Major Project MBA

FINANCIAL MODELLING FOR PORTFOLIO SELECTION

AND RISK MANAGEMENT

Submitted in the partial fulfillment of the requirements for the award of degree of

MASTER OF BUSINESS ADMINISTRATION

SUBMITTED BY

ARUN K T

(CUALMGT004)

UNDER THE GUIDANCE OF

Dr. B. JOHNSON

READER

DCMS

UNIVERSITY OF CALICUT

DEPARTMENT OF COMMERCE AND MANAGEMENT STUDIES


2011-13



Dr.E K Satheesh Calicut University

Associate Professor Malappuram District

& Head of the Department Kerala State – 673635

CERTIFICATE

This is to certify that Mr. Arun K T, the student of this department conducted the study entitled

“Financial Modelling for Portfolio Selection and Risk Management” submitted for the partial

requirement of degree of Master of Business Administration at Department of Commerce and

Management Studies, University of Calicut is a bonafide record of work done by him under the

guidance of Dr. B Johnson, Professor, DCMS, University of Calicut.

Place: CU Campus

Date: Dr.E K Satheesh



Dr. B.Johnson Calicut University

Reader Malappuram District

DCMS Kerala State -673635

CERTIFICATE

This is to certify that Mr. Arun K Tis a bonafide student of the Department of Commerce and

Management Studies, University of Calicut. This report entitled “Financial Modelling for

Portfolio Selection and Risk Management” is an authentic record of the project work done by him

under my supervision in partial fulfillment of the requirements for the award of the degree of Master

of Business Administration, University of Calicut.

Place: CU Campus

Date: Dr. B. Johnson

DECLARATION

I, Arun K T, student of MBA 4th semester, Department of Commerce and Management

Studies, University Of Calicut ,hereby declare that the project report entitled “Financial Modelling

for Portfolio Selection and Risk Management” submitted to University of Calicut for the partial

fulfillment of Master of Business Administration is a record of original work done by me under the

guidance of Dr. B. Johnson, Reader, DCMS, University of Calicut during the academic year

2011-2013.

The empirical findings in this report are based on data collected by me, while studying and preparing

this project report.

Date :

Place: CU Campus Arun K T

ACKNOWLEDGEMENTS

First of all, I express our heartfelt gratitude to God, the almighty, without whose blessings I

would not have completed this endeavor in time.

I express my sincere and cordial gratitude to my guide, Dr. B Johnson, Reader, Department of

Commerce and Management Studies, University Of Calicut, for his profound inspiration,

valuable insights, continuous support and assistance throughout the study.

I feel great delight in expressing my earnest thankfulness to Dr.E K Satheesh, Head, Department

of Commerce and Management Studies, University Of Calicut, for providing all necessary help

and guidance throughout the project.

I am also indebted to Dr. K P Rajendran, visiting faculty, Department of Commerce and

Management Studies, University of Calicut for his support and guidance for this project work.

I am indebted to all my faculty members in the Department of Commerce and Management

Studies, University of Calicut for their timely suggestions and guidance for this project work.

I would like to extend my sincere gratitude to Mr.Thomas George, Faculty ,Cochin Stock

Exchage Ltd. for providing me with all necessary aids to complete the tasks.

Special thanks must go to my parents and friends for their zealous prayers and muse that

strengthened our efforts to do this research work in time.

The success of this project is the result of cooperation from different people. I would like to take

this opportunity to express my ardent gratitude to all those people for the whole- hearted

contribution made to this project that can never be forgotten

ARUN K T

TABLE OF CONTENTS CHAPTER 1: INTRODUCTION 1

1.1.1 Research problem 2

1.1.2 Significance of the study 3

1.1.3 Scope of the study 3

1.1.4 Objectives of the study 4

1.1.5 Research Methodology 4

1.1.6Sources of data 4

1.1.7 Tools for data collection 5

1.1.8 Sampling Plan 5

1.1.9 Tools for analysis 5

1.1.10 Variables of the study 9

1.1.11 Period of study 9

1.1.12 Conceptual model of the study 10

1.1.14 Limitations 10

1.2 Literature Review 11

CHAPTER 2: INDIAN CAPITAL MARKET-AN OVERVIEW 31

CHAPTER 3: COCHIN STOCK EXCHANGE LTD-A PROFILE 45

CHAPTER 4: DATA ANALYSIS PART 1 53

CHAPTER 5: DATA ANALYSIS PART 2 95

CHAPTER 6: FINDINGS, SUGGESTIONS & CONCLUSION 117

BLIOGRAPHY

CHAPTER 6: ANNEXURE 123

LIST OF TABLES

Table No. Details Page No

Table 4.1 Return of Securities

55

Table 4.2 Risk of Securities 56

Table 4.3 Beta of Securities 58

Table 4.4 Alpha of the Securities 60

Table 4.5 Systematic risk of Securities. 62

Table 4.6 Unsystematic risk/residual variance of Securities. 63

Table 4.7.1 Ranks of Securities based on excess return to beta. 64

Table 4.7.2 Calculation of cut-off point. 65

Table 4.8.1 Calculation of optimal portfolio 65

Table 4.8.2 Optimal portfolio 66

Table 4.9.1 Portfolio alpha in optimal portfolio 66

Table 4.9.2 Portfolio beta in optimal portfolio 67

Table 4.9.4 Optimal portfolio return , risk ,alpha ,beta , residual, variance 68

Table 4.9.5 Benefit of diversification. 68

Table 4.10.1 Portfolio alpha in equal weight 71

Table 4.10.2 Portfolio beta in equal weight 71

Table.4.10.3 Portfolio residual variance in equal weight 72

Table.4.10.4 Benefit of diversification in equal weight. 73

Table.4.11.1 Calculation of weight based on PE ratio 74

Table.4.11.2 Portfolio alpha based on PE ratio. 74

Table.4.11.3 Portfolio beta based on PE ratio. 75

Table 4.11.4 Portfolio residual variance based on PE ratio 75

Table 4.11.5 Benefit of diversification in based on PE ratio. 76

Table 4.12.1 Calculation of weight based on risk adjusted rate of return 77

Table 4.12.2 Portfolio alpha based on risk adjusted rate of return. 77

Table 4.12.3 Portfolio beta based on risk adjusted rate of return. 78

Table 4.12.4 Portfolio residual variance based on risk adjusted rate of return. 78

Table 4.12.5 Benefit of diversification in based on risk adjusted rate of

return. 80

Table 4:13.1 Sharpe ratio of the portfolios. 82

Table 4.13.2 Treynor ratio of portfolios. 83

Table 4.13.3 Jensen measure of portfolios. 85

Table 4.14.1.1 Portfolio value for Mont Carlo Simulation. 88

Table 4.14.1.2 Changes in the total value of portfolio. 89

Table 4.14.2.1 Changes in total value of portfolio in Back testing. 92

Table 4.14.3.1 Variance Co-variance matrix. 93

Table 4.14.3.2 Portfolio PE weights 93

Table 5.1 Gender of the respondents. 96

Table 5.2 Age group of the respondents. 97

Table 5.3 Qualification of the respondents. 98

Table 5.4 Occupation of the respondents. 99

Table 5.5 Annual income of the respondents. 100

Table 5.6 Investment experience of the respondents. 101

Table 5.7 Investment preference of the respondents 102

Table 5.8 Sector Preference of the respondents 103

Table 5.9 Type of Analysis used by the respondents for investing 104

Table 5.10 Investment Objective of the respondents. 105

Table 5.11 Preferred rate of growth. 106

Table 5.12 Investment in stock market securities. 107

Table 5.13 Whether the respondents have financial advisor or not. 108

Table 5.14 Level of Knowledge of the respondents in Portfolio

Management. 109

Table 5.15 Technique used by the respondents to balance risk and return. 110

Table 5.16 Technique used by the respondents for portfolio diversification. 111

Table 5.17 Familiarity of the respondents with the Financial Modelling. 112

Table 5.18 Portfolio evaluation techniques used by respondents. 113

Table 5.19 Awareness of VAR concepts among the respondents. 114

Table 5.20 Methods for measuring VAR used by the respondents 115

Table 5.22 Qualification and awareness of the investors. 116

Table 5.23 Chi-Square Tests 117

LIST OF FIGURES

Figure No Details Page No

Fig.1.1.12 Conceptual Model 17

Fig.1.2 Efficient frontier. 21

Fig.3.1 Organisational Structre. 47

Fig.4.1 Return of Securities

55

Fig.4.2 Risk of Securities 56

Fig.4.3 Beta of Securities 58

Fig.4.4 Alpha of the Securities 60

Fig.4.5 Systematic risk of Securities. 62

Fig.4.6 Unsystematic risk/residual variance of Securities. 63

Fig.4:13.1 Sharpe ratio of the portfolios. 82

Fig.4.13.2 Treynor ratio of portfolios. 83

Fig.4.13.3 Jensen measure of portfolios. 85

Fig.5.1 Gender of the respondents. 96

Fig.5.2 Age group of the respondents. 97

Fig.5.3 Qualification of the respondents. 98

Fig.5.4 Occupation of the respondents. 99

Fig.5.5 Annual income of the respondents. 100

Fig.5.6 Investment experience of the respondents. 101

Fig.5.7 Investment preference of the respondents 102

Fig.5.8 Sector Preference of the respondents 103

Fig.5.9 Type of Analysis used by the respondents for investing 104

Fig.5.10 Investment Objective of the respondents. 105

Fig.5.11 Preferred rate of growth. 106

Fig.5.12 Investment in stock market securities. 107

Fig.5.13 Whether the respondents have financial advisor or not. 108

Fig.5.14 Level of Knowledge of the respondents in Portfolio

Management. 109

Fig.5.15 Technique used by the respondents to balance risk and

return. 110

Fig.5.16 Technique used by the respondents for portfolio

diversification. 111

Fig.5.17 Familiarity of the respondents with the Financial Modelling. 112

Fig.5.18 Portfolio evaluation techniques used by respondents. 113

Fig.5.19 Awareness of VAR concepts among the respondents. 114

Fig.5.20 Methods for measuring VAR used by the respondents 115

CHAPTER 1

INTRODUCTION

Financial modelling for portfolio selection and risk management

DCMS,UNIVERSITY OF CACLICUT

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Financial health plays a pivotal role in the overall well-being of an economy, organization, or

individual. This can certainly be assessed qualitatively, but in order to make comparisons both

vertically and horizontally, it makes sense to quantify this notion with the use of numbers and

statistics. Therefore, it is vitally important to have standards and means to manage, monitor,

maintain, and grow wealth.

Even though there is lot of improvements happening day by day in financial and investment

management area, the individual investors who are the main part of stock market are much

concerned about the aspects like portfolio selection and risk management. Their intention is to

maximize return by minimizing risk associated with their investment .So there are mainly two

basic problems any individual investor is concerned. They are formation of an optimal portfolio

and efficient management of its risk.

The development of quantitative finance and financial modeling is helping both the

investors and portfolio managers in improving the efficiency of their portfolio and effectiveness

of risk management tools. Financial models are used to predict financial performance. It is the

task of building an abstract model of a financial decision making situation. It normally involves

application of quantitative and analytical techniques to build a statistical or mathematical model

for explaining an investment situation and for explaining a financial process or product. A

financial model can be compared to a prototype for a machine. Financial modeling is extensively

used in investment management and corporate finance. It includes the application of various

financial models in solving various problems in finance.

The study titled “Financial modeling for portfolio selection and risk management” is an attempt

to find out the application of different financial models for portfolio selection and management of

risk. William Sharpe optimization model is used for finding out the optimal portfolio. Different

Value at Risk measures like Monte Carlo simulation and Variance –Covariance method is used

for studying the role of financial models in risk management.



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1.1.1: RESEARCH PROBLEM

Today’s Financial Market is more complex and uncertain due to introduction of new

processes and innovative products. Financial modeling strategies are effective analytical methods

for making scientific and efficient investment decisions in such complex and volatile market. The

three main problems faced by investors in managing their investment are

1. How to obtain superior performance of portfolio by striking a trade-off between risk &

return

2. How to identify under-priced securities for making investment decision.

3. How to manage the risk associated with the portfolio.

Because of volatility and complexity of capital market traditional methods based on intuitive

investment decisions fails to achieve this purpose. Investors have to use financial models for

striking an optimal trade-off between risk and return.

The study mainly focuses on studying the effectiveness of financial models in portfolio

optimization, portfolio risk management.

1.1.2: SIGNIFICANCE OF THE STUDY

Every investment decision is based on an efficient risk-return trade-off. Increased complexity of

financial instruments and the economic conditions such as recession, boom, etc makes it difficult

for any investment manager to plan his investments.

The study recognizes the importance of in generating an optimal portfolio for making right

investment decision and devising superior strategy for risk management.

1.1.3: SCOPE OF THE STUDY

The study entitled “Financial Modelling and Risk Management” focuses on how effectively an

investor can apply Financial Modelling in Portfolio Selection,Optimization and Portfolio Risk

Management. The study also tries to study to Value at Risk risk management techniques using

Montecarlo Simulation, Backtesting and Variance covariance model. The scope of the study is

also limited to Indian Stock Market and Indian Derivative Securities Market.



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1.1.4: OBJECTIVES

Broad objective of the study is to review the different financial models for portfolio selection &

portfolio risk management. Specific objectives of the study are:-

To study the application of Sharpe’s optimization model in portfolio selection and

optimization

To study the role of VaR matrics by using variance- covariance method and Monte Carlo

simulation method in portfolio risk management.

To perform a back test in order to determine the reliability of the VaR model so

developed.

To evaluate the awareness of Financial Modelling techniques among the investors.

1.1.5: RESEARCH METHODOLOGY

Research design

Research design is the conceptual structure within which research will be conducted. Design

includes an outline of what the researcher will do from writing the hypothesis and its operational

implications to the final analysis of the data. The study is based on analytical type of research.

1.1.6: SOURCES OF DATA

Primary data and secondary data were collected in order to fulfill the purpose of the research.

Primary data

The primary data required for the study were collected from the respondents through

questionnaire and personal interviews.

Secondary data

The main source of information is from the website Historical data of closing price of the

selected equities are collected from websites of the exchange. Data is also collected from

newspapers, magazines and journals. Five years historical data was analyzed for doing this

research.



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1.1.7: TOOLS FOR DATA COLLECTION

The research instrument mainly used for the data collection was questionnaire. Personal

interview was another tool.

1.1.8: SAMPLING PLAN

The sampling method used for the research was purposive sampling. The research was done

according to the ease of accessibility and proximity to the researcher.

a. Sampling unit

The sampling unit used by the researcher includes investors investing in Indian

stock market.

b. Sample size The sample size taken for the study was 30.

c. Contact Method

Direct contact method was used for the study. Questionnaires were circulated

among the sample respondents.

Criteria for selection of stocks

Ten securities which included in the CNX NIFTY are only selected on the base that they

represent major stocks in the capital market.

1.1.9: TOOLS FOR ANALYSIS

The data collected has been analysed using basic statistical tools like standard deviation, mean

etc.

Important Terms and Formula’s used

Portfolio construction

Ri= (Today’s price- yesterday’s price)*100

Yesterday’s price

Return (Ri) = (PE -PB) *100

PB

Alpha = Stock Return – (Beta x Market Return)

Alpha (αi) =Ri-βi*Rm



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NΣxy-ΣxΣy

Beta (β) =

NΣx²-(Σx) ²

Risk (σ²) =Σ(xi-x)²

N

Residual variance (σ²ei) = σ i²- βi ² * σ² m

n

Portfolio alpha (αp) = Σ ωi αi

i=1

n

Portfolio beta (βp) = Σ ωi βi

i=1

n

Portfolio residual variance (σ²ei) = Σ ωi² σ²

i=1

Portfolio return = Portfolio alpha+ (Portfolio beta * Market return)

Rp= αp+ (βp*Rm)

n

Portfolio risk, (σ²p) = β ²p σ²m+ Σ ωi ² σ²ei

i=1

Cut off point

n σ²m Σ ((Ri - Rf) x βi)/ σ²ei

i =1

Ci =

n

1+ σ²m Σ βi²)/ σ²ei

i=1

Proportion of fund invested in each security

Zi

Xi =

n

Σ Zi

i=1



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Markowitz model

Portfolio return (Rp)=X1R1+X2R2+X3R3

Portfolio Risk (σ ² p)

σp2= σ1

2 X1 2+ σ2 2 X2

2+ σ3 2 X3 2+2 X1 X2 COV12+2 X2 X3 COV 23+2X1X3 COV13

Rp=Portfolio Return

σp2=Portfolio Variance

X1 = Proportion of funds invested in first security

R1=Return of first security

X2= Proportion of funds invested in second security

R2= Return of second security

X3= Proportion of funds invested in third security

R3= Return of second security

COV12=Covariance between the return of first and second securities

COV 23 = Covariance between the return of second and third securities

COV13 = Covariance between the return of first and third securities

TANGENCY PORTFOLIO:

A = MMULT (MMULT (TRANSPOSE (ONES), MINVERSE

(VARIANCE CO-VARIANCE MATRIX)), ONES)

B = MMULT (MMULT (TRANSPOSE (ONES), MINVERSE

(VARIANCE CO-VARIANCE MATRIX)), 1+ E®)

C. = MMULT (MMULT (TRANSPOSE (1+ E®), MINVERSE

(VARIANCE CO-VARIANCE MATRIX)), 1+ E®)

DELTA : A x C. - B2

GAMMA: 1 / (B-A x R.)

