Real estate abstract
The method discloses a rule-based decision process which formulates
an investment strategy in terms of short term debt, long term debt,
short term equity, and/or long term equity for a variety of property
types and geographic markets. The first phase of the method achieves
a visual representation of the condition of each of a selected territory's
major markets, showing market direction and volatility determined
on the basis of commercially available market research data which
has been adjusted by the investing entity in light of actual local
experience in the market. The second phase deals with the implications
of the first phase results on four possible alternative investment
types, namely, short term debt, long term debt, short term equity,
and/or long term equity. This is accomplished by formulating a set
of decision rules which enable the individual investors of the investing
entity to uniformly evaluate specific types of investment for each
property type in a respective market area. The result is again graphically
portrayed so that the investing entity can easily formulate an actionable
real estate investment strategy expressed in terms of investment
types (namely, short term debt, long term debt, short term equity,
and/or long term equity), for each market/property pair.
Real estate claims
What is claimed is:
1. A method for formulating a real estate investment strategy,
comprising the steps of: receiving market data for at least one
market/property pair from at least one data source, wherein said
market/property pair represents a respective combination of a strategic
market area and a property type; analyzing said received market
data so as to develop at least one respective value for each said
market/property pair; determining at least one trend indicator corresponding
to each said at least one respective value; representing said at
least one respective value graphically as respective first graphic
representations, said respective first graphic representations including
graphic symbols selected, ordered, oriented, and positioned on a
nine-product risk/reward matrix according to said at least one respective
values and said at least one trend indicators; receiving local market
data corresponding to said at least one market/property pair; adjusting
said respective at least one first graphic representations in terms
of the received local market data to yield respective locally adjusted
first graphic representations; formulating a set of decision rules,
said decision rules being operable for analyzing said respective
locally adjusted first graphic representations in terms of short
term debt, long term debt, short term equity, and long term equity;
analyzing said respective locally adjusted first graphic representations
in terms of said decision rules to yield respective investment rank
values; and representing said respective investment rank values
as corresponding respective second graphic representations including
graphic symbols selected, ordered, oriented, and positioned on a
four-product short term-long term/debt-equity matrix according to
said respective investment rank values, wherein said respective
second graphic representations form the basis for selecting a real
estate investment strategy.
2. The method as set forth in claim 1, further comprising the step
of adjusting said respective investment rank values in terms of
existing market exposure.
3. The method as set forth in claim 1, wherein the step of selecting
a real estate strategy comprises for each said market/property pair
the step of determining whether to pursue an investment type selected
from the group of short term debt, long term debt, short term equity,
and long term equity investment types.
4. The method as set forth in claim 1, wherein said property type
comprises at least one of a group comprising office, industrial,
retail, and domestic property types.
5. The method as set forth in claim 1, wherein said at least one
data source is a commercial market research company.
6. The method as set forth in claim 5, wherein said market data
is represented in a known econometric model driven by demographic
metrics which enables projections of changes in at least supply/demand
and vacancy rate, resulting changes in NOI/capital value, and derived
market return driven by demographic metrics.
7. The method as set forth in claim 1, wherein the step of analyzing
further comprises analyzing at least one risk value, return value,
and trend of the return value.
8. The method as set forth in claim 7, wherein the at least one
risk value is defined as historical volatility of the unlevered
returns, as measured by standard deviation, and the at least one
return value is defined as expected five year unlevered return.
9. The method as set forth in claim 1, wherein said graphic symbols
comprise an up-arrow, a down-arrow, and a double-headed, sideways-arrow
corresponding respectively to an up-trend, a down-trend and an unchanging
trend.
10. The method as set forth in claim 9, wherein said respective
investment rank values each represent a degree of investment interest
and said corresponding respective second graphic representations
each comprise a gradation of shading selected from a series of shading
including a first shading level indicating weak investment focus,
a second shading level indicating medium investment focus, and a
third shading level indicating strong investment focus.
