1.1INDUSTRY PROFILE: US Real Estate Industry: Real estate in United States is one of the largest markets in the world. In fact, it is so significant to world economic activity that the availability of easy money and the subsequent Housing Bubble triggered the Sub-Prime Crisis and eventually the global Financial Crisis of 2008 - 2009 that brought the world's economy to its knees. The US real estate market is divided into 2 sectors: commercial real estate and residential real estate. Most discussion tends to focus on residential real estate (i.e. houses), but commercial real estate is also a critical sector of the economy, and is made up of offices, shopping malls, factories, warehouses and other commercial buildings. In order to be successful in real estate investment, an investor needs to understand house price trends, assess the condition and value of the investment property, and secure a suitable mortgage or other form of real estate finance. The US real estate industry has been experiencing wonderful growth due to the relatively steady good economy. In 2006, some markets had major gains in occupied space, others saw record sales transactions. The market has begun to tighten, developers remained cautious possibly eye toward the future, particularly predictions of escalating rental rates. Major Participants in the Real Estate Industry Developers 1
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Factors Affecting Capitalization Rate of US Real Estate
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1.1INDUSTRY PROFILE:
US Real Estate Industry:
Real estate in United States is one of the largest markets in the world. In fact, it is so significant to world
economic activity that the availability of easy money and the subsequent Housing Bubble triggered the Sub-
Prime Crisis and eventually the global Financial Crisis of 2008 - 2009 that brought the world's economy to its
knees. The US real estate market is divided into 2 sectors: commercial real estate and residential real estate.
Most discussion tends to focus on residential real estate (i.e. houses), but commercial real estate is also a
critical sector of the economy, and is made up of offices, shopping malls, factories, warehouses and other
commercial buildings.
In order to be successful in real estate investment, an investor needs to understand house price trends, assess
the condition and value of the investment property, and secure a suitable mortgage or other form of real
estate finance. The US real estate industry has been experiencing wonderful growth due to the relatively
steady good economy. In 2006, some markets had major gains in occupied space, others saw record sales
transactions. The market has begun to tighten, developers remained cautious possibly eye toward the future,
particularly predictions of escalating rental rates.
Major Participants in the Real Estate Industry
Developers
Development is an idea that comes to fruition when consumers – tenants or owner- occupants acquire
and use the space put in place by the development team. Land, labor, capital management and
entrepreneurship are needed to transform an idea into reality. Developers balance the needs of diverse
providers and consumers of the real estate product. The developers have to demonstrate the project's
feasibility to the capital markets and pay interest or assign Equity positions in return for funding.
Appraisers
Appraisers can be a part of every stage of the property development process. Appraisers are primarily
responsible for valuation of the project. They estimate the market value of the property and typically prepare
a formal document called appraisal. Appraisal may be necessary when a developer transfers ownership, seeks
financing and credit, resolves tax matters, and establishes just compensation in condemnation proceedings.
Appraisers can also evaluate a project as input to market studies and feasibility studies. Some of the familiar 1
names in the US Real Estate markets include CB Richard Ellis, Cushman and Wakefield and Grubb and
Ellis.
Property managers
Property managers focus on the day operation of the asset. Property managers carry responsibility for
all respects of the physical space in accordance with the asset manager's plan. The responsibilities of a
property manager include:
Marketing and leasing
Maintenance and repair
Tenant relations including rent collection
Insurance
Accounting
Human resource management
Providing timely information to the asset manager about events affecting the property.
Some of the major property managers include Trammel Crow Company and Grubb and Ellis Company.
Brokers/ Leasing Agents
Real Estate brokers and leasing agents are hired to act in the name of the developer or asset manager
in leasing and selling space to prospective tenants or buyers. Their function, particularly in leasing large
industrial and commercial spaces is to carry out one of the most complex financial negotiations in the
development process. Leasing agents must balance all the various uses' individual needs against the
developer's financial model.
Lenders
A) Construction Lenders are usually commercial banks, which are responsible for financial during
project construction and for seeing that the developer completes the project within the budget and according
to the specifications.
B) Permanent lenders seek to originate safe loans generating the maximum possible return. The
market value of the completed project is very critical in that it serves as the primary collateral for the loan.