RISK = SQRT (MMULT (MMULT (TRANSPOSE (OPTIMAL

COMBINATION OF RISKY ASSETS), VARIANCE CO-VAR

MATRIX), OPTIMAL COMBINATION OF RISKY ASSETS))

RETURN: MMULT (TRANSPOSE (OPTIMAL COMBINATION OF RISKY

ASSETS), 1+E®)-1



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Portfolio evaluation:

Sharpe ratio

Sharpe ratio (SR) = Portfolio return-Risk free rate of return

Portfolio Standard deviation

= Rp-Rf

σp

Where

Rp- realized return on the portfolio

Rf- Risk free rate of return

σp- Standard deviation of portfolio return

Treynor ratio

Treynor ratio = Rp-Rf

βp

Where

Rp - realized return on the portfolio

Rf - Risk free rate of return

βp - Portfolio beta

Jensen measure

Jensen measure (αp) = Rp -E(Rp)

Where,

Rp - Realized return of the portfolio

E (Rp) – Expected return of the portfolio

E (Rp) = Rf + βp(Rm – Rf):-Where,

βp - Beta of portfolio

Rm - Market Return

Rf - Risk free rate of return



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Value at Risk

At 95% confidence level

VaR = portfolio value x 1.65σ

At 99% confidence level

VaR = portfolio value x 2.33σ

Monte Carlo Simulation

∂s = μS∂t + σSЄ√∂ t

Where,

∂s = change in the stock price for a small change in time interval ∂ t

S= stock price at time t

μ = expected rate of return per unit of time

Є = Random drawing from a standardized normal distribution

σ = Volatility of stock price or standard deviation of the expected return

∂ t = A small time interval

1.1.10: VARIABLES OF THE STUDY

Return

Risk

Awareness

Optimization

Stock Price

1.1.11: PERIOD OF STUDY

The study was conducted for a period of 45 days extending from April 1st to May 15 2013



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1.1.12: CONCEPTUAL MODEL OF THE STUDY

Fig.No:1.1.12

1.1.3: LIMITATIONS

Duration of the study is limited to the period of one month .So in depth study is not

possible.

Only four portfolio were constructed

The conclusion cannot be conclusive as market is unpredictable

Data considered is only for past 5 year period



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Value at Risk estimate the market risk, based on the past data

Security beta is assumed to be static

1.2: LITERATURE REVIEW

PORTFOLIO MANAGEMENT

Portfolio is a collection of assets .Creation of portfolio helps to reduce risk without sacrificing

returns. It is rare to find investors investing in a single security, instead of this they tend to invest

in a group of securities. Such a group of securities is called a portfolio.

Portfolio management deals with the analysis of individual securities as well as with the

theory and practice of optimally combining securities in to portfolio. An investor is faced with

problems in choosing the securities among the large number of securities. His choice depends

upon risk return returns characteristics of individual securities. Another problem is how much to

invest in each security. The risk return characteristics of a portfolio differ from those of

individual securities combining to form a portfolio. The investor tries to choose the optimal

portfolio taking in to consideration the risk return characteristics of all possible portfolios.

Portfolio management is a complex process which tries to make investment activity more

rewarding and less risky.

Portfolio management process consist of the following five process,

1. Security analysis

2. Portfolio analysis

3. Portfolio selection

4. Portfolio revision

5. Portfolio evaluation



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The success of portfolio management depends on how effectively each phase is carried out.

1. Security analysis

Security analysis is the initial phase of the portfolio management process. This step consists of

examining the risk return characteristics of individual securities. For the purpose of analysis ten

securities are selected and the return, risk and risk adjusted rate of return are determined. There

are two alternative approaches to security analysis they are fundamental analysis and technical

analysis. They are based on different premises and follow different techniques.

Fundamental analysis concentrates on fundamental factors affecting the company such as the

EPS of the company, the dividend pay-out ratio, competition faced by the company, market share

.quality management, etc According to this approach the share price of this company is

determined by these fundamental factors. The fundament analysts works out the true worth or

intrinsic values of a security based on its fundamentals and then compares this value with the

current market price. If the current market price is higher than the intrinsic value the share is said

to be overpriced. Fundamental analysis helps to identify fundamentally strong companies whose

shares are worthy to be included in the investors’ portfolio.

Technical analysis concentrates on price movements and ignores the fundamental s of shares.

The technical analyst believes that the share price movements are systematic and exhibit certain

consistent patterns .He therefore studies past movements in the prices of shares to identify trends

and patterns .He then tries to predict the future price movement s. The current market are

compared with the future predicted price to determine the extend of mis pricing.

More recent approach to security analysis is the efficient market hypothesis. This hypothesis

holds that share movements are random and not systematic. According to this approach it is

possible for an investor to earn normal returns by randomly choosing securities of a given risk

level.

2. PORTFOLIO ANALYSIS

Portfolio analysis phase of portfolio management consist of identifying the range of

portfolios that can be constituted from a given set of securities and calculating their return and

risk for further analysis. It is better to invest in a group of securities rather than a single security.

Such a group of securities held together as an investment is known as a portfolio. A rational



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investor attempts to find out the most efficient portfolio. The efficiency can be evaluated only in

terms of the expected return and risk of different portfolio.

Security analysis provides the investor with a set of worthwhile or desirable securities.

From this set of securities an indefinitely large number of portfolios can be constructed by

choosing different set of securities and also by varying the proportion of investment in each

security. Each of these securities has its own risk return characteristics which are not just the

aggregate of individual security characteristics. The risk and return can be measured and

expressed quantitatively.

3. Portfolio selection

The proper goal of portfolio construction is to generate a portfolio that provides the highest

return at a given level of risk .A portfolio having this characteristic is known as efficient

portfolio. From this set of efficient portfolios, optimal portfolio has to be selected for investment.

4. Portfolio revision

Having constructed the optimal portfolio, the investor has to constantly monitor the portfolio to

ensure that it continues to be optimal. Portfolio revision involves changing the existing mix of

securities. The main objective of portfolio revision is to ensure the optimality of the revised

portfolio. Portfolio revision is not a causal process of portfolio management, portfolio revision is

as important as portfolio analysis and selection.

Portfolio revision may also be necessitated by some investor related changes such as availability

of additional fund, changes in risk attitude, need of cash for other alternative use, etc. Portfolio

revision has to be done scientifically and objectively so as to ensure the optimality of the revised

portfolio.

5. Portfolio evaluation

The objective of constructing and revising it periodically is to earn maximum returns with

minimum risk. Portfolio evaluation is the process which is concerned with assessing the

performance of the portfolio over a selected period of time in terms of return and risk. It provides

mechanism for identifying weakness in the investment process for improving these deficient

areas. It provides a feedback mechanism for improving the entire portfolio management process



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Portfolio Theory

Portfolio theory is concerned with the risk-reducing role played by individual assets in an

investment portfolio of several assets. The benefits of diversification were first formalized in

1952 by Harry Markowitz, who later was awarded the Nobel prize in economics for his work.

Portfolio Theory is today a corner stone of modern financial theory, as well as a widely used tool

for managing risk-return tradeoffs in investment portfolios.

Means and standard deviations of Total Return

The return and risk of an asset are commonly measured in terms of the mean and standard

deviation of total return, where total return represents income plus capital gains or losses. The

mean is the return one expects to obtain on average; standard deviation is a measure of

dispersion.

The mean and standard deviation of return for a given asset can be computed from historical

returns. In that case, however, they are merely summary descriptors of past performance, and

may or may not reflect the probability distribution of future returns.

Portfolio selection

Optimal Portfolio selection using Sharpe’s optimization model

Sharpe had provided a model for the selection of appropriate securities in a portfolio. In this

model, the ranking criteria are used to order the stocks for selecting the optimal portfolio.

Formation of optimal portfolio

The inclusion of any security in the portfolio directly related to its excess return to beta

ratio. Excess return is the difference between the expected return on the stock and the risk free

rate of interest such as rate of return on Govt. securities. The excess return-to-beta ratio measures

the additional return on a stock (excess return over the risk free rate) per unit of non –

diversifiable risk. This ratio gets easy interpretation and acceptance because this ratio gives

relationship between potential reward risks. The numerator of this ratio gives the extra return

over the risk- free rate and the denominator give the non-diversifiable risk



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Excess return to beta ratio= (Ri-Rf)/βi

Where

Ri = the expected return on security ‘I’

Rf = the return on risk less asset

βi = the expected change in the ratio of return on stock I associated with a 1%

change in the market return

If the stock ranked by excess return –to – beta (from highest to lowest), ranking

represents the desirability of a stock inclusion in the portfolio. This implies that if a

particular stock with a specific ratio of (Ri-Rf)/βi included in the optimal portfolio, all

stocks with higher ratio will also be included. On the other hand, if a stock with a

particular (Ri-Rf)/βi is excluded from an optimal portfolio; all stocks with a lower ratio

will be excluded. The number of stocks included in the optimal portfolio depends on a

unique cut off rate which ensures that all stocks with higher (Ri-Rf)/βi will be included

and all stocks with lower ratios should be excluded. Cut off rate is denoted by “C*”

The steps for finding out the stocks to be included in the optimal portfolio are given below

1. Find out the “ excess return to beta” ratio for each stock under consideration

2. rank them from the highest to lowest

3. proceed to calculate Ci for all stocks according to the ranked order using the following

formula N

σ2m∑ (RI-RF) βi/ σ2

ei

i=1

Ci = N

1+ σ2m

∑ βi2/ σ2ei

i=1

4. The cumulated values of Ci starts 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*

CONSTRUCTING THE OPTIMAL PORTFOLIO

Once the cut-off rate is determined the next step is calculating the proportion to be

invested in each security. The proportion invested in each security is:



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Zi

Xi = N

∑ Zi i=1

Where

βi (RI-RF)

Zi = - C*

σi βi

Xi = weight on each security

Βi=Beta of each security

σi=Risk of security

Ri=return of each security

Rf=Risk free rate of return

C*= cut off rate

The Markowitz Portfolio Theory

(Concept of Expected Risk and Expected Rates of Return)

Creating an optimum portfolio doesn't involve simply finding the best risk vs. return situations,

but considering varying relationships between different asset classes.

In the early 1960s, there was much contemplation among investment industry professionals about

risk and its implications on selecting specific securities and other types of assets when

constructing an optimum portfolio. Yet, there were also no effective means or models of

measuring risk available at the time. By the same token, it was very clear that to construct the

optimum portfolio, capable of meeting an investor’s investment objectives within the constraints

of his or her chosen investment horizon, was not going to be possible without adequate and

quantifiable measures of risk.

Prompted by this largely unmet need, Harry M. Markowitz introduced the preliminary portfolio

model in a paper titled Portfolio Selection, which he had published in the 1952 Journal of

Finance. Markowitz was further credited with the formulation of two terms critical to the

development of the portfolio theory: the expected rate of return and the expected risk measure.

Note that almost four decades after publishing Portfolio Selection, Markowitz shared a Nobel

Prize with Merton Miller and William Sharpe for his contribution to the development of what has

become known as the capital market theory.



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Investor Behavior Assumptions

The Markowitz Portfolio Theory relies on a number of assumptions regarding investor behavior;

such is that investors will always seek “the second opinion.” When presented with a spectrum of

alternatives, investors will consider all expected rates of return over a specified holding period.

Furthermore, investors are very much interested to know the estimated risk level of all securities

contained within a portfolio. In fact, we could say that their investment decisions are solely based

on these two variables: the levels of expected return and the expected risk.

Notably, for any given risk level, investors will always rather go for portfolios with higher

expected returns than for those with lower returns. Alternatively, for any given expected return

level, investors are likely to prefer portfolios with less risk than those with more risk.

Based on these assumptions, most of which are pretty much common sense, when comparing a

single security or a portfolio of securities, only securities or portfolios with the highest expected

return at the same or lower risk level are considered as efficient.

The Efficient Frontier

The Markowitz Portfolio Theory also examines the curve called the efficient frontier. The idea

behind this curve is a graphic presentation of a set of portfolios that offer the maximum rate of

return for any given level of risk. Alternatively, the efficient frontier identifies portfolios that

offer the minimum risk for any given level of return.

The Markowitz efficient investor will seek his or hers optimum portfolio somewhere along the

efficient frontier curve, depending on their individual perception of the return-risk relationship.

Each portfolio on the curve will either have a higher rate of return for the same or lower risk, or

lower risk for an equal or better rate of return when compared to portfolios or securities that are

not on the efficient frontier.

Because portfolios enjoy benefits of diversification due to imperfectly correlated assets contained

within them, the efficient frontier is really made up of portfolios rather than individual securities

or assets. The two potential exemptions would be the efficient frontier curve’s end points, at the

beginning of which could be the asset with the lowest risk and at the end of which could be the

asset with the highest return.

What Harry Markowitz started back in the early 1960s was continued through the development

of the capital market theory, whose final product, the capital asset pricing model (CAPM),

allowed a Markowitz efficient investor to estimate the required rate of return for any risky

security or asset.

http://portfolio-management.suite101.com/article.cfm/the_capital_market_theory

http://investment.suite101.com/article.cfm/understanding_the_concept_of_capm



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The capital asset pricing model

The capital asset pricing model was developed in mid – 1960’s by three researchers William

Sharpe, John Lintner and Jan Mossin independently. This model is also known as Sharpe-Linter-

Mossin Capital Asset Pricing Model.

The Capital Asset Pricing Model or CAPM is really an extension of the Portfolio theory of

Markowitz. The portfolio theory is a description of how rational investors should build efficient

portfolios and select the optimal portfolio. The Capital Asset Pricing Model derives the

relationship between the expected return and risk of individual securities and portfolios in the

capital markets if everyone behaves in the way the portfolio theory suggested.

Fundamental Notions of Portfolio theory

Return and risk are two important characteristic of every investment. Investors place their

investment decisions on the expected return and risk of investments. Risk is measured by the

variability in return.

Investors attempt to reduce the variability of returns through diversification of

investment. This results in the creation of a portfolio. With a given set of securities, any number

of portfolios may be created by altering the proportion of funds invested in each security. Among

these portfolios some dominate others or some are more efficient than the vast majority of

portfolios because of lower risk or higher returns. Investors identify this efficient set of

portfolios.

CAPM decomposes a portfolio's risk into systematic and specific risk. Systematic risk is the risk

of holding the market portfolio. As the market moves, each individual asset is more or less

affected. To the extent that any asset participates in such general market moves, that asset entails

systematic risk. Specific risk is the risk which is unique to an individual asset. It represents the

component of an asset's return which is uncorrelated with general market moves.

According to CAPM, the marketplace compensates investors for taking systematic risk but not

for taking specific risk. This is because specific risk can be diversified away. When an investor

holds the market portfolio, each individual asset in that portfolio entails specific risk, but through

diversification, the investor's net exposure is just the systematic risk of the market portfolio

http://www.riskglossary.com/articles/correlation.htm

http://www.riskglossary.com/articles/hedging_and_diversification.htm



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Systematic risk can be measured using beta. According to CAPM, the expected return of a stock

equals the risk-free rate plus the portfolio's beta multiplied by the expected excess return of the

market portfolio Capital asset pricing model

An estimation of the CAPM and the Security Market Line (purple) for the Dow Jones Industrial

Average over the last 3 years for monthly data.

The Capital Asset Pricing Model (CAPM) is used in finance to determine a theoretically

appropriate required rate of return of an asset, if that asset is to be added to an already well-

diversified portfolio, given that asset's non-diversifiable risk. The model takes into account the

asset's sensitivity to non-diversifiable risk (also known as systemic risk or market risk), often

represented by the quantity beta (β) in the financial industry, as well as the expected return of the

market and the expected return of a theoretical risk-free asset.

The model was introduced by Jack Treynor, William Sharpe, John Lintner and Jan Mossin

independently, building on the earlier work of Harry Markowitz on diversification and modern

portfolio theory. Sharpe received the Nobel Memorial Prize in Economics (jointly with

Markowitz and Merton Miller) for this contribution to the field of financial economics.

Asset pricing

Once the expected return, E(Ri), is calculated using CAPM, the future cash flows of the asset can

be discounted to their present value using this rate (E(Ri)), to establish the correct price for the

asset.

In theory, therefore, an asset is correctly priced when its observed price is the same as its value

calculated using the CAPM derived discount rate. If the observed price is higher than the

valuation, then the asset is overvalued (and undervalued when the observed price is below the

CAPM valuation).

Alternatively, one can "solve for the discount rate" for the observed price given a particular

valuation model and compare that discount rate with the CAPM rate. If the discount rate in the

model is lower than the CAPM rate then the asset is overvalued (and undervalued for a too high

discount rate).

http://www.riskglossary.com/articles/beta.htm

http://www.riskglossary.com/articles/common_stock.htm

http://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

http://en.wikipedia.org/wiki/Dow_Jones_Industrial_Average

http://en.wikipedia.org/wiki/Finance

http://en.wikipedia.org/wiki/Rate_of_return

http://en.wikipedia.org/wiki/Asset

http://en.wikipedia.org/wiki/Portfolio_%28finance%29

http://en.wikipedia.org/wiki/Diversification_%28finance%29

http://en.wikipedia.org/wiki/Risk

http://en.wikipedia.org/wiki/Systemic_risk

http://en.wikipedia.org/wiki/Market_risk

http://en.wikipedia.org/wiki/Beta_coefficient

http://en.wikipedia.org/wiki/Risk-free_interest_rate

http://en.wikipedia.org/wiki/Jack_L._Treynor

http://en.wikipedia.org/wiki/William_Forsyth_Sharpe

http://en.wikipedia.org/wiki/John_Lintner

http://en.wikipedia.org/wiki/Jan_Mossin

http://en.wikipedia.org/wiki/Harry_Markowitz


http://en.wikipedia.org/wiki/Modern_portfolio_theory

http://en.wikipedia.org/wiki/Modern_portfolio_theory

http://en.wikipedia.org/wiki/Bank_of_Sweden_Prize_in_Economic_Sciences_in_Memory_of_Alfred_Nobel

http://en.wikipedia.org/wiki/Merton_Miller

http://en.wikipedia.org/wiki/Financial_economics

http://en.wikipedia.org/wiki/Cash_flow

http://en.wikipedia.org/wiki/Discounted

http://en.wikipedia.org/wiki/Present_value



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Asset-specific required return

The CAPM returns the asset-appropriate required return or discount rate - i.e. the rate at which

future cash flows produced by the asset should be discounted given that asset's relative riskiness.

