosen. But such a point
of view has few contradictions. The first contradiction is the excluding of future possibilities. Of
course, the perception and choosing of pessimistic or optimistic possibilities do not excite any
problems or doubts. Pessimistic possibility has the lowest value from chosen level of confidence
interval if the factor has possessive impact on indicators of investment’s efficiency and the biggest
value – if the factor has negative impact on the investment. In the case of optimistic possibility the
biggest value is chosen if the factor has positive impact on efficiency of investment.
Meanwhile, the selection and understanding of realistic possibility is problematical. What is the
realistic value of the factor? Practically, it is the average of pessimistic and optimistic values. But it
is true only in the case of symmetrical distribution.
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However, main reproaches may be declared against presumption that pessimistic, realistic and
optimistic values of economical indicators of investment are obtained when all the factors have
pessimistic, realistic and optimistic variants accordingly. Of course, the probability of such
coincidence is zero. Indirect evidence of such proposition may be the circumstance, that when
pessimistic and optimistic values of separate investments’ factors are comparatively compatible,
optimistic and pessimistic values of received indicators of investment efficiency can’t be treated as
separate possibilities of the same investment.
So the natural way of determination of possibilities of investment indicators should refer to
assumption about analysis of interaction between factors, taking into account their possible
interdependency. Of course, such analysis of investment possibilities demands purposeful
preparation of information and absolutely new technique for decision making.
3.3. The comparison of strategies and analysis of results
In this section of article we’ll try to compare traditional variant of strategy (first column) with
probabilistic variants (second-fourth columns).
Table 1. Triplex example with a first and second mortgage
Variants
The
table
of
1
2
3
4
exogenously
Under point
Under statistical
Under line
Under log-normal
forecasted data
forecasting
independence of
dependence of
distribution of
factors
factors
factors’ possibilities
95 000 LTL
95 000 LTL
95 000 LTL
95 000 LTL
Rent
350
N(350;3,5)
N(350;3,5)
LN(a=350; σ=3,5)
Annual increase of
0,05
0,05
0,05
0,05
Number of units
3
3
3
3
Coefficient of
0,3
0,3
0,3
0,3
5%
N(0,05;0,001)
N(0,05;0,001)
LN(a=0,05;
The price of triplex
dwelling
rent
operating expenses
Increase of operating
σ=0,001)
expenses
Holding period
27,5 years
27,5 years
27,5 years
27,5 years
Depreciation
0,85
0,85
0,85
0,85
First mortgage
70000 LTL
70000 LTL
70000 LTL
70000 LTL
First mortgage
12%
N(0,12;0,01)
N(0,12;0,01)
LN(a=0,12;
Financing:
interest rate
σ=0,01)
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First mortgage
20 years
20 years
20 years
20 years
Price of mortgage
0,04 of sum
0,04 of sum
0,04 of sum
0,04 of sum
Financing expenses
2800 LTL
2800 LTL
2800 LTL
2800 LTL
Refusal costs
0,06 of sum
0,06 of sum
0,06 of sum
0,06 of sum
Second mortgage
10000 LTL
10000 LTL
10000 LTL
10000 LTL
Payments from
1500 LTL annually
1500 LTL annually
1500 LTL annually
15 00 LTL annually
after 3 years
after 3 years
after 3 years
after 3 years
Tax rate
0,28
0,28
0,28
0,28
Expected selling
140000
N(140000; 700)
N(140000; 700)
LN(a=140000;
maturity
of first mortgage
second mortgage
Repayment from
second mortgage
σ=700)
price
Selling expenses
0,08
0,08
0,08
0,08
Income discount rate
0,11
N(0,11;0,001)
N(0,11;0,001)
LN(a=0,11;
σ=0,001)
Matrix of factors
–
Cii = 1
Cii = 1
Cii = 1
Cij = 0, i≠j
Cij = 0,3, i≠j
Cij = 0, i≠j
5 years
5 years
5 years
5 years
2160,3
N(2109; 2189)
N(2132; 2374)
LN(a=2501;
interdependency
Property holding
period
The table of
endogenously
forecasted data
Net present value
σ=2480)
(NPV)
Internal rate of return
(IRR)
13,08%
N(0,1297; 0,0180)
N(0,1298; 0,0174)
LN(a=0,1313;
σ=0,0207)
Lets examine four cases, shown in Table 1:
1. Exogenously forecasted indicators of strategy are defined in deterministic manner.
2. Five exogenous variables (rents, rate of growth of operating costs, interest rate for the first
mortgage, selling price of investment, discount rate of income) are defined using their possible
probability distributions. In this case distributions are normal. Other indicators are the same as
in the first column.