11. The method as set forth in claim 10, wherein in an upper right
corner of said nine-product risk/reward matrix said up-arrow is
represented by a first 2.times.2 matrix of squares in which left
top and bottom matrix squares have said first shading level and
the right top and bottom squares have said third shading level,
the sideways-arrow is represented by a second 2.times.2 matrix of
squares in which all left and right top matrix squares and a left
bottom matrix square have said second shading level and a right
bottom matrix square has said first shading level, the downward
pointing arrow is represented by a third 2.times.2 matrix of squares
in which top right and left matrix squares have said second shading
level and bottom right and left matrix squares have said first shading
level, wherein in an upper left corner of said nine-product risk/reward
matrix said up-arrow is represented by a fourth 2.times.2 matrix
of squares in which all matrix squares have said third shading level,
the sideways-arrow is represented by a fifth 2.times.2 matrix of
square in which top left and right squares and a left bottom square
have said third shading level, and a right bottom square has said
second shading level, the down-arrow is represented by a sixth 2.times.2
matrix of squares in which left and right top squares have said
third shading level and said left bottom square has said second
shading level and a right bottom square has said first shading level,
and wherein in a lower left corner and a lower right corner of said
nine-product risk/reward matrix said up-arrow, said sideways-arrow
and said down-arrow are represented by a seventh 2.times.2 matrix
of squares in which all squares have said third shading level.
Real estate description
BACKGROUND OF THE INVENTION
The present invention relates generally to a method for assessing
real estate investments, and more particularly, to a rule-based
decision process which formulates an investment strategy in terms
of short term debt, long term debt, short term equity, and/or long
term equity for a variety of property types and geographic markets.
There is a need for a consistent approach to assessing real estate
markets that identifies areas of opportunity and, conversely, of
caution. Often, market evaluations have been conducted on a deal-by-deal
basis, and business decisions made this way can be the result of
a tactical, rather than a strategic approach to investment analysis.
Moreover, within any investment decision making process, is not
uncommon for reasonable minds to differ on what factors contribute
to the formulation of a successful investment strategy. For example,
it is recognized that many believe that investment performance is
attributed primarily to the broader market, i.e., the quality of
investment decision primarily reflects the quality of the underlying
market. Others may hold a different view. Such controversy during
the investment strategy formulation process can be polarizing and
differing opinions about the underlying investment market can lengthen
the timing of the process and add complexity.
Thus, there is a need to reach consensus in advance of an investment
deal transaction. Such preliminary consensus needs to be reached
by having in place, a standard framework of decision rules and method
of applying those decision rules that is agreed upon, in advance,
by all parties proceeding through the investment decision process.
The framework would be used to analyze the condition and expected
trend of primary markets and property types. The steps of a process
within the framework need to include the identification of regional
and national trends and the systematic application of the pre-determined
decision rules to the trends and associated demographic data, so
that informed choices about where to focus marketing/sales effort
can be made.
BRIEF SUMMARY OF THE INVENTION
The method of the present invention is a two-phase process, in
which the first phase achieves a visual analytical representation
of the condition of each of a selected territory's major markets,
showing market direction and volatility. This view is determined
on the basis of commercially available market research data which
has been adjusted by the investing entity in light of actual local
experience in the market. The second phase deals with what implications
that performance has on four possible alternative investment types,
namely, short term debt, long term debt, short term equity, and/or
long term equity. The second phase enables the investing entity
to formulate an investment strategy for various investment types
for each property type in a respective market area. As a final step,
consideration is given to how the existing investment position of
the entity might further adjust the component elements of the investment
strategy.
Commercially available market research data can be generated by
sources internal to a given business enterprise, or accessed from
commercial market research and forecasting firms. One such commercial
research firm having a national reputation is Property & Portfolio
Research, Inc. (PPR), a Boston, Mass. based research firm, which
offers research and forecast data supportive of a quantitative approach
to real estate investment and application of modern financial theory.
PPR is an econometrics real estate group that predicts performance
in 240 markets (60 cities and four property types) across the United
States. The econometric model employed by PPR is a sophisticated
analytical tool, which generates projections of changes in supply/demand/vacancy
rate, resulting changes in NOI/capical value, and derived market
return, which is equivalent to investor's rate of return (IRR),
defined as current yield plus capital value change. Other commercial
marketing research and forecasting firms are also available and
would also cooperate with the present invention.
