SAPM - Portfolio Construction and Comparison for Securities on BSE

Security Analysis & Portfolio Management PGDM-Exec 2012

Security Analysis and Portfolio Management

Portfolio Construction and
Comparison for Securities on BSE

Bishnu Kumar 11EX-013
Davinder Singh 11EX-015
Prateek Wadhwa 11EX-040
Rajat Goel 11EX-043

Institute of Management Technology
Ghaziabad

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Table of Contents
Introduction ............................................................................................................................................ 3
Factors Impacting the Performance of a Company ................................................................................ 4
Economic Analysis ............................................................................................................................... 4
Industry Analysis ................................................................................................................................. 6
Company Analysis ............................................................................................................................... 7
Literature Review .................................................................................................................................... 9
Statement of Problem........................................................................................................................... 10
Objectives of the Study ......................................................................................................................... 10
Research Methodology ......................................................................................................................... 10
Data Analysis and Interpretation .......................................................................................................... 10
Calculation of Beta ............................................................................................................................ 11
Portfolio Construction using Sharpe’s Single Index Model ................................................................... 12
Determination of Optimal Portfolio.................................................................................................. 15
Comparison of the Portfolios ............................................................................................................ 19
Observations ..................................................................................................................................... 19
Portfolio Construction Worksheet ........................................................................................................ 20
References ............................................................................................................................................ 21

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Introduction
The foundation of Modern Portfolio Theory was laid by Markowitz in 1951. He
began with the simple premise that since almost all investors invest in multiple
securities rather than one, there must be some benefit in investing in a portfolio
of securities. He measured riskiness of a portfolio through variability of returns
and showed that investment in several securities reduced this risk. His work won
him the Nobel Prize for Economics in 1990. Markowitz‘s work was extended by
Sharpe in 1964, Lintner in 1965 and Mossin in 1966. Sharpe shared the Nobel
Prize for Economics in 1990 with Markowitz and Miller for his contribution to the
Capital Asset Pricing Model (CAPM). This model breaks up the riskiness of each
security into two components - the market related risk which cannot be
diversified called systematic risk measured by the beta coefficient and another
component which can be eliminated through diversification called unsystematic
risk. The Markowitz model is extremely demanding in its data needs for
generating the desired efficient portfolio. It requires N (N+3)/2 estimates (N
expected returns + N variances of returns + N*(N-1)/2 unique covariance‘s of
returns). Because of this limitation the single index model with less input data
requirements has emerged. The Single index model requires 3N+2 estimates
(estimates of alpha for each stock, estimates of beta for each stock, estimates of
variance σei2 for each stock, estimate for expected return on market index and
an estimate of the variance of returns on the market index σm2) to use the
Markowitz optimization framework. The single index model assumes that co-
movement between stocks is due to movement in the index. The basic equation
underlying the single index model is:

Ri = ai + βi*Rm where

Ri = Return on the ith stock
ai = component of security i‘s that is independent of market performance
βi = coefficient that measures expected change in Ri given a change in Rm
Rm = rate of return on market index

The term ai in the above equation is usually broken down into two elements ai
which is the expected value of ai and ei which is the random element of ai. The
single index model equation, therefore, becomes:

Ri = αi + βi*Rm + ei

Single index model has been criticized because of its assumption that stock
prices move together only because of common co-movement with the market.
Many researchers have found that there are influences beyond the market, like
industry-related factors, that cause securities to move together.

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Factors Impacting the Performance of a Company
The performance of a company depends on its management, competitive
advantages, its competitors, markets etc.

Intrinsic value is defined to be the present value of all future net cash flows to
the company. The intrinsic value of an equity share depends on a multitude of
factors. The earnings of the company, the growth rate and risk exposure of the
company have a direct bearing on the price of the share. These factors in turn
rely on the host of other factors like economic environment in which they
function, the industry which they belong to, and finally company’s own
performance. Hence, we can say that the intrinsic value of shares can be
appraised through:

 Economic Analysis
 Industry Analysis
 Company Analysis

Economic Analysis

The level of economic activity has an impact on investment in many ways. If the
economy grows rapidly, the industry can also be expected to show rapid growth
and vice-versa. When the level of economic activity is low, stock prices are low,
and when the level of economic activity is high, stock prices are high reflecting
the prosperous outlook for sales and profits of the firms. The analysis of
macroeconomic environment is essential to understand the behavior of the stock
prices. The commonly analyzed macro-economic factors are as follows:

 Gross Domestic Product:
GDP indicates the rate of growth of the economy. GDP represents the
aggregate value of the goods and services produced in the economy. GDP
consists of personal consumption expenditure, gross private domestic
investment and government expenditure on goods and services and net
export of goods and services. The growth rate of economy points out the
prospects for the industrial sector and return investors can expect from
investment in shares. The higher growth rate is more favorable to the
stock market.