Betas exceeding one signify more than average "riskiness"; betas below one indicate lower than

average. Thus a more risky stock will have a higher beta and will be discounted at a higher rate;

less sensitive stocks will have lower betas and be discounted at a lower rate. The CAPM is

consistent with intuition - investors (should) require a higher return for holding a more risky

asset.

Since beta reflects asset-specific sensitivity to non-diversifiable, i.e. market risk, the market as a

whole, by definition, has a beta of one. Stock market indices are frequently used as local proxies

for the market - and in that case (by definition) have a beta of one. An investor in a large,

diversified portfolio (such as a mutual fund) therefore expects performance in line with the

market.

Risk and diversification

The risk of a portfolio comprises systematic risk, also known as diversifiable risk, and

unsystematic risk which is also known as idiosyncratic risk or diversifiable risk. Systematic risk

refers to the risk common to all securities - i.e. market risk. Unsystematic risk is the risk

associated with individual assets. Unsystematic risk can be diversified away to smaller levels by

including a greater number of assets in the portfolio (specific risks "average out"). The same is

not possible for systematic risk within one market. Depending on the market, a portfolio of

approximately 30-40 securities in developed markets such as UK or US will render the portfolio

sufficiently diversified to limit exposure to systemic risk only. In developing markets a larger

number is required, due to the higher asset volatilities.

A rational investor should not take on any diversifiable risk, as only non-diversifiable risks are

rewarded within the scope of this model. Therefore, the required return on an asset, that is, the

return that compensates for risk taken, must be linked to its riskiness in a portfolio context - i.e.

its contribution to overall portfolio riskiness - as opposed to its "stand alone riskiness." In the

CAPM context, portfolio risk is represented by higher variance i.e. less predictability. In other

http://en.wikipedia.org/wiki/Risk

http://en.wikipedia.org/wiki/Mutual_fund

http://en.wikipedia.org/wiki/Portfolio_%28finance%29

http://en.wikipedia.org/wiki/Systematic_risk

http://en.wikipedia.org/w/index.php?title=Unsystematic_risk&action=edit&redlink=1

http://en.wikipedia.org/w/index.php?title=Idiosyncratic_risk&action=edit&redlink=1

http://en.wikipedia.org/wiki/Market_risk


http://en.wikipedia.org/wiki/Return_on_investment

http://en.wikipedia.org/wiki/Variance



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words the beta of the portfolio is the defining factor in rewarding the systematic exposure taken

by an investor.

The efficient frontier

Fig.No:1.2

The (Markowitz) efficient frontier

The CAPM assumes that the risk-return profile of a portfolio can be optimized - an optimal

portfolio displays the lowest possible level of risk for its level of return. Additionally, since each

additional asset introduced into a portfolio further diversifies the portfolio, the optimal portfolio

must comprise every asset, (assuming no trading costs) with each asset value-weighted to achieve

the above (assuming that any asset is infinitely divisible). All such optimal portfolios, i.e., one for

each level of return, comprise the efficient frontier.

Because the unsystematic risk is diversifiable, the total risk of a portfolio can be viewed as beta.

The market portfolio

An investor might choose to invest a proportion of his or her wealth in a portfolio of risky assets

with the remainder in cash - earning interest at the risk free rate (or indeed may borrow money to

fund his or her purchase of risky assets in which case there is a negative cash weighting). Here,

http://en.wikipedia.org/wiki/Image:Markowitz_frontier.jpg

http://en.wikipedia.org/wiki/Infinite_divisibility


http://en.wikipedia.org/wiki/Beta_coefficient



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the ratio of risky assets to risk free asset does not determine overall return - this relationship is

clearly linear. It is thus possible to achieve a particular return in one of two ways:

1. By investing all of one's wealth in a risky portfolio,

2. or by investing a proportion in a risky portfolio and the remainder in cash (either

borrowed or invested).

For a given level of return, however, only one of these portfolios will be optimal (in the sense of

lowest risk). Since the risk free asset is, by definition, uncorrelated with any other asset, option 2

will generally have the lower variance and hence be the more efficient of the two.

This relationship also holds for portfolios along the efficient frontier: a higher return portfolio

plus cash is more efficient than a lower return portfolio alone for that lower level of return. For a

given risk free rate, there is only one optimal portfolio which can be combined with cash to

achieve the lowest level of risk for any possible return. This is the market portfolio.

Assumptions of CAPM

All Investors:

Aim to maximize utilities.

Are rational risk-averse.

Are price takers i.e. they cannot influence prices.

Can lend and borrow unlimited under the risk free rate of interest.

Securities are all highly divisible into small parcels.

No transaction or taxation costs incurred.

Capital market line & security market line

The efficient frontier represents the efficient set of portfolios. The line formed by the action of all

investors mixing the market portfolio with the risk free assets is known as the Capital market

line. All efficient portfolios of all investors will lie along this CML.

CML does not describe the risk return relationship of inefficient portfolios. The CAPM specifies

the relationship between expected return and risk of all securities and all portfolios, whether

efficient or inefficient.

http://en.wikipedia.org/wiki/Correlation

http://en.wikipedia.org/wiki/Market_portfolio



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SML gives the relationship between expected return and beta value (β) of a security. Beta value

is a measure of the security’s sensitivity to changes in the market return. Beta value greater than

one indicates higher sensitivity to changes in the market changes, whereas beta value less than

one indicates lower sensitivity to market changes. When the beta value equals to one it indicates

that security moves at the same rate and in the same direction as the market.

Pricing securities with CAPM

The CAPM can also be used for evaluating the pricing of securities. It provides a frame work for

assessing whether a security is underpriced, overpriced or correctly priced. According to CAPM

each security is expected to provide a return commensurate with its level of risk. A security may

be offering more returns than expected returns, making it more attractive. Another security may

be offering less return than the expected return, making it less attractive.

Shortcomings of CAPM

The model assumes that asset returns are (jointly) normally distributed random variables.

It is however frequently observed that returns in equity and other markets are not

normally distributed. As a result, large swings (3 to 6 standard deviations from the mean)

occur in the market more frequently than the normal distribution assumption would

expect.

The model assumes that the variance of returns is an adequate measurement of risk. This

might be justified under the assumption of normally distributed returns, but for general

return distributions other risk measures (like coherent risk measures) will likely reflect the

investors' preferences more adequately.

The model does not appear to adequately explain the variation in stock returns. Empirical

studies show that low beta stocks may offer higher returns than the model would predict.

Some data to this effect was presented as early as a 1969 conference in Buffalo, New

York in a paper by Fischer Black, Michael Jensen, and Myron Scholes. Either that fact is

itself rational (which saves the Efficient Market Hypothesis but makes CAPM wrong), or

it is irrational (which saves CAPM, but makes the EMH wrong – indeed, this possibility

makes volatility arbitrage a strategy for reliably beating the market).

The model assumes that given a certain expected return investors will prefer lower risk

(lower variance) to higher risk and conversely given a certain level of risk will prefer

http://en.wikipedia.org/wiki/Normal_distribution

http://en.wikipedia.org/wiki/Random

http://en.wikipedia.org/wiki/Coherent_risk_measure

http://en.wikipedia.org/wiki/Buffalo%2C_New_York

http://en.wikipedia.org/wiki/Buffalo%2C_New_York

http://en.wikipedia.org/wiki/Fischer_Black

http://en.wikipedia.org/wiki/Michael_Jensen

http://en.wikipedia.org/wiki/Myron_Scholes

http://en.wikipedia.org/wiki/Efficient_Market_Hypothesis

http://en.wikipedia.org/wiki/Volatility_arbitrage



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higher returns to lower ones. It does not allow for investors who will accept lower returns

for higher risk. Casino gamblers clearly pay for risk, and it is possible that some stock

traders will pay for risk as well.

The model assumes that all investors have access to the same information and agree about

the risk and expected return of all assets (homogeneous expectations assumption).

The model assumes that there are no taxes or transaction costs, although this assumption

may be relaxed with more complicated versions of the model.

The market portfolio consists of all assets in all markets, where each asset is weighted by

its market capitalization. This assumes no preference between markets and assets for

individual investors, and that investors choose assets solely as a function of their risk-

return profile. It also assumes that all assets are infinitely divisible as to the amount which

may be held or transacted.

The market portfolio should in theory include all types of assets that are held by anyone

as an investment (including works of art, real estate, human capital...) In practice, such a

market portfolio is unobservable and people usually substitute a stock index as a proxy

for the true market portfolio. Unfortunately, it has been shown that this substitution is not

innocuous and can lead to false inferences as to the validity of the CAPM, and it has been

said that due to the inobservability of the true market portfolio, the CAPM might not be

empirically testable. This was presented in greater depth in a paper by Richard Roll in

1977, and is generally referred to as Roll's critique

Tools for portfolio evaluation

Sharpe ratio

The performance measured developed by William Sharpe is referred to as the Sharpe ratio or the

reward to variability ratio. It is the ratio of the reward or risk premium to the variability of return

or risk as measured by the standard deviation of return. The formula for calculating Sharpe ratio

may be stated as

Sharpe ratio (SR)= Rp-Rf

σp

Where

Rp=realized return on the portfolio


σp=Standard deviation of portfolio return

http://en.wikipedia.org/wiki/Richard_Roll

http://en.wikipedia.org/wiki/Roll%27s_critique



- 25 -

Treynor ratio

The performance measure developed by Jack Treynor is referred to as Treynor ratio or reward to

volatility ratio. It is the ratio of the reward or risk premium to the volatility of return as measured

by the portfolio beta. The formula for calculating Treynor ratio may be stated as

Treynor ratio= Rp-Rf

Βp

Where

Rp=realized return on the portfolio


Βp=Portfolio beta

Both the measures are relative measures of performance because they relate the return to the risk

involved. However they differ in the measure of risk used for the purpose. Sharpe uses the total

risk as measured by standard deviation, while Treynor employs the systematic risk as measured

by the beta coefficient in a fully diversified portfolio all the unsystematic risk would be

diversified away and the relevant measure of risk would be the beta coefficient. For such a

portfolio Treynor ratio would be the appropriate measure of performance evaluation .For a

portfolio that is not so well diversified, the Sharpe ratio using the total risk measure would be the

appropriate performance measure.

Jensen ratio

Another type of risk adjusted performance has been developed by the Michael Jensen and is

referred to a Jensen ratio. This ratio measures the differential between actual return earned on a

portfolio given its level of risk. The CAPM model is used to to calculate the expected return on a

portfolio. The difference between the return that a portfolio should earn for a given level of risk

.The difference between the return actually earned on a portfolio and the return expected from the

portfolio is a measure of the excess return.



- 26 -

Using the CAPM model the expected return of the portfolio can be calculated as follows

E(Rp) =Expected portfolio return

Rf =Risk free rate

Rm= Return on market index

Βp=Systematic risk of the portfolio

The differential return is calculated as follows:

αp= Rp- E(Rp)

Where

αp =Differential return earned

Rp= actual return earned on the portfolio

E (Rp) =Expected return

Value at Risk

Risk management attempts to provide financial predictability for a company. Every day firms

face financial risks. Interest and exchange rate volatility, default on loans, and changes in credit

rating are some examples. These risks can be sorted into two categories-credit risk and market

risk. Credit risk includes all risks associated with the credit of specific participants, such as

potential default or changes in credit rating.

Market risk refers to risks affecting broad sectors of the economy, such as an increase in interest

rates, currency devaluation, or a decline in commodities prices, like aluminum and oil. Financial

analysts use a number of innovations to calculate and hedge against these kinds of risk. One

innovation that has been receiving immense attention is Value at Risk.

Value at Risk is a summary statistic that quantifies the exposure of an asset or portfolio to market

risk, or the risk that a position declines in value with adverse market price changes. Measuring

risk using VaR allows managers to statements regarding the expected losses for a certain period.

To arrive at a VaR measure for a given portfolio, a firm must generate a probability distribution

of possible changes in the value of some portfolio over a specific time or “risk horizon”

.J.P.Morgan Chairman Dennis Weatherstone introduced this concept.



- 27 -

Different approaches for calculating VaR

VaR can be calculated in many ways. As a result, firms using different calculating methods can

arrive at different Value at Risk numbers for the same portfolio. There are advantages and

disadvantages in each method of calculating VaR


Variance Covariance model

Historical Simulation Method


For applying Monte Carlo simulation technique, security prices are assumed to be a random

variable. It is also assumed that the stock market is efficient in the weak form (which is true for

Indian Market).Since stock price is a random variable; the stock price movement is a stochastic

process.

The Wiener process, which is a particular type of Markov stochastic process, best defines the

stock price movement. The mathematical model which defines the stock price movements under

Wiener process is given by the following mathematical relation:


Where,

∂s = change in the stock price for a small change in time interval ∂ t

S= stock price at time t

μ = expected rate of return per unit of time

ε = Random drawing from a standardized normal distribution

σ = Volatility of stock price or standard deviation of the expected return

∂ t = A small time interval

The stock price after a small time interval ∂ t would be

ST = S+∂s



- 28 -

Since the period considered is very small, a logo normal return or continuously

compounded return would be more appropriate. So the expected return μ for period T is defined

as

μ = 1 ℓn * ST

T SO

Where

ST = Stock price at time T

SO = Stock price at time Zero

ℓn = Natural logarithm

T =Time interval in years

Following steps are involved in Monte Carlo Simulation to calculate one-day VaR for a

portfolio.

1. Determining the expected return and standard deviation of the return for the stock (μ and

σ).These are assumed to be constant.

2. Value the portfolio today.(in our case 31.4.2008) in the usual way by using current value of

the stock price .

3. Sample once from the multivariate normal probability distribution to determine the value of

ε (for the purpose we have used a random number generator to obtain the random number ε

with the computer by using Microsoft Excel)

4. Determine the change in value of the security and the new value of the security using the

relation.


Where

∂s = Change in the stock price for one day

S = Price of stock today

μ = Expected return for period T

ε = Random number

∂ t = a small time interval



- 29 -

For our analysis ∂ t = 1 day

The expected return μ

μ = 1 ℓn * ST

T SO

ST = Stock price at time T

SO = Stock price at time Zero

5. Revalue the portfolio at the end of the day in the usual way.

6. Subtract the value calculated in step 2 from the value in steps to determine a sample change

in portfolio value ∂P.

7. Repeat steps (3) to (6) many times (in our case 500 times) to build up a probability

distribution for ∂P.

We have repeated the steps to obtain 500 sample values for ∂P. The VaR is calculated at

99%and95% confidence level.

The 500 simulated values of changes in portfolio values so obtained are then sorted in ascending

order.1-day VaR at 99% is the 5th worst outcome and 1-day VaR at 95% is the 25th worst

outcome.

Variance Covariance model

This model is termed as correlation models. It is based on J.P.Morgan’s Risk Metrics and

Modern Portfolio Theory (MPT).Using this, expected return or standard deviation can be

explained as function of volatility of return of each security in the portfolio and the covariance

between each securities position.

These are less flexible models which require normal probability distribution, using equation

based on Markowitz model. Inputs of data required are the variance and covariance of individual

assets in the portfolio. The equation gives a value of portfolio variance and whose square root is



- 30 -

the standard deviation of the portfolio .The VaR in this model is the multiple of standard

deviation depending on the required confidence level. At 95% confidence level, the VaR equals

to standard deviation. This method is used only to the portfolios that conform to normal

distribution.

Historical Simulation Method

This method is similar to the delta Normal method in that it also uses historical data of

asset returns and the exposure to these risk factors. The difference is that this return does not

represent an actual portfolio but rather reconstructs the history of a hypothetical portfolio using

the current position .both the methods would generate the same VAR if asset returns are all

normally distributed

This is also relatively simple .the drawback to this is that only one sample path is used for

simulation, which may not adequately represent future distributions.

Back Testing

Statistically perverse nature of the asset returns compel risk managers to perform back

testing. In back testing, the performance of VaR estimates of extreme losses with respect to

realized losses is examined. That is, it allows the risk manager to determine whether VaR

methods employed are adequate. Through back testing, the reasons for increase in actual losses

than those predicted by VaR can be found out.

Sometimes, the composition of the portfolio can drive actual losses beyond VaR.If selling an

asset in one day can be only accomplished only by accepting a large price- discount; the value

change caused by an adverse set of price changes should reflect this. Accordingly, bid prices

should be used for the computation of VaR, particularly if the risk manager believes that parts of

the portfolio will be liquidated after adverse price movements. For this reason, institutions will

often adjust their VaR for the liquidity of their positions.