In the preferred embodiment, four property types, including multifamily,
office, retail and warehouse, are identified. Each property type,
being located in a specific geographic real estate market, forms
a market/property pair. Each market/property pair is ranked into
a nine-product risk/reward matrix on the basis of the application
of a set of decision rules which address various aspects of performance:
return (high/medium/low), trend (up/flat/down), and risk (high/medium/low
volatility). The ranked results are graphically displayed for subsequent
analysis.
In the second phase of the process, a set of decision rules which
determine whether, and to what extent, to pursue short term debt,
long term debt, short term equity, and/or long term equity for a
given market/property pair are formulated and each market/property
pair graphically portrayed in the first phase is ranked into a simplified
four-product matrix on the basis of the application of the set of
decision rules. This is accomplished by a systematic application
of a set of rules to the contents of each "box" of the
nine-product matrix. The result is again graphically portrayed so
that the investing entity can easily formulate an actionable real
estate investment strategy expressed in terms of investment types
(namely, short term debt, long term debt, short term equity, and/or
long term equity), for each market/property pair.
BRIEF DESCRIPTION OF THE DRAWINGS
FIG. 1 shows the two-phase process of the present invention;
FIG. 2 shows an example 3.times.3 risk/reward matrix, according
to the present invention;
FIG. 3 shows the 3.times.3 risk/reward matrix of FIG. 2, applied
to four property types located in a number of different metropolitan
statistical areas, according to the present invention;
FIG. 4 shows the framework of the second phase in the form of a
simplified, four-product debt/equity-short/long term matrix, according
to the present invention;
FIG. 5 shows a nine-product risk/reward decision rule matrix, according
to the present invention.
DETAILED DESCRIPTION OF THE INVENTION
FIG. 1 shows the method 100 of the present invention as including
a two-phase process having a first phase 110 and a second phase
210. The first phase 110 achieves a visual representation of the
condition of each of a selected territory's major property/market
pairs, showing market direction and volatility. It is a view of
the real estate market performance in terms of real estate ownership.
This view is determined on the basis of commercially available market
research data which has been adjusted by the investing entity in
light of actual local experience in the market. The second phase
210 deals with what implications that performance has on four possible
alternative investment types, namely, short term debt, long term
debt, short term equity, and/or long term equity, and enables the
investing entity to make a selection of a specific investment type
for each property type in a respective market area.
In Step S1 of the first phase 110, the investing entity obtains
market demographics, risk/reward and projected trend data from a
commercially available real estate market research and forecasting
source 114. In the calculation of the preferred embodiment, 240
market/property pairs are considered to comprise a statistically
significant, large population. Such data is represented in a known
econometric model, which enables projections of changes in supply/demand
and vacancy rate, resulting changes in NOI/capital value, and derived
market return, which is equivalent to IRR, defined as current yield
plus capital value change. This model is driven by relationships
among demographic metrics, available from a variety of sources over
a fifteen year history, which has been correlated with historical
real estate performance.
The commercially available demographic metrics include population/employment
growth, employment by SIC code, unemployment, inflation, and sales.
The history data and forecasts based on an econometric model include
supply (contract awards, stock, depreciation), demand (population
growth, employment growth/SIC concentration), vacancy rate (historical
data, future projection based on supply/demand changes), and NOI/capital
value changes (proxy based). Subjective variables for "intensity
of use of office space", forecast construction, and depreciation
are also used.
FIG. 2 shows an example 3.times.3 risk/reward matrix 116, which
includes "Risk" on the vertical axis 118 and "Return"
on the horizontal axis 119 of the matrix. Optionally, other size
matrices and investment parameters can be used. "Risk"
is defined as historical volatility of the unlevered returns, as
measured by standard deviation and adjusted during the review process
110. "Return" is defined as the expected five year unlevered
return, i.e., the expected IRR from buying without any financing.
Values begin at the lower left corner as "low" and range
to "high" in directions leading up, and also to the right.