 Savings and investment:
It is obvious that growth requires investment which in turn requires
substantial amount of domestic savings. Stock market is a channel
through which the savings of the investors are made available to
corporate bodies. Savings are distributed over various assets like equity
shares, deposits, mutual fund units, real estate and bullion. The saving
and investment patterns of the public affect the stock to a great extent.

 Inflation:
Along with the growth of GDP, if inflation also increases, then the real rate
of growth would be very little. The demand in the consumer product
industry is significantly affected. If there is a mid level of inflation, it is

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good to the stock market but high rate of inflation is harmful to the stock
market.

 Interest rates:
The interest rate affects the cost of financing to the firms. A decrease in
interest rate implies lower cost of finance for firms and more profitability.
More money is available at a lower interest rate for the brokers who are
doing business with borrowed money. Availability of cheap fund
encourages speculation and rise in price of shares.

 Budget:
The budget draft provides an elaborate account of the government
revenues and expenditures. A deficit budget may lead to high rate of
inflation and adversely affect the cost of production. Surplus budget may
result in deflation. Hence, balanced budget is highly favorable to the stock
market.

 The tax structure:
Concessions and incentives given to a certain industry encourage
investment in that particular industry. Tax relief given to savings
encourages savings. The type of tax exemption has an impact on the
profitability of the industries.

 The Balance of payment:
BOP is the measure of the strength of rupee on external account. If the
deficit increases, the rupee may depreciate against other currencies,
thereby, affecting the cost of imports. The volatility of the foreign
exchange rate affects the investment of the foreign institutional investors
in the Indian Stock Market. A favorable balance of payment renders a
positive effect on the stock market.

 Monsoon and Agriculture:
Agriculture is directly and indirectly linked with the industries. A good
monsoon leads to higher demand for input and results in bumper crop.
This would lead to buoyancy in the stock market. When the monsoon is
bad, Agriculture and hydroelectric production would suffer. They cast a
shadow on the share market.

 Infrastructure facilities:
Infrastructure facilities are essential for the growth of industrial and
agricultural sector. A wide network of communication system is a must for
the growth of the economy. Regular supply of power without any power
cut would boost the production. Banking and financial sectors should also
be sound enough to provide adequate support to industry and agriculture.

 Demographic factors:
The demographic data provides details about the population by age,
occupation, literacy and geographic location. This is needed to forecast
the demand for the consumer goods. The population by age indicates the
availability of able work force. Population, by providing labor and demand
for products, affects the industry and stock market.

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Industry Analysis

Industry analysis is a type of investment research that begins by focusing on the
status of an industry or an industrial sector. Each industry has differences in
terms of its customer base, market share among firms, industry-wide growth,
competition, regulation and business cycles. Learning about how the industry
works will give an investor a deeper understanding of a company's financial
health. The Industry life cycle analysis and Porter‘s 5 forces model for
competitive advantage are common valuation techniques.

 Industry Life Cycle Model:
This model is a useful tool for analyzing the effects of an industry's
evolution on competitive forces. Using the industry life cycle model, we
can identify five industry environments, each linked to a distinct stage of
an industry's evolution.
a. Pioneering development: - During this start up stage, the industry
experiences modest sales growth and very small or negative profit
margins and profits. The market for the industry‘s product or
service during this time period is small, and the firms involved incur
major development costs.
b. Rapid accelerating growth: - During this rapid growth stage, a
market develops for the product or service and demand becomes
substantial. The profit margins are very high. The industry builds its
productive capacity as sales grow at an increasing rate as the
industry attempts to meet excess demands.
c. Mature stage: - The success in stage 2 has satisfied most of the
demands of the industry goods and services. Thus, further sales
growth may be above normal but it no longer accelerates. The rapid
growth of sales and the high profit margins attract competitors to
the industry, which causes an increase in supply and lower price,
which the profit margin begin to decline to normal levels.
d. Stabilization and market maturity: - During this stage which is
probably the longest stage, the industry growth rate declines to the
growth rate of aggregate economy or its industry segment.
Competition produces tight profit margins, and the rate of return on
capital eventually becomes below the competitive level.
e. Deceleration of growth and decline: - At this stage of maturity, the
industries sales growth declines because of shifts in demand or
growth in substitutes. Profit margins continue to be squeezed, and
some firms experiences low profits or even losses.