- 31 -

CHAPTER 2

INDIAN CAPITAL MARKET-AN

OVERVIEW



- 32 -

Stock exchanges are intricacy inter-woven in the fabric of a nation's economic life. The history of

Indian capital markets spans back 200 years, around the end of the 18th century. It was at this

time that India was under the rule of the East India Company. In 1860-61 the American Civil

War broke out and cotton supply from United States of Europe was stopped; thus, the 'Share

Mania' in India begun. The number of brokers increased to about 200 to 250. However, at the end

of the American Civil War, in 1865, a disastrous slump began (for example, Bank of Bombay

Share which had touched Rs 2850 could only be sold at Rs.87)

At the end of the American Civil War, the brokers who thrived out of Civil War in 1874,

found a place in a street (now appropriately called as Dalal Street) where they would

conveniently assemble and transact business. In 1887, they formally established in Bombay, the

"Native Share and Stock Brokers' Association" (which is alternatively known as " The Stock

Exchange "). In 1895, the Stock Exchange acquired a premise in the same street and it was

inaugurated in 1899. Thus, the Stock Exchange at Bombay was consolidated The capital market

of India initially developed around Mumbai; with around 200 to 250 securities brokers

participating in active trade during the second half of the 19th century. . In 1887, an indenture

was executed and the Bombay Stock Exchange (BSE) was formally established as a society

named Native Share and Stock Brokers Association.

The effects of Industrial Revolution began to be felt in India by the dawn of 20th century.

After Independence, the Indian Government gave priority to infrastructure development

considering the urgency of proceeding with large scale industrial development,. Accordingly,

Industrial Finance Corporation was formed in 1948with the objective of providing financial

assistance to the industrial sector. In 1955, Industrial Credit and Investment Corporation of India

(ICICI) were set up for providing the capital market with underwriting facility. Establishment of

Life Insurance Corporation in 1956 was another landmark in the field of institutionalization of

the capital market. Apart from the insurance business it also invested in government securities.

An important development in company law took place when the government of India

promulgated the Companies Act, 1956 based on the recommendations of the company law

committee. This was the largest statute ever passed by the Parliament. Unit Trust of India (UTI)

was formed in 1964 for providing facilities of equity investment for small investors thereby

supplementing the efforts of institutions engaged in mobilizing the savings of the community.

Mutual fund scheme was first introduced in Indian by UTI in 1964. Industrial Development Bank



- 33 -

of India (IDBI) was also formed in 1964 as a subsidiary of Reserve bank of India (RBI) to

provide long term financial assistance to medium and large scale industries. As the apex

development bank of the country, IDBI has been vested with the responsibility of strengthening

the resources off the financial institutions including banks. The passing of Foreign Exchange

Regulation Act, 1973 limited the shareholding of foreign firms to 40%, if they were to be

recognized as Indian companies. For diluting their share holdings, many multinational companies

offered shares to the public at attractive rates.

During 1980s, debentures emerged as a powerful device for mobilizing funds in the

capital market. Also, many public sector undertakings came out with bonds. There was also an

impressive growth in the secondary market as ten stock exchanges were established in mid-

eighties. Moreover, several instruments like convertible debentures and mutual fund schemes

were offered to meet the expectations of emerging investors.

During eighties, however, many stock exchanges were established: Cochin Stock

Exchange (1980), Uttar Pradesh Stock Exchange Association Limited (at Kanpur, 1982), and

Pune Stock Exchange Limited (1982), Ludhiana Stock Exchange Association Limited (1983),

Gauhati Stock Exchange Limited (1984), Kanara Stock Exchange Limited (at Mangalore, 1985),

Magadh Stock Exchange Association (at Patna, 1986), Jaipur Stock Exchange Limited (1989),

Bhubaneswar Stock Exchange Association Limited (1989), Saurashtra Kutch Stock Exchange

Limited (at Rajkot, 1989), Vadodara Stock Exchange Limited (at Baroda, 1990) and recently

established exchanges - Coimbatore and Meerut. Thus, at present, there are totally twenty one

recognized stock exchanges in India excluding the Over The Counter Exchange of India Limited

(OTCEI) and the National Stock Exchange of India Limited (NSEIL).

The Indian stock markets till date have remained stagnant due to the rigid economic

controls. It was only in 1991, after the liberalization process that the India securities market

witnessed a flurry of IPOs serially. The market saw many new companies spanning across

different industry segments and business began to flourish .

The launch of the NSE (National Stock Exchange) and the OTCEI (Over the Counter Exchange

of India) in the mid-1990s helped in regulating a smooth and transparent form of securities

trading.

The stock market however received a dubbing in 1995-1996 onwards because of the

sudden erosion of the saving of the investors. The investor lost confidence in the securities

market and therefore the public issues dried up , thus ending of a golden era of public issues .

However the resource mobilization continued to grow this time through other channels like

bonds, mutual funds and more considerably through private placements.



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The regulatory body for the Indian capital markets was the SEBI (Securities and Exchange Board

of India). Another sea change that the security market has witnessed is the introduction of demat

trading in India. Now we have one of the best demat trading in the world, and almost 100%

trading at the bourses take place in demat mode only.The capital markets in India experienced

turbulence after which the SEBI came into prominence. The market loopholes had to be bridged

by taking drastic measures.

Trading Pattern Of The Indian Stock Market:-

Trading in Indian stock exchanges is limited to listed securities of public limited

companies. They are broadly divided into two categories, namely, specified securities (forward

list) and non-specified securities (cash list). Equity shares of dividend paying, growth-oriented

companies with a paid-up capital of at least Rs.50 million and a market capitalization of at least

Rs.100 million and having more than 20,000 shareholders are, normally, put in the specified

group and the balance in non-specified group.

Two types of transactions can be carried out on the Indian stock exchanges: (a) spot

delivery transactions "for delivery and payment within the time or on the date stipulated when

entering into the contract which shall not be more than 14 days following the date of the

contract" : and (b) forward transactions "delivery and payment can be extended by further period

of 14 days each so that the overall period does not exceed 90 days from the date of the contract".

The latter is permitted only in the case of specified shares. The brokers who carry over the out

standings pay carry over charges (can tango or backwardation) which are usually determined by

the rates of interest prevailing.

A member broker in an Indian stock exchange can act as an agent, buy and sell securities

for his clients on a commission basis and also can act as a trader or dealer as a principal, buy and

sell securities on his own account and risk, in contrast with the practice prevailing on New York

and London Stock Exchanges, where a member can act as a jobber or a broker only.

The nature of trading on Indian Stock Exchanges are that of age old conventional style of

face-to-face trading with bids and offers being made by open outcry. However, there is a great

amount of effort to modernize the Indian stock exchanges in the very recent times.

OVER THE COUNTER EXCHANGE OF INDIA (OTCEI)

The traditional trading mechanism ,which prevailed in the Indian stock exchanges,

resulted in much functional inefficiency such as absence of liquidity ,lack of transparency, undue

delay in settlement of transactions, fraudulent practices etc. with the objective of providing more

efficient services to investors, the country’s first electronic which facilitates ringless,scripless



- 35 -

trading was set up in 1992with the name Over the Counter Exchange Of India. It was sponsored

by the country’s premier financial institutions such as Unit Trust of India (UTI), Industrial Credit

and Investment Corporation of India (ICICI), Industrial Development Bank of India (IDBI) ,SBI

Capital Markets, Industrial Finance Corporation of India (IFCI), General Insurance Corporation

(GIC) and its subsidiaries and Canbank Financial services.

The exchange was set up to aid enterprising promoters in raising finance for new projects

in a cost effective manner and to provide investors with a transparent and efficient mode of

trading. The OTCEI has many novel features. It introduced screen based trading for the first time

in the Indian stock market. Trading takes place through a network of computers of over the

counter dealers located at several places, linked to a central OTC computer using tele -

communication links. All the activities of the OTC trading process are fully computerized.

Moreover, OTCEI is a national exchange having a country wide reach. OTCEI has an exclusive

listing in any other stock exchanges. For being listed in OTCEI the companies have to be

sponsored by members of OTCEI. It was the first exchange in the country to introduce the

practice of market making that is dealers in securities providing two way quotes (bid prices and

offer prices of securities)

Compared to the traditional Exchanges, OTC Exchange network has the following advantages:

OTCEI has widely dispersed trading mechanism across the country which provides

greater liquidity and lesser risk of intermediary charges.

Greater transparency and accuracy of prices is obtained due to the screen-based scrip less

trading.

Since the exact price of the transaction is shown on the computer screen, the investor gets

to know the exact price at which s/he is trading.

Faster settlement and transfer process compared to other exchanges.

In the case of an OTC issue (new issue), the allotment procedure is completed in a month

and trading commences after a month of the issue closure, whereas it takes a longer

period for the same with respect to other exchanges.



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NATIONAL STOCK EXCHANGE (NSE):-

With the liberalization of the Indian economy, it was found inevitable to lift the Indian

stock market trading system on par with the international standards. On the basis of the

recommendations of high powered Pherwani Committee, the National Stock Exchange was

incorporated in 1992 by Industrial Development Bank of India, Industrial Credit and Investment

Corporation of India, Industrial Finance Corporation of India, all Insurance Corporations,

selected commercial banks and others.

The National Stock Exchange of India Limited has genesis in the report of the High

Powered Study Group on Establishment of New Stock Exchanges. It recommended promotion of

a National Stock Exchange by financial institutions (FIs) to provide access to investors from all

across the country on an equal footing. Based on the recommendations, NSE was promoted by

leading Financial Institutions at the behest of the Government of India and was incorporated in

November 1992 as a tax-paying company unlike other stock exchanges in the country. On its

recognition as a stock exchange under the Securities Contracts (Regulation) Act, 1956 in April

1993, NSE commenced operations in the Wholesale Debt Market (WDM) segment in june 1994.

The following years witnessed rapid development of Indian capital market with

introduction of internet trading, Exchange traded funds (ETF), stock derivatives and the first

volatility index India VIX in April2008, by NSE.

August 2008 saw introduction of Currency derivatives in India with the launch of Currency

Futures in USD INR by NSE. Interest Rate Futures was introduced for the first time in India by

NSE on 31st August 2009, exactly after one year of the launch of Currency Futures.

The National Stock Exchange (NSE) is India's leading stock exchange covering various

cities and towns across the country. NSE was set up by leading institutions to provide a modern,

fully automated screen-based trading system with national reach. The Exchange has brought

about unparalleled transparency, speed & efficiency, safety and market integrity. It has set up

facilities that serve as a model for the securities industry in terms of systems, practices and

procedures.

NSE has played a catalytic role in reforming the Indian securities market in terms of

microstructure, market practices and trading volumes. The market today uses state-of-art

information technology to provide an efficient and transparent trading, clearing and settlement



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mechanism, and has witnessed several innovations in products & services viz. demutualization of

stock exchange governance, screen based trading, compression of settlement cycles,

dematerialization and electronic transfer of securities, securities lending and borrowing,

professionalization of trading members, fine-tuned risk management systems, emergence of

clearing corporations to assume counterparty risks, market of debt and derivative instruments and

intensive use of information technology.

STOCK MARKET:-

A stock market is a market for the trading of shares, debentures, derivatives and other

instruments of different companies listed on different Stock Exchanges.

Although common, the term 'the stock market' is a somewhat abstract concept for the mechanism

that enables the trading of company stocks. It is also used to describe the totality of all stocks,

especially within a country, for example in the phrase "the stock market was up today", or in the

term "stock market bubble".It is distinct from a stock exchange, which is an entity (a corporation

or a mutual organization) in the business of bringing buyers and sellers of stocks together.

Trading:-

Participants in the stock market range from small individual stock investor to large hedge

fund traders. Their orders usually end up with a professional at a stock exchange, who executes

an order.

Most stocks are traded on exchanges, which are places where buyers and sellers meet and

decide on a price. Some exchanges are physical locations where transactions are carried out on a

transaction floor, by a method known as open outcry. This type of auction is used in stock

exchanges and commodity exchanges where traders may enter "verbal" bids and offers

simultaneously. The other type of exchange is a virtual kind, composed of a network of

computers where trades are made electronically via traders at computer terminals.

Actual traders are based on an auction market paradigm where a potential buyer bids a

specific price for a stock and a potential seller quotes a specific price for the stock. (Buying or

selling at market means one will accept any bid or ask price for the stock.) When the bid and ask

prices match, a sale takes place on a first come first serve basis if there are multiple bidders or

askers at a given price.

The purpose of a stock exchange is to facilitate the exchange of securities between buyers

and sellers, thus providing a marketplace (virtual or real). Just imagine how difficult it would be

to sell the shares (and what a disadvantage one would be at with respect to the buyer) if one had

to call around trying to locate a buyer, as when selling a house. Really, a stock exchange is



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nothing more than a super-sophisticated farmers' market providing a meeting place for buyers

and sellers.

The New York Stock Exchange is a physical exchange, where much of the trading is done

face-to-face on a trading floor. This is also referred to as a "listed" exchange (because only stocks

listed within the exchange may be traded).

The NASDAQ is a virtual (listed) exchange, where all of the trading is done by

computers. The process is similar to the above, in that the seller provides an asking price and the

buyer provides a bidding price. However, buyers and sellers are electronically matched. One or

more NASDAQ market makers will always provide a bid and ask price at which they will always

purchase or sell 'their' stock.

Major Participants in the Indian Stock Market:-

There are 23 stock exchanges in India. Among them two are national level stock exchanges

namely Bombay Stock Exchange (BSE) and National Stock Exchange of India (NSE). The rest

21 are Regional Stock Exchanges (RSE). Even though there are 23 stock Exchanges in India,

increase in turnover took place mostly in the large exchanges at the expense of smaller ones.

Bombay Stock Exchange:

A very common name for all traders in the stock market, BSE, stands for Bombay Stock

Exchange. The Bombay Stock Exchange, established in 1875, as “The Native Share and Stock

Brokers Association” is the oldest in Asia, even older than the Tokyo Stock Exchange, founded

in 1878 until the establishment of National Stock Exchange; it was considered the premier stock

exchange and trend setter in the country. Among the 23 stock exchanges recognized by the

Government of India under the Securities Contract (Regulation) Act, 1956, it was the first one to

be recognized and the only one that has been granted the privilege of permanent registration. In

1994, the Bombay Stock Exchange faced competition for the first time when National Stock

Exchange was formed with completely automated trading system. It rose to the challenges of

technology and in 1995, put the automated trading programming and transferred over 5000 scrips

from floor to screen. The Bombay On-Line Trading (BOLT) network has been expanded to

centers outside Mumbai.

Market returns on equity shares as well as volatility in prices are measured through share price

indices. In India, Bombay Stock Exchange 30 shares Sensitive Index (BSE SENSEX) is one of

the popular benchmarks of share prices.



- 39 -

BSE Vision:-

The vision of the Bombay Stock Exchange is to "Emerge as the premier Indian stock

exchange by establishing global benchmarks."

Regional Stock Exchanges (RSE)

Ahmedabad Stock Exchange

Bangalore Stock Exchange

Bhubaneshwar Stock Exchange

Calcutta Stock Exchange

Cochin Stock Exchange

Coimbatore Stock Exchange

Delhi Stock Exchange

Guwahati Stock Exchange

Jaipur Stock Exchange

Ludhiana Stock Exchange

Madhya Pradesh Stock Exchange

Madras Stock Exchange

Magadh Stock Exchange

Mangalore Stock Exchange

Meerut Stock Exchange

OTC Exchange Of India

Pune Stock Exchange

Saurashtra Kutch Stock Exchange

Uttar Pradesh Stock Exchange

The Regional Stock Exchanges started clustering from the year 1894, when the first RSE,

the Ahmedabad Stock Exchange (ASE) was established. In the year 1908, the second in the

series, Calcutta Stock Exchange (CSE) came into existence. During the early sixties, there were

only few recognized RSEs in India namely Calcutta, Madras, Ahmedabad, Delhi, Hyderabad and

Indore. The number remained unchanged for the next two decades. 1980s was the turning point

and many RSEs were incorporated. The latest is Coimbatore Stock Exchange and Meerut Stock

Exchange.

http://www.surfindia.com/finance/ahmedabad-stock-exchange.html

http://www.surfindia.com/finance/bangalore-stock-exchange.html

http://www.surfindia.com/finance/bhubaneshwar-stock-exchange.html

http://www.surfindia.com/finance/calcutta-stock-exchange.html

http://www.surfindia.com/finance/cochin-stock-exchange.html

http://www.surfindia.com/finance/coimbatore-stock-exchange.html

http://www.surfindia.com/finance/delhi-stock-exchange.html

http://www.surfindia.com/finance/guwahati-stock-exchange.html

http://www.surfindia.com/finance/jaipur-stock-exchange.html

http://www.surfindia.com/finance/ludhiana-stock-exchange.html

http://www.surfindia.com/finance/madhya-pradesh-stock-exchange.html

http://www.surfindia.com/finance/madras-stock-exchange.html

http://www.surfindia.com/finance/magadh-stock-exchange.html

http://www.surfindia.com/finance/mangalore-stock-exchange.html

http://www.surfindia.com/finance/meerut-stock-exchange.html

http://www.surfindia.com/finance/otc-exchange-india.html

http://www.surfindia.com/finance/pune-stock-exchange.html

http://www.surfindia.com/finance/kutch-stock-exchange.html

http://www.surfindia.com/finance/uttar-pradesh-stock-exchange.html



- 40 -

Financial Market:

Financial market is the market where financial securities like stocks and bonds and

commodities like valuable metals are exchanged at efficient market prices. Here by efficient

market prices we mean the unbiased price that reflects belief at collective speculation of all

investors about the future prospect. Markets work by placing many interested buyers and sellers

in one "place", thus making it easier for them to find each other.

The trading of stock and bonds in the Financial Market can take place directly between

buyers and sellers or by the medium of stock exchange .Financial markets can be domestic or

international. Financial market is constituted mainly with money markets and capital markets. It

also include other markets like bond market, stock market, commodity market, derivative market,

futures market, insurance market, foreign exchange market etc..