Thus, a high risk, high return value would be graphically represented
by a symbol 120 located in a determined position 121 in the upper
right block of the 3.times.3 matrix 116. Advantageously, the symbol
120 is an arrow pointing in the direction of the market trend, as
determined by market research data provided by market resource 114.
This scheme therefore includes three possible arrows, including
upward 122, double-headed sideways pointing arrows 123, and downward
124.
Referring again to FIG. 1, in step S2, the investing entity analyzes
the risk, the return, and trend of the return data for property
types within a major strategic market area. For example, in the
preferred embodiment, the major strategic area is a metropolitan
statistical area, four property types are identified as multifamily,
office, retail and warehouse and the graphic symbol is an arrow.
Other definitions for major strategic area and property type are
also possible. As will be described later in connection with steps
S5 and S6, the assumptions made by the commercial market research
data source are examined in terms of local market data inputs, and
the analysis is adjusted, as necessary.
The measure of risk used in the present invention is the standard
deviation of return and preferably is calculated over a 5-year projected
period. For each measured property of the 240 market/property pairs,
a corresponding 3.times.3 matrix 116 is arranged such that the X-axis
(Risk) 119 of the matrix is scaled in levels of standard deviation,
and the Y-axis (Reward) 118 is scaled as derived market return or
IRR. The scale for the X-axis is defined such that two standard
deviation values are identified such that 1/3 of the standard deviation
values for the 240 market/property pairs fall below the lower standard
deviation value, 1/3 fall between the lower and higher values, and
1/3 fall above the higher standard deviation value. For example,
the Risk scale can be defined such that 1/3 of the standard deviation
values fall below the 5% standard deviation, 1/3 fall between 5%
and 10% standard deviation, and 1/3 fall above 10% standard deviation.
Thus, for a given measured parameter, using an arrow symbol, each
point is plotted in the 3.times.3 matrix in terms of the where the
standard deviation falls along the X-axis (high/medium/low volatility).
Likewise, the scale for the Y-axis is defined such that two investor's
rate of return (IRR) values are identified such that 1/3 of the
IRR values for the 240 market/property pairs fall below the lower
IRR value, 1/3 fall between the lower and higher values, and 1/3
fall above the higher IRR value.
In step S3, the direction of the arrow symbol 120 is determined
by examining the trend in return over the period of time, and in
step S4, that trend is symbolized by arrow 122, 123 or 124 (up/flat/down)
on a position 121 of matrix 116. The return is the average 5-yr
IRR, but more practically, the annual values that comprise the 5-yr
average are examined to determine if the values for Return are increasing
year by year over that period of time, remaining the same, or downward
trending. For example, for arbitrary values 10 5,6,7,8,9, the average
is 7, and therefore a point is plotted at 7 and shown as an up-arrow.
If the values are 7,7,7,7,7, a flat arrow is plotted, and for values
of 9,8,7,6,5, a down-arrow is plotted.
In step S5, which, as a practical matter, is more reasonably performed
earlier, the investing entity obtains local market data 115 corresponding
to respective market/property pairs. This includes knowledge of
local facts of which a nationwide market research firm may not be
aware, such as, for example, specific developer plans, actual housing
starts, changing commercial demographics such as an expected closing
(or arrival) of a large employer.
In step S6, once all market/property pairs have been plotted, the
investing entity evaluates a number of the key factors that have
lead the commercial market research entity to the obtained results,
and which have been plotted. The investment entity compares those
key factors with the local experience, knowledge and estimates obtained
in step S5, and then subjectively adjusts the plotted location or
trend symbol of the plotted market/property pair. For example, the
market researcher may have arrived at a very high reward for a given
market/property pair, for example, apartments in Orlando, Fla.,
because the researcher assumed in its econometric model that there
will be very few new apartment starts, and therefore an ongoing
low supply of new apartments with correspondingly high prices. However
local knowledge of the Orlando apartment market may include information
about specific, new development contracts and local investor interest
that will lead to completion of housing units over the projected
5-year term. With this local input in hand, the investing entity
subjectively adjusts a plot point according to local experience.
