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A STUDY ON CONSTRUCTION OF OPTIMUM PORTFOLIO USING SHARPE’S SINGLE INDEX MODEL

A STUDY ON CONSTRUCTION OF OPTIMUM PORTFOLIO USING SHARPE’S INDEX MODEL

SUJAY J

SURANA COLLEGE, 4TH SEM M.COM

BANGALORE-004

Under the Guidance of

DR. HARISH KUMAR

ABSTRACT

Numerous financial specialists need to put their reserve funds in different venture Product to increase arrival and the individuals who are daring individuals they put their reserve funds in the securities exchange. It is an unstable market which moves towards all over based on straightforward financial idea request and gracefully. This unpredictability is known as the danger of the market furthermore, to spare the speculators against this instability of the market. Stock trade presents another idea for example Portfolio where the speculators get the chance to lessen the hazard through the sectioning the aggregate venture sum in the bundle of protections. In the diverse proportion, the best strategy for developing a Portfolio is Sharp Single Index Model which covers all the components like portfolio return, portfolio change, portfolio standard deviation, and weightage of stocks. The information ought to be taken from www.bseindia.com for the timespan of January 2010 to December 2013 on a month to month premise in BSE Sensex as a market entertainer.

The fundamental destinations of the examination are to get a knowledge into the thought implanted in Sharpe's Single Index Model, to build an ideal portfolio experimentally utilizing the Sharpe's Single Index Model, to decide return and danger of the ideal portfolio developed by utilizing. Sharpe's Single Index Model. The technique is figured a one of a kind cut off rate and select those protections whose abundance come back to beta proportion is more prominent than a cut off rate. at that point extent of interest in each chosen protection ought to settle based on the beta worth, unsystematic hazard, overabundance come back to beta proportion and cut off the pace of each security is concerned.

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CHAPTER 1

INTRODUCTION

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1.1 INTRODUCTION TO INVESTEMET

Investing capital has become a very complicated job in the present market scenario. Lots of people have no clear understanding of how to increase their wealth with earned income. All investments are risky and investors must make a lot of effort to consider the factors affecting investments such as risk and return. This study is about "making the optimal portfolio using a single index model of Sharpe."

This project focuses on creating an ideal stock portfolio in the National Stock Exchange and assessing the investor's risk and return on investment and helping investors optimize their return with minimal risk.

Investment is the fund's employment on the assets to gain an increase in profits. Every investment comes with a return and a risk. The capacity for variance in actual return is called investment risk. The anticipation of return is an integral part of an investment. The expected return will be realized in the future, and there is a probability that the anticipated return will be higher or lower than the actual return and risk associated with an investment. And the main considerations of any investment are risk and return.

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1.2 OPTIMUM PORTFOLIO

Optimal stock portfolio refers to a stock portfolio that incorporates stocks configured in such a way that an optimal return is analytically probable at a given level of risk received by the investor. An ideal portfolio is an asset selection that sufficiently helps an investor meet his or her financial goals. Such a portfolio is designed to include assets that the investor is comfortable with, and carries a degree of risk that is acceptable to the overall investment approach employed by the investor.

Determining whether or not a portfolio is efficient or optimal is subjective since what is good for one investor may or may not serve the needs of another investor with equal capacity.

To determine the portfolio is truly optimal, it is important to be closely aligned with investor preferences and objectives. This later involves the calculation of the general model or the investor's approach to finance is general. Someone who is extremely reactionary with money may be very uncomfortable with buying an asset that has a higher rate of instability.

Investors who are interested in taking more chances are likely to be unrecognized by collecting somewhat traditional and lower-yielding assets. When this was the point at which the optimal portfolio would focus on the acquisition of stocks, commodities and other investments that would give rise to higher returns while the opportunity to earn higher returns is present, the investments are also more volatile, increasing the possibility of incurring some losses along the way. With attention to detail and taking into account investment preferences, it is possible to build an ideal portfolio that strikes a balance between risk and return and helps the investor to reach financial goals. (Mani, 2016)

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1.3 PORTFOLIO REVISION

Portfolio revision is one of the pillars of the overall process of portfolio management. It entails assessing the change in portfolio composition over some time and taking steps, if required, to get it back in line with the investment objective and risk tolerance framework with which the portfolio was initially constructed. Portfolio revision also helps investors in keeping their investments relevant to changing times and trends. The primary intention behind portfolio revision is to achieve an optimal amount of returns for a given level of risk.

Active Portfolio Revision

As the name of the technique suggests, an investor or professional portfolio manager makes adjustments to the portfolio very hands-on. The fundamental theory behind the active revision of portfolios is that in-depth equity research and analysis will uncover investments that can beat market returns as inefficient markets. To gain an advantage over others, subscribers of this strategy do not find the concept of market returns appealing and respond to changes in market situations.

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Passive Portfolio Revision

In a passive revision of the portfolio, the primary goal is to preserve earning market returns by implementing, for the most part, a buy-and-hold approach. This is not to say that changes are not made to the portfolio at throughout the investment horizon, just the portfolio changes are less in number compared to the active strategy and portfolio managers do not react to every change in the direction of markets.

1.4 PORTFOLIO REVISION STRATEGIES

There were essentially two different portfolio revision strategies, they are

• Active portfolio revision strategies

• Passive portfolio revision strategies

An investor prefers both of these strategies aimed at creating a portfolio using conventional and modern portfolio strategies and then managing and monitoring the portfolio to achieve investment objectives. The fund managers who use successful market strategies or components strategy are called market timers. Active management will increase the return the portfolio receives.

Reflect in the price of the securities. If that was right investor wouldn't expect to do better consistently than the market by handling or managing their portfolios.

Passive portfolio revision approach requires only small and infrequent changes, according to the above-timed portfolio. The portfolio manager following this strategy believes the market is insightful effective, and the investors have expectations similarly. They consider a meagre reason to regularly update successful trading and review the portfolio.

Under this set of techniques, certain fixed procedures and rules are modified.

1.5 PORTFOLIO RISK AND RETURN

Our risk-return study has so far been limited to single assets kept in solitary confinement. In the real world, we never see investors pouring all of their resources into one asset or investment. Instead, they construct a portfolio of investments and thus the study of risk-return is expanded in portfolio sense.

A portfolio consists of two stocks or more. Each portfolio has its risk-return characteristics. A portfolio of securities offering maximum return for a given level of risk or minimal risk for a given level of return is called a 'productive portfolio.

Portfolio theory provides investors with a rational approach to making decisions to invest their capital in under-risk assets or securities. The theory is based on the assumption that investors are averse to risk. Harry Markowitz's original portfolio theory notes that portfolio risk, unlike portfolio return, is more than a pure accumulation of risk, unlike portfolio return, is more than a simple aggregate of the risks of individual assets.

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I. Portfolio Return:

The expected return of a portfolio represents the weighted average of the expected returns on the securities comprising that portfolio with weights being the proportion of total funds invested in each security.

The following formula can be used to determine the expected return of a portfolio:

II. Portfolio Risk:

Unlike the expected return on a portfolio that is merely the weighted average of the expected returns on the portfolio assets, portfolio risk is not the plain, weighted average of the standard deviations of the portfolio assets.

For this reason, considering a weighted average of individual security deviations amounts to ignoring the relationship or covariance between securities returns. Moreover, the portfolio's total risk involves the asset's interactive risk relative to the others, calculated by the covariance of returns. Covariance is a statistical measure of the extent to which two variables (the returns of securities) shift together. And covariance relies on the association of returns on portfolio securities. (YourArticleLibrary, n.d.)

The formula for determining the covariance of returns of two securities is:

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1.6 INDEX MODELS

The central and primary goal of o investment analysis is to provide a way of determining the investor's optimal portfolio when there are more possibilities. An optimal portfolio is a feasible portfolio that provides an investor with the highest fulfilment level that produces higher returns at the lowest price.

The one big drawback of the Markowitz model is that it requires a large number of input details to be inserted into the portfolio to measure the return variance of all securities and also the return covariance for each securities combination.

A much greater simplification is required to reduce the number of assessments as well as the computational frame function. Such simplification can be done using an index model. They assume that those movements are aware of various factors in the form of return on protection. Index approach aims to incorporate more economic variables as a return-creating mechanism that methodically shift the prices of all securities. A return generating process is a statistical model tool which derives how the security returns are produced. Index model is a powerful portfolio management method that provides the data for calculating the expected return, variance and covariance.

There are two types of index model

Single Index Model Multi-Index Model.

1.7 SINGLE INDEX MODEL

Sharps assume that security returns are linearly related to a single index, such as the stock index.

• Over-time casual analysis of stock prices shows that the majority of stock prices shift with the market index.

• As the stock price rises Sensex wi1l always continues to grow and vice versa.

• This means that other variables below are having an impact on the we1l market index as stock prices.