 Porter’s Five Forces Model:
This model identifies five competitive forces that shape every single
industry and market. These forces help us to analyze everything from
the intensity of competition to the profitability and attractiveness of an
industry.
a. Threat of New Entrants: - The easier it is for new companies to
enter the industry, the more cutthroat competition there will be.
Factors that can limit the threat of new entrants such as high
fixed cost, existing loyalty to major brands, government
regulations etc act as barriers to entry.

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b. Power of Suppliers: - This is how much pressure suppliers can
place on a business. If one supplier has a large enough impact
to affect a company's margins and volumes, then they hold
substantial power. When there are very few suppliers of a
particular product or there are no substitutes or switching to
another (competitive) product is very costly, the supplier is
powerful and vice versa.
c. Power of Buyers: - This is how much pressure customers can
place on a business. Some companies serve only a handful of
customers, while others serve millions. In general, it's a red flag
(a negative) if a business relies on a small number of customers
for a large portion of its sales because the loss of each customer
could dramatically affect revenues. If one customer has a large
enough impact to affect a company's margins and volumes, then
they hold substantial power.
d. Availability of Substitutes: - What is the likelihood that someone
will switch to a competitive product or service? If the cost of
switching is low, then this poses to be a serious threat. The
main issue is the similarity of substitutes. If substitutes are
similar, then it can be viewed in the same light as a new
entrant, which is a threat to the company.
e. Competitive Rivalry: - This describes the intensity of competition
between existing firms in an industry. A highly competitive
market might result from:
 Many players of about the same size, no dominant firm.
 Little differentiation between competitor‘s products and
services.
 A mature industry with very little growth. Companies can
only grow by stealing customers away from competitors.

Company Analysis

In the company analysis the investor assimilates the several bit of information
related to the company and evaluates the present and future value of stock. The
risk and return associated with the purchase of the stock is analyzed to take
better investment decision.

The present and future are affected by a number of factors. They are:-

 Competitive advantage of the company:
Competitive advantage (CA) is a position that a firm occupies in its
competitive landscape. A company's long-term success is driven largely by
its ability to maintain a competitive advantage - and keep it. Competitive
advantages vary from situation to situation and from time to time. Some
basic examples of CAs can be divided in 4 main global areas:
o Cost - Low cost operations
o Quality - High quality and consistent quality
o Time - delivery speed, on time delivery and development speed
o Flexibility - customization, volume flexibility and variety

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 Earnings of the company:
Sales alone do not increase the earnings but the costs and expenses of
the company also influence the earnings of the company. Further,
earnings do not always increase with the increase in sales. The company‘s
sales might have increased but its earnings may decline due to the rise in
costs.

 Capital structure:
The equity holder’s return can be increased manifold with the help of
financial leverage, i.e. using debt financing along with equity financing.
The effect of financial leverage is measured by computing leverage ratios.
The debt may be in the form of debentures and term loans from financial
institutions.

 Management:
Good and capable management generates profit to the investors. The
management of the firm should efficiently plan, organize, actuate and
control the activities of the company. The basic objective of management
is to attain the stated objectives of the company for the good of the equity
share holders, the public and the employers. Good management depends
on the quality of the manager. Some believe that management is the
most important aspect for investing in a company. It makes sense - even
the best business model is doomed if the leaders of the company fail to
properly execute the plan.

 Operating efficiency:
The operating efficiency of a company directly affects the earnings of a
company. An expanding company that maintains high operating efficiency
with a low break-even point earns more than the company with high
break-even points. If a firm has stable operating ratio, the revenue will
also be stable. Efficient use of fixed assets with a raw materials, labor and
management would lead to more income from sales. This leads to internal
fund generation for the expansion of the firm. A growing company should
have low operating ratio to meet the growing demand for its product.

 Business Model:
Even before an investor looks at a company's financial statements or does
any research, one of the most important questions that should be asked
is: What exactly does the company do? This is referred to as a company's
business model – it's how a company makes money. You can get a good
overview of a company's business model by checking out its website.
Unless you understand a company's business model, you don't know what
the drivers are for future growth, and you leave yourself vulnerable to
being blindsided.