For an apartment market/property pair, the plot of which is in the
upper right corner, which signifies high Risk, high Reward, may
be adjusted to a Medium Risk, High Reward, or alternatively, if
knowledge about trend indicates a change in direction of magnitude,
the direction of an arrow symbol may be changed.
FIG. 3 shows, as a non-limiting example, the 3.times.3 risk/reward
matrix 116 applied to four property types located in a metropolitan
statistical area. Each property type is represented by an individual
matrix, including "Apartments" matrix 125, "Retail"
126, "Office" 127 and "Warehouse" 128. Multiple
instances of arrow symbols 120 (typical) are shown, each representing
respective market/property pairs. Arrow symbols 120 are shown as
each representing a separate market/property pair. For instance,
the warehouse property type located in Orlando, Fla. is represented
by arrow symbol 120A in matrix 128. The specific sideways-pointing
aspect of arrow 120A indicates that the investment return trend
for the warehouse market in Orlando is neither up, nor down.
The diagonal threshold line 135 in each matrix 125-128 represents
an exemplary arbitrary dividing line between favorable and unfavorable
reward. Any such boundary may be selected by the investor, however
it is important (from a consensus viewpoint) that this be determined
in advance of ongoing evaluations of market/property pairs. Arrow
symbol 120 for a particular property type located on line 135 represents
the instance in which risk equals reward, which generally is thought
to be a suitable investment. A symbol 120 falling to the left of
line 135 represents a favorable reward/risk ratio, i.e., the reward
is better than the corresponding risk. A symbol 120 falling to the
right of line 135 represents an unfavorable reward/risk ratio, i.e.,
the reward is less than the corresponding risk. Typically, the investor
would choose to regard all blocks falling below threshold line 135,
however defined, as unattractive.
In FIG. 3, the lower, right corner is understood to be low reward,
high risk, and therefore an investment decision in connection with
a market/property pair in the lower-right block would be one of
caution, also termed "selective". The same logic applies
to the lower-middle and right-middle blocks, which also would be
"selective". It can be seen that these blocks are all
below diagonal line 135. The center box, being on line 135, is valued
by interpolation. The middle-high block (top row, middle column)
and left-middle block (left column, middle row), being above the
diagonal line 135 represent more positive investment choices. For
example, with reference to the above discussion of the Orlando,
Fla. warehouse market/property pair symbolized by arrow 120A, the
right column-middle block location of the arrow in matrix 128 is
indicative of a medium reward with high risk, and also happens to
fall below the exemplary arbitrary threshold diagonal line 135.
Steps S2-S6 are repeated until the first phase 110 of method 100
has been applied to each major strategic area under consideration.
In the preferred embodiment, the resulting four matrices, shown
in example form in FIG. 3, graphically indicate the outlook for
unlevered equity returns by metropolitan statistical area and property
type over the next 3-5 years, together with volatility and trend.
It is apparent that the risk/reward matrix, as exemplified by matrices
124, 126, 128 and 130, is a compact visual representation of the
condition of each of the territory's major markets, where they are
headed, and how volatile they tend to be. Although seemingly simple
in appearance, significant amounts of complex and varied data are
incorporated in, and represented by, the easily understood and comprehensive
form shown in FIGS. 2 and 3. The simplicity of form lends to the
decision process necessary for management of a complex real estate
portfolio.
It will be recalled that the objective of first phase 110 is to
indicate how the real estate properties will perform in the corresponding
market, as expressed graphically in terms of a risk/reward and trend
profile for each property/market pairs, as exemplary illustrated
in FIGS. 2 and 3. In the second phase 210, the investment entity
wants to determine what its appetite will be for making one of four
investment options, or investment types, for each of those performing
market/property pairs. The investment entity wants to determine
how, and if, it should invest in one of four investment types, namely,
short term debt, long term debt, short term equity, and/or long
term equity for each of the performing market/property pairs illustrated
in the first phase 110.