• Stock prices are market index-related and the relation may be used to estimate stock returns

Some investors argue that return generating process for securities involves a single index factor that is market model. Normal observation of the share prices over a term of time reveals, that the greatest number of share prices increases with the increase in the index and vice-versa. This recommends that some essential factors influence the market index as well as the stock prices. It refers that share price and index are correlated and where is a co-movement of stock with a market index. can be studied with the help out of simple linear regression analysis. In this analysis, the return on the single securities is taken as a dependent variable (Ri) and the gain on the market index (Rm) as an independent or individual variable.

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Sometimes named single index model as a one-factor model. It is the portfolio selection method which is the simplest and most commonly used. The Sharpe Single Index is Markowitz model modification of the complexity of dealing with a large number of covariances by providing a simpler technique of representing the relationships between the securities.

Fundamental rule or concept underlying Sharpe’s simplified approach to portfolio analysis is that the only form of movement between the securities comes from a common response to a common market index such as Sensex, nifty.

The Single Index Model (SIM) is an asset pricing model, according to which the returns on security can be represented as a linear relationship with any economic variable relevant to the security. In the case of stocks, this single factor is the market return.

The SIM for stock returns can be represented as follows:

Where:

Alpha (α) represents the abnormal returns for the stock

β(rm − rf) represents the movement of the market modified by the stock’s beta

ε represents the unsystematic risk of security due to firm-specific factors.

According to this equation, asset’s returns are influenced by the market (reflected in beta), it has firm-specific excess returns (reflected in alpha) and also has firm-specific risk (the residual). (FinanceTrain, n.d.)

Single index model features There were two essential features of the single index model Sharpe they are: -

• Tangible portfolio

• Diversification

• Tangible portfolio

This is also one of the main features of the single-index model. One of the premises of the single-index model is that the return on the reaction of securities to the single common factor which is the index of markets. The hypothesis simplifies the task of defining the portfolios of tangency. To order to determine the composition of tangency portfolios, the investor must presume all of the projected returns, volatility and co-variance on bonds. With a single index model, this can be easily achieved by estimating αi, βi and σei for the N risky securities. The assumed value of the factor (Rm) and its standard deviation (σm) are also needed. With these assess the efficiency set of Markowitz can be obtained easily and the tangency portfolio can be calculated for the given level of risk-free rate (Rf) of return.

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https://financetrain.com/how-to-calculate-stock-beta-in-excel/

https://financetrain.com/jensens-alpha/


• Diversification

The diversification is another important aspect of the single-index model. As stated earlier, diversification reduces different portfolio-related risks. When the portfolio becomes more diversified, each security ratio or weight becomes greater or bigger with a constant βp (the price of) βp not increasing dramatically unless deliberate attempts are made to do so, diversification leads to an average factor risk and decreases the non-factor risk.

1.8 MULTI-INDEX MODEL

A multifactor model is a financial model that uses multiple variables in its equations to describe market conditions and/or asset prices in equilibrium. The multifactor model can be used to describe either an individual security or a securities portfolio. Comparing two or more factors to evaluate the relationships between variables and the resulting results, it does so.

Multi-factor models can be divided into three categories: macroeconomic models, fundamental models and statistical models. Macroeconomic models compare a security's return to such factors as employment, inflation and interest. Fundamental models analyze the relationship between a security's return and its underlying financials, such as earnings. Statistical models are used to compare the returns of different securities based on the statistical performance of each security in and of itself.

The three most commonly used approaches to construct a multi-factor model are “Combination model, Sequential model, and an Intersectional model”. In a combination model, multiple single-factor models, which utilize a single factor to distinguish stocks, are combined to create a multi-factor model. For example, stocks may be sorted based on momentum alone in the first pass. Subsequent passes will use other factors, such as volatility, to classify them. A sequential model sorts stocks based on a single factor sequentially to create a multi-factor model.

The model with a single index is the simplest or the easiest. It can be regarded as being at another extreme point in one significant point of continuity with the Markowitz model. The multi-index can be put at the midpoint of portfolio selection tool continuity. This also means the stock price moves together due to single causes, i.e. market index. Nevertheless, dosage does not constitute accounts for all factors that affect the stock price. These considerations aside from market conditions:

• Exchange rate

• Interest cost

• GDP growth rate

• Inflation rate. (Investopedia, 2019)

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CHAPTER 2

REVIEW OF LITERATURE AND RESEARCH DESIGN

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RESEARCH DESIGN

2.1 TITLE OF THE STUDY

‘‘A STUDY ON CONSTRUCTION OF OPTIMUM PORTFOLIO USING SHARPE’S SINGLE INDEX MODEL”

2.2 INTRODUCTION TO STUDY

In today's long-term stock market scenario or situation, making an investment decision is more complicated, because of the uncertainty on the long-term capital market it is very hard or difficult for the investor to make decisions. Before investing, there are factors such as risk and return that must be analyzed by the investor. And he needs to use various strategies and methods to build an optimal portfolio to reduce the risk and optimize the investment benefit.

In the different ratio, the best method of constructing a Portfolio is Sharp Single Index Modelwhich covers all the factors like portfolio return, portfolio variance,portfolio standard deviation, and weightage of stocks. (Sen, 2014)

‘Research on the optimum portfolio using Sharp's index model’ is carried out to evaluate stock risk and return and constructing an optimum portfolio. That assist the investor in determining the investment percentage and lowering the risk by diversifying their investment and maximizing their return on investment.

2.3 STATEMENT OF THE PROBLEM

This study is concentrated on the creation of an optimal portfolio by analyzing the risks and return analysis of different sectors by using Sharpe’s single index model. Which will be helpful for the investors in making the investment decisions on the percentage of investment to make on stocks. As the Indian capital market is performing or doing well and it’s the right opportunity for the investor to invest and reduce risk and maximize their returns.

A problem arises for an investor in selecting the security from more securities available on the long-term capital market. Selecting certain securities that perform well and offer nice returns with low risk attached to it is difficult for investors. Because many investors are unaware of the risk involved in many of the securities they invest in securities of this type and end up losses. (Mani, 2016)

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2.4 OBJECTIVE OF THE STUDY

➢ To evaluate the percentage of investment to be made in the selected portfolio

➢ To analysis the risk and return for the investments made by an investor

➢ To assist the investor in maximizing their return with the minimum risk

➢ To analyze the movements of stocks and the performance of selected securities

➢ To get the practical knowledge or information involved in sharp’s single index model

➢ To analyze the marketability of securities involved

The main objectives of the study are: -

1. To get an insight into the idea embedded in Sharpe’s Single Index Model.2. To construct an optimal portfolio empirically using the Sharpe’s Single IndexModel.3. To determine return and risk of the optimal portfolio constructed by usingSharpe’s Single Index Model.

2.5 SCOPE OF THE STUDY

Selection of companies is restricted BSE index only for the Pharmaceutical sector. The biggest and effective pharma companies are chosen and analyzed based on their one-month performance.

The number of companies selected is 15 based on their previous historical data.

2.6 LIMITATIONS OF THE STUDY

• Stock values are considered only for the one-month duration.

• Portfolio was to be constructed using Sharp’s single index model basically which uses companies stock values movement and does not consider another factor.

• The number of companies is also restricted to 15 companies.

• Portfolio is built or constructed based on risky and return.

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2.7 RESEARCH METHODOLOGY

To address the key research objectives, this research used both qualitative and quantitative methods and the combination of primary and secondary sources. The qualitative data support quantitative data analysis and results. The result obtained is triangulated since the researcher utilized the qualitative and quantitative data types in the data analysis.

The methodology of analysis is a way to figure out the outcome of a particular situation on a clear-cut issue or question which has also been referred to as the study question. Both qualitative and quantitative need to be used in research methods.

The method used in this study is descriptive and objective research since it deals with statistical data and secondary data sources are used in stock analysis.

Techniques adopted

❖ The calculation is made through excel using historical data

❖ The graphical representation is done on the performance of stock return with companies return

❖ Tables are drawn based on historical data and the result obtained from an optimal portfolio.

2.8 SOURCES OF DATA

Instead, there are two data sources:

1. Internal Source

This is known as the primary source because data are gathered from the organization’s own documentation and documents.

A business publishes, for example, the 'Annual Report' on Profit and Loss, Net Revenue, Loans, Wages etc.

2. External Source

It is known as the external source when data are obtained from outside the organization.

For example, if a Tour and Travel Company gets information from Karnataka Transport Corporation about 'Karnataka Tourism' it will be considered as external data sources.

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Primary Data:

This is the data of raw data, which is collected for the first time by a person for the research study which includes personal opinions. In this data collected for the companies’ profile is primary data. In other words, primary data is a source of data it is collected by the researcher for the first time using methods like survey, interview, experiment etc.

Secondary Data:

Secondary data is referring to data which is collected by anyone who is someone other than the user of it. This is the data which is already collected by anyone for study purpose. In the study secondary data has been collected for stock analysis data are collected from a website like NSK.com, Yahoofinance.com, textbooks and journals used in literature review and nifty stock exchange etc.