 Corporate Governance:
Corporate governance describes the policies in place within an
organization denoting the relationships and responsibilities between
management, directors and stakeholders. These policies are defined and
determined in the company charter and its bylaws, along with corporate
laws and regulations. The purpose of corporate governance policies is to

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ensure that proper checks and balances are in place, making it more
difficult for anyone to conduct unethical and illegal activities Good
corporate governance is a situation in which a company complies with all
of its governance policies and applicable government regulations in order
to look out for the interests of the company's investors and other
stakeholders.

 Financial analysis:
The best source of financial information about a company is its own
financial statements. This is a primary source of information for evaluating
the investments prospects in the particular company‘s stock. Financial
statement analysis is the study of a company‘s financial statement from
various viewpoints. The statement gives the historical and current
information about the company‘s operations. Historical financial
statements help to predict the future. The current information aids to
analyze the present status of the company. The two main statements
used in analysis are:-
o Balance sheet
o Profit and loss account

Literature Review
Elton, Edwin J (1977), is among the prominent researchers, who have worked on
Sharpe's Single Index Model. They presented a new method for selecting optimal
portfolios when upper bound constraints on investments in individual stocks
were present and when the variance-covariance matrix of returns possessed a
special structure such as that implied by standard single index model. Extending
their previous work, more commonly called as EPG approach to portfolio
optimization, it was shown that upper bounds could be dealt within a more
complex fashion that shares many of the features of ranking procedures of
standard single index model.

Bawa, Vijay S (1979), showed that the construction of optimal portfolio could be
simplified by using simple ranking procedures when returns followed a stable
distribution and the dependence structure had any of several standard forms.
The ranking procedures simplified the computations necessary to determine an
optimum portfolio.

Faaland, Bruce H. and Jacob, Nancy l (1981), examined alternative solution
procedure to achieve the objective of choosing 'n' securities from a universe of
'm' securities in order to maximize the portfolio's excess-return-to Beta ratio.

Mulvey, John M (2003), observed that a multi-period portfolio model provides
significant advantages over traditional single-period approaches-especially for
long-term investors. Such a framework can enhance risk adjusted performance
and help investors evaluate the probability of reaching financial goals by linking
asset and liability policies.

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Statement of Problem
Investors generally hold a portfolio of securities to take advantage of
diversification, while individual return and risks are important, what matters
finally is the return and risk of the portfolio. In constructing a portfolio
fundamental analysis can be used to select securities or Sharpe single index
model can be used to construct an optimal portfolio. In many cases it is seen
that securities trade above their intrinsic value especially in the recent times
because of boom in stock market, as a result investors pay more to purchase
them and the returns are not up to the mark.

Objectives of the Study
 To undertake study of Banking Index as Compared to Information
Technology Index in Sensex (BSE)
 To construct a portfolio of banking index stocks and IT index stocks on
BSE
 To construct a portfolio of banking stocks using Sharpe single index model
 To find the return difference in optimal portfolio constructed using stocks
from these indexes

Research Methodology
Type of Study
The research conducted is basically a statistical analysis of historical stock price
on Sensex. It involves univariate regression of historical data against the
historical market data. In this project a study is conducted to determine the level
of significance in portfolio mean returns constructed through fundamental
analysis and Sharpe single index model.

Type of Data
Data required for this study was secondary data collected from BSE portal for
last 3 years.

Sample Size
The sample consists of companies of the banking and IT industry selected from
the respective industry index on Sensex.

Data Analysis and Interpretation
The process starts by selecting stocks to construct an optimum portfolio using
past share price data through the Sharpe‘s optimization model for both the
industries on Sensex. The return and risk aspects are then compared between
the two portfolios. Then the level of significance between the return of portfolios
is determined.

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Companies used for Analysis –

Banking Companies Information Technology Companies
Axis Bank Infosys Technologies
Bank of India HCL Technologies
Canara Bank Hexaware Technologies
Federal Bank mPhasis
HDFC Bank Oracle Financial Services
ICICI Bank Tata Consultancy Services
IDBI Bank Tech Mahindra
IndusInd Bank Wipro Technologies
Kotak Bank Fintech
Punjab National Bank
State Bank of India
Union Bank
Yes Bank

Calculation of Beta

Beta is a measure of a stock's volatility in relation to the market. The beta
coefficient is a key parameter in the capital asset pricing model (CAPM). It
measures the part of the asset's statistical variance that cannot be mitigated by
the diversification provided by the portfolio of many risky assets, because it is
correlated with the return of the other assets that are in the portfolio. The
formula for the Beta of an asset within a portfolio is,

For the analysis, we have regressed the historical prices of given securities
against the Sensex value for last 3 years.