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1.2 COMPANY PROFILE:
Zenta Knowledge Services Pvt. Ltd .,
About Zenta:
Zenta which is founded in 2001 is a world-class knowledge process outsourcing (KPO) and business process
outsourcing (BPO) and Company, offering a full range of back-office, voice and on-site support solutions
such as Credit Card Servicing, Consumer Lending Servicing, Accounts Receivable Management, Mortgage
Servicing and Real Estate Capital Market Analytics. The Company serves in the area of Consumer Credit
services, Insurance and Financial Services, and Commercial and Residential Real Estate services. With
4,500+ employees worldwide, Zenta has operations in six locations across three continents. Zenta is a
preferred employer in India. Zenta pioneered the concept of developing and delivering higher level offshore
solutions for the real estate industry. The unique onshore/offshore approach combines US domain expertise,
a proven process migration methodology and a large team of highly trained offshore finance professional.
Zenta allows the clients to focus on their core business by utilizing its cost effective resources and scalable
platform to execute non- core activities.
Vision & Mission
The May 2007 realignment of the Company’s services under the Zenta brand reflects the new corporate
vision of building a world-class Knowledge and Business Process Outsourcing Company focused on the real
estate and financial services industries. As a fully integrated global enterprise, Zenta now offers real estate
and financial services customers a broad array of services from its centers of excellence around the globe.
Zenta Solutions
From origination and throughout the customer lifecycle, Zenta delivers deep, end-to-end servicing solutions.
Zenta's specialized focus on the financial services industry and our management expertise and experience,
are the reasons we have been chosen to provide high-end business processing for some of the world's most
prestigious banks and financial institutions. Instead of coordinating multiple vendors, Zenta's complete
solution set makes it possible for clients to work with one company only - providing a single source for all
their business processing needs. Zenta's end-to-end solutions include Credit card servicing and Commercial
Correlation determines the degree of association between two variables X, Y. A plot
of the observations generally helps to visualize whether the variables are correlated. This plot
is called as Scatter Diagram. If the observations tend to flare out or narrow it may suggest
that the variance over the samples is not constant.
The correlation coefficient formula is:
n∑xy - ∑x * ∑y
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Figure 4.1 Scatter Diagram
r =
√ (n ∑x2 – (∑x)2) * √ (n ∑y2 – (∑y)2)
The correlation coefficient r, a value between +1 and -1, expresses the degree of
association between X and Y.
In order to scrutinize the vital factors which affect the capitalization rate of the property, in this study we take Capitalization Rate as a dependent Variable and all the other factors as a independent variable.
The Output of the correlation analysis is shown in the Table 4.2
Scatter diagram showing between Capitalization rates and other Factors:
0.8
1.3
1.8
2.3
2.8
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
PR
OP
ER
TY
TY
PE
Figure 4.2 Correlation – Capitalization rate and Property type
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0.5
1
1.5
2
2.5
3
3.5
4
4.5
5
5.5
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Qu
an
tifi
ed
Lo
cati
on
Figure 4.3 Correlation - Capitalization rate and Location
0
10
20
30
40
50
60
70
80
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Ag
e o
f th
e P
rop
ert
y
Figure 4.4 Correlation – Capitalization rate and Age of the property
0
5
10
15
20
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Lease T
erm
Figure 4.5 Correlation – Capitalization rate and Lease term
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0.05
0.055
0.06
0.065
0.07
0.075
0.08
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Inte
rest
Rate
Figure 4.6 Correlation – Capitalization rate and Interest rate
0.019
0.021
0.023
0.025
0.027
0.029
0.031
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Infl
ati
on
Figure 4.7 Correlation – Capitalization rate and Inflation
0.05
0.06
0.07
0.08
0.09
0.1
0.11
0.12
0.13
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Dis
co
un
t ra
te
20
Figure 4.8 Correlation – Capitalization rate and Discount rate
0.05
0.055
0.06
0.065
0.07
0.075
0.08
0.085
0.09
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
Mo
rtg
ag
e C
on
stan
t
Figure 4.9 Correlation – Capitalization rate and Mortgage Constant
0.4
0.45
0.5
0.55
0.6
0.65
0.7
0.75
0.8
0.85
0.9
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
LT
V
Figure 4.10 Correlation – Capitalization rate and Loan to Value
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1
1.2
1.4
1.6
1.8
2
2.2
0.05 0.06 0.07 0.08 0.09 0.1
Cap Rate
DS
CR
Figure 4.11 Correlation – Capitalization rate and DSCR
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Interpretation:
In the table 4.1, we can see four factors (Age of the Property, Inflation, Lease Term and
LTV) are negatively related with Capitalization Rate. And the Remaining Factors (Location,
Property Type, Interest Rate, No of Tenant, Discount Rate, DSCR and Mortgage Constant)
are positively related with Capitalization Rate. But seeing the significance level, only four
independent variables (Age of the Property, Interest Rate, Discount Rate and Mortgage
Constant) have significance level below 10%. Remaining Seven independent variables have
significance level more than 10%.
Therefore considering the significance level, only the below mentioned four independent
variables are considered for regression analysis.
Age of the Property
Interest Rate
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Discount Rate and
Mortgage Constant
4.2 MULTIPLE LINEAR REGRESSION ANALYSIS:
Multiple linear regressions are used to predict the variance in an interval dependent,
based on linear combinations of independent variables. Multiple regression can establish that
a set of independent variables explains a proportion of the variance in a dependent variable at
a significant level (through a significance test of R2), and can establish the relative predictive
importance of the independent variables. One can test the significance of difference of two
R2's to determine if adding an independent variable to the model helps significantly. Using
hierarchical regression, one can see how most variance in the dependent can be explained by
one or a set of new independent variables, over and above that explained by an earlier set.
The estimates (b coefficients and constant) can be used to construct a prediction equation and
generate predicted scores on a variable for further analysis.
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The multiple regression equation takes the form y = b1x1 + b2x2 + ... + bnxn + c. The b's
are the regression coefficients, representing the amount the dependent variable y changes
when the corresponding independent changes one unit. The c is the constant, where the
regression line intercepts the y axis, representing the amount the dependent y will be when all
the independent variables are 0. Associated with multiple regression is R2, multiple
correlation, which is the percent of variance in the dependent variable, explained collectively
by all of the independent variables. Multiple regression shares all the assumptions of
correlation: linearity of relationships, the same level of relationship throughout the range of
the independent variable, interval or near-interval data, absence of outliers, and data whose
range is not truncated. Here,
R2 - coefficient of determination, gives the proportion of the variance of one variable that is
predictable from the other variable.
Standard Error - The standard error of a statistic is the standard deviation of the sampling
distribution of that statistic.
F-Ratio – F-ratio is the test statistic used in analysis of variance to compare the magnitude of
two estimates of the population variance to determine whether the two estimates are
approximately equal.
Significance Level - The probability of a false rejection of the null hypothesis in a statistical
test.
Multiple linear regression analysis is done using SPSS. As discussed earlier only the below
mentioned factors are considered for regression analysis.
Dependent variable : Capitalization rate
Independent variables : Age of the Property, Interest Rate, Discount Rate and
Mortgage Constant.
Multiple Regression Results:
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Model Summary
Model RR
SquareAdjusted R
SquareStd. Error of the Estimate
Change Statistics
R Square Change F Change df1 df2
Sig. F Change
1 .644a .415 .321 .760519% .415 4.428 4 25 .008
Table 4.3 Regression Statistics – Model Summary
The coefficient of determination of R square is 0.415; therefore, about 41.5% of the variation
in the dependent variable is explained by independent variable. The regression equation is
not very useful for making predictions since the value of r is not close to 1.
ANOVAb
ModelSum of Squares df Mean Square F Sig.
1 Regression 10.245 4 2.561 4.428 .008a
Residual 14.460 25 .578
Total 24.705 29
Table 4.4 Regression Statistics – Anova
A one-way between subjects ANOVA was conducted to know which of the four factors affect
the capitalization rate. Looking at the Sig value in the last column, it is only 0.8% i.e. it is
less than the significance level of 10%. Hence H0 can be rejected and H1 can be accepted.
So therefore we can say that there is significant relationship between Capitalization rate and