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REVIEW OF LITERATURE

2.9 LITERATURE REVIEW

(Dr. Navya V, October 2019, pp. 1-365)

Investments are quite an efficient tool for every investor and thus it adds a great significance to the collection of portfolios. As William Sharpe’s model mainly suggests on the maximum return out of minimum risk, every investment involves risk and return in equal proportionality where the investor needs to properly analyze his plans when and where to invest. These techniques help investors to meet their financial goals. Single Index Model has been used to study and understand the excess return to beta ratios of various securities under the various amount of considerable studies. Over the years of investment, the BSE (1875) has made an enormous amount of progress and raise in terms of capital appreciation. The appropriate decisions should be made only after considering effective factors of investment techniques.

(Hyung Park, February 18, 2020)

In this paper, we propose a simple and intuitive single-index regression approach to estimating from an observational study an optimally individualized dose rule from. To model interaction effects between the covariates of patients and a treatment variable defined on a continuum.

A portfolio is a package of or a mixture of individual assets or securities and normative approach is given by portfolio theory. The belief that investors are risk-averse is based on that. This means that investors hold investments that are well diversified, rather than investing all of their capital in a single or few properties. Investors who oppose investment strategies that are fair play, or worse, are risk-averse.

Low risk to the portfolio for the expected return. This can be done on behalf of Sharpe's proposed single index (beta) model.

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(Tanuj Nandan, 2017, pp. 74-83)

In recent years, designing an ideal portfolio has become increasingly difficult, as investors expect their respective investments to optimize returns and reduce risks. To make the right investment choices, an investor needs to have good knowledge of the security analysis and portfolio theory. Harry Markowitz developed a comprehensive model in early 1950, which stated that investors can reduce their risk through diversification. Sharpe's Single Index Model (SIM) is used in the present study to build an optimal portfolio. The reason for choosing SIM over the Markowitz model is that it needs fewer inputs and can be measured more easily.

Investment is called the use of funds on assets to earn a return and capital appreciation. Any investment includes risk and return. To make the right investment decisions, an investor needs to have sufficient information about security analysis and portfolio theory. This can be achieved through either traditional or modern portfolio building approach.

(J.Murthy, 2018, pp. 126-134)

When making investment decisions particularly on the equity market, risk and return play an important role, perhaps the most major issue is what stocks should be put in the portfolio. A successful portfolio mix of equity stocks can yield a better return for a given level of risk.

The main focus of this research is to create an optimal portfolio with the aid of the Sharpe Single Index model in Indian stock market. In this report, a total of 14 metal stocks were selected from the iron and steel industries and these stocks form the NSE Nifty Metal Index.

The most critical thing for sound investment and decision-making has emerged the security analysis and portfolio management. The portfolio is a mix of securities, shares, and money market instruments. The process of mixing the large asset classes to achieve maximum return with minimal risk is called portfolio building. By not placing all eggs in a single basket, a portfolio seeks to play off an investor's risk-return expectations and thus allows for adequate diversification.

The analysis is carried out to check the usefulness of Sharpe's single index model in optimal portfolio construction. From the study, it is concluded that only two stocks, namely Vedanta and Tata steel, are included in the Optimal Portfolio established in this study with a maximum suggested investment of 86 per cent in Vedanta and 14 per cent in Tata Steel, the 14 stocks included in the NSE Nifty metal index.

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(Bendigeri, 2018, pp. 329-335)

The management of portfolios is a critical part of any investor's decision-making process. Taking a call on where to invest and how much to invest is important to the investor. With the support of the Sharpe Single Index model, the present study focuses on constructing the optimal portfolio. The Sharpe Single Index model uses various inputs, such as excess beta-ratio return, unsystematic risk, market return and variance, etc.

For portfolio design, William Sharpe conceived and developed the Sharpe Single Index model. Input variables for this model are significantly less than Harry Markowitz's proposed model. Sharpe's Single Index model primarily assumes that a single factor known as the index will explain the co — security variance. The other variant uses the stock index as an independent variable, such as the S&P 500. This model is called the paradigm of the business. The performance of an asset or security is related to portfolio performance according to the market model, which in turn varies as per the security beta.

Sharpe Single index model is very convenient and crucial for the construction of an optimum portfolio. However, due to the competitive nature of the market, investors should continuously monitor and track their portfolio. It is therefore imperative that investors change their portfolio constantly in line with changing market conditions to maximize their returns.

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. CHAPTER 3

DATA ANALYSIS AND INTERPRETATION

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4.1 SHARPE’S SINGLE INDEX MODEL

This is the clarified model that proposes a relationship between each pair of securities can indirectly be measured by comparing each security to a common or normal factor market performance index that is shared among all the securities. As a result of this model reduce the risk of large input requirements and difficult to calculate in the mean-variance approach. Unlike the Markowitz model which requires 3N+2 estimates. Due to this simplicity sharps model as gained popularity in the area of investment finance.

4.2 ASSUMPTION OF SHARPE’S SINGLE INDEX MODEL

• All market participants have standards which are homogeneous or similar.

• A standardized holding period is used for determining the risk and return of each safe.

• Securities' price fluctuations about one another do not depend solely on the quality of such securities. The market changes are often influenced by industry and economics.

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• The relationship between securities emerges from their impact, along with other indices of economic and business activity.

• The return of each security is associated with certain indices which are the proxy of other securities on the market.

• The word random disturbance has an estimated value of zero and a finite variance. This doesn't contribute to the return on the market portfolio.

4.3 STEPS IN CONSTRUCTION OF OPTIMAL PORTFOLIO

W.E. Sharpe (1964) explained the definition of portfolio risk about their return co-movement with the economy, and not necessarily concerning security co-movement within the portfolio.

Therefore, he concluded that the desirability of security for its inclusion is directly related to its excess return on the beta ratio,

R(i) – R(f)/β(i)

Where R(i) = expected return on security I

R(f) = return on a riskless security ̈(i) = beta of security

This ranking order gives the best securities to be chosen for the portfolio.

Step1: calculate the excess return to the Beta ratio of each stock under consideration

Excess return to Beta ratio=(𝑅𝑖−𝑅𝑓)/𝛽𝑖 Where Ri= Expected return of security i Rf= Risk-free rate of return.

Indian Treasury bill rate for 91-day yield rate is taken as present Rf rate

βi= Expected change in the rate of return of stock I associated with the one-unit change

In market return

Step2: Rank the excess return to the Beta ratio from Highest to Lowest.

Step3: Calculate the cut off rate using the formula, according to the ranked order.

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Where,

σ2m= Variance of market value

Ri-Rf = Market risk premium

σ2ei = Unsystematic risk of the security

Step4: Selection of securities for investment if an excess return to Beta ratio is greater than the cut-off rate then the security will be included in the portfolio.

Step5: Calculate the proportion to be invested in each security is calculated.

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Where,

Xi= Proportion of Investment.

Where,

σ2ei = Unsystematic Risk

β= beta

C*=Cut off Point.

4.3a FORMULAS USED FOR CALCULATION

• The rate of return of the stocks included in the portfolio using daily closing prices of each company listed in National stock exchange computed using the formula to find estimate return of the stock.

𝑅𝑖=𝑃 1− 𝑃 0 ∗100𝑃0Where,

P1= closing price

P0= opening price

• To find the estimated return on the market. The equation is used.

𝑅𝑚=𝑃 1− 𝑃 0 *100𝑃0

Where,

P1= closing price

P0= opening price.

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• To calculate the Beta component, the equation is used

𝛽=𝑛 Σ 𝑥𝑦 −Σ 𝑥 Σ 𝑦 𝑛Σ𝑥2−(Σ𝑥)2

Where,

β= beta

x= return on a market index

y= return on stock index

n= No. of units.

• To calculate the variance of market Index is computed as under

• The variance of the stock price movements is computed as

• The systematic and unsystematic risks are computed as under

Systematic risk = β2*σ2m

Unsystematic risk= Total variance of security return –systematic risk

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4.4 LIST OF COMPANIES IN BSE INDEX

Companies are selected on the sector basis of Nifty and BSE Pharma index are obtained; Historical data has been collected from their official website for an optimal portfolio for one month. The selected companies are listed below: -

LIST OF COMPANIES ON BSE INDEX

SL NO NAME OF COMPANY SECTOR1 Sun Pharmaceutical Industries Limited Pharmaceuticals2 Aurobindo Pharma Limited Pharmaceuticals3 Lupin Limited Pharmaceuticals4 Cipla Limited Pharmaceuticals5 Dr Reddy’s Laboratories Pharmaceuticals6 HDFC Financial Service7 India Bulls Finance Limited Financial Service8 LIC Housing Finance Limited Financial Service9 Bajaj Capital Limited Financial Service10 ICICI Bank Limited Financial Service11 Vadilal Industries Limited Consumer Foods12 Britannia Limited Consumer Foods13 Parle Agro Limited Consumer Foods14 Nestle India Limited Consumer Foods15 LT Foods Consumer Foods

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MARKET RETURN

4.5 Table Showing the Calculation of BSE Market Return for March 2020

Analysis: From the above table it can be understood that the BSE Index market return for one month is -0.2659, which is calculated as under the following information.

Calculations:

Return on the market: - 𝑅𝑖=𝑃 1− 𝑃 0 ∗100𝑃0

Here: P1= closing price

P0=opening price

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BSE RETURNSDate Open Close Return2-03-2020 38,910.95 38,144.023-03-2020 38,480.89 38,623.70 0.01264-03-2020 38,715.72 38,409.48 -0.00555-03-2020 38,604.25 38,470.61 0.00166-03-2020 37,613.96 37,576.62 -0.02329-03-2020 36,950.20 35,634.95 -0.051711-03-2020 35,468.90 35,697.40 0.001812-03-2020 34,472.50 32,778.14 -0.081813-03-2020 31,214.13 34,103.48 0.040416-03-2020 33,103.24 31,390.07 -0.079617-03-2020 31,611.57 30,579.09 -0.025818-03-2020 30,968.84 28,869.51 -0.055919-03-2020 27,773.36 28,288.23 -0.020120-03-2020 28,460.82 29,915.96 0.057523-03-2020 27,608.80 25,981.24 -0.131524-03-2020 27,056.23 26,674.03 0.026725-03-2020 26,499.81 28,535.78 0.069826-03-2020 29,073.71 29,946.77 0.049427-03-2020 30,747.81 29,815.59 -0.004430-03-2020 29,226.55 28,440.32 -0.0461RM -0.2659


4.5a Graph showing the return on market BSE

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18-M

ar-20

19-M

ar-20

20-Mar-2

0

21-Mar-2

0

22-Mar-2

0

23-M

ar-20

24-Mar-2

0

25-M

ar-20

26-Mar-2

0

27-Mar-2

0

28-Mar-2

0

29-M

ar-20

30-M

ar-20

-0.15

-0.1

-0.05

0

0.05

0.1

Stock Return

Stock Return

Interpretation: From the above graph it’s clear that the BSE Market return for the month starting is showing less return, with the certain price fluctuations there was a rise in 24 th

March and again on 26th March market showed less return due to more selling happened in the market and on 25th March again return gradually decreased and at the end of the month.

SURANA COLLEGE 26


1.SUN PHARMA LIMITED

4.6 Table Showing Calculation for March 2020

Date Market Return Stock Return x*y x2

2/3/20203/3/2020 0.01 0.06642267 0.000664227 0.00014/3/2020 -0.01 0.03139698 -0.00031397 0.00015/3/2020 0 -0.0020951 0 06/3/2020 -0.02 -0.0097567 0.000195134 0.00049/3/2020 -0.05 -0.0148416 0.00074208 0.002511/3/2020 0 -0.0219015 0 012/3/2020 -0.08 -0.0814134 0.006513073 0.006413/03/2020 0.04 0.08341553 0.003336621 0.001616/03/2020 -0.08 -0.0407075 0.0032566 0.006417/03/2020 -0.03 0.00474512 -0.000142354 0.000918/03/2020 -0.06 -0.0217245 0.001303468 0.003619/03/2020 -0.02 -0.0063448 0.000126897 0.000420/03/2020 0.06 0.01554692 0.000932815 0.003623/03/2020 -0.13 -0.1142701 0.014855112 0.016924/03/2020 0.03 0.03410494 0.001023148 0.000925/03/2020 0.07 0.03581555 0.002507089 0.004926/03/2020 0.05 -0.0244921 -0.001224607 0.002527/03/2020 0 -0.0011815 0 030/03/2020 -0.05 -0.0133077 0.000665385 0.0025Total -0.27 -0.0805889 0.034440718 0.0537

Analysis: From the above table it is clear that Ashok Leyland return is -0.0805 and market return is-027. Beta is 0.6677, systematic risk is 0.00185 and unsystematic risk is -0.08, the market variance is 0.0028, the stock variance is 0.0021, which are calculated as under

Calculations:

Return on stock: - Ri=P1−P0P0

∗¿100

Here: P1= closing price, P0=opening price

Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

SURANA COLLEGE 27


= 0.6677

Systematic risk= βi2 * variance of the market

= 0.00185

Unsystematic Risk = Total Variance of Security Return – Systematic Risk

= -0.08

Variance

So, σ 2m= variance of the market index σ 2ei= variance of the stock price.

4.6a Graph showing the return on the market and stock return

2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

020

16/03/2

020

17/03/2

020

18/03/2

020

19/03/2

020

20/03/2

020

23/03/2

020

24/03/2

020

25/03/2

020

26/03/2

020

27/03/2

020

30/03/2

020

-0.15

-0.1

-0.05

0

0.05

0.1

Market Return Stock Return

Interpretation: From the above graph it is clear that the monthly returns of Sun Pharma

compared with BSE stock return. we can absorb that both the returns i.e. market return &

stock return showing more returns and with the certain price fluctuations in the return both

the returns end up within Increasing trend. This graph shows the stock return is more volatile

when we compare to the market return.

SURANA COLLEGE 28


2.AUROBINDO PHARMA LIMITED

4.7 Table showing calculation for March 2020


2/3/20203/3/2020 0.01 0.0334 0.000334445 0.00014/3/2020 -0.01 0.0183 -0.000182831 0.00015/3/2020 0 0.0114 0 06/3/2020 -0.02 -0.0319 0.000637934 0.00049/3/202020 -0.05 -0.0776 0.003878211 0.002511/3/202020 0 -0.0436 0 012/3/202020 -0.08 -0.1675 0.013400022 0.006413/03/2020 0.04 0.1109 0.004437917 0.001616/03/2020 -0.08 -0.0269 0.002153587 0.006417/03/2020 -0.03 0.0204 -0.000611338 0.000918/03/2020 -0.06 -0.1195 0.007167756 0.003619/03/2020 -0.02 -0.0493 0.000986942 0.000420/03/2020 0.06 0.0035 0.000208213 0.003623/03/2020 -0.13 -0.1517 0.019724784 0.016924/03/2020 0.03 0.1074 0.003220656 0.000925/03/2020 0.07 0.0232 0.001621414 0.004926/03/2020 0.05 0.0837 0.004182909 0.002527/03/2020 0 0.0855 0 030/03/2020 -0.05 -0.0076 0.00038236 0.0025Total -0.27 -0.1780 0.061542982 0.0537

Analysis: From the above table it is clear that Aurobindo pharma return is -0.1780 and market return is -027. Beta is 0.5064, systematic risk is 0.0014 and unsystematic risk is -0.1794, the market variance is 0.0028, the stock variance is 0.0064, which are calculated as

under return on stock: - Ri=P1−P0P0

∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.5064

SURANA COLLEGE 29



= 0.0014


= -0.1794

Variance


4.7a Graph showing return on the market and stock return

2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/0

3/20

27/03/2

0

30/03/2

0

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15


Interpretation: From the above graph it is clear that the monthly returns of Aurobindo Pharma compared with BSE stock return. we can absorb that both the returns i.e. market return & stock return showing consistent returns and with the certain price fluctuations in the return both the returns end up within Increasing trend. This graph shows the stock return is more volatile when we compare to the market return.

SURANA COLLEGE 30


3.LUPIN LIMITED



2/3/20203/3/2020 0.01 0.032099158 0.000320992 0.00014/3/2020 -0.01 0.022247883 -0.000222479 0.00015/3/2020 0 0.018751412 0 06/3/2020 -0.02 -0.020402129 0.000408043 0.00049/3/2020 -0.05 -0.017280411 0.000864021 0.002511/3/2020 0 -0.019503955 0 012/3/2020 -0.08 -0.071109719 0.005688778 0.006413/03/2020 0.04 0.020655931 0.000826237 0.001616/03/2020 -0.08 -0.010986288 0.000878903 0.006417/03/2020 -0.03 0.030067652 -0.00090203 0.000918/03/2020 -0.06 -0.005351496 0.00032109 0.003619/03/2020 -0.02 0.033749083 -0.000674982 0.000420/03/2020 0.06 0.011907578 0.000714455 0.003623/03/2020 -0.13 -0.078553616 0.01021197 0.016924/03/2020 0.03 0.000930311 2.79093E-05 0.000925/03/2020 0.07 -0.044359949 -0.003105196 0.004926/03/2020 0.05 -0.012997347 -0.000649867 0.002527/03/2020 0 -0.019976709 0 030/03/2020 -0.05 0.023948812 -0.001197441 0.0025Total -0.27 -0.106163798 0.013510402 0.0729

Analysis: From the above table it is clear that Lupin Limited return is -0.0135 and market return is -027. Beta is 0.6161, systematic risk is 0.0017 and unsystematic risk is -0.108, the market variance is 0.0028, the stock variance is 0.00108, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

= 0.6161

SURANA COLLEGE 31



= 0.0017


= -0.108

Variance


4.8a Graph Showing market and stock return

2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3

/2020

13/03/2

0

16/0

3/20

17/0

3/20

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/0

3/20

25/03/2

0

26/0

3/20

27/03/2

0

30/0

3/20

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of Lupin Limited compared with BSE stock return. we can absorb that both the returns i.e. market return is showing more returns and with the certain price fluctuations in the return, market returns end up with an Increasing trend. This graph shows market return is more volatile when we compare to stock return.

SURANA COLLEGE 32


4.CIPLA LIMITED

4.9 Table showing the calculation of return for March 2020


2/3/20203/3/2020 0.01 0.054495913 0.000544959 0.00014/3/2020 -0.01 0.051679587 -0.000516796 0.00015/3/2020 0 -0.01619388 0 06/3/2020 -0.02 -0.014757634 0.000295153 0.00049/3/2020 -0.05 -0.019357069 0.000967853 0.002511/3/2020 0 -0.018799201 0 012/3/2020 -0.08 -0.054364747 0.00434918 0.006413/03/2020 0.04 0.076864632 0.003074585 0.001616/03/2020 -0.08 -0.067732832 0.005418627 0.006417/03/2020 -0.03 0.013496468 -0.000404894 0.000918/03/2020 -0.06 -0.037461108 0.002247666 0.003619/03/2020 -0.02 -0.031290406 0.000625808 0.000420/03/2020 0.06 0.050720769 0.003043246 0.003623/03/2020 -0.13 -0.040650407 0.005284553 0.016924/03/2020 0.03 0.000132415 3.97246E-06 0.000925/03/2020 0.07 -0.002515557 -0.000176089 0.004926/03/2020 0.05 0.026413592 0.00132068 0.002527/03/2020 0 0.056381741 0 030/03/2020 -0.05 0.057901824 -0.002895091 0.0025Total -0.27 0.084964101 0.023183412 0.0729

Analysis: From the above table it is clear that Cipla Limited return is 0.0849 and market return is -027. Beta is 0.7185, systematic risk is 0.0019 and unsystematic risk is 0.083, the market variance is 0.0027, the stock variance is 0.0018., which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

= 0.7185


SURANA COLLEGE 33


= 0.0019


= 0.083

Variance


4.9.a Graph showing returns of market and stock

2/3/2020

3/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of Cipla Limited compared with BSE stock return. we can absorb that both the returns i.e. market return is showing more returns and with the certain price upwards in the return though market returns made a downfall on 23rd march, stock returns end up within Increasing trend. This graph shows the stock return is more volatile when we compare to the market return.

SURANA COLLEGE 34


5.DR REDDY’S LABORATORY



2/3/20203/3/2020 0.01 0.051558318 0.000516 0.00014/3/2020 -0.01 0.042002594 -0.000420 0.00015/3/2020 0 0.00245828 0.000000 06/3/2020 -0.02 -0.003458304 0.000069 0.00049/3/2020 -0.05 -0.03358309 0.001679 0.002511/3/2020 0 -0.020794568 0.000000 012/3/2020 -0.08 -0.048273103 0.003862 0.006413/03/2020 0.04 0.012295082 0.000492 0.001616/03/202 -0.08 -0.021973079 0.001758 0.006417/03/2020 -0.03 -0.012471695 0.000374 0.000918/03/2020 -0.06 -0.044211167 0.002653 0.003619/03/2020 -0.02 -0.016868147 0.000337 0.000420/03/2020 0.06 0.104985225 0.006299 0.003623/03/2020 -0.13 -0.045685104 0.005939 0.016924/03/2020 0.03 0.033608128 0.001008 0.000925/03/2020 0.07 0.023035349 0.001612 0.004926/03/2020 0.05 0.006377158 0.000319 0.002527/03/2020 0 -0.008885038 0.000000 030/03/2020 -0.05 0.026448406 -0.001322 0.0025Total -0.27 0.046565245 0.025175 0.0729

Analysis: From the above table it is clear that DR Reddy’s Laboratories return is 0.04656 and market return is -027. Beta is 0.9628, systematic risk is 0.00267 and unsystematic risk is 0.044, the market variance is 0.0027, the stock variance is 0.00149, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.9628

SURANA COLLEGE 35



= 0.0026


= 0.044

Variance



2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

Interpretation: From the above graph it is clear that the monthly returns of DR Reddy’s Laboratories compared with BSE stock return. we can absorb that both the returns i.e. market return is showing more returns and with the certain price upwards in the return though market returns made a downfall on 23rd march, market returns end up within Increasing trend. This graph shows market return is more volatile when we compare to stock return.

SURANA COLLEGE 36


6.HDFC



2/3/20203/3/2020 0.01 0.005 0.00005 0.00014/3/2020 -0.01 0.005 (0.00005) 0.00015/3/2020 0 -0.004 - 06/3/2020 -0.02 -0.039 0.00078 0.00049/3/2020 -0.05 -0.038 0.00191 0.002511/3/2020 0 0.004 - 012/3/2020 -0.08 -0.079 0.00633 0.006413/03/2020 0.04 0.103 0.00413 0.001616/03/2020 -0.08 -0.109 0.00875 0.006417/03/2020 -0.03 -0.047 0.00142 0.000918/03/2020 -0.06 -0.075 0.00448 0.003619/03/2020 -0.02 -0.002 0.00003 0.000420/03/2020 0.06 0.082 0.00491 0.003623/03/2020 -0.13 -0.129 0.01673 0.016924/03/2020 0.03 -0.017 (0.00052) 0.000925/03/2020 0.07 0.094 0.00661 0.004926/03/2020 0.05 0.065 0.00324 0.002527/03/2020 0 0.002 - 030/03/2020 -0.05 -0.109 0.00546 0.0025Total -0.27 -0.289 0.06426 0.0729

Analysis: From the above table it is clear that HDFC return is -0.2089 and market return is -027. Beta is 0.7163, systematic risk is 0.00198 and unsystematic risk is -0.291, the market variance is 0.0028, the stock variance is 0.0046, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

SURANA COLLEGE 37


= 0.7163


= 0.0019


= -0.291

Variance



2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

Interpretation: From the above graph it is clear that the monthly returns of HDFC Bank compared with BSE stock return. we can absorb that both the returns i.e. market return is showing more returns and the stock returns end up within Increasing trend. This graph shows the stock return is more volatile when we compare to the market return.

7.INDIA BULLS FINANCE LIMITED

SURANA COLLEGE 38


4.12 Table showing the calculation of returns for March 2020


2/3/20203/3/2020 0.01 0.0281 0.00028 0.00014/3/2020 -0.01 -0.0320 0.00032 0.00015/3/2020 0 0.0087 0.00000 06/3/2020 -0.02 -0.1088 0.00218 0.00049/3/2020 -0.05 -0.1606 0.00803 0.002511/3/2020 0 -0.0848 0.00000 012/3/2020 -0.08 -0.1665 0.01332 0.006413/03/2020 0.04 0.0034 0.00014 0.001616/03/2020 -0.08 -0.0606 0.00485 0.006417/03/2020 -0.03 0.0427 -0.00128 0.000918/03/2020 -0.06 -0.1458 0.00875 0.003619/03/2020 -0.02 -0.3400 0.00680 0.000420/03/2020 0.06 0.0094 0.00057 0.003623/03/2020 -0.13 0.0543 -0.00706 0.016924/03/2020 0.03 -0.0619 -0.00186 0.000925/03/2020 0.07 0.0566 0.00396 0.004926/03/2020 0.05 0.0053 0.00026 0.002527/03/2020 0 -0.0507 0.00000 030/03/2020 -0.05 0.0050 -0.00025 0.0025Total -0.27 -0.9983 0.03900 0.0729

Analysis: From the above table it is clear that India Bulls Finance Limited return is -0.9983 and market return is -027. Beta is 0.1401, systematic risk is 0.00038 and unsystematic risk is -0.999, the market variance is 0.0028, the stock variance is 0.0098, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.1401


SURANA COLLEGE 39


= 0.00038


= -0.999

Variance



2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/03/2

0

27/03/2

0

30/03/2

0

-0.4

-0.35

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of India Bulls Finance Limited compared with BSE stock return. we can absorb that both the returns i.e. market and stock return is showing fewer returns and with the certain price downwards in the return though market returns made a downfall consistently, market returns end up with a slightly Increasing trend. This graph shows market return and stock return is more volatile.

SURANA COLLEGE 40


8.LIC HOUSING FINANCE LIMITED

4.13 Table showing return calculation for March 2020


2/3/20203/3/2020 0.01 0.028011204 0.000280112 0.00014/3/2020 -0.01 -0.02876173 0.000287617 0.00015/3/2020 0 -0.00124688 0 06/3/2020 -0.02 -0.05649189 0.001129838 0.00049/3/2020 -0.05 -0.0593781 0.002968905 0.002511/3/2020 0 0.013539652 0 012/3/2020 -0.08 -0.11311589 0.009049271 0.006413/03/2020 0.04 0.09643975 0.00385759 0.001616/03/2020 -0.08 -0.08813559 0.007050847 0.006417/03/2020 -0.03 -0.01878302 0.000563491 0.000918/03/2020 -0.06 -0.09511466 0.005706879 0.003619/03/2020 -0.02 -0.01410313 0.000282063 0.000420/03/2020 0.06 0 0 0.003623/03/2020 -0.13 -0.14349575 0.018654448 0.016924/03/2020 0.03 0.004697286 0.000140919 0.000925/03/2020 0.07 0.091428571 0.0064 0.004926/03/2020 0.05 0.088053308 0.004402665 0.002527/03/2020 0 0.039151356 0 030/03/2020 -0.05 -0.03788676 0.001894338 0.0025

Analysis: From the above table it is clear that Life Insurance Housing Finance limited return is -0.0378 and market return is -027. Beta is 0.7037, systematic risk is 0.00195 and unsystematic risk is -0.297, the market variance is 0.0028, the stock variance is 0.004616, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.7037

SURANA COLLEGE 41



= 0.00195


= -0.297

Variance



2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15


Interpretation: From the above graph it is clear that the monthly returns of LIC Housing Finance Limited compared with BSE stock return. we can absorb that both the returns i.e. market return is showing promising returns and the stock returns end up with an Increasing trend. This graph shows the stock return is more volatile when we compare to the market return.

SURANA COLLEGE 42


9.BAJAJ CAPITAL LIMITED


Date Market Returns Stock Returns x*y x2

2/3/20203/3/2020 0.01 0.02125709 0.000212571 0.00014/3/2020 -0.01 -0.037915171 0.000379152 0.00015/3/2020 0 0.011324804 0 06/3/2020 -0.02 -0.025140696 0.000502814 0.00049/3/2020 -0.05 -0.048786258 0.002439313 0.002511/3/2020 0 0.002462442 0 012/3/2020 -0.08 -0.073443664 0.005875493 0.006413/03/2020 0.04 0.059194494 0.00236778 0.001616/03/2020 -0.08 -0.070866042 0.005669283 0.006417/03/2020 -0.03 -0.062638604 0.001879158 0.000918/03/2020 -0.06 -0.111093371 0.006665602 0.003619/03/2020 -0.02 -0.102379047 0.002047581 0.000420/03/2020 0.06 0.077874593 0.004672476 0.003623/03/2020 -0.13 -0.235680292 0.030638438 0.016924/03/2020 0.03 0.097750006 0.0029325 0.000925/03/2020 0.07 0.040268726 0.002818811 0.004926/03/2020 0.05 0.080610232 0.004030512 0.002527/03/2020 0 -0.088714728 0 030/03/2020 -0.05 -0.119460425 0.005973021 0.0025Total -0.27 -0.585375911 0.079104504 0.0537

Analysis: From the above table it is clear that Bajaj Capital Limited return is -0.5853 and market return is -027. Beta is 0.5483, systematic risk is 0.0015 and unsystematic risk is -0.587, the market variance is 0.0028, the stock variance is 0.007172, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

= 0.5483

SURANA COLLEGE 43



= 0.0015


= -0.587

Variance



2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.3

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

Market Return Stock Returns

Interpretation: From the above graph it is clear that the monthly returns of Bajaj Capital Limited compared with BSE stock return. we can absorb that both the returns i.e. market and stock return are consistently in nominal position and the stock returns end up within slightly an increasing trend. This graph shows the stock return is more volatile when we compare to the market return.

10.ICICI BANK LIMITED


SURANA COLLEGE 44



2/3/20203/3/2020 0.01 0.021459652 0.000214597 0.00014/3/2020 -0.01 -0.015393552 0.000153936 0.00015/3/2020 0 -0.007374631 0 06/3/2020 -0.02 -0.036651808 0.000733036 0.00049/3/2020 -0.05 -0.059845758 0.002992288 0.002511/3/2020 0 0.018046593 0 012/3/2020 -0.08 -0.086807048 0.006944564 0.006413/03/2020 0.04 0.052823529 0.002112941 0.001616/03/2020 -0.08 -0.099564197 0.007965136 0.006417/03/2020 -0.03 -0.089476297 0.002684289 0.000918/03/2020 -0.06 -0.029576121 0.001774567 0.003619/03/2020 -0.02 -0.047331461 0.000946629 0.000420/03/2020 0.06 0.019312988 0.001158779 0.003623/03/2020 -0.13 -0.178767718 0.023239803 0.016924/03/2020 0.03 0.044734061 0.001342022 0.000925/03/2020 0.07 0.069285233 0.004849966 0.004926/03/2020 0.05 0.04682327 0.002341163 0.002527/03/2020 0 0.02439759 0 030/03/2020 -0.05 -0.076742135 0.003837107 0.0025Total -0.27 -0.430647809 0.063290823 0.0537

Analysis: From the above table it is clear that ICIC Bank Limited return is -0.43064 and market return is -0.27. Beta is 0.7581, systematic risk is 0.0021 and unsystematic risk is -0.433, market variance is0.0028, the stock variance is 0.00418, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.7581

SURANA COLLEGE 45



= 0.0021


= -0.433

Variance



2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of ICIC Bank Limited compared with BSE stock return. we can absorb that both the returns i.e. market and stock return are consistently in nominal position and the stock returns end up within slightly an increasing trend, on 23rd of march there is a downtrend due to less activity in the market. This graph shows the stock return is more volatile when we compare to the market return.

11.VADILAL INDUSTRIES LIMITED


SURANA COLLEGE 46



2/3/20203/3/2020 0.01 0.000 0.0000 0.00014/3/2020 -0.01 0.005 -0.0005 0.00015/3/2020 0 -0.008 0.0000 06/3/2020 -0.02 -0.066 0.0013 0.00049/3/2020 -0.05 -0.076 0.0038 0.002511/3/2020 0 -0.010 0.0000 012/3/2020 -0.08 -0.179 0.0143 0.006413/03/2020 0.04 0.078 0.0031 0.001616/03/2020 -0.08 -0.033 0.0027 0.006417/03/2020 -0.03 -0.026 0.0008 0.000918/03/2020 -0.06 -0.104 0.0063 0.003619/03/2020 -0.02 0.004 -0.0001 0.000420/03/2020 0.06 0.057 0.0034 0.003623/03/2020 -0.13 -0.189 0.0246 0.016924/03/2020 0.03 0.046 0.0014 0.000925/03/2020 0.07 -0.090 -0.0063 0.004926/03/2020 0.05 0.075 0.0038 0.002527/03/2020 0 0.029 0.0000 030/03/20 -0.05 -0.056 0.0028 0.0025

Analysis: From the above table it is clear that Vadilal Limited return is -0.056 and market return is -0.27. Beta is 0.5169, systematic risk is 0.001432 and unsystematic risk is -0.546, the market variance is 0.0028, the stock variance is 0.005804, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

= 0.5169


= 0.001432


= -0.546

SURANA COLLEGE 47


Variance


4.16 Graph showing returns of market and stock

2/3/2020

3/3/2020

4/3/2020

5/3/2020

6/3/2020

9/3/2020

11/3/2020

12/3/2020

13/03/20

16/03/20

17/03/20

18/03/20

19/03/20

20/03/20

23/03/20

24/03/20

25/03/20

26/03/20

27/03/20

30/03/20

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

Stock Return Market Return

Interpretation: From the above graph it is clear that the monthly returns of Vadilal Limited compared with BSE stock return. we can absorb that both the returns i.e. market and stock return are consistently in nominal position and the stock returns end up within slightly an increasing trend. This graph shows market return is more volatile when we compare to stock return.

12.BRITANIA LIMITED



SURANA COLLEGE 48


2/3/20203/3/2020 0.01 -0.00226 (0.00002) 0.00014/3/2020 -0.01 -0.01179 0.00012 0.00015/3/2020 0 0.00923 - 06/3/2020 -0.02 -0.01761 0.00035 0.00049/3/2020 -0.05 -0.02064 0.00103 0.002511/3/2020 0 -0.02568 - 012/3/2020 -0.08 0.02429 (0.00194) 0.006413/03/2020 0.04 -0.00244 (0.00010) 0.001616/03/2020 -0.08 0.03820 (0.00306) 0.006417/03/2020 -0.03 0.02336 (0.00070) 0.000918/03/2020 -0.06 -0.00305 0.00018 0.003619/03/2020 -0.02 0.01219 (0.00024) 0.000420/03/2020 0.06 0.01533 0.00092 0.003623/03/2020 -0.13 -0.05528 0.00719 0.016924/03/2020 0.03 -0.03754 (0.00113) 0.000925/03/2020 0.07 0.00134 0.00009 0.004926/03/2020 0.05 -0.03093 (0.00155) 0.002527/03/2020 0 -0.01049 - 030/03/2020 -0.05 0.00012 (0.00001) 0.0025Total -0.27 -0.093632725 0.00114 0.0537

Analysis: From the above table it is clear that Britania Limited return is -0.0936 and market return is -0.27. Beta is 0.0194, systematic risk is -0.00005 and unsystematic risk is -0.094, the market variance is 0.0028, the stock variance is 0.000538, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.0194


= -0.00005


= -0.094

SURANA COLLEGE 49


Variance



2/3/2

020

3/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/03/2

0

27/03/2

0

30/03/2

0

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of Britania Limited compared with BSE stock return. we can absorb that both the returns i.e. market return is stable and stock return is consistently in a fixed position and the market returns end up within slightly an increasing trend. This graph shows market return is more volatile when we compare to stock return.

13.PARLE AGRO LIMITED


SURANA COLLEGE 50



2/3/20203/3/2020 0.01 0.008972268 0.000090 0.00014/3/2020 -0.01 -0.011317704 0.000113 0.00015/3/2020 0 -0.013900245 0.000000 06/3/2020 -0.02 -0.015754561 0.000315 0.00049/3/2020 -0.05 0.046335299 -0.002317 0.002511/3/2020 0 -0.026570048 0.000000 012/3/2020 -0.08 -0.046319272 0.003706 0.006413/03/2020 0.04 -0.053772767 -0.002151 0.001616/03/2020 -0.08 0.016498625 -0.001320 0.006417/03/2020 -0.03 0.028854824 -0.000866 0.000918/03/2020 -0.06 -0.020157756 0.001209 0.003619/03/2020 -0.02 0.029516995 -0.000590 0.000420/03/2020 0.06 0.033883579 0.002033 0.003623/03/2020 -0.13 0.05210084 -0.006773 0.016924/03/2020 0.03 0.004792332 0.000144 0.000925/03/2020 0.07 0.008744038 0.000612 0.004926/03/2020 0.05 0.09929078 0.004965 0.002527/03/2020 0 0.099641577 0.000000 030/03/20 -0.05 0.049543677 -0.002477 0.0025

Analysis: From the above table it is clear that Parle Agro Limited return is 0.04954 and market return is -0.27. Beta is 0.0251, systematic risk is 0.0001 and unsystematic risk is 0.290, the market variance is 0.0028, the stock variance is 0.001816, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.0251


= -0.0001


= 0.290

SURANA COLLEGE 51


Variance



2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/03/2

0

27/03/2

0

30/03/2

0

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

Interpretation: From the above graph it is clear that the monthly returns of Parle Agro Limited compared with BSE stock return. we can absorb i.e. market return is stable and stock return is and the stock returns are fluctuating from up to down end up within slightly an increasing trend at the end of the month. This graph shows the stock return is more volatile when we compare to the market return.

14.NESTLE INDIA LIMITED


SURANA COLLEGE 52



2/3/20203/3/2020 0.01 0.014547372 0.000145474 0.00014/3/2020 -0.01 0.011238669 -0.000112387 0.00015/3/2020 0 0.001823069 0 06/3/2020 -0.02 -0.008528386 0.000170568 0.00049/3/2020 -0.05 -0.02267622 0.001133811 0.002511/3/2020 0 0.000109004 0 012/3/2020 -0.08 -0.027201415 0.002176113 0.006413/03/2020 0.04 -0.041205168 -0.001648207 0.001616/03/2020 -0.08 -0.041580416 0.003326433 0.006417/03/2020 -0.03 0.013126084 -0.000393783 0.000918/03/2020 -0.06 -0.070701097 0.004242066 0.003619/03/2020 -0.02 -0.029951752 0.000599035 0.000420/03/2020 0.06 0.079352183 0.004761131 0.003623/03/2020 -0.13 -0.085798492 0.011153804 0.016924/03/2020 0.03 0.047970993 0.00143913 0.000925/03/2020 0.07 0.064645824 0.004525208 0.004926/03/2020 0.05 0.041852311 0.002092616 0.002527/03/2020 0 0.003674588 0 030/03/2020 -0.05 0.039288448 -0.001964422 0.0025Total -0.27 -0.010014401 0.03164659 0.0537

Analysis: From the above table it is clear that Nestle India Limited return is -0.0100 and market return is -0.27. Beta is 0.9104, systematic risk is 0.002521 and unsystematic risk is -0.013, the market variance is 0.0028, the stock variance is 0.00192, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑ x∑ yn∑ x 2−(∑x )2

= 0.9104


= 0.00252


SURANA COLLEGE 53


= -0.013

Variance



2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/03/2

0

27/03/2

0

30/03/2

0

-0.15

-0.1

-0.05

0

0.05

0.1


Interpretation: From the above graph it is clear that the monthly returns of Nestle India Limited compared with BSE stock return. we can absorb i.e. market return is stable and stock return is also showing stable returns as they are both showing maximum returns from 19 th

March to 27Th March. This graph shows the stock return is more volatile when we compare to the market return.

15.LT FOODS



SURANA COLLEGE 54


2/3/20203/3/2020 0.01 0.020325203 0.000203252 0.00014/3/2020 -0.01 -0.077689243 0.000776892 0.00015/3/2020 0 0.01511879 0 06/3/2020 -0.02 -0.034042553 0.000680851 0.00049/3/2020 -0.05 -0.092511013 0.004625551 0.002511/3/2020 0 -0.026699029 0 012/3/2020 -0.08 -0.189526185 0.015162095 0.006413/03/2020 0.04 0.030769231 0.001230769 0.001616/03/2020 -0.08 0.014925373 -0.00119403 0.006417/03/2020 -0.03 0.055882353 -0.001676471 0.000918/03/2020 -0.06 -0.04735376 0.002841226 0.003619/03/2020 -0.02 -0.046783626 0.000935673 0.000420/03/2020 0.06 0.009202454 0.000552147 0.003623/03/2020 -0.13 -0.106382979 0.013829787 0.016924/03/2020 0.03 0.044217687 0.001326531 0.000925/03/2020 0.07 0.016286645 0.001140065 0.004926/03/2020 0.05 0.073717949 0.003685897 0.002527/03/2020 0 0 0 030/03/2020 -0.05 0.08358209 -0.004179104 0.0025Total -0.27 -0.256960613 0.039941131 0.0537

Analysis: From the above table it is clear that Nestle Larsen and Turbo Limited return is -0.2569 and market return is -0.27. Beta is 0.4303, systematic risk is 0.00119 and unsystematic risk is -0.258, the market variance is 0.0028, the stock variance is 0.004684, which are calculated as under


∗¿100


Beta calculation:

β=n∑ xy−∑x∑ yn∑ x 2−(∑x )2

= 0.4303


= 0.00119


= -0.258

SURANA COLLEGE 55


Variance



2/3/2

020

3/3/2

020

4/3/2

020

5/3/2

020

6/3/2

020

9/3/2

020

11/3/2

020

12/3/2

020

13/03/2

0

16/03/2

0

17/03/2

0

18/03/2

0

19/03/2

0

20/03/2

0

23/03/2

0

24/03/2

0

25/03/2

0

26/03/2

0

27/03/2

0

30/03/2

0

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

Market Return Stock Retun

Interpretation: From the above graph it is clear that the monthly returns of L & T Limited compared with BSE stock return. we can absorb that the stock return is showing consistent returns than the market at some days. Ultimately the graph shows market return is more volatile than a stock return.

4.21 Table showing Beta value stocks listed in BSE Index

SL. No Name of the company Beta1 Sun Pharmaceutical Industries limited 0.66772 Aurobindo Pharma Limited 0.50643 Lupin Limited 0.6161

SURANA COLLEGE 56


4 Cipla Limited 0.71855 Dr Reddy’s Laboratories 0.96286 HDFC 0.71637 India Bulls Finance Limited 0.14018 LIC Housing Finance Limited 0.70379 Bajaj Capital Limited 0.548310 ICICI Bank Limited 0.758111 Vadilal Industries Limited 0.516912 Britania Limited -0.019413 Parle Agro Limited 0.025114 Nestle India Limited 0.910415 LT Foods 0.4303

This table shows the beta values of stock returns. Beta is a measure of the risk arising from the exposure to general market movements as opposed to idiosyncratic factors. A beta below 1 indicates a volatile investment whose price movements are not highly correlated with the market and beta greater than 1 means that the asset is volatile and tends to move up and down with the market. Dr Reddy’s Laboratory has the highest Beta value of 0.9628 that means it is highly volatile amongst the others, ICICI Bank Limited stands next with 0.7581, Cipla limited with 0.7185, HDFC with 0.7163 which are higher closer to the beta value of 1.

Parle Agro Limited 0.0251, Britania Limited with -0.0194, India Bulls Finance limited 0.1401 stands at lowest beta value.

SURANA COLLEGE 57


4.22 Table showing Ranking of the stocks based on Excess Return to Beta Ratio

Sl. No

Company Beta Ri Rf Ri –Rf βi

Rank

1 Sun Pharmaceutical Industries limited

0.6677 -0.0805 3.23-4.95806 6

2 Aurobindo Pharma Limited 0.5064 -0.1780 3.23 -6.72986 93 Lupin Limited 0.6161 -0.1061 3.23 -5.41487 84 Cipla Limited 0.7185 0.0849 3.23 -4.37731 35 Dr. Reddy’s Laboratories 0.9628 0.04656 3.23 -3.30644 16 HDFC 0.7163 -0.289 3.23 -4.91275 57 India Bulls Finance Limited 0.1401 -0.9983 3.23 -30.18059 138 LIC Housing Finance Limited 0.7037 -0.2951 3.23 -5.00938 79 Bajaj Capital Limited 0.5483 -0.5853 3.23 -6.95842 1010 ICICI Bank Limited 0.7581 -0.4306 3.23 -4.82865 411 Vadilal Industries Limited 0.5169 -0.5441 3.23 -7.30141 1112 Britania Limited 0.0194 -0.0936 3.23 -171.31959 1513 Parle Agro Limited 0.0251 0.2903 3.23 -117.11952 1414 Nestle India Limited 0.9104 -0.0100 3.23 -3.55888 215 LT Foods 0.4303 -0.2569 3.23 -8.10342 12

The above table shows the ranking of the stocks based on an excess return to beta ratio. Excess

return is investment returns from the security that exceeds the riskless rate on security

perceived to be risk-free. The risk-free rate is India treasury bill rate for 91-day yield which is

quoted 3.23% on March 2020. excess return to beta ratio measures the additional return on a

security per unit of systematic risk, this ratio provides the relationship between potential risk

and reward from the company’s stock. The raking of stocks based on an excess return to beta

ratio shows that DR. Reddy’s Laboratories stands at the top, Nestle India Limited at the

second and Cipla Limited ranks at the last.