Banking Securities

Security Return (1 Day) Variance Beta
HDFC Bank 0.0053 234.1810 1.2595
IndusInd Bank 0.0022 6.6013 1.1826
Yes Bank 0.0016 6.4847 1.3314
Federal Bank 0.0010 4.2658 0.9435
Canara Bank 0.0009 5.4607 1.0837
Axis Bank 0.0006 5.1921 1.3298
SBI 0.0005 4.3828 1.2307
PNB 0.0004 3.5339 0.9162
ICICI Bank 0.0005 5.0845 1.5054
Kotak Bank 0.0003 7.2809 1.1216
Bank of India 0.0003 5.7607 1.0850
Union Bank 0.0002 5.2375 0.9745
IDBI Bank 0.0001 5.4580 1.3846

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Information Technology Securities

Security Return (1 Day) Variance Beta
Hexaware Technologies 0.0022 15.3188 0.9982
TCS 0.0018 3.7571 0.9982
HCL Technologies 0.0015 5.0972 1.0524
Oracle Financial Services 0.0011 3.7010 0.6392
Infosys 0.0006 2.7709 0.8302
Wipro 0.0004 5.1139 0.7742
mPhasis 0.0002 6.6170 0.7564
Tech Mahindra 0.0002 5.9242 0.7550
FinTech -0.0004 7.2675 0.8669

Portfolio Construction using Sharpe’s Single Index Model
Every investor faces the dilemma, of which scrip‘s to select for his portfolio to
get adequate return. Besides, the investor has to decide how much to invest in
each script. Simple Sharpe Portfolio Optimization model enables the investor to
find a portfolio that best meets the goals, objectives and risk tolerance of the
investor. The method also stresses on portfolio optimization, which is an
important component of the portfolio selection process. It helps to select a set of
script‘s, which provides the highest rate of return for the lowest risk that the
investor is willing to take.
Steps for finding the stocks to be included in the optimal portfolio are:
1. Find out the ―excess return to beta‖ ratio for each stock under
consideration.
2. Rank them from the highest to the lowest.
3. Proceed to calculate Ci for all stocks according to the ranked order using
the following formula-

The cumulative values of Ci start declining after a particular Ci and that point is
taken as the cut-off point and that stock ratio is the cut-off ratio C.

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Sharpe’s Excess Return to Beta Ratio

It is a single number that measures the desirability of any stock to be included in
the optimal portfolio. The excess return to beta ratio measures the additional
return on a security (excess of the risk free asset return) per unit of systematic
risk or non-diversifiable risk.

Excess return to beta = (Ri – RF) / Bi
Where:
Ri = expected return on stock i
Rf = return on risk free asset
Bi = expected change in the rate of return on stock i associated with a 1%
change in the market return. Stocks are ranked by excess return to beta (from
the highest to the lowest). The higher the excess return to beta ratio, the more
is the desirability of the stock to be included in the portfolio.

Ranking of Securities According to Excess Return to Beta

Banking Securities

SN Rank Security Return Variance Beta ERTB
1 5 HDFC Bank 0.0053 234.1810 1.2595 0.393%
2 8 IndusInd Bank 0.0022 6.6013 1.1826 0.159%
3 13 Yes Bank 0.0016 6.4847 1.3314 0.097%
4 4 Federal Bank 0.0010 4.2658 0.9435 0.073%
5 3 Canara Bank 0.0009 5.4607 1.0837 0.054%
6 1 Axis Bank 0.0006 5.1921 1.3298 0.024%
7 11 SBI 0.0005 4.3828 1.2307 0.018%
8 10 PNB 0.0004 3.5339 0.9162 0.011%
9 6 ICICI Bank 0.0005 5.0845 1.5054 0.010%
10 9 Kotak Bank 0.0003 7.2809 1.1216 0.002%
11 2 Bank of India 0.0003 5.7607 1.0850 -0.005%
12 12 Union Bank 0.0002 5.2375 0.9745 -0.016%
13 7 IDBI Bank 0.0001 5.4580 1.3846 -0.017%

Information Technology Securities

SN Rank Security Return Variance Beta ERTB
5 1 Hexaware Technologies 0.0022 15.3188 0.9982 0.190%
8 2 TCS 0.0018 3.7571 0.9982 0.149%
11 3 HCL Technologies 0.0015 5.0972 1.0524 0.113%
1 4 Oracle Financial Services 0.0011 3.7010 0.6392 0.124%
6 5 Infosys 0.0006 2.7709 0.8302 0.033%
2 6 Wipro 0.0004 5.1139 0.7742 0.007%
4 7 mPhasis 0.0002 6.6170 0.7564 -0.012%
12 8 Tech Mahindra 0.0002 5.9242 0.7550 -0.015%
9 9 FinTech -0.0004 7.2675 0.8669 -0.087%