In step S7 (second phase 210), the investing entity formulates
a set of decision rules that enables the investor to determine what
investment type to pursue (i.e., short term debt, long term debt,
short term equity, and/or long term equity) and to what degree a
given investment type is pursued for each of the four property types
(i.e., in the preferred embodiment, apartment, retail, office or
warehouse). The process of generating decision rules is one of deciding
on rules which embody the investment policies and investment theory
of the investing entity. In step S7, the investing entity determines
what specific investment strategy should be followed in light of
the portrayal of the market/property pairs developed in first phase
110. To accomplish this, a pre-determined set of decision rules
must be established, which are acceptable to all investor-members
of the investing entity. The decision rules determine for a given
property type residing in a given market, how different investment
types (namely, short term debt, long term debt, short term equity,
and/or long term equity), which have that underlying property market
as collateral to that investment, will be selected.
For example, a market/property pair such as Orlando, Fla. apartments,
that has a very high return, high risk, would not be an equally
suitable investment in terms of each of the four investment types.
A market with high return and high risk, would be a good equity
investment, however, the debt investment would likely be less preferable
because the high volatility is a stronger consideration in making
a debt investment. In that case, the lender would get the downside
risk/reward, but none of the upside risk/reward. Similarly, if a
property/market pair has a high risk/reward, but a downward trend,
it may be preferable for a short term equity bet, but not for the
long term, because it is trending down.
To accomplish this rule-generation process, a framework is established
for visually representing the ownership-oriented information graphically
portrayed in the first phase 110 in a form meaningful to the potential
investor. This framework will be described and then an exemplary
set of decision rules be will discussed in connection with the framework.
With reference to FIGS. 2 and 3, which show the 3.times.3 matrix
116 as including three possible direction-arrows, 122, 123, 124,
it can be seen that there are twenty seven possible decision rules
associated with a given market/property pair portrayed in matrix
116. (Nine blocks times three types of arrows.) These twenty seven
possibilities translate to four possible investment types for that
given property/market pair. This is further compounded by application
of these twenty seven times four occurrences over a number of property
types, resulting in a substantially complex set of data. The simplified
approach of the present invention deals with such complexity by
systematically applying decision rules to the data set and graphically
portraying the results for ease of analysis.
Rather than considering all nine boxes of the 3.times.3 matrix,
the method of the present invention focuses on the four corners
of the 3.times.3 matrix. The remaining five boxes can be informally
interpolated, as necessary. This reduces the possibilities to four
boxes times three possible types of arrows, or twelve decision rules,
as they relate to the four investment types, namely, short term
debt, long term debt, short term equity, and/or long term equity.
The interpolative process for arriving at values for the remaining
boxes can be a process of "informed guessing" by the experienced
user.
FIG. 4 illustrates the framework of the second phase 210 in the
form of a simplified, four-product matrix 132, which is useful for
illustrating the results of the application of the twelve possible
decision rules. This 2.times.2 matrix consists of "Debt"
and "Equity" variables arranged along the horizontal axis
134 and "Short" and "Long" variables arranged
along the vertical axis 136 of the matrix. The "Short"
variable is arbitrarily set at 3 years, although any period appropriate
to the investment principles employed by the investing entity will
do. Within the four squares of the matrix, any suitable symbol representing
degrees of investment interest is written or affixed, for example,
three degrees are selected as weak focus, medium focus and strong
focus. Any graphic symbolism can be utilized, for example, in the
preferred embodiment, gradations of shading from light to heavy
are employed, wherein light shading represents weak investment focus,
in which investment would be made on a "selective" basis,
shown in square 138, medium shading represents medium investment
focus, in which investment would be made on a "pursue"
basis, shown in square 140, and heavy shading represents investment
made on a "strong" basis, shown in square 142.
Referring again to the three types of arrows, "up" 122,
"sideways" 123, and "down" 124 of the first
phase of the present invention, a new graphic representation is
formed, which combines the information represented by the direction
of an arrow 120 with the information represented by the position
121 of arrow 120 within a particular square of the 3.times.3 risk/reward
matrix 116.