3. Five variables, mentioned in the second case are not only normally distributed, but also
statistically interdependent (Cii= 1, Cij= 0,3, i≠j).
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4. The same five variables are not statistically interdependent, but they have log-normal
probabilistic distribution.
Geometrical view of probability distribution for main endogenous characteristics (NPV and
IRR) possible meanings is shown in Figure 2.
Data, presented in the first column of Table 1, can serve only as illustration of investment
process, because we can form the view of real possibilities only after making some additional
presumptions. The data presented in Columns 2-4 may be used as the realisation of these
possibilities. The data in the second column and Figure 2a shows the possibility distribution of NPV
and IRR. From the third column of Table 1 and Figure 2b we can make the conclusion that it is very
important to take into account statistical dependence of separate factors. This dependence may
become the object of management because of the purpose of economical benefit. If the difference
between the data, presented in Figure 2b and in Figure 2a is the function of controlled processes, so
the difference between data in Figure 2c and Figure 2a is predetermined by the formation of
different forms probability distributions. The comparison shows that this difference is quite a big so
any search of its management possibilities is necessary.
Now lets analyse investor’s utility function, which has the same shape as T. F. Knight used
it in 1921. In the case of our investment its concretisation should be such as depicted in the figure
3b. Two utility functions u1(x) and u2(x) are shown in this figure and we can see that the second
from them - u2(x) has higher reaction at possible decrease of cash flow under expectation or higher
reaction on risk. However, speaking about possibility to define utility as point estimated curve is
very conventional. Really investor can describe his utility as casual function. Stochastic image of
u1(x) is presented in figure 3c. In this figure u1(x) by itself serves as the curve of average of values.
Three utility values U1, U2, U3, generated from utility function u1(x), are shown in figure 2b. Their
quantity depends on probability distributions p1(x), p2(x) and p3(x) of net present values of cash
flows, taken from figure 2. EU value (fig. 2c) would be the same with EU1, EU2 and EU3 if the
utility were evaluated according to average line. But average line is not suitable for representation
of utility possibilities. So more adequate criterions are necessary.
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Figure 2. Separate variants of real estate development strategy
NP
Vnorm
al;distribution:Norm
al
IRRnorm
al;distribution:Norm
al
M=2109;S
D=2189
M=0,1297;S
D=0,0180
Chi-S
quare:6.130764,df=8,p=.6325884(dfadjusted)
130
130
120
120
110
110
100
100
90
90
80
80
70
70
60
60
Noofobs
Noofobs
Chi-S
quare:13.57508,df=9,p=.1383187(dfadjusted)
50
50
40
40
30
30
20
20
10
10
0
-5000
-3000
-1000
1000
3000
5000
7000
9000
0
0,07
E
xpected
Category(upperlim
its)
0,09
0,11
0,13
0,15
0,17
0,19
E
xpected
Category(upperlim
its)
NP
Vunderdependenceoffactors;distribution:Norm
al
IRRunderdependenceoffactors;distribution:Norm
al
M=2132;S
D=2374
M=0,1298;S
D=0,0174
Chi-S
quare:4.913710,df=6,p=.5549363(dfadjusted)
Chi-S
quare:3.265830,df=7,p=.8593616(dfadjusted)
160
140
130
140
120
110
120
100
90
100
80
70
Noofobs
Noofobs
80
60
60
50
40
40
30
20
20
10
0
-8000 -6100 -4200 -2300 -400 1500 3400 5300 7200 9100 11000
E
xpected
0