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Combined Portfolio

Rank SN Security Return Variance Beta ERTB
1 19 TCS 0.0018 3.7571 0.8867 0.168%
2 8 IndusInd Bank 0.0022 6.6013 1.1826 0.159%
3 13 Yes Bank 0.0016 6.4847 1.3314 0.097%
4 15 HCL Technologies 0.0015 5.0972 1.0524 0.113%
5 4 Federal Bank 0.0010 4.2658 0.9435 0.073%
6 18 Oracle Financial 0.0011 3.7010 0.6392 0.124%
7 16 Hexaware 0.0022 15.3188 0.9982 0.190%
8 3 Canara Bank 0.0009 5.4607 1.0837 0.054%
9 14 Infosys 0.0006 2.7709 0.8302 0.033%
10 1 Axis Bank 0.0006 5.1921 1.3298 0.024%
11 11 SBI 0.0005 4.3828 1.2307 0.018%
12 6 ICICI Bank 0.0005 5.0845 1.5054 0.010%
13 10 PNB 0.0004 3.5339 0.9162 0.011%
14 5 HDFC Bank 0.0053 234.1810 1.2595 0.393%
15 21 Wipro 0.0004 5.1139 0.7742 0.007%
16 9 Kotak Bank 0.0003 7.2809 1.1216 0.002%
17 2 Bank of India 0.0003 5.7607 1.0850 -0.005%
18 17 mPhasis 0.0002 6.6170 0.7564 -0.012%
19 20 Tech Mahindra 0.0002 5.9242 0.7550 -0.015%
20 12 Union Bank 0.0002 5.2375 0.9745 -0.016%
21 7 IDBI Bank 0.0001 5.4580 1.3846 -0.017%
22 22 FinTech -0.0004 7.2675 0.8669 -0.087%

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Determination of Optimal Portfolio

Risk Free Rate Rf (1 Day) 0.0321%
Market Variance 1.5088

Banking Portfolio

ERTB (Rs-Irf)*Beta Cumm. Beta^2 Cumm. Cut-off Xi
Rank SN Security Return Variance Beta Zi
(Rs-Irf)/Beta /Variance Summ. /Variance Summ. (B) Weight
1 5 HDFC Bank 0.0053 234.1810 1.2595 0.393% 0.0000266 0.00027 0.0068 0.0068 0.004% 0.002% 5.72%
2 8 IndusInd Bank 0.0022 6.6013 1.1826 0.159% 0.0003360 0.00363 0.2119 0.2186 0.041% 0.018% 57.48%
3 13 Yes Bank 0.0016 6.4847 1.3314 0.097% 0.0002643 0.00627 0.2734 0.4920 0.054% 0.008% 25.66%
4 4 Federal Bank 0.0010 4.2658 0.9435 0.073% 0.0001526 0.00779 0.2087 0.7007 0.057% 0.004% 11.15%
5 3 Canara Bank 0.0009 5.4607 1.0837 0.054% 0.0001170 0.00897 0.2151 0.9157 0.057%
6 1 Axis Bank 0.0006 5.1921 1.3298 0.024% 0.0000817 0.00082 0.3406 0.3406 0.008%
7 11 SBI 0.0005 4.3828 1.2307 0.018% 0.0000624 0.00144 0.3456 0.6862 0.011%
8 10 PNB 0.0004 3.5339 0.9162 0.011% 0.0000269 0.00171 0.2376 0.9237 0.011%
9 6 ICICI Bank 0.0005 5.0845 1.5054 0.010% 0.0000431 0.00214 0.4457 1.3694 0.011%
10 9 Kotak Bank 0.0003 7.2809 1.1216 0.002% 0.0000034 0.00218 0.1728 1.5422 0.010%
11 2 Bank of India 0.0003 5.7607 1.0850 -0.005% -0.0000095 0.0208 0.2044 1.7466 0.009%
12 12 Union Bank 0.0002 5.2375 0.9745 -0.016% -0.0000289 0.00179 0.1813 1.9279 0.007%
13 7 IDBI Bank 0.0001 5.4580 1.3846 -0.017% -0.0000606 0.00118 0.3513 2.2792 0.004%
Cut-off 0.057% 0.032%
Weight Return Beta Weighted Return Weighted Beta Excess return on Beta
5.716% 0.53% 1.2595 0.0003015 0.0720 0.393% 0.0002
57.479% 0.22% 1.1826 0.0012628 0.6797 0.159% 0.0009
25.656% 0.16% 1.3314 0.0004127 0.3416 0.097% 0.0002
11.149% 0.10% 0.9435 0.0001127 0.1052 0.073% 0.0001
100.000% 0.00209 1.19851 0.00147