FIG. 5 shows a nine-product risk/reward decision rule matrix 144
which includes "Risk" on the vertical axis 131 and "Return"
on the horizontal axis 133 of the matrix. Matrix 144 includes the
three possible arrows 122-124 arranged in the upper and lower, left
and right, corners of the matrix. For any given application, arrows
corresponding to the remaining five boxes are also present, but
for clarity of description, they are omitted here.
The upper left corner of matrix 144 represents the high return/low
risk market, and the direction of the arrow represents the direction
of the trend in that particular market. In the preferred embodiment,
the decision rules are defined such that an upward pointing arrow
122 is represented by a 2.times.2 matrix 145 in which all four squares
are heavy-shaded. The sideways pointing arrow 123 is represented
by a 2.times.2 matrix 146 in which all squares are heavy-shaded
except for the lower right square, which is medium-shaded. The downward
pointing arrow 124 is represented by a 2.times.2 147 matrix in which
the left and right top squares are heavy-shaded, the lwer righet
square is medium-shaded, and the lower right square is light-shaded.
Thus, for the downward arrow, the decision rule graphically portrayed
by the 2.times.2 matrix 147 indicates that for the Equity investment
type, a "strong" focus is indicated for the Short Term,
and for the Debt investment type, a "strong" focus is
indicated for the short term and a "Pursue" focus is indicated
for the long term.
Turning to the upper right corner of the 3.times.3 risk/reward
matrix 144, in the preferred embodiment, the decision rules are
defined such that the upward pointing arrow 150 is represented by
a 2.times.2 matrix 155 in which left top and bottom squares are
light-shaded and the right top and bottom squares are heavy-shaded.
The sideways pointing arrow 151 is represented by a 2.times.2 matrix
156 in which all squares are medium-shaded except for the light-shaded
square at the lower right. The downward pointing arrow 152 is represented
by a 2.times.2 matrix 157 in which the top right and left squares
are medium-shaded and the bottom right and left squares are light-shaded.
Turning to the lower left and right corners of matrix 144, in the
preferred embodiment, a decision rule is established in which the
bottom 1/3 of the Reward scale is determined to be below a certain
minimum threshold of acceptability for investment purposes. As a
result the rule for the bottom lower right and left corners of matrix
144 requires that all possible arrows be represented by light-shaded
boxes (indicative of least preferable investment value), and therefore
corresponding 2.times.2 matrices are omitted from FIG. 5.
In step S8, the graphic portrayal of the process will operate generally
with any set of decision rules. The investing entity ranks each
market/property pair into the four-product matrix 144 on the basis
of the application of the particular set of decision rules acceptable
to that entity, which determine whether to pursue a short term/long
term debt or equity strategy for that market/property pair. In particular,
lower volatility markets favor debt investments. Higher return markets
favor equity investment. Market trend drives term and debt appetite.
Possibly, depending on the particular set of rules employed, below
certain minimum threshold returns, no investment type is favored.
For example, with reference to the four-product matrix 158, located
in the upper left corner of matrix 144, in total, the graphic symbol
158 is located in a high return/low risk market that has a downward
trend. The appearance of graphic symbol 158 represents underlying
data indicating for equity, a "strong focus" over the
short term, and for debt, a "strong focus" over the short
turn, and "pursue" over the long term.
In step S9, the investor again makes an adjustment to the derived
results. It will be recalled that the adjustment step S5, in which
the market/property pair analysis, which was based on commercial
research of national marketing data, was further adjusted in the
face of known local market information. In a similar fashion, knowledge
of the investor's existing market exposure is applied to the results
derived in step S8. Using this knowledge, and while not necessarily
changing the graphic portrayal set forth in step S8, the investment
conclusions indicated by the symbology resulting from decision rule
application, as shown in FIG. 5, are either upgraded, downgraded,
or utilized as is. Alternatively, simple graphic icons are selected
and applied, each indicating one of the three alternative adjustments
reflecting the investor's existing market exposure.
In step S10, the investor, evaluates the graphic portrayal of the
results obtained in step S9 to determine whether to pursue a short
term debt, long term debt, short term equity, and/or long term equity
investment type for each property type in a respective market area. |