0,070,080,090,100,110,120,130,140,150,160,170,180,190,20
Category(upperlim
its)
E
xpected
Category(upperlim
its)
NP
Vlognorm
al;distribution:Norm
al
IRRlognorm
al;distribution:Lognorm
al
M=2501;S
D=2480
M=0,1313;S
D=0,0207
Chi-S
quare:18.32544,df=8,p=.0189384(dfadjusted)
Chi-S
quare:8.167499,df=8,p=.4173083(dfadjusted)
130
160
120
140
110
100
120
90
80
100
70
80
Noofobs
Noofobs
60
50
40
60
30
40
20
10
20
0
-6000
-2400
-4200
1200
-600
4800
3000
Category(upperlim
its)
8400
6600
12000
10200
E
xpected
0
0,070 0,089 0,108 0,127 0,146 0,165 0,184 0,203 0,222
E
xpected
Category(upperlim
its)
9
3a
NP
Vnorm
al;distribution:Norm
al
NPVunderdependenceoffactors;distribution:Norm
al
M=2109;S
D=2189
NP
Vlognorm
al;distribution:Norm
al
M=2132;SD=2374
Chi-S
quare:13.57508,df=9,p=.1383187(dfadjusted)
M=2501;S
D=2480
Chi-Square:4.913710,df=6,p=.5549363(dfadjusted)
130
Chi-S
quare:18.32544,df=8,p=.0189384(dfadjusted)
160
130
120
120
140
110
100
110
100
120
90
90
70
70
80
50
60
Noofobs
Noofobs
60
60
40
20
10
10
-3000
-1000
1000
3000
5000
7000
E
xpected
9000
0
-8000 -6100 -4200 -2300 -400 1500 3400 5300 7200 910011000
Category(upperlim
its)
40
20
20
0
-5000
50
30
40
30
0
-6000
Expected
-2400
-4200
Category(upperlim
its)
1200
-600
4800
3000
8400
6600
12000
10200
E
xpected
Category(upperlim
its)
3b
8000
6000
4000
2000
y(u)
Noofobs
80
100
80
u2(x)
0
-4000
-2000
-2000 0
2000
4000
6000
8000
u1(x)
bisector
-4000
-6000
-8000
-10000
x (cfo)
3c
8000
6000
4000
2000
0
-4000
-2000
-2000
0
2000
4000
6000
8000
-4000
-6000
-8000
-10000
Figure 3. The scheme of criterion selection on the base of utility functions
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Conclusions:
1. Including risk and uncertainty into processes of strategy preparation and realisation is the most
important mean for improvement real estate investment strategy.
2. The preparation and realisation of investment strategies, where investment processes is
understood like probabilistic, help to take into account possibilities of separate subject to choose
an investment, to realise investment strategy and to evaluate the impact of risk on investment
efficiency.
3. Adequate risk management strategy could considerable improve efficiency of resources
involved e.g. financial resources.
4. Invisible factors, such as statistical interdependence between indicators of investment efficiency
and distribution differences between these indicators has an appreciable impact on the whole
efficiency of investment.
Literature
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investment strategy. Fourth edition. USA: Prentice Hall Press. 1985.
2. Rutkauskas A.V., Rutkauskas V. Adekvataus pelno galimybių nevienareikšmiškumui investicijų
portfelio sudarymas // Ekonomika, 2000, № 52, psl. 62-83.
3. Galbraith J.K. The age of uncertainty. London: BBC and Andre Deutsh Ltd. 1977.
4. Marshall P. and Kennedy C. Development valuation techniques // Journal of property valuation
and investment, 1992, № 11(1), p. 57-66.
5. Gerald R. Brown, George A. Matysiak. Real estate investment. A capital market approach.
England: Financial Times Prentice Hall, 2000.
6. Haugen R. A. Modern investment theory, 3rd edn. Englewwod Cliffs, NJ: Prentice Hall, 1993.
7. Liu C., Hartzell D., Grisson T., Grieg W. The composition of the market portfolio and real
estate investment performance. AREUEA Journal 18, p.49-75, 1990.
8. Lusht K. M. Real estate valuation. Chicago: Irwin. 1997.
9. Spaudling D. Measuring investment performance. New York: McGraw-Hill. 1997.
10. Knight F. H. Risk, Uncertainty and Profit, Houghton Mifflin. Boston and New York, 1921.
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