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.

2

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

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Realty Services, Residential Realty Services and Account Receivables management, Healthcare Revenue

Cycle Management and Residential Mortgage Services.

Zenta’s executive, client facing and management teams are based in the U.S. and are comprised of leaders

with deep and broad industry expertise from top Fortune 1000 companies. They deliver the depth of

experience necessary to build long-term, strategic relationships with our clients and provide easy access to

Zenta's decision-makers. In addition, an experienced delivery team has extensive expertise in operating

global delivery centers while adhering to the highest industry and quality standards.

Zenta believes in long-term partnerships - but with flexible engagement models. Put simply, we partner with

clients to transform the way they do business. As the global operating model gains momentum, we help

clients meet their business challenges by designing and implementing complex solutions that deliver rapid

and enduring savings, allow clients to quickly introduce new products or services, augment highly skilled

internal resources and minimize large-scale investments. We believe these accomplishments will be achieved

through the innovative ways in which data is captured, collated, analyzed and disseminated.

Our proven ability to scale rapidly, both in volume and skill sets, enables us to create high-impact programs

for our clients. We engage with clients at the early stages of their offshoring program to develop an offshore

"roadmap" that best meets their objectives. Furthermore, we build flexible client relationships and have

experience working on a variety of engagement models.

1.3 CAPITALIZATION RATE:

The capitalization rate in the real estate literature refers to the ratio of Net Operating Income to

property value which is the inverse of the price earnings ratio in the stock market. This rate has a particularly

important role in property valuation, because the income capitalization method converts the expected income

stream from commercial property into an estimate of asset value by dividing the net operating income stream

by the capitalization rate. Most investors associate movements in cap rates with changes in asset values, e.g.,

falling cap rates signal rising property values-changes in income or asset prices (or both) can cause cap rates

to move up or down. This is because there is a positive correlation between the property income and the asset

values, the movements in one variable frequently dilute the cap rate effects of movements in the other. For

example, when rents (income) are rising, property values also tend to increase, such that both the numerator

and denominator of the cap rate equation increase; and when rents are falling, property values usually fall,

although this has not been the case for the last few years.

4

A market cap rate is determined by evaluating the financial data of similar properties which have

recently sold in a specific market. It provides a more reliable estimate of value than a market Gross Rent

Multiplier since the cap rate calculation utilizes more of a property's financial detail. The GRM calculation

only considers a property's selling price and gross rents. The Cap Rate calculation incorporates a property's

selling price, gross rents, non rental income, vacancy amount and operating expenses.

If we have a seller and an interested buyer for particular piece of income producing property, the

seller is trying to get the highest price for the property or sell at the lowest cap rate possible. The buyer is

trying to purchase the property at the lowest price possible which translates into a higher cap rate. The lower

the selling price the higher the cap rate. The higher the selling price, the lower is the cap rate. In summary,

from an investor's or buyer's perspective, the higher the cap rate, the better. Investors expect a larger return

when investing in high risk income properties.

The Cap rate may vary in different areas of a city for many reasons such as desirability of location,

level of crime and general condition of an area. You would expect lower capitalization rates in newer or more

desirable areas of city and higher cap rates in less desirable areas to compensate for the added risk. In a real

estate market where net operating incomes are increasing and cap rates are declining over time for a given

type of investment property such as office buildings, values will be generally increasing. If net operating

income is decreasing and capitalization rates are increasing over time in a given market place, property

values will be declining.

The cap rate (R) equals (expected) net operating income NOI1 divided by the value of the

property (V) as follows (Ellwood, 1970),

Net operating income is determined by subtracting vacancy amount and operating expenses from a

property's gross income. Operating expenses includes advertising, insurance, maintenance, property taxes,

property management, repairs, supplies, utilities, etc. Operating expenses do not include the following

Appraisers use the Income Approach, Cost Replacement and Market Comparison methods to estimate the

value of property. The Income Approach utilizes the theory of Capitalization.

5

The property value for determining the cap rate is based on the sales price in a competitive market

commonly called the market value. Brueggeman and Fisher (1993) noted that the cap rate is not an internal

rate of return on investment (IRR) because it does not consider changes in projected future income (or

changes in the value of a property over time because of changes in the income stream). If the income stream

is expected to grow at a constant growth rate (g) into the foreseeable future, Brueggeman and Fisher (1993)

show that the value of a property is estimated as the present value of a perpetual stream of future net

operating income cash flows using discount rate r:

Rearranging equation, the cap rate equals the total required return on the property less the expected growth

rate as given:

The 3 Major determinants of cap rates are,

(1) The Opportunity Cost of Capital (OCC),

(2) Growth Expectations in the property’s future cash flows, and

(3)Risk perceptions and preferences among investors regarding the property

The following table shows the movement of capitalization rate for 1992-2010. These movements are due to

various factors which internally or externally affect the property. There has been initial increase over the

capitalization rate but after 2002, a decline can be noted.