SURANA COLLEGE 58


4.23 Table Showing Companies Stocks on their Ranks and Unsystematic risk

Rank Companies Ratio σ 2ei1 DR. Reddy’s Laboratories -3.30 (0.08)2 Nestle India Limited -3.55 (0.1794)3 Cipla Limited -4.37 (0.108)4 ICICI Bank Limited -4.82 0.0835 HDFC -4.91 0.0446 Sun Pharmaceutical Limited -4.95 (0.291)7 LIC Housing Finance Limited -5.00 (0.999)8 Lupin Limited -5.41 (0.297)9 Aurobindo Pharma Limited -6.72 (0.587)10 Bajaj Capital Limited -6.95 (0.433)11 Vadilal Industries Limited -7.30 (0.546)12 LT Foods -8.10 (0.094)13 India Bulls Finance Limited -30.18 0.29014 Parle Agro Limited -117.11 (0.013)15 Britania Limited -171.31 (0.258)

The above shows Companies Stocks on their Ranks and Unsystematic risk. In this table

company’s stocks are in the ranked order based on an excess return to beta ratio and along

with the systematic risk of individual securities, their unsystematic risk as measured by using

mentioned below formula,

Unsystematic risk also known as residual risk is the type of uncertainty that comes with the

company to invest in and it can be reduced through diversification. LIC Housing Finance

Limited has the highest unsystematic risk of 0.0094 and DR. Reddy’s Laboratories with the

lowest risk of 0.08 as less in unsystematic risk.

Unsystematic risk is calculated using the formula below: -

Unsystematic risk = Total variance of security return – Systematic risk.

SURANA COLLEGE 59


4.24 Table Showing Ci of Companies Stocks

Sl. No Companies Ci

1 DR. Reddy’s Laboratories 0.067002 0.99 0.07

2 Nestle India Limited 0.091025 0.98 0.09

3 Cipla Limited 0.13864 0.97 0.14

4 ICICI Bank Limited 0.070567 0.99 0.07

5 HDFC -0.10379 1.04 (0.10)

6 Sun Pharmaceutical Limited -0.08216 1.04 (0.08)

7 LIC Housing Finance Limited -0.08068 1.04 (0.08)

8 Lupin Limited -0.05982 1.03 (0.06)

9 Aurobindo Pharma Limited -0.05092 1.03 (0.05)

10 Bajaj Capital Limited -0.03491 1.04 (0.03)

11 Vadilal Industries Limited -0.02597 1.03 (0.03)

12 LT Foods -0.02769 1.03 (0.03)

13 India Bulls Finance Limited -0.02833 1.03 (0.03)

14 Parle Agro Limited 0.560966 0.87 (0.65)

15 Britania Limited 0.575483 0.87 (0.66)

The above table shows the Ci of the company’s stocks. The highest Ci value is the cut-off point i.e. c*, the stocks ranked above C* have highest excess return to Beta ratio than the cut-off and all the stocks ranked below C* stock have low excess return to Beta. The Ci value goes on increasing from 0.07 to 0.14 and thereafter starts declining.

Therefore, the value 0.14 is considered as the ‘Cut-off point’ and the securities which come after will not be considered in the optimal portfolio construction. The Ci is calculated as under

SURANA COLLEGE 60


The Ci value of the stock is calculated using the formula, according to the ranked order

Where

σ2m= Variance of market value

Ri-Rf = Market risk premium

σ2ei = Unsystematic risk of the security

4.25 Table showing the proportion of investment proposed.

Sl.No. Company Name Zi Xi

1 DR. Reddy’s Laboratory 0.2425 53%

2 Nestle India Limited 0.0615 13%

3 Cipla Limited 0.1527 33%

The above table represents the proportion of investment to be made in each security. Zi

indicates the relative investment in each security and Xi indicates the weight on each

security, as out of 15 stocks of BSE index 3 stocks have been selected for the optimal

portfolio construction.

Xi and Zi are to be determined to know how much funds to be invested in each security using

the following formula below,

SURANA COLLEGE 61

https://www.google.co.in/url?sa=i&rct=j&q=&esrc=s&source=images&cd=&cad=rja&uact=8&ved=0ahUKEwiS6YbitIrTAhUT02MKHXTyCzcQjRwIBw&url=https://www.wisdomjobs.com/e-university/security-analysis-and-investment-management-tutorial-356/sharpe-s-single-index-model-11628.html&psig=AFQjCNGl5bnkd4P-txs9fM7cdqEVVDFDDw&ust=1491381900707519


Where,

Xi= Proportion of Invetment

Where,

σ2ei = Unsystematic Risk

β= beta

C* = Cut-off Point.

4.27 Figure showing the proportion of investment

0.530980214565507; 53%

0.134705181737307; 13%

0.334314603697186; 33%

Chart Title

DR.Reddy's LabNestle Cipla

The figure represents the proportion of investment to be made by the investor to earn

maximum returns. The figure shows that out of 15 companies which were from BSE index 3

companies have been selected for the optimal portfolio construction by applying the SIM

model. The chart shows that 53% has to be made in the Dr Reddy’s Lab, where half of the

portion of the amount is invested here and 14% investment to be made in Nestle, stands in

second. Further 33% in Cipla Limited has been invested.

SURANA COLLEGE 62


CHAPTER 4

CONCLUSIONS, FINDINGS AND RECOMMENDATIONS

SURANA COLLEGE 63


5.1 FINDINGS

The findings of the present study are presented below

• Dr.Reddy’s Laboratories has the highest Beta value of (0.9628) and Nestle India Limited (0.9104), ICICI Bank Limited (0.7581), Cipla Limited (0.7185) which means this stock highly volatile in nature. So, volatile stocks tend to move up and down with the market.

• The stock return of Parle Agro shows the highest return of 0.2903 and return of Nestle India Limited less return of -0.0100. The investor who is interested in investment can invest in those stocks which yield a higher return, but every investment has involved risk in it if it even provides higher returns. So, risk must be considered while making an investment decision.

• By using Sharpe Single Index model which is used to construct an optimal portfolio, which diversifies the risk. In this study out of 15 companies from four sectors, an optimum portfolio was created of which 3 companies are selected they were Dr Reddy’s Laboratories, Cipla Limited, Nestle India Limited.

• In this study 15 stocks were selected from Nifty index of which 3 stock was selected for portfolio construction. The proportion of investment made on those stocks was 53% has to be made in the Dr Reddy’s Laboratory and 14% investment to be made in Nestle India Limited, 33% in Cipla India Limited has to be invested. As here we have to make a major portion of investment in Tech Mahindra which is performing well in stock return.

• In this study it is identified that Pharma sector provides good and consistent returns for the investor because out of three stocks that is Dr Reddy’s Laboratory, Cipla Limited, Nestle India Limited is from service food sector only.

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5.2 CONCLUSION

This project was an attempt to construct an optimal portfolio using the method Sharpe’s

Single Index Model. As for an investor, it’s difficult to take investment decision by himself

as an investment involves risk in it. In this study among 15 stocks, only 3 stocks were

selected for an optimal portfolio of which SIM helps the investor in decision making on

investments which reduces risk and maximizes his profits. The investment decision should be

made after considering all factors like economic factors or other factors that govern securities

in the market.

As in India capital market is growing of which the number of investors is increasing and of

which foreign investors also attracted by the development of the Indian capital market which

has maintained consistently in the market. So, SIM has become a guiding tool for the

investors and institutional buyers in decision making. This analysis confirms that there is a

relation between risk and return.

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5.3 RECOMMENDATIONS

The investor should invest for longer-term rather than investing for a shorter duration

to maximize his returns, long investments are less volatile.

A financial advisor has to analyze the company balance sheet and its quality of

management and its past track records to make a fundamental analysis of the

company, which guides the investor before investing.

Sharpe single index model suggests the investor know about the performance of each

company within a selected period. So, to construct an effective portfolio one can use

this model.

Investors are not aware of the market risk and its fluctuations, so investor training

program has to be conducted.

The proportion of investment made on those stocks was 53% has to be made in the Dr

Reddy’s Laboratories and 14% investment to be made in Nestle India Limited, 33% in Cipla

India Limited has to be invested. So, the portion of investment which is generated above an

investor can go for the same proportion or he can decide on other factors for making his

portfolio.

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