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Information Technology Portfolio

ERTB (Rs-Irf)*Beta Cumm. Beta^2 Cumm. Cut-off Xi
Rank SN Security Return Variance Beta Zi
(Rs-Irf)/Beta /Variance Summ. /Variance Summ. (B) Weight
5 1 Hexaware Tech. 0.0022 15.3188 0.9982 0.190% 0.0001 0.0001 0.0650 0.0650 0.017% 0.008% 16.380%
8 2 TCS 0.0018 3.7571 0.9982 0.149% 0.0004 0.0005 0.2652 0.3303 0.052% 0.021% 44.328%
11 3 HCL Technologies 0.0015 5.0972 1.0524 0.113% 0.0002 0.0008 0.2173 0.5476 0.063% 0.009% 19.313%
1 4 Oracle Financial 0.0011 3.7010 0.6392 0.124% 0.0001 0.0009 0.1104 0.6580 0.068% 0.010% 19.980%
6 5 Infosys 0.0006 2.7709 0.8302 0.033% 0.0001 0.0010 0.2487 0.9067 0.063%
2 6 Wipro 0.0004 5.1139 0.7742 0.007% 0.0000 0.0010 0.1172 1.0239 0.059%
4 7 mPhasis 0.0002 6.6170 0.7564 -0.012% 0.0000 0.0010 0.0865 1.1103 0.055%
12 8 Tech Mahindra 0.0002 5.9242 0.7550 -0.015% 0.0000 0.0010 0.0962 1.2066 0.052%
9 9 FinTech -0.0004 7.2675 0.8669 -0.087% -0.0001 0.0009 0.1034 1.3100 0.044%
Cut-off 0.068% 0.048%

Weight Return Beta Weighted Return Weighted Beta Excess return on Beta
Summary
16.380% 0.22% 0.9982 0.0003629 0.1635 0.190% 0.0003
Portfolio Return (1 Day) 0.168%
44.328% 0.18% 0.9982 0.0008014 0.4425 0.149% 0.0007
Portfolio Return (Annual) 42.331%
19.313% 0.15% 1.0524 0.0002927 0.2033 0.113% 0.0002
Portfolio Beta 0.9370
19.980% 0.11% 0.6392 0.0002228 0.1277 0.124% 0.0002
100.000% 0.0016798 0.9370 0.0014