The financial instruments that have short or medium term maturity periods are dealt in the

money market whereas the financial instruments that have long term maturity periods are dealt in

the capital market. Here we are mainly focusing on money market and capital market as they are

the major constituents in the financial market system.

Money Market

Money market is the market for short term financial assets with maturities of one year or

less. Treasury bills, commercial bills, commercial papers,etc. are the short term securities traded

in the money market . these instruments being close substitutes for money ,the market for their

trading is known as money market.

Money market is the main source of working capital funds for business and industry. It

provides a mechanism for evening out short term surpluses and deficits. The short term

requirements of borrowers can be met by the creation of money market securities, which can be

purchased by lenders with short term surpluses to park their funds for short durations. In India,

the money market has a narrow base with limited number of participants who are mostly

financial institutions.

Capital Market

Capital market is the market segment where securities with maturity than one year are

bought and sold. The market where investment funds like bonds, equities and mortgages are

traded is known as the capital market. The primal role of the capital market is to channelize

investments from investors who have surplus funds to the ones who are running a deficit. The

capital market offers both long term and overnight funds. The different types of financial



- 41 -

instruments that are traded in the capital markets are equity instruments, credit market

instruments, insurance instruments, foreign exchange instruments, hybrid instruments and

derivative

Capital markets may be classified as primary markets and secondary markets. In primary

markets, new stock or bond issues are sold to investors via a mechanism known as underwriting.

In the secondary markets, existing securities are sold and bought among investors or traders,

usually on a securities exchange, over-the-counter, or elsewhere.

Primary Market:

The market mechanism for buying and selling of new issues of securities is known as

primary market. This market is also known as new issue market as it deals in new issues of

securities. Companies, governments or public sector institutions can obtain funding through the

sale of a new stock or bond issue. The process of selling new issues to investors is called

underwriting. In the case of a new stock issue, this sale is an initial public offering (IPO).

Secondary Market:-

The secondary market deals with securities which have already been issued and are

owned by investors, both individual and institutional. These may be traded between investors.

The buying and selling of securities already issued and outstanding takes place in stock

exchanges. Hence, stock exchanges constitute the secondary market in securities. For the general

investor, the secondary market provides an efficient platform for trading of his securities. For the

management of the company, Secondary equity markets serve as a monitoring and control

conduit—by facilitating value-enhancing control activities, enabling implementation of

incentive-based management contracts, and aggregating information (via price discovery) that

guides management decision.

The main financial products dealt in secondary market includes:

Equity: The ownership interest in a company of holders of its common and preferred

stock. The various kinds of equity shares are as follows –

Equity Shares: An equity share, commonly referred to as ordinary share also represents

the form of fractional ownership in which a shareholder, as a fractional owner, undertakes

the maximum entrepreneurial risk associated with a business venture. The holders of such

shares are members of the company and have voting rights. A company may issue such

shares with differential rights as to voting, payment of dividend, etc.

http://en.wikipedia.org/wiki/Primary_market

http://en.wikipedia.org/wiki/Secondary_market

http://en.wikipedia.org/wiki/Underwriting

http://en.wikipedia.org/wiki/Securities_exchange

http://en.wikipedia.org/wiki/Over-the-counter_(finance)

http://en.wikipedia.org/wiki/Funding

http://en.wikipedia.org/wiki/Underwriting

http://en.wikipedia.org/wiki/Initial_public_offering



- 42 -

Rights Issue/ Rights Shares: The issue of new securities to existing shareholders at a

ratio to those already held.

Bonus Shares: Shares issued by the companies to their shareholders free of cost by

capitalization of accumulated reserves from the profits earned in the earlier years.

Preferred Stock/ Preference shares: Owners of these kinds of shares are entitled to a

fixed dividend or dividend calculated at a fixed rate to be paid regularly before dividend

can be paid in respect of equity share. They also enjoy priority over the equity

shareholders in payment of surplus. But in the event of liquidation, their claims rank

below the claims of the company’s creditors, bondholders / debenture holders.

Cumulative Preference Shares: A type of preference shares on which dividend

accumulates if remains unpaid. All arrears of preference dividend have to be paid out

before paying dividend on equity shares.

Cumulative Convertible Preference Shares: A type of preference shares where the

dividend payable on the same accumulates, if not paid. After a specified date, these

shares will be converted into equity capital of the company.

Participating Preference Share: The right of certain preference shareholders to

participate in profits after a specified fixed dividend contracted for is paid. Participation

right is linked with the quantum of dividend paid on the equity shares over and above a

particular specified level.

Security Receipts: Security receipt means a receipt or other security, issued by a securitization

company or reconstruction company to any qualified institutional buyer pursuant to a scheme,

evidencing the purchase or acquisition by the holder thereof, of an undivided right, title or

interest in the financial asset involved in securitization.

Government securities (G-Secs): These are sovereign (credit risk-free) coupon bearing

instruments which are issued by the Reserve Bank of India on behalf of Government of India, in

lieu of the Central Government's market borrowing programme. These securities have a fixed

coupon that is paid on specific dates on half-yearly basis. These securities are available in wide

range of maturity dates, from short date (less than one year) to long date (up to twenty years).

Debentures: Bonds issued by a company bearing a fixed rate of interest usually payable half

yearly on specific dates and principal amount repayable on particular date on redemption of the

debentures. Debentures are normally secured/ charged against the asset of the company in favor

of debenture holder.

Bond: A negotiable certificate evidencing indebtedness. It is normally unsecured. A debt security

is generally issued by a company, municipality or government agency. A bond investor lends



- 43 -

money to the issuer and in exchange, the issuer promises to repay the loan amount on a specified

maturity date. The issuer usually pays the bond holder periodic interest payments over the life of

the loan. The various types of Bonds are as follows;

Zero Coupon Bond: Bond issued at a discount and repaid at a face value. No periodic

interest is paid. The difference between the issue price and redemption price represents

the return to the holder. The buyer of these bonds receives only one payment, at the

maturity of the bond.

Convertible Bond: A bond giving the investor the option to convert the bond into equity

at a fixed conversion price.

Commercial Paper: A short term promise to repay a fixed amount that is placed on the market

either directly or through a specialized intermediary. It is usually issued by companies with a

high credit standing in the form of a promissory note redeemable at par to the holder on maturity

and therefore, doesn’t require any guarantee. Commercial paper is a money market instrument

issued normally for tenure of 90 days.

Treasury Bills: Short-term (up to 91 days) bearer discount security issued by the Government

as a means of financing its cash requirements.

Future of the capital market

In the liberalized economic environment, the capital market is all set to play a highly critical role

in the process of economic development. The Indian capital market has to arrange funds to meet

the financial needs of both domestic and foreign resources. What is more critical is that the

changed environment is characterized by cutthroat competition. Ability of enterprises to mobilize

funds at cheap cost will determine their competitiveness vis-à-vis their rivals.



- 44 -

CONCLUSION:

Over the last few years, there has been a rapid change in the Indian securities market especially

in the secondary market. Advanced technology and online-based transactions have modernized

the stock exchanges. In terms of the number of companies listed and total market capitalization,

the Indian equity market is considered large relative to the country’s stage of economic

development. The debt market, however, is almost nonexistent in India even though there has

been a large volume of Government bonds traded. Banks and financial institutions have been

holding a substantial part of these bonds as statutory liquidity requirement. Securities market

development has to be supported by overall macroeconomic and financial sector environments. If

an investor has a clear understanding of the India financial market, then formulating investing

strategies and tips would be easier. Unless stock markets provide professionalized service, small

investors and foreign investors will not be interested in capital market operations. And capital

market being one of the major source of long-term finance for industrial projects, India cannot

afford to damage the capital market path. Further liberalization of interest rates, reduced fiscal

deficits, fully market-based issuance of Government securities and a more competitive banking

sector will help in the development of a sounder and a more efficient capital market in India.



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CHAPTER 3

COCHIN STOCK EXCHANGE LTD-

PROFILE



- 46 -

COCHIN STOCK EXCHANGE LTD. is one of the premier Stock Exchanges in India,

established in the year 1978. The exchange had a humble beginning with just 5 companies listed

in 1978 -79, and had only 14 members. Today the Exchange has more than 508 members and

240 listed companies. In 1980 the Exchange computerized its offices. In order to keep pace with

the changing scenario in the capital market, CSE took various steps including trading in

dematerialized shares. CSE introduced the facility for computerized trading - "Cochin Online

Trading (COLT)" on March 17, 1997. CSE was one of the promoters of the "Interconnected

Stock Exchange of India (ISE)". The objective was to consolidate the small, fragmented and less

liquid markets into a national level integrated liquid market. With the enforcement of efficient

margin system and surveillance, CSE has successfully prevented defaults. Introduction of fast

track system made CSE the stock exchange with the shortest settlement cycle in the country at

that time. By the dawn of the new century, the regional exchanges faced a serious challenge from

the NSE & BSE. To face this challenge CSE promoted a 100% subsidiary called the "Cochin

Stock Brokers Ltd. (CSBL)" and started trading in the National Stock Exchange (NSE) and

Bombay Stock Exchange (BSE).

CSBL is the first subsidiary of a stock exchange to get membership in both NSE & BSE.

CSBL also became a depository participant in the Central Depository Services Ltd. The CSE has

been playing a vital role in the economic development of the country in general, and Kerala in

particular and striving hard to achieve the following goals:

Providing investors with high level of liquidity whereby the cost and time involved in the

entry into and exit from the market are minimized.

Bringing in high tech solutions and make all operations absolutely transparent.

Building infrastructure for capital market by turning CSE into a financial super market.

Serve the investors of the region.

Professional stock broking and investment management.

Imparting Capital Market knowledge to all intermediaries on a continuous basis

The Cochin Stock Exchange is directly under the control and supervision of Securities &

Exchange Board of India (the SEBI), and is today a demutualized entity in accordance with the

Cochin Stock Exchange (Demutualization) Scheme, 2005 approved and notified by SEBI on

29th of August 2005. Demutualization essentially means de-linking and separation of ownership

and trading rights and restructuring the Board in accordance with the provisions of the



- 47 -

scheme. The Exchange has been demutualised and the notification thereof published in the

Gazette

MANAGEMENT OF CSE LTD

The policy decisions of the CSE are taken by the Board of Directors. The Board is

constituted with 12 members of whom less than one-fourth are elected from amongst the trading

member of CSE, another one fourth are Public Interest Directors selected by SEBI from the

panel submitted by the Exchange and the remaining are Shareholder Directors. The Board

appoints the Executive Director who functions as an ex-officio member of the Board and takes

charge of the administration of the Exchange.

Fig.No:3.1

Organisation Structure

Management - Board of Directors

The Exchange is professionally managed, under the overall direction of the Board of

Directors. The Board consists of eminent professionals from fields such as judiciary,

administration and management, who are known as Public Representative Directors. The

composition of the Board is such that 75% of the total strength of the Board consists of



- 48 -

Public Representative Directors and Govt. And SEBI nominee Directors and the balance 25%

are represented by the Brokers of the Exchange.

DEPARTMENTS

Legal:-

Guided by the Officer-Legal, the Legal Department is primarily responsible for advising

the management of the merits and demerits of legal issues involving the Exchange. The

department consistently monitors the compliance parameters in terms of the Companies Act,

SEBI Act, Securities Contracts Regulation Act and other related statutes. Listing Guidelines and

related criteria stipulated by SEBI, and the rules, regulations, directives and circulars issued by

SEBI with regard to trading in the Capital Market are consistently scrutinized and necessary

directions are given to the concerned departments to ensure strict and continued compliance.

Relevant developments are brought to the notice of the members and the investing public.

Officer-Legal is the Compliance Officer as per the provisions of SEBI regulations and also

functions as Secretary to the Board of Directors. Other major activities undertaken by the

department relate to Investor Grievance Service, Arbitration and Resolution of issues pertaining

to declared defaulters.

Systems:-

The Systems Department is the heart of the various operations of CSE. The department

provides the necessary technical support for screen based trading and the computerized

functioning of all the other departments.

The activities of the department include: -

Developments of software needed for the functions of the exchange.

Maintenance of Multex software, which enables online trading with NSE and BSE.

Maintenance of an effective network of computers for the smooth functioning of the

exchange.

Providing the necessary services to the Settlement and Surveillance Departments.

The support for maintenance of depository participants’ accounts with the CSBL DP.

Membership:-

The Membership Department screens applications from prospective members to ensure

that they are eligible to be members of the Exchange as per provisions of the Securities Contracts

Regulation Act. It is also verified whether they are ‘Fit and Proper’ persons eligible to be

members as per the SEBI (Criteria for Fit and Proper persons) Regulation 2004. The eligible



- 49 -

applications are processed and forwarded to SEBI for the purpose of obtaining registration with

SEBI. The department continuously follows up the status of the applications with SEBI and

provides necessary data if any required by SEBI. The members are informed of their fee liability

as and when information in this regard is obtained from SEBI. The Membership Department also

assists SEBI by ensuring proper delivery of notices and letters issued by SEBI to the concerned

members. The changes in status and constitution of the Brokers are sent for approval to the

Governing Board of the Exchange and thereafter to SEBI and Members are given necessary

directions wherever required. Change in address and contact information are updated in the

Finance and Accounting System and SEBI intimated.

Settlement:-

Settlement Department is a key department of the Exchange, dealing with cash and

securities. It assists the brokers in settling the matters related to their pay-in and payout, recovery

of dues and settling issues related to bad deliveries. This department is headed by a Deputy

Manager assisted by two Senior Officers who take care of the operations involved in the

settlement activities in CSE. The Exchange follows the T+2 settlement system.

Listing:-

The Listing Department guides prospective companies desirous of being listed on the

Exchange by providing the knowledge base and information on the statutory requirements that

have to be complied with. The major functions undertaken by the department include post-listing

monitoring and compliance with the listing agreement, monitoring the listing agreements and

reviewing the provisions of listing agreement from time to time with specific reference to SEBI

Regulations/Circulars that are in force. The department also ensures diligence in scrutinizing

listing applications and adhering to the Listing Norms.

Compliance Monitoring is carried out with specific emphasis on the following clauses in

the Listing Agreement.

Clauses 15/16 - Short/non intimation of BC/RD

Clause 19 – Intimation of Board Meeting including advance notice wherever required

Clause 20- Outcome of Board Meeting

Clause 24 – In-principle approvals

Clause 31 – Annual Reports



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Clause 32 – Name Change, Cash Flow, Consolidated Financial Statement, Related Party

Disclosures etc.

Clause 35 – Quarterly submission of Shareholding Pattern.

Clause 36 – Material Price sensitive Information

Clause 40 - Continuous Listing requirements

Clause 41 – Financial Results and Limited Review Reports

Clause 47 – Appointment of Compliance Officer

The department also performs the processing of the documents submitted by companies

on new listings/additional listings and provides them with the listing approval/trading permission

and also ensures that listing fee/processing fee is paid at the stipulated time.

Marketing:-

The Marketing Department interacts with the brokers of the exchange trading both within

the state and outside and collects their opinions and suggestions. These are brought to the notice

of the Committee constituted for the purpose and decisions of the committee are placed for

approval of the Governing Board of the Exchange .The efforts are aimed at improving the quality

and efficiency of the service offered. In addition, the department conducts extensive surveys and

campaigns in remote areas and where necessary organizes awareness programmes about capital

markets. Experts with sufficient experience in the trade brief the participants and address their

queries. Talk shows and interviews are conducted on television channels, clippings are displayed

in theatres all with a view to increase public awareness and motivate their interest in the Capital

Markets .The marketing wing also coordinates the off campus programmes of the CSE Institute

and organizes regular classes at authorized centers after verifying the availability of suitable

infrastructure and facilities.

Finance:-

The Finance Department controls the financial transactions of the Exchange and is the

life line of the organization. The department is headed by a Finance Officer.

The activities of the department include:-

Fund Management

Interaction with bankers

Maintaining general accounts of the Exchange

Preparation of various financial statements.

Maintaining payrolls and cash register.



- 51 -

Coordinating accounting transactions of different branches and departments.

Taxation

Budgeting and Expense research.

Maintenance of internal control system.

Liaison with external and internal auditors

Annual Report Generation

Procedure for Acquiring Membership

Transactions pertaining to the Capital market can be carried out only through a broker or

a sub-broker registered with SEBI. A Broker is a member of a recognized Stock Exchange

permitted to trade on the Screen Based Trading System of different Exchanges. A Member has to

be qualified for membership of a recognized Stock Exchange as per the provisions of Section 8

of the Securities Contracts Regulation Act. In addition eligibility as per the stipulations in the

SEBI (Criteria for fit and proper persons) Regulation 2004 is also a pre-requisite.

Trading Membership Selection Committee has been constituted by the Governing Board

and entrusted with the specific responsibility of screening applications for admission to trading

membership of the Exchange. Persons admitted as trading Members of Exchange are required to

maintain the Base Minimum Capital as may specified by SEBI from time to time irrespective of

whether they choose to exercise their right to trade or not. At present the Base Minimum Capital

required to be maintained is Rs. 2 lakhs. In addition, annual subscription and contribution to the

Investor Protection Fund has to be paid by Members. Individuals – Rs. 2,520/- and Corporates

Rs. 6,120/- One time admission fee as may be prescribed by the Governing Board will also have

to be remitted.

Investor Grievance Services at CSE Ltd

The Cochin Stock Exchange remains committed to the protection of investor interests.

The complaints received from the investors are taken up with the companies/brokers concerned

and wherever necessary with the enforcement authorities for redress.