Table 1.1 4Q Moving Average of Capitalization rate 1992-2010

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Year 4Q Moving Average1992 7.00%1994 6.80%1996 8.20%1998 9.00%2000 9.00%2002 9.50%2004 8.00%2006 9.74%2008 6.25%2010 10.00%

Figure 1.1 General Movement of cap rate of 4Q from 1992 – 2010

The capitalization rate differs from property to property. It ranges from high in Retail property to low in

Industrial property. The following table provides the capitalization rate for the various property types from

2005 – 2010.

Table 1.2 Cap rate for various property types from 2005 – 2010

Figure 1.2 Capitalization rates from 2005 – 2010

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Property Type 2005 2006 2007 2008 2009 2010

Retail 9.30% 9.00% 9.00% 8.25% 7.50% 7.50%

Office 8.40% 8.75% 8.75% 8.50% 8.00% 7.50%

Multifamily 7.90% 7.60% 7.25% 5.80% 5.50% 6.80%

Industrial 8.70% 8.60% 8.50% 8.25% 7.80% 7.00%

1.4 FACTORS AFFECTING THE CAPITALIZATION RATE:

The major determinants of capitalization rates are as follows,

Property Type

The Property type is the category to which it belongs. The various types of properties are Retail,

Office, Mixed Use, Hotel, Multi-family, Self storage and Industrial properties.

Location

Location means the state in which the subject property is situated.

Loan To Value

Loan to value is the portion of the amount borrowed compared to the cost or value of the property

purchased. A higher LTV ratio means higher leverage and thus greater risk.

Age of the Property

The age of the property is measured as the time gap between its year built and present date.

Mortgage Constant

The relationship between annual mortgage loan requirement and the initial mortgage loan principal

expressed as a decimal or percentage, for level payment mortgage loan.

Lease Term

Lease term is the term during which the tenant agrees to stay in the property by entering into a

lease agreement with the landlord.

Interest rate

Interest rate is the percentage of a sum of money charges for its use. It is the return on an investment.

8

Discount Rate

Discount rate is rate of interest charged by Federal Reserve System to banks who borrow money

from the Federal Reserve. An increase in the rate not only discourages from borrowing but also

serves as a signal to money market that the interest rates are probably going to increase.

Accordingly, interest rates charged by banks to customers usually increases as a result of increase in

discount rate. The term is also used to explain the compound interest rate used in the approach to

value to convert expected future cash flows into present value.

Inflation

Inflation is the loss in purchasing power of money and increase in the general price level. Generally

measured by the consumer price index published by Bureau of Labor Statistics

Number of Tenants

Number of tenants occupied in the property is the number of tenants. It may be single tenant for the

office property and multi-tenant for the retail property.

Debt Service Coverage Ratio

Debt service coverage ratio is the relationship between annual net operating income of a property

and annual debt service of the mortgage loan on property. Lenders and investors calculate the ratio

to assist them in determining the likelihood of the property generating enough income to pay the

mortgage payments. From lenders view point the higher the ratio the better.

1.5 NEED FOR THE STUDY:

Property valuation forms the basis of real estate inventory decision making. Property valuation is

done not only at the time of making the inventory decision, but throughout the period of ownership of the

asset. Decisions are also made periodically about rehabilitation, modernization, expansion, conversion of the

property to another use, demolition of the existing improvements and ever abandoning the asset.

The purpose of this study is to facilitate the company to value the property in various states of US

Real Estate market using the capitalization rate which in turn enables the company to analyse and

recommend investment strategies for clients such as lending institution, bankers or owners etc through a risk

return analysis of the income streams of different commercial and Real estate properties.

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1.6 SCOPE OF THE STUDY:

The project seeks to study the various factors to be considered while estimating the capitalization rate.

To understand the most relevant and reliable methodology for income producing properties.

To conclude a market value for some subject property in US real estate market.

1.7 PRIMARY OBJECTIVES:

To scrutinize the vital factors which affects the capitalization rate of the property and to find out the

importance of each factor.

SECONDARY OBJECTIVES:

To study the impact of property type in determining capitalization rate.

To determine the effect of location in Real estate market.

1.8 STUDY METHOD:

Description study method is chosen for the study because of the vast amount of data available in

different books, magazine and websites relating to US real estate. The focussed study of the data can give

good insight into factors influencing capitalization rate.

1.9 DATA COLLECTION:

For the purpose of the study, secondary data was collected through,

The materials available about US real estate in various websites like realestatejournal.com,

realtyrates.com, bloomberg.com.

The materials maintained in the organization about the properties.

Research publication of other institutes and organization like REIS, PULASKI, CBRE.

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2.1 LITERATURE REVIEW:

Sirmans and Webb (1978, 1980) and Ricks (1969) used the ACLI data source. They estimated

imputed equity yields on the investments by hypothesizing average holding periods with no price

appreciation and imputing tax rates. They relate the yield and its variance to alternative investments by using

only the cap rate.

Nourse (1987) uses the REIS data source to estimate the impact of change in capitalization rate for

real estate. His model, however does not take into account the potential variation driven by property types.

Evans (1990) used ACLI data source to estimate the time-series properties for capitalization rates.

His study focuses on comparing the stochastic nature of the stock market earnings/price ratio with real estate

capitalization rate.

Froland (1987) uses the ACLI data source to explain variation in capitalization rate and the

interaction of those rates with the capital market. Froland finds that the capitalization rate is a function of the

mortgage contract rate, the spread between Treasury bills and bonds and the corporate earning price ratio.

However his study has several significant problems like the impact of variation is not considered and does

not specify the relationship between the capitalization rate and the independent variables and the

interpretation of his correlation coefficients is weakened by autocorrelation present in the dataset.

Guntermann and Smith (1987) derived estimates of equity rates and costs of capital for property

REITs, mortgage REITs, and homebuilders/developers. While operating properties and REITs had a before-

tax cost of capital of 16.6%, homebuilders/ developers’ cost of capital was substantially greater at 34.9%.

Their study concluded that the data sources and procedures permit the estimation of cost of capital and equity

rates with satisfactory precision and reliability for the majority of investment or appraisal applications.

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A study by Evans (1990) noted the sensitivity of the multifamily and nonresidential real

estate cap rates to the earnings/price ratio in the stock market. This study of quarterly cap

rates for 1966–1988 reported a strong positive relation of real estate cap rates lagging the

earnings/price ratio by one period. Although short of statistical significance, a somewhat

lesser positive correlation occurred in the same quarter and a negative correlation occurred in

the second quarter. Evans concluded that these results were not consistent with the theory that

real estate markets are information efficient.

Ambrose and Nourse (1993) examined mean quarterly capitalization rates for

commercial/retail, office buildings, commercial services, industrial, and hotel properties for

1966 through 1988. The theoretical base for their study is the traditional WACC model that

has been used so extensively in the finance literature. Their empirical model related cap rates

to a local variable, the spread between long-term and short-term Government bond rates, the

earnings/price ratio of the S&P 500, and debt-to-equity components. The debt-to-equity

components were estimated from the average loan-to value and property mortgage costs.

Using seemingly unrelated regression (SUR), they reported that cap rates were not closely

tied to either the S&P 500 or the bond risk premium spread. Using a cross-sectional/time-

series regression approach, they found that Weighted cost of debt of .98, not significantly

different from one. Also, the return on equity was estimated at 4.85% and was statistically

different from zero. The intercept and slope coefficients were found to vary significantly by

property type; however, the panel data regression did not permit separate slope coefficients

by area.

The above researchers made a detailed study about Capitalization rate and have built a

various dynamic Cap rate models for the use of investors so that they can use these models to

predict Cap rates based on past information. The researchers have used ACLI and REIS data

source to estimate the impact of change in capitalization rate for US real estate industry.

2.2 Research Gap:

The above researchers made a detailed study to built Cap Rate model for the purpose of the

investors. But this current study is made to find out which of the factors have most

influential effect on capitalization rates. Unlike other studies that have used the ACLI

database, this study uses NREI database for office, warehouse/distribution, retail, and

apartment properties.

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3.1 RESEARCH METHODOLOGY:

Research Methodology is the way in which the data are collected for the research

project.

Type of Research:

In this study, the type of research is “Exploratory Research”.

Exploratory Research:-

Exploratory research is a type of research conducted for a problem that has not been

clearly defined. It helps to determine the best research design, data collection method and

selection of subjects. It should draw definitive conclusions only with extreme caution. Given

its fundamental nature, exploratory research often concludes that a perceived problem does

not actually exist.

Exploratory research often relies on secondary research such as reviewing available

literature and/or data, or qualitative approaches such as informal discussions with consumers,

employees, management or competitors, and more formal approaches through in-depth

interviews, focus groups, projective methods, case studies or pilot studies. The Internet

allows for research methods that are more interactive in nature.

The results of exploratory research are not usually useful for decision-making by

themselves, but they can provide significant insight into a given situation. Although the

results of qualitative research can give some indication as to the "why", "how" and "when"

something occurs, it cannot tell us "how often" or "how many". Exploratory research is not

typically generalizable to the population at large.

Variables Used:

Independent Variables: The independent variable is the variable that we use to

explain a particular outcome.

Components of independent variables in this study are:

Location

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Property Type

Age of the Property

Interest Rate

Inflation

Lease Term

No of tenant

Discount Rate

LTV

DSCR

Mortgage Constant

Dependent Variable: The dependent variable is what we are trying to explain.

Capitalization Rate

3.2 LIMITATIONS OF THE STUDY

The study is limited only to real estate market in certain states in U.S.A.

The study is restricted only to vital factors which affect the capitalization rate.

Only secondary data has been used in the study.

3.3 DATA PROCESSING:

Type of data

Secondary Data

Sources

Internal documents maintained in the company

Research Period

6 years (from 2005 to 2010)

14

Tools Used

Descriptive method

Mean

Standard deviation

Quantitative method

Hypothesis Testing

Correlation

Regression

SPSS software used for analysis.

HYPOTHESIS TESTING:

Null Hypothesis (Ho1): There is no significant relationship between Capitalization

rate /dependent variable and other factors/independent variable.

Alternative hypothesis (H11): There is no significant relationship between

Capitalization rate /dependent variable and other factors/independent variable.

.

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4.1 DESCRIPTIVE ANALYSIS:

Descriptive analysis refers to mathematical methods (such as mean, median, standard

deviation) that summarize and interpret some of the properties of a set of data (sample) but do

not infer the properties of the population from which the sample was drawn. Generally the

measures of central tendency (mean, median and mode) and measures of dispersion such as

standard deviation are the tools used in Descriptive Statistics.

All the above factors that affect the Capitalization Rate are used in the Descriptive Statistics.

Descriptive Statistics

MeanStd.

Deviation N

Cap rate 7.47333 .922984 30

Location 8.10 5.683 30

Property Type 1.60 .675 30

Age of the Property

22.87 21.365 30

Interest Rate 5.99000 .342566 30

Inflation 2.86667 .260415% 30

Lease Term 4.10 4.845 30

No of tenant 1.83 .379 30

Discount Rate 8.6417 1.38217 30

LTV 71.433 7.5324 30

DSCR 1.3353 .28832 30

Mortgage Constant

7.138667 .6568931 30

Table 4.1: Descriptive Statistics for Cap Rate and Other Factors

From this descriptive statistics we can able to identify that there are some deviations in the

variables taken for analysis. Among all the factors Loan to Value (LTV) is the factor which

is highly deviated from its actual mean.

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4.2 CORRELATION ANALYSIS:

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

17

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

19

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

21

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

other factors.

Coefficientsa

Model

Unstandardized Coefficients

Standardized

Coefficients

t Sig.

Collinearity Statistics

B Std. Error Beta Tolerance VIF

1 (Constant) 2.298 2.546 .902 .375

Age of the Property

-.011 .007 -.254 -1.627 .116 .964 1.038

Interest Rate .137 .495 .051 .277 .784 .694 1.442

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Coefficientsa

Discount Rate .338 .108 .506 3.114 .005 .887 1.127

Mortgage Constant

.236 .254 .168 .930 .361 .718 1.393

Table 4.5 Regression Statistics – Coefficients

From the above output, the regression equation is:

Capitalization Rate = 2.298 - .011Age of the Property + .137 Interest Rate + .338 Discount Rate + .236 Mortgage Constant

Looking at the above Coefficient table, P value for the age of the property, Interest Rate and

Mortgage Constant is greater than significance level (0.375, 0.116, 0.361 > .10). Hence we

can conclude that there is no significant relationship between Capitalization rate and Age of

the Property, Interest Rate and Mortgage Constant.

But there exists enough evidence to conclude that for the Discount Rate alone P value is less

than the significance level of 10% (0.005 < .10). So therefore we can say that there is

significant relationship only between Capitalization rate and Discount Rate.

5.1 FINDINGS:

By analyzing the various factors affecting the capitalization rate the following were observed:

It is observed from the 4 quarter moving average that for the past 10 years the

capitalization rates for the properties are showing a downward trend. This means the

value of the properties is continuously increasing.

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From the descriptive statistics, it is found that there are deviations in the variables

taken. Among the eleven variables it is clear that Loan to value has deviated highly

for about 7.5324 from its actual mean 71.433.

The independent variables and dependent variable are significantly correlated .Among

independent variables: Age of the property, Inflation, Lease Term and Loan to value

are negatively correlated and the remaining factors are positively correlated with the

Capitalization Rate.

Only four factors (Age of the Property, Interest Rate, Discount Rate and Mortgage

Constant) are considered for regression analysis since their sig value is alone less than

10% significance level.

The independent variables explain 41.5% of dependent variable (Capitalization Rate)

at 0.8% level of significance which is less than 10% level of significance.

The coefficient interpret that there is negative association between Age of the

Property and Capitalization Rate, and there is positive association between Interest

Rate, Discount Rate and Mortgage Constant and Capitalization Rate.

The model of this analysis explains only Discount Rate has slight influence on

capitalization Rate at 10% significance level and all the other factors doesn’t have any

influence on capitalization rate.

5.2 SUGGESTIONS:

Since Investors are the one in Real estate market who consider capitalization rate as

an important element to estimate the reversionary value of the subject property. The

following suggestions are made from the investors’ point of view:

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Investors should not only consider Discount Rate but should also consider the

other factors such as Property type, Location and Market while investing in

the Real Estate Market.

Investors should take into consideration the per capita income while deciding

the location of the property.

The investors should consider the lease term while investing in properties as

very low lease term leads to roll over risk and higher cost of tenant

improvements.

The investor must consider the property type as some properties such as hotels

are more risky due to unpredictable occupancy rate.

The investors can use the regression model developed in this study to estimate

the capitalization rate of the property.

5.3 CONCLUSION:

A capitalization rate is simply a ratio of a property’s net operating income (NOI) to its

Property value, much like the inverse of a price earnings ratio in the stock market. Given the

limited number of properties that actually sell in a period, changes in simple average cap rates

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from period to period are unlikely to reflect accurately what is happening to real estate values

per dollar of income.

The results from this study indicate that only one factor has a slight impact in

evaluating capitalization rates. This may not be true for all the time. Factors that seem

important today may become outdated and irrelevant after few years. This is a dynamic,

competitive, and highly complex industry. The framework of factors presented in the text will

indubitably help the investors to achieve their set objectives, gain a competitive advantage,

and maximize the return on the real estate property. Real estate capitalization rates have

plunged amid fierce competition for core assets with secure and predictable cash flows. The

real estate industry is capital intensive and relies heavily on debt.

5.4 DIRECTIONS FOR FUTURE RESEARCH:

This study can be made in some other organisations belonging to KPO Industry.

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This same study can be conducted by using various other Techniques like sampling,

probability, etc

After scrutinising the important factors that affect the Capitalization Rate, a separate

dynamic cap rate model can be built for the investors’ purpose.

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CLASSIFICATION OF DATA:

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Property Classification

Classification of Property type - Based on risk in that property

Location and Market Classification

Classification for Location and Market - Based on per capita income of the County

Per Capita Income Rank

Less than $25,000 5

$25,000 - $50,000 4

$50,000 - $75,000 3

$75,000 - $1,00,000 2

More than $1,00,000 1

BIBLIOGRAPHY

Books Referred:

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Property Type Rank

Hotel 3

Office / Retail 2

Industrial / Mixed

Use / Multifamily /

Self storage

1

Business statistics – C.B.Gupta

Research methodology – C.R. Kothari

Research Papers

Journal of Real Estate Research: Ambrose, B. and H.O. Nourse. 1993. Factors

Influencing Capitalization Rates.

Journal of Real Estate Research: Evans, R. 1990. A Transfer Function Analysis of

Real Estate Capitalization Rates.

Journal of Portfolio Management: Froland, C. 1987. What Determines Cap Rates on

Real Estate.

Journal of Real Estate Research: Jud, D., and D. Winkler. "The Capitalization Rate of

Commercial Properties and Market Returns."

Websites:

www.zenta.com

www.cbre.com

www.pulawski.com

www.realestatejournal.com

www.realtyrates.com

www.census.gov

www.reis.com

www.ncreif.com

www.bloomberg.com

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