16


Portfolio using combination of securities from both the indexes

(Rs-
ERTB Cumm. Beta^2 Cumm. Cut-off Xi
Rank SN Security Return Variance Beta Irf)*Beta Zi
(Rs-Irf)/Beta Summ. /Variance Summ. (B) Weight
/Variance
1 19 TCS 0.0018 3.7571 0.8867 0.168% 0.0004 0.0004 0.2093 0.2093 0.040% 0.020% 34.058%
2 8 IndusInd Bank 0.0022 6.6013 1.1826 0.159% 0.0003 0.0007 0.2119 0.4211 0.063% 0.014% 23.119%
3 13 Yes Bank 0.0016 6.4847 1.3314 0.097% 0.0003 0.0010 0.2734 0.6945 0.070% 0.003% 5.009%
4 15 HCL Technologies 0.0015 5.0972 1.0524 0.113% 0.0002 0.0012 0.2173 0.9118 0.076% 0.006% 10.904%
5 4 Federal Bank 0.0010 4.2658 0.9435 0.073% 0.0002 0.0014 0.2087 1.1205 0.076%
6 18 Oracle Financial 0.0011 3.7010 0.6392 0.124% 0.0013709 0.00149 0.1104 1.2308 0.079% 0.007% 12.245%
7 16 Hexaware 0.0022 15.3188 0.9982 0.190% 0.0012342 0.00161 0.0650 1.2959 0.082% 0.007% 11.838%
8 3 Canara Bank 0.0009 5.4607 1.0837 0.054% 0.0011705 0.00173 0.2151 1.5110 0.079%
9 14 Infosys 0.0006 2.7709 0.8302 0.033% 0.0008177 0.00181 0.2487 1.7597 0.075%
10 1 Axis Bank 0.0006 5.1921 1.3298 0.024% 0.0008173 0.00189 0.3406 2.1003 0.068%
11 11 SBI 0.0005 4.3828 1.2307 0.018% 0.0006242 0.00195 0.3456 2.4459 0.063%
12 6 ICICI Bank 0.0005 5.0845 1.5054 0.010% 0.0004308 0.00200 0.4457 2.8916 0.056%
13 10 PNB 0.0004 3.5339 0.9162 0.011% 0.0002690 0.00202 0.2376 3.1291 0.053%
14 5 HDFC Bank 0.0053 234.1810 1.2595 0.393% 0.0002664 0.00205 0.0068 3.1359 0.054% 0.002% 2.826%
15 21 Wipro 0.0004 5.1139 0.7742 0.007% 0.0000819 0.00206 0.1172 3.2531 0.053%
16 9 Kotak Bank 0.0003 7.2809 1.1216 0.002% 0.0000342 0.00206 0.1728 3.4259 0.050%
17 2 Bank of India 0.0003 5.7607 1.0850 -0.005% -0.0000949 0.00205 0.2044 3.6302 0.048%
18 17 mPhasis 0.0002 6.6170 0.7564 -0.012% -0.0001050 0.00204 0.0865 3.7167 0.047%
19 20 Tech Mahindra 0.0002 5.9242 0.7550 -0.015% -0.0001460 0.00203 0.0962 3.8129 0.045%
20 12 Union Bank 0.0002 5.2375 0.9745 -0.016% -0.0002894 0.00200 0.1813 3.9943 0.043%
21 7 IDBI Bank 0.0001 5.4580 1.3846 -0.017% -0.0006065 0.00194 0.3513 4.3455 0.039%
22 22 FinTech -0.0004 7.2675 0.8669 -0.087% -0.0008999 0.00185 0.1034 4.4489 0.036%
Cut-off 0.082% 0.059%

17


Portfolio Securities Weights Return Beta Weighted Return Beta Excess Return to Beta

TCS 34.058% 0.18% 0.8867 0.0006 0.3020 0.168% 0.0006
IndusInd Bank 23.119% 0.22% 1.1826 0.0005 0.2734 0.159% 0.0004
Yes Bank 5.009% 0.16% 1.3314 0.0001 0.0667 0.097% 0.0000
HCL Technologies 10.904% 0.15% 1.0524 0.0002 0.1148 0.113% 0.0001
Oracle Financial 12.245% 0.11% 0.6392 0.0001 0.0783 0.124% 0.0002
Hexaware 11.838% 0.22% 0.9982 0.0003 0.1182 0.190% 0.0002
HDFC Bank 2.826% 0.53% 1.2595 0.0001 0.0356 0.393% 0.0001
100.000% 0.0019 0.9889 0.0016

Summary
Portfolio Return (Day) 0.192%
Portfolio Return (Annual) 48.318%
Portfolio Beta 0.9889

18

Once the securities to be included in the portfolio are decided, the next step is to
determine the weight of each security to be included in the portfolio as follows –

In the above formula the second expression determines the relative investment
in each security. The first determines the weight of each security in the portfolio
so that they sum to 1. This ensures full investment.

Comparison of the Portfolios

Number of Included in Weighted Weighted
Industry
Securities Portfolio Return Beta
Banking 13 4 52.661% 1.1985
IT 9 4 42.331% 0.9370
Combined 22 7 48.318% 0.9889

Equation of SML: y = 2.996x + 8.1

Observations

 Banking Portfolio has higher return than IT Portfolio and at the same time
is riskier than the other.
 We see that, the return is directly proportional to the risk incurred by the
portfolio means greater the risk, higher is the return.
 Banking Portfolio is more volatile than IT Portfolio because it has higher
beta value hence there are chances to get more return.

19


 All our portfolios lies above the SML Line hence are undervalued. So, we
can invest on any of the given portfolios depending on our risk and return
requirement.
 When combining both the industries into one portfolio, we can work out
our risk and return equation to obtain required results.

Portfolio Construction Worksheet

Banking Index.xlsx IT Index.xlsx Combined
Portfolio.xlsx

20


References
 Portfolio Construction Using Fundamental Analysis, Alliance Business
Academy
 Investopedia
 Wikipedia
 bseindia.com
 in.finance.yahoo.com
 money.rediff.com

21

SAPM - Portfolio Construction and Comparison for Securities on BSE

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