Resolution of complaints proceeds in two phases:-

1. At the preliminary stage when the Exchange receives a complaint, the concerned

broker/company is requested to settle the same. A copy of the complaint is sent to the concerned

broker/company.

2. If the issue is still not resolved, it is referred to the Grievance Committee constituted by

the Exchange. Notice is issued to both parties. Opportunity to adduce evidence and privilege of



- 52 -

detailed and fair hearing is given to the parties’ .After weighing the evidence/documents on

record and taking into consideration the arguments raised, a decision is given on merits which are

communicated to the parties. If the concerned broker/company does not comply with the

decision, the matter is referred to the Board Of Directors which initiates necessary action to

ensure compliance.

Complaints against Defaulters:-

All claims and complaints against a trading member who is declared a defaulter is dealt

with by the Committee for Settlement of Claims against Defaulters. Tenable claims are adjudged

on merits after verification of records and a report is submitted to the Board Of Directors for

taking the final decision. It may however be noted that belated claims will not be entertained.

Claims against Defaulter by a Trading Member:-

Within such time of the declaration of a defaulter every trading member carrying on

business on the Exchange shall, be required to compare with the Committee for Settlement of

Claims Against Defaulters his accounts with the defaulter / deemed defaulter, as provided in the

Rules and Procedure, or furnish a statement of such accounts with the defaulter / deemed

defaulter in such form or form as the Committee for Settlement of Claims Against Defaulters

may prescribe or render a certificate that he has no such account.

Claims against Defaulter by Investors/Clients:-

Within the time frame decided by the Executive Director, on the declaration of defaulter /

deemed defaulter, every person who had a transaction / dealing with the defaulter / deemed

defaulter in relation to and/ or in connection with the stock broking business, and has to recover

any amount and / or securities, shall be required to lodge a claim in the prescribed form, together

with supporting papers / proof as may be specified in the Notice published in the daily newspaper

by the Exchange /Clearing Corporation.



- 53 -

CHAPTER 4

DATA ANALYSIS PART I



- 54 -

Security analysis:

Security analysis is the initial phase of the portfolio management process. This step consists of

examining the risk return characteristics of invidual securities. For the purpose of analysis ten

securities are selected and the return, risk and risk adjusted rate of return are determined.

Risk and return of securities:

The return of the securities is measured by the arithmetic mean of the security’s return. The risk

of the security is measured by the variance or standard deviation of its securities. The risk

adjusted rate of return of the security is the excess return per unit of risk, the excess return being

the difference between the security return and the risk free rate of return. For our analysis the

risk free return is taken as 8.1%



- 55 -

4.1:Return of the Securities

The Table No: 4.1 shows the corresponding returns of the securities and the graphical

representation of the same is given below.

TABLE No: 4.1

Showing the Return of Securities

COMPANY RETURN(%) RANK

AMBUJACEMENT 15.37 14

ASIANPAINTS 32.25 2

BHARATIAIRTEL 18.59 7

CIPLA 15.50 13

HCL 33.74 1

HDFC 23.27 6

HUL 17.53 10

ITC 15.70 11

LUPINLTD 26.79 5

M&M 18.59 8

MARUTHI 15.58 12

MINDTREE 29.25 4

ONGC 9.86 15

SUNTVLTD 17.20 9

YESBANK 32.23 3

Source: Computed from Secondary data.

Fig.No:4.1

Showing Return of Securities

From the above table and chart it can be seen that the security HCL is giving maximum return of

33.74% and ONGC has minimum return of 9.86%.



- 56 -

4.2:Risk of the Securities

The Table No:4.2 shows the corresponding risk of the securities and the graphical representation

of the same is given below.

TABLE No: 4.2

Showing the Risk of Securities

COMPANY RISK(%)

AMBUJACEMENT 39.94

ASIANPAINTS 26.82

BHARATIAIRTEL 48.82

CIPLA 29.19

HCL 45.49

HDFC 34.01

HUL 27.50

ITC 36.50

LUPINLTD 48.39

M&M 48.82

MARUTHI 35.85

MINDTREE 44.30

ONGC 34.06

SUNTVLTD 49.07

YESBANK 50.50

Source: Computed from secondary data

Fig No: 4.2

Showing Return of Securities

From the above table and chart it can be seen that the security YES BANK is having maximum

risk of 50.50%)and ASIAN PAINTS is having minimum risk of 26.82(%)



- 57 -

BETA

The beta value indicates the measure of systematic risk of security. Beta describes the

relationship between the stock return and market index return. Beta of security may be positive or

negative. If beta is one, one percent change in the market index return causes exactly one percent

changes in the stock return. It indicates that the stock moves in tandem with the market. If the

portfolio is efficient, the beta measures the systematic risk efficiently.

N∑XY-∑X∑Y

βi =

N∑X2-(∑X) 2

N = Number of Observation =750

Y = Current Stock Price – Yesterday’s Stock Price

× 100

Yesterday’s Stock Price

X = Current Market Index- Yesterday’s Market Index ×100 Yesterday’s Market Index



- 58 -

4.3:Beta of the securities.

The Table No: 4.3 shows the beta of the securities. The graphical representation of the same is

given below.

TABLE No: 4.3

Showing the Beta of Securities

COMPANY ∑Y ∑X ∑X2 ∑XY (∑X)2 BETA(β)

AMBUJACEMENT 76.16 36.06 3527.56 2976.32 1300.476 0.84

ASIANPAINTS 159.85 36.06 3527.56 988.80 1300.476 0.28

BHARATIAIRTEL 92.14 36.06 3527.56 3755.48 1300.476 1.06

CIPLA 76.80 36.06 3527.56 1764.90 1300.476 0.50

HCL 167.24 36.06 3527.56 3618.89 1300.476 1.02

HDFC 115.31 36.06 3527.56 3370.87 1300.476 0.95

HUL 86.87 36.06 3527.56 1480.64 1300.476 0.42

ITC 77.80 36.06 3527.56 1993.14 1300.476 0.56

LUPINLTD 132.77 36.06 3527.56 1564.20 1300.476 0.44

M&M 92.14 36.06 3527.56 3755.48 1300.476 1.06

MARUTHI 77.21 36.06 3527.56 2559.31 1300.476 0.73

MINDTREE 144.99 36.06 3527.56 1638.63 1300.476 0.46

ONGC 48.88 36.06 3527.56 2814.77 1300.476 0.80

SUNTVLTD 85.24 36.06 3527.56 2654.71 1300.476 0.75

YESBANK 159.72 36.06 3527.56 4671.52 1300.476 1.32

Source: Computed from secondary data.

Fig. No: 4.3

Showing Beta of Securities

From the above table and graph it can be seen that YES BANK has the maximum beta value,

which means maximum sensitivity to market (1.32). The minimum sensitivity to market is for

ASIAN PAINTS (0.28).



- 59 -

ALPHA

The alpha value indicates the extra return earn by the stock over and above the market

return. Alpha measures the unsystematic risk of security.

Return of stock = Alpha + (Beta ×Market Return per Year)

Ri = αi+ (βi×Rm)

So

Alpha (αi) = Ri-( βi×Rm)

Where,

αi - Alpha of the security

Ri - return of the security

βi - Beta of the security

Rm - Return of the market



- 60 -

4.4: Alpha of the securities.

The Table No: 4.4 shows the alpha of the securities. The graphical representation of the same is

given below.

TABLE No: 4.4

Showing the Alpha of Securities

COMPANY Ri βI Rm ALPHA(αi)

AMBUJACEMENT 15.37 0.84 7.27 9.23

ASIANPAINTS 32.25 0.28 7.27 30.23

BHARATIAIRTEL 18.59 1.06 7.27 10.85

CIPLA 15.50 0.50 7.27 11.86

HCL 33.74 1.02 7.27 26.29

HDFC 23.27 0.95 7.27 16.32

HUL 17.53 0.42 7.27 14.48

ITC 15.70 0.56 7.27 11.59

LUPINLTD 26.79 0.44 7.27 23.57

M&M 18.59 1.06 7.27 10.85

MARUTHI 15.58 0.73 7.27 10.31

MINDTREE 29.25 0.46 7.27 25.89

ONGC 9.86 0.80 7.27 4.06

SUNTVLTD 17.20 0.75 7.27 11.73

YESBANK 32.23 1.32 7.27 22.61

Fig No: 4.4

Showing Alpha of Securities

ASIAN PAINTS has the maximum Alpha 30.23 indicating that it has maximum extra return and

ONGC has the minimum Alpha 4.06 which indicate its earning is below market return.



- 61 -

DECOMPOSITION OF TOTAL RISK OF SECURITIES

The total risk of security can be resolved in to two components; the systematic or

market risk, which cannot be diversified, and the unsystematic or specific risk, which can be

diversified by construction of the portfolio. An investor would be interested in knowing these

two risks of the security in order to plan his portfolio. For the purpose of the analysis the

systematic and unsystematic risk of the securities are measured by using Sharpe’s single index

model. According to Sharpe index model:

Systematic risk =β12*

2 m

Unsystematic risk = 2 -β

1

2*

2 m



- 62 -

4.5: Systematic risk of the securities

The Table No: 4.5 shows the systematic risk of the securities. The graphical representation of the

same is given below.

TABLE No: 4.5

Showing the Systematic Risk of Securities

COMPANY βi2 σi

2 σm2

Systematic Risk(βi2 x

σm2)

AMBUJACEMENT 0.71 1595.54 712.14 506.51

ASIANPAINTS 0.08 719.11 712.14 55.46

BHARATIAIRTEL 1.13 2383.77 712.14 806.46

CIPLA 0.25 852.11 712.14 177.92

HCL 1.05 2069.39 712.14 747.92

HDFC 0.91 1156.39 712.14 649.37

HUL 0.18 755.99 712.14 125.11

ITC 0.32 1332.03 712.14 226.97

LUPINLTD 0.20 2341.89 712.14 139.42

M&M 1.13 2383.77 712.14 806.46

MARUTHI 0.53 1284.87 712.14 374.42

MINDTREE 0.21 1962.88 712.14 152.97

ONGC 0.64 1159.83 712.14 453.23

SUNTVLTD 0.57 2407.79 712.14 402.81

YESBANK 1.75 2550.71 712.14 1247.17


Fig No: 4.5

Showing Systematic Risk of Securities

Systematic risk or non-diversifiable risk is the component of the total risk, which cannot be

diversified. From the above table it is clear that YESBANK has the maximum systematic risk

1247.17% and ASIANPAINTS has minimum systematic risk 55.46%.



- 63 -

4.6: Unsystematic risk of the securities

The Table No: 4.6 shows the unsystematic risk of the securities. The graphical representation of

the same is given below.

TABLE No: 4.6

Showing the unsystematic Risk/residual variance of Securities

COMPANY βi2 σi

2 σm2

Unsystematic Risk(σei2)=σi2-

(βi2*σm

2)

AMBUJACEMENT 0.71 1595.54 712.14 1089.03

ASIANPAINTS 0.08 719.11 712.14 663.64

BHARATIAIRTEL 1.13 2383.77 712.14 1577.30

CIPLA 0.25 852.11 712.14 674.19

HCL 1.05 2069.39 712.14 1321.46

HDFC 0.91 1156.39 712.14 507.02

HUL 0.18 755.99 712.14 630.88

ITC 0.32 1332.03 712.14 1105.07

LUPINLTD 0.20 2341.89 712.14 2202.48

M&M 1.13 2383.77 712.14 1577.30

MARUTHI 0.53 1284.87 712.14 910.45

MINDTREE 0.21 1962.88 712.14 1809.91

ONGC 0.64 1159.83 712.14 706.60

SUNTVLTD 0.57 2407.79 712.14 2004.98

YESBANK 1.75 2550.71 712.14 1303.54


Fig No: 4.6

Showing Unsystematic Risk/Residual Variance

From the above table and chart shows LUPIN LTD has maximum residual variance or

unsystematic risk 2202.48 and HDFC has minimum unsystematic risk 507.02.



- 64 -

CONSTRUCTION OF PORTFOLIO USING SHARPE’S MODEL

After the decomposing the risk of the securities it is required to construct the optimal portfolio.

For the construction of optimal portfolio first the best stocks from the current 15 stocks need to

be selected. This can be done by first ranking the stocks based on excess return to beta .Then a

cut-off point is determined. This cut-off point is taken as the basis for selecting the stock. After

That Sharpe’s optimization model is used to determine the weights for each security and hence

the portfolio is formed.

4.7: Ranking of Securities

The Table No: 4.7.1 shows the computation for ranking the securities by finding the excess

return on beta.

TABLE: 4.7.1

Showing ranks of securities based on excess return to beta

Sl.No: Security name

Mean

return

Ri Rf

Excess

return

beta

Ri-Rf

Beta

β

Excess return

to beta

Ri-Rf/βi RANK

1 AMBUJACEMENT 15.37 8.1 7.2665427 0.84 8.650646071 14

2 ASIANPAINTS 32.25 8.1 24.15407754 0.28 86.26456264 1

3 BHARATIAIRTEL 18.59 8.1 10.49079027 1.06 9.896971952 13

4 CIPLA 15.50 8.1 7.39694599 0.5 14.79389198 8

5 HCL 33.74 8.1 25.64452304 1.02 25.14168925 4

6 HDFC 23.27 8.1 15.16633789 0.95 15.9645662 7

7 HUL 17.53 8.1 9.42763104 0.42 22.44674057 5

8 ITC 15.70 8.1 7.599091749 0.56 13.56980669 9

9 LUPINLTD 26.79 8.1 18.68898194 0.44 42.47495896 3

10 M&M 18.59 8.1 10.49079027 1.06 9.896971952 12

11 MARUTHI 15.58 8.1 7.478317992 0.73 10.24427122 11

12 MINDTREE 29.25 8.1 21.15469397 0.46 45.98846515 2

13 ONGC 9.86 8.1 1.762090632 0.8 2.20261329 15

14 SUNTVLTD 17.20 8.1 9.09950262 0.75 12.13267016 10

15 YESBANK 32.23 8.1 24.12741325 1.32 18.27834337 6




- 65 -

Calculation of cut off point

The Table No: 4.7.2 shows the calculation for finding the cut-off point.

TABLE: 4.7.2

Showing Calculation of cut off point

Source:Computed from secondary data.

From the calculation shown in the table it can be seen that the cut off value is 15.55.

4.8.1: Optimal Portfolio

The Table No: 4.8.1 shows the calculation for obtaining optimal portfolio by using Sharpe’s

optimization model.

TABLE: 4.8.1

Showing calculation of optimal portfolio

COMPANY σ²ei (Ri-Rf)/βi C* Zi ∑Zi Xi

ASIANPAINTS 719.11 86.26 15.55 0.74 1.70 0.43

MINDTREE 1962.88 45.99 15.55 0.32 1.70 0.19

LUPINLTD 2341.89 42.47 15.55 0.24 1.70 0.14

HCL 2069.39 25.14 15.55 0.22 1.70 0.13

HUL 755.99 22.45 15.55 0.11 1.70 0.06

YESBANK 2550.71 18.28 15.55 0.07 1.70 0.04

HDFC 1156.39 15.96 15.55 0.01 1.70 0.01


Sl.No COMPANY σ²ei

(Ri-

Rf)*βi/σ²ei

Σ(Ri-

Rf)*βi/σ²ei βi²/σ²ei Σβi²/σ²ei Ci

1 ASIANPAINTS 719.11 0.009 0.009 0.000109024 0.000109024 6.22

2 MINDTREE 1962.88 0.005 0.014 0.000107801 0.000216825 8.86

3 LUPINLTD 2341.89 0.004 0.018 8.26682E-05 0.000299494 10.49

4 HCL 2069.39 0.013 0.031 0.000502757 0.000802251 13.83

5 HUL 755.99 0.005 0.036 0.000233336 0.001035587 14.65

6 YESBANK 2550.71 0.012 0.048 0.000683104 0.001718691 15.45

7 HDFC 1156.39 0.012 0.061 0.000780447 0.002499138 15.55

8 CIPLA 852.11 0.004 0.065 0.000293391 0.002792529 15.50

9 ITC 1332.03 0.003 0.068 0.00023543 0.003027958 15.39

10 SUNTVLTD 2407.79 0.003 0.071 0.000233617 0.003261575 15.23

11 MARUTHI 1284.87 0.004 0.075 0.000414751 0.003676327 14.82

12 BHARATIAIRTEL 2383.77 0.005 0.080 0.000471355 0.004147682 14.41

13 M&M 2383.77 0.005 0.085 0.000471355 0.004619037 14.05

14 AMBUJACEMENT 1595.54 0.004 0.088 0.000442232 0.005061269 13.68

15 ONGC 1159.83 0.001 0.090 0.000551806 0.005613075 12.78



- 66 -

TABLE: 4.8.2

Showing optimal portfolio

Sl.No COMPANY PROPOTION

1 ASIANPAINTS 0.43

2 MINDTREE 0.19

3 LUPINLTD 0.14

4 HCL 0.13

5 HUL 0.06

6 YESBANK 0.04

7 HDFC 0.01


4.9:Return and Risk of optimal portfolio

In order to determine the effectiveness of optimization, the return and risk of the optimal

portfolio are determined.

The Table No: 4.9.1 shows the calculation for obtaining the alpha of the portfolio.

TABLE: 4.9.1

Shows portfolio alpha in optimal portfolio

COMPANY WEIGHT(ωI) ALPHA(αi) ALPHA*WEIGHT(αIωI)

ASIANPAINTS 0.43 30.23 13.1083261

MINDTREE 0.19 25.89 4.804989058

LUPINLTD 0.14 23.57 3.389463848

HCL 0.13 26.29 3.321486146

HUL 0.06 14.48 0.896023331

YESBANK 0.04 22.61 0.946829668

HDFC 0.01 16.32 0.111044348

TOTAL 1.00 26.58


n

Portfolio alpha = Σ ωiαi

i=1

= 26.58



- 67 -

The Table No: 4.9.2 shows the calculation for obtaining the beta of the portfolio. For that weight

of each stock is multiplied with its corresponding beta.

TABLE: 4.9.2

Shows portfolio beta in optimal portfolio

Sl.No COMPANY WEIGHT(ωI) BETA(βi) BETA*WEIGHT(βiωI)

1 ASIANPAINTS 0.43 0.28 0.12

2 MINDTREE 0.19 0.46 0.09

3 LUPINLTD 0.14 0.44 0.06

4 HCL 0.13 1.02 0.13

5 HUL 0.06 0.42 0.03

6 YESBANK 0.04 1.32 0.06

7 HDFC 0.01 0.95 0.01

TOTAL 1.00 0.49


n

Portfolio Beta=Σ ωiβi =0.49

i=1

TABLE: 4.9.3

Shows portfolio residual variance in optimal portfolio

COMPANY WEIGHT(ωi) ωi2

RESIDUAL

VARIANCE (σ²ei) ωi2 *σ²ei

ASIANPAINTS 0.43 0.19 719.11 135.25

MINDTREE 0.19 0.03 1962.88 67.64

LUPINLTD 0.14 0.02 2341.89 48.42

HCL 0.13 0.02 2069.39 33.02

HUL 0.06 0.00 755.99 2.89

YESBANK 0.04 0.00 2550.71 4.47

HDFC 0.01 0.00 1156.39 0.05

TOTAL 1.00 26.58 291.76

Source:Computed from secondary data.



- 68 -

n

Portfolio residual variance=Σωi2σ2

ei

i=1

=291.76

MEASURING PORTFOLIO RETURN AND RISK

PORTFOLIOS RETURN (RP)

PORTFOLIO RETURN= PORTFOLIOALPHA+(PORTFOLIOBETA×MARKET RETURN)

RP =αP+ (βp×Rm)

αP = 26.58

βp = 0.49

Rm =7.27

RP = 26.58+(0.49 X 7.27)

= 30.14

PORTFOLIO RISK (σ2P)

n

Portfolio risk (σ2p) = βp

2σ2m+Σwi

2σ2ei

βp2 = 0.49

σ2m

= 712.14

Σωi2σ2

ei = 221.76

σ2p

= 462.74

σp = 21.51



- 69 -

TABLE: 4.9.4 Shows optimal portfolio Return, Risk, Alpha, Beta, Residual variance


The Table No: 4.9.4 illustrates the benefit that have been achieved due to diversification of the

portfolio

TABLE: 4.9.5 Shows Benefit of Diversification

Risk Class

Total for

securities Portfolio

Benefit of

Diversification

% of risk

reduction

Systematic Risk 8438.93 170.98 8267.95 97.97

Unsystematic

Risk 3117.42 291.76 2825.66 90.64

Total Risk 11556.35 462.74 11093.61 96.00


Portfolio

Return

Risk

Alpha

Beta

Residual variance

Optimal

30.14

21.51

26.54

0.49

291.76



- 70 -

Effectiveness of Optimization

To examine the effectiveness of optimization three different portfolios are constructed

with the securities included in the optimal portfolio. The criteria used for construction of these

portfolios are based on the proportion of investment in different securities for the three portfolios

under consideration are:

1. Equal investment in each security

2. Investment in each security in proportion to the P/E multiple of each security.

3. Investment in each security in proportion to the risk adjusted rate of return of the

security.

The return and risk of these portfolios are determined for the purpose of evaluation of

the performance of these portfolios



- 71 -

4.10:1st PORTFOLIO ( By giving equal weight to each security.)

First portfolio is constructed by giving equal weights to the six securities and then the portfolio

alpha, portfolio beta and weighted residual variance are calculated to arrive at portfolio return

and risk.

The Table No: 4.10.1 shows the calculation for obtaining the portfolio alpha. Portfolio alpha can

be obtained by multiplying weight of each security by its corresponding alpha.

TABLE: 4.10.1

Shows portfolio alpha in equal weight


ASIANPAINTS 0.14 30.23 4.32

MINDTREE 0.14 25.89 3.70

LUPINLTD 0.14 23.57 3.37

HCL 0.14 26.29 3.76

HUL 0.14 14.48 2.07

YESBANK 0.14 22.61 3.23

HDFC 0.14 16.32 2.33

TOTAL 1.00 22.77


n

Portfolio alpha = Σ ωiαi

i=1

=22.77

The Table No: 4.10.2 shows the calculation for obtaining the portfolio beta. Portfolio beta can be

obtained by multiplying weight of each security by its corresponding alpha.

TABLE: 4.10.2

Shows portfolio beta in equal weight

COMPANY WEIGHT(ωI) BETA(βi) BETA*WEIGHT(βiωI)


MINDTREE 0.14 0.46 0.07

LUPINLTD 0.14 0.44 0.06

HCL 0.14 1.02 0.15

HUL 0.14 0.42 0.06

YESBANK 0.14 1.32 0.19

HDFC 0.14 0.95 0.14

TOTAL 1.00 0.70




- 72 -

n

Portfolio Beta=Σ ωiβi =0.70

i=1

TABLE: 4.10.3

Shows portfolio residual variance in equal weight


RESIDUAL VARIANCE

(σ²ei) ωi2 *σ²ei

ASIANPAINTS 0.14 0.02 719.11 14.68

MINDTREE 0.14 0.02 1962.88 40.06

LUPINLTD 0.14 0.02 2341.89 47.79

HCL 0.14 0.02 2069.39 42.23

HUL 0.14 0.02 755.99 15.43

YESBANK 0.14 0.02 2550.71 52.06

HDFC 0.14 0.02 1156.39 23.60

TOTAL 1.00 26.58 235.84


n

Portfolio residual variance=Σ ωi 2*σ 2

ei

i=1

=235.84



Portfolio Return= Portfolio Alpha + (Portfolio Beta × Market return)

RP =αP+ (βp×Rm)

Where,

αP = 22.77

βp = 0.70

Rm =7.27

RP =22.77+ (0.70 x 7.27)

= 27.85



- 73 -

PORTFOLIO RISK (σP2)

n

Portfolio risk (σp2) = βp

2σ2m+Σωi

2σ2ei

i=1

Where,

βp2 = 0.49

σ2m

= 712.14

Σωi2σ2

ei = 235.84

σ2p

= 583.37

σp = 24.15


portfolio

TABLE: 4.10.4

Shows Benefit of diversification

Risk Class Total for securities Portfolio

Benefit of

Diversification

% of risk

reduction

Systematic Risk 8438.93 347.53 8091.41 95.88

Unsystematic

Risk 3117.42 235.84 2881.58 92.43

Total Risk 11556.35 583.37 10972.98 94.95




- 74 -

4.11:2nd PORTFOLIO (BASED ON PE Ratio)

Second portfolio is constructed on the basis on PE Ratio of the six securities and then the

portfolio alpha, portfolio beta and weighted residual variance are calculated to arrive at portfolio

return and risk

The Table No: 4.11.1 shows the calculation of the weight based on the PE ratio of the securities.

TABLE: 4.11.1

Shows the calculation of weight based on PE ratio

COMPANY P/E RATIO WEIGHT(ωI)

ASIANPAINTS 40.58 0.14

MINDTREE 15.80 0.06

LUPINLTD 32.19 0.11

HCL 13.96 0.05

HUL 78.00 0.27

YESBANK 14.30 0.05

HDFC 89.08 0.31

TOTAL 283.91 1.00



TABLE: 4.11.2

SHOWS PORTFOLIO ALPHA


n

Portfolio alpha =Σ ωiαi

i=1

=19.96



MINDTREE 0.06 25.89 1.44

LUPINLTD 0.11 23.57 2.67

HCL 0.05 26.29 1.29

HUL 0.27 14.48 3.98

YESBANK 0.05 22.61 1.14

HDFC 0.31 16.32 5.12

TOTAL 1.00 19.96



- 75 -


obtained by multiplying weight of each security by its corresponding beta.

TABLE: 4.11.3

SHOWS PORTFOLIO BETA



MINDTREE 0.06 0.46 0.03

LUPINLTD 0.11 0.44 0.05

HCL 0.05 1.02 0.05

HUL 0.27 0.42 0.12

YESBANK 0.05 1.32 0.07

HDFC 0.31 0.95 0.30

TOTAL 1.00 0.65


n

Portfolio Beta = Σ ωiβi = 0.65

i=1

TABLE: 4.11.4

SHOWS PORTFOLIO RESIDUAL VARIANCE


RESIDUAL VARIANCE


ASIANPAINTS 0.14 0.02 719.11 14.69

MINDTREE 0.06 0.00 1962.88 6.08

LUPINLTD 0.11 0.01 2341.89 30.11

HCL 0.05 0.00 2069.39 5.00

HUL 0.27 0.08 755.99 57.06

YESBANK 0.05 0.00 2550.71 6.47

HDFC 0.31 0.10 1156.39 113.84

TOTAL 1.00 26.58 233.25


n

Portfolio residual variance=Σ ωi2σ2

ei

i=1

=233.25



- 76 -


PORTFOLIO RETURN (RP)

PORTFOLIO RETURN = PORTFOLIO ALPHA + (PORTFOLIO BETA×MARKET

RETURN)

RP =αP+ (βp×Rm)

αP = 19.96

βp = 0.65

Rm =7.27

RP = 19.96+ (0.65*7.27)

= 24.65

PORTFOLIO RISK (σ2P)

n

Portfolio risk (σ2p) = βp

2σ2m+Σωi

2σ2ei

i=1

βp2 = 0.42

σm2 = 712.14

Σwi2σ2

ei = 233.25

σ2p

= 530.1

σp = 23.02

The Table No: illustrates the benefit that have been achieved due to diversification of the

portfolio

TABLE: 4.11.5

Benefit of diversification

Risk Class

Total for


Benefit of

Diversification

% of risk

reduction

Systematic Risk 8438.93 296.83 8142.10 96.48

Unsystematic Risk 3117.42 233.25 2884.17 92.52

Total Risk 11556.35 530.08 11026.27 95.41




- 77 -

4.12:3rd PORTFOLIO BASED ON RISK ADJUSTED RATE OF RETURN)

Third portfolio is constructed on the basis on Risk Adjusted Rate of Return of the six

securities and then the portfolio alpha, portfolio beta and weighted residual variance are

calculated to arrive at portfolio return and risk. For this purpose the risk free rate return is taken

as 8.1.

The Table No: 4.12.1 shows the calculation of the weight based on risk adjusted rate of return.

TABLE: 4.12.1

Shows calculation of weight based on risk adjusted rate of return

COMPANY σ²ei

RETURN

(Ri) Rf (Ri-Rf)/σ WEIGHT(ωI)

ASIANPAINTS 719.11 32.25 8.10 0.90 0.25

MINDTREE 1962.88 29.25 8.10 0.48 0.13

LUPINLTD 2341.89 26.79 8.10 0.39 0.11

HCL 2069.39 33.74 8.10 0.56 0.16

HUL 755.99 17.53 8.10 0.34 0.10

YESBANK 2550.71 32.23 8.10 0.48 0.13

HDFC 1156.39 23.27 8.10 0.45 0.12

TOTAL 3.59




TABLE: 4.12.2

Shows portfolio alpha in risk adjusted rate of return



MINDTREE 0.13 25.89 3.44

LUPINLTD 0.11 23.57 2.53

HCL 0.16 26.29 4.12

HUL 0.10 14.48 1.38

YESBANK 0.13 22.61 3.00

HDFC 0.12 16.32 2.03

TOTAL 1.00 24.08



- 78 -

n

Portfolio alpha =Σ ωiαi

i=1

=24.08


obtained by multiplying weight of each security by its corresponding beta.

TABLE: 4.12.3

Shows portfolio beta in risk adjusted rate of return



MINDTREE 0.13 0.46 0.06

LUPINLTD 0.11 0.44 0.05

HCL 0.16 1.02 0.16

HUL 0.10 0.42 0.04

YESBANK 0.13 1.32 0.18

HDFC 0.12 0.95 0.12

TOTAL 1.00 0.67


n

Portfolio Beta= Σ wiβi =0.67

i=1

TABLE: 4.12.4

Shows portfolio residual variance in risk adjusted rate of return



RESIDUAL

VARIANCE


ASIANPAINTS 0.25 0.06 719.11 45.15

MINDTREE 0.13 0.02 1962.88 34.63

LUPINLTD 0.11 0.01 2341.89 27.03

HCL 0.16 0.02 2069.39 50.89

HUL 0.10 0.01 755.99 6.88

YESBANK 0.13 0.02 2550.71 45.05

HDFC 0.12 0.02 1156.39 17.80

TOTAL 1.00 26.58 227.43



- 79 -

n

Portfolio residual variance=Σ ωi 2 σ 2

ei

i=1

= 227.43



Portfolio Return = Portfolio Alpha + (Portfolio Beta×Market Return)

RP =αP+ (βp×Rm)

αP = 24.08

βp = 0.67

Rm =7.27

RP = 24.08+ (0.67*7.27)

=28.96

PORTFOLIO RISK (σP2)

n

Portfolio risk (σp2) = βp

2σ 2 m+ Σ ω i

2 σei2

i=1

βp2 = 0.45

σ 2m

= 712.14

Σ ωi2 σ2

ei = 204.74

σ 2p

= 548.87

σp =23.43



- 80 -


portfolio

TABLE: 4.12.5

Benefit of diversification

Risk Class

Total for


Benefit of

Diversification % of risk reduction

Systematic Risk 8438.93 321.44 8117.50 96.19

Unsystematic Risk 3117.42 227.43 2889.99 92.70

Total Risk 11556.35 548.87 11007.49 95.25




- 81 -

4.13: PORTFOLIO EVALUATION

Portfolio evaluation is the process to determine the performance of the portfolio. The best

measure for evaluation of portfolio is the risk adjusted rate of return as determined by SHARPE

ratio and TREYNEOR ratio. The following three different evaluation processes is used.

SHARPE RATIO

TREYNOR RATIO

JENSEN MEASURE

4.13.1: SHARPE RATIO:

Sharpe Ratio (SR) = Rp –Rf

σP

Where,

Rp = is the realized return on the portfolio

Rf = is the risk free rate of return

σP = is the standard deviation of portfolio return



- 82 -

The Table No 4.13.1 shows the calculation for obtaining the Sharpe ratio of the portfolios.

TABLE: 4.13.1

Shows Sharpe Ratio of the portfolios

PORTFOLIO Rp(%) Rf(%) σpi(%) (Rp-Rf)/σp

OPTIMAL 30.14 8.10 21.51 1.02

1 27.85 8.10 24.15 0.82

2 24.66 8.10 23.02 0.72

3 28.96 8.10 23.43 0.89


Fig No: 4.13.1

Shows the Sharpe ratio of different portfolios

Optimal portfolio has highest Sharpe ratio (1.02) and PE ratio portfolio has lowest Sharpe ratio

(0.72).



- 83 -

4.12.2: TREYNOR RATIO

Treynor ratio is also the ratio of excess return to risk. But here risk is defined as the systematic

risk or market risk on the assumption that the portfolio is well diversified.

Treynor Ratio = Rp-Rf

βp

Where,

Rp =Return of the portfolio

Rf =Risk free rate return

βp =Standard deviation of portfolio

The Table No 4.13.2 shows the calculation for obtaining the Treynor’s ratio of the portfolios.

TABLE: 4.13.2

Shows Treynor ratio of the portfolio

PORTFOLIO Rp(%) Rf(%) βp

(Rp-

Rf)/βp

OPTIMAL 30.14 8.10 0.49 45.29

1 27.85 8.10 0.70 28.27

2 24.66 8.10 0.65 25.65

3 28.96 8.10 0.67 31.14


Fig No: 4.12.2

Shows the Treynor ratio of different portfolios

Optimal portfolio has highest Treynor ratio (45.29) and PE ratio portfolio has lowest Treynor

ratio (25.65).



- 84 -

4.13.3: JENSEN’S MEASURE

In finance, Jensen's alpha is used to determine the excess return of a stock, other security, or

portfolio over the security's required rate of return as determined by the Capital Asset Pricing

Model. This model is used to adjust for the level of beta risk, so that riskier securities are

expected to have higher returns. The measure was first used in the evaluation of mutual fund

managers by Michael Jensen in the 1970's.

It is mentioned as a measure of absolute performance because a definite standard is set and

against that the performance is measured.

Where,

Rp = Average return of portfolio

Rf = Riskless rate of interest

βp= Portfolio beta

Rm= Average market return



- 85 -

The Table No: 4.13.3 shows the calculation for obtaining the Jensen’s measure of the portfolios.

The graphical representation of the same is given below.

TABLE: 4.13.3

Shows Jensen measure of the portfolio

PORTFOLIO Rp(%) Rf(%) Βp Rm(%)

E(Rp)=

Rf+βp(Rm-

Rf)

Rp-

E(Rp)

OPTIMAL 30.14 8.10 0.49 7.27 7.70 22.45

1 27.85 8.10 0.70 7.27 7.52 20.33

2 24.66 8.10 0.65 7.27 7.56 17.09

3 28.96 8.10 0.67 7.27 7.54 21.42


Fig No: 4.13.3

Optimal portfolio has highest Jensen alpha (22.45) and PE ratio portfolio has lowest Jensen alpha

(17.09)



- 86 -

44..1144:: VVAALLUUEE AATT RRIISSKK

Every type of business involves some extent of risk. Risk can be minimized but can not be

eliminated. The only way to totally eliminate the risk is by stopping the business itself .in the

1990 VaR concepts become more popular. It is latest concept in the field of risk management.

VAR is a method of assessing risk using standard statistical techniques. Formally, it is the

maximum loss over a target horizon such that there is a low, predetermined probability that the

actual loss will be larger. VAR has a scientific basis and provides users with summary measure

of market risk

METHODS FOR CALCULATING VaR

Various methods are possible to compute Value At Risk .these methods basically differ in

terms of:

Distributional assumptions for the risk factors (normal versus other distributions )

Linear vs Full valuation , where the former approximates the exposure to risk factors by a

linear mode

Some important methods for measuring VaR are:

1. Monte Carlo Method

2. Variance Covariance Method

3. Historical Simulation Method



- 87 -

44..1144..11::MMOONNTTEE CCAARRLLOO SSIIMMUULLAATTIIOONN

Under this method VaR for a portfolio is calculated using a one day time horizon at 95% and

99% confidence level for 500 days of data. The following steps are involved in Monte Carlo

simulation.

1. the data is collected on the movements of each securities for the past 500days before 1st

April 2013.

2. the daily returns of each security for this 500days is calculated

3. This provides us 500 alternative scenarios for what can happen between today (1st April

2013) and tomorrow.

4. the closing price of each security for each scenario is then calculated by using the

formula Vp= Vop(1+r)

Simulated price = closing price × (1+(r/100))

r =return of each day

5. the value of the portfolio and change in value of the portfolio is then determined for each

scenario and then arranged in ascending order

6. the estimate of VaR is the portfolio loss at 1st percentile point (5th item ) for 99%

confidence level and 5th percentile point (25th item) for 95% confidence level

The following tables show the estimation of VaR using this method .the first table

gives the value of the opening value of the portfolio for today (31st march 2008). Only part of

the table containing the critical values of VaR is shown in the following table. The detailed

calculation for the change in the value of the portfolio for 500 scenarios are shown in a

separate table in Appendix no.1



- 88 -

Here initial amount taken is Rs.7000000.The Table No shows the value of the portfolio on 1st

April 2013 for the Monte Carlo simulation.

TABLE: 4.14.1.1

Showing Portfolio Value on 1st April 2013 (Today) For the Monte Carlo simulation


COMPANY ωi

Closing

Price

Total

Value

No: of

Shares

Actual

No: Actual Value

ASIANPAINTS 0.43 174.25 3035833.92 17422.29 17422.00 3035783.50

MINDTREE 0.19 904.30 1299396.33 1436.91 1437.00 1299479.10

LUPINLTD 0.14 631.10 1006541.62 1594.90 1595.00 1006604.50

HCL 0.13 788.50 884264.03 1121.45 1121.00 883908.50

HUL 0.06 471.35 433153.95 918.96 919.00 433170.65

YESBANK 0.04 432.30 293191.21 678.21 678.00 293099.40

HDFC 0.01 623.85 47618.95 76.33 76.00 47412.60

TOTAL 1.00 7000000.00 6999458.25



- 89 -

The Table No 4.14.1.2 shows possible values of portfolio sorted in ascending order. From here

we get VAR at 99% and 95% confidence level.

TABLE: 4.14.1.2

Showing Changes in Total Value of Portfolio (sorted in ascending order).


Day Portfolio

Change in

value Value at risk

1 7104535.15 105076.9 -344389.44

2 7007990.43 8532.18 -220221.61

3 7023208.27 23750.02 -212887.14

4 6964696.47 -34761.78 -208741.57

5 7032340.33 32882.08 -191274.86 At 99% confidence level

6 7053401.26 53943.01 -186838.82

7 7096244.09 96785.84 -183370.59

8 6933708.56 -65749.69 -181937.14

9 7063724.04 64265.79 -180199.11

10 7000630.03 1171.78 -168804.28

11 7065147.3 65689.05 -151046.86

12 7061278.1 61819.85 -147821.96

13 7085987.24 86528.99 -147565.37

14 7060857.77 61399.52 -145795.8

15 6892250.87 -107207.38 -145175.34

16 7089498.86 90040.61 -142423.07

17 7010892.88 11434.63 -142356.96

18 7083021.82 83563.57 -140817.87

19 6937416.36 -62041.89 -138025.75

20 7010557.9 11099.65 -135355.82

21 6983163.28 -16294.97 -133757.55

22 6984084.42 -15373.83 -126985.56

23 6934340.52 -65117.73 -126778.15

24 7078443.42 78985.17 -124133.04

25 6888207.84 -111250.41 -123742.83 At 95% confidence level

26 7116990.29 117532.04 -123135.48

27 6907362.93 -92095.32 -121446.22

28 6994994.46 -4463.79 -120378.58

29 7076745.58 77287.33 -119874.81

30 6997460.86 -1997.39 -119802.56

31 7193596.6 194138.35 -118653.96

32 7084282.08 84823.83 -116866.12

33 6923717.06 -75741.19 -116728.77

34 7176085.07 176626.82 -116492.93

35 6937661.14 -61797.11 -115205.76

36 6944139.17 -55319.08 -115101.11



- 90 -

From the above table it is clear that:-

Value at Risk At 99% of confidence level =191274.86

At 99% confidence level the maximum daily loss or gain of the portfolio will be Rs191274.86.;

that is portfolio value will lie between 6808183.39

and 7190733.11

Value at Risk at 95% of confidence level=123742.83

At 95% confidence level the maximum daily loss or gain of the portfolio will be Rs.123742.83;

that is portfolio value will be lie between Rs.6875715.42

and Rs.7123201.08



- 91 -

44..1144..22:: BBAACCKK TTEESSTTIINNGG

In back testing risk management teams examines the performance of their VaR estimates of

extreme losses with respect to realized losses. That is back testing allows the risk manager to

determine whether the VaR methods employed are adequate. While in back testing, the risk

manager must be aware that there will be periods in which actual losses will exceed those

predicted by VaR. For example, the risk manager must realize that statistically, actual losses will

exceed a 5% of VaR, 5% of the time.

Here the VaR through Monte Carlo simulation method, from that Value at Risk At 99%

of confidence level = -Rs.1817415.70 and Value at Risk at 95% of confidence

level=Rs.1336210.65 was found. For back testing past 250 days of data selected from before 1st

April 2013

The detailed calculation for the change in the value of the portfolio for 250 days are

shown in a separate table in Appendix no.4



- 92 -

The Table No: 4.14.2.1 shows values of portfolio sorted in ascending order. From here we get

Back testing values in 99% and 95% confidence level.

TABLE: 4.14.2.1

Showing Change in Total Value of the Portfolio (Sorted In Ascending Order) in Back Testing

Sl.No Change

1 -4251543.8

2 -2024189.35

3 -1817415.7

99% Confidence Interval

4 -1688437.1

5 -1633201.25

6 -1574157.1

7 -1568466.5

8 -1525137.4

9 -1461409.85

10 -1445007.35

11 -1391928.4

12 -1370060.35

13 -1336210.65

95% Confidence Interval

14 -1327271.15

15 -1257758.45

16 -1240362.85

17 -1219338.6

18 -1195918.95

19 -1190387.75

20 -1150599.2

21 -1121047.6

22 -1114543.8

23 -1104266.3

24 -1092375.1

25 -1006020.55

26 -981703.85

27 -980731.9

28 -900990.6

29 -875899.55

30 -849582.45

31 -795150.15

32 -788465.15

33 -770526.4

34 -767259.2

35 -767245.4




- 93 -

4.14.3:Variance-Covariance Model

The Table No: 4.13.3.1 shows the variance covariance matrix. From this matrix VAR can be

calculated.

TABLE: 4.14.3.1

Shows Variance co-variance matrix

COMPANY ASIANPAINTS MINDTREE LUPINLTD HCL HUL YESBANK HDFC

ASIANPAINTS 1040.33 96.94 191.00 190.13 85.67 391.59 201.86

MINDTREE 96.94 855.84 169.97 565.40 133.72 442.61 272.62

LUPINLTD 191.00 169.97 717.65 362.02 145.96 485.67 312.89

HCL 190.13 565.40 362.02 1138.69 314.69 1016.64 677.08

HUL 85.67 133.72 145.96 314.69 307.22 755.38 277.02

YESBANK 391.59 442.61 485.67 1016.64 755.38 1038.61 960.40

HDFC 201.86 272.62 312.89 677.08 277.02 960.40 541.32

TABLE: 4.14.3.2

COMPANY ASIANPAINTS MINDTREE LUPINLTD HCL HUL YESBANK HDFC

Portfolio Weight(P/E) 0.14 0.06 0.11 0.05 0.27 0.05 0.31


Variance per year = 0.0359

Standard deviation per year = 0.1875

Standard deviation per day = 0.01875(standard deviation per day/√250)

Daily volatility = 0.01875

Value of portfolio = Rs.6999458.25

Value at Risk at 5% significant level.

VaR = Value of portfolio*1.65*σp

= 6999458.25 x 1.65 x 0.01875

= Rs.216545.70

At 5% significant level the maximum daily loss or gain of the portfolio will be

Rs.216545.70 , that is portfolio value will lie between Rs. 6782912.51

and Rs.7216003.99.



- 94 -

Value at Risk at 25% significant level.

VaR = Value of portfolio*2.33*σp

= 6999458.25 x 2.33 x 0.01875

= Rs.305788.83

At 25 % significant level the maximum daily loss or gain of the portfolio will be

Rs.305788.83, that is portfolio value will lie between Rs. 6693669.418

and Rs. 7305247.08.

.



- 95 -

CHAPTER 5

DATA ANALYSIS PART II



- 96 -

5.1: Gender of the respondents.

The Table No: 5.1 shows the gender of the respondents. The percentage analysis of the same is

given below.

TABLE: 5.1

Source: Primary Data

Fig No: 5.1

Majority of the respondents are male. Male respondents constitute 87%.

Gender

Male 26

Female 4

Total 30



- 97 -

5.2: Age group of the respondents.

The Table No: 5.2 shows the age group of the respondents. The percentage analysis of the same

is given below.

TABLE: 5.2

Age Group

Below 25 3

25-30 5

35-45 10

45-55 9

55 & Above 3

Total 30


Fig No: 5.2

Majority of the respondents are in the age group 35-55 i.e. about 63%.



- 98 -

5.3: Qualification of the respondents.

The Table No: 5.3 shows the qualification of the respondents. The percentage analysis of the


TABLE: 5.3

Qualification

Graduate 8

Post graduate 10

Professional 12

Total 30


Fig No: 5.3

About 40% of the respondents have professional qualification, 33% are post graduates

And the rest are graduates.



- 99 -

5.4: Occupation of the respondents.

The Table No: 5.4 shows the occupation of the respondents. The percentage analysis of the same

is given below.

TABLE: 5.4

Occupation

Entrepreneurs 2

Business 6

Professional 14

Others 8

Total 30


Fig No: 5.4

About 46% of the respondents are professionals and 27% of the respondents are doing

business.



- 100 -

5.5: Annual Income of the respondents.

The Table No: 5.5 shows the income range of the respondents. The percentage analysis of the


TABLE: 5.5

Annual Income

Below 2 lakh 2

2-5 lakhs 8

5-10 lakhs 16

Above 10 lakhs 4

Total 30


Fig No: 5.5

About 53% of the respondents are in the income range 5-10 lakhs,27% in the range 2-5 lakhs

13% in the range above 10 lakhs and the rest are below 2 lakhs range.



- 101 -

5.6:Investment experience of the respondents.

The Table No: 5.6 shows the investment experience of the respondents. The percentage analysis


TABLE: 5.6

Investment Experience

Less than 1 2

2-5 years 6

5-10 years 15

Above 10 years 7

Total 30


Fig No: 5.6

About 50% of have investment experience of 5-10 years,23% in the range above 10 years range

20% in the range above 2-5 years and the rest are below 1 year range.



- 102 -

5.7: Investment preference of the respondents.

The Table No: 5.7 shows the investment preference of the respondents. The percentage analysis


TABLE: 5.7

Type of Investment Frequency Total

Stock 25 30

Bond 5 30

Gold 24 30

ETF 3 30

Bank Deposit 26 30

Mutual Fund 5 30

Life Insurance 16 30

Real Estate 8 30


Fig No: 5.7

From the above data it is clear that respondents are more interested in investing in stock

gold and in bank deposits



- 103 -

5.8: Sector preference of the respondents while investing.

The Table No: 5.9 shows the sector preference of the respondents. The percentage analysis of the


TABLE: 5.8

Sector

Government 5

Private 4

Foreign 2

Diversify 19

Total 30


Fig No: 5.8

Majority of the respondents are interested to diversify their investment rather than putting their

money in a single sector.



- 104 -

5.9:Type of analysis used by the respondents for investing.

The Table No: 5.10 shows the types of analysis used by the respondents. The percentage analysis


TABLE: 5.9

Type of Analysis

Fundamental 8

Technical 12

Both 9

None 1

Total 30


Fig No: 5.9

About 40 % of the respondents use technical analysis,27% use fundemental analysis and

30% use both.



- 105 -

5.10:Investment objective of the respondents.

The Table No: shows the investment objective of the respondents. The percentage analysis of the


TABLE: 5.10

Investment Objective

Income & Capital Preservation 10

Long-term growth 7

Short term growth 6

Safety 4

Liquidity 3

Total 30


Fig No: 5.10

About 34 % of the respondent’s objective is Income & Capital Preservation,23 % of the

respondents objective is long-term growth,20% of respondents aim short-term growth,13%

aims at the saftey of their investment and rest 10% aims at short-term growth.



- 106 -

5.11: Preferred rate of growth of investment by the respondents

The Table No: preferred rate of growth of investments by the respondents. The percentage

analysis of the same is given below.

TABLE: 5.11

Preferred Investment Growth

Steadily 10

Average Rate 16

Fast 4

Total 30


Fig No: 5.11

About 53 % of the respondents preferres investment to grow at an average rate,34% at a steady

rate and the rest at a fast rate.



- 107 -

5.12: Percentage of investment in stock market securities by the respondents

The Table No: 5.13 percentage of investments in stock market securities by the respondents. The

percentage analysis of the same is given below.

TABLE: 5.12

Investment in Stock Market

Securities

0-15% 13

15-30% 14

30-50% 2

More than 50% 1

Total 30


Fig No: 5.12

About 47% of the respondents is investing about 15-30% in stock market securities,43% in

0-15% investment range,7% in 30-50% range and rest 3% in more than 50% range.



- 108 -

5.13:Whether the respondents have a financial advisor or not.

The Table No: 5.14 percentage of respondents having financial advisor.The percentage analysis


TABLE: 5.13

Whether there is Financial

Advisor

Yes 7

No 23

Total 30


Fig No: 5.13

About 77% of the respondents does not have a financial advisor and the rest 23% has financial

advisor.



- 109 -

5.14:Level of Knowledge of the respondents in Portfolio Management

The Table No: 5.15 level of knowledge of the respondents in portfolio management. The


TABLE: 5.14

Knowledge in Portfolio

Management

Expert 5

High 10

Moderate 8

Basic 6

No 1

Total 30


Fig No: 5.14

About 33% has high level of knowledge,27% Moderate,17% expert,20% basic and 3%

no knwoledge.



- 110 -

5.15: Technique used by the respondents to balance risk and return.

The Table No: 5.16 technique used by the respondents to balance risk and return. The percentage


TABLE: 5.15

Balance Risk/Return

Portfolio Optimization 8

Portfolio Diversification 7

Both 15

Total 30


Fig No: 5.15

About 50% respondents use both portfolio diversification and optimization,27% uses portfolio

diversification and rest uses portfolio optimisation



- 111 -

5.16: Technique used by the respondents for portfolio diversification

The Table No: 5.16 technique used by the respondents for portfolio diversification. The


TABLE: 5.16

Technique Used For Portfolio diversification

Investing in different Securities 23

Including more securities to portfolio 7

Total 30


Fig No: 5.16

About 77% respondents diversifies by investing in different securities and the rest by

Including more securities to portfolio.



- 112 -

5.17: Familiarity of the respondents with Financial modeling.

The Table No: 5.17 the familiarity of the respondents with financial modeling techniques. The


TABLE: 5.17

Familiarity with Financial

Modelling Frequency

Yes 9

No 21

Total 30


Fig.No:5.17

About 70% respondents are not familiar with financial modelling techniques.



- 113 -

5.18: Portfolio evaluation techniques used by respondents.

The Table No: 5.18 the familiarity of the respondents with financial modeling techniques. The


TABLE: 5.18

Technique Used for evaluation of

Portfolio

Sharpe 25 30

Treynor 22 30

Jenson 20 30

Information 5 30


Fig No: 5.18

From the above data it is clear that Sharpe ,Teynor ratios are the most used for portfolio

evaluation.



- 114 -

5.19: Awareness of VAR Concepts among the respondents.

The Table No: 5.19 shows the awareness of VAR concepts among the respondents. The


TABLE:5.19

Awareness of VAR Concepts

Yes 12

No 18

Total 30


Fig No:5.19

Only 40% of the respondents are aware of VAR Concepts.



- 115 -

5.20: Methods for measuring VAR used by the respondents

The Table No: 5.20 shows the techniques used by respondents to measure VAR. The percentage


TABLE: 5.20

Method used for measuring VAR

Monte-Carlo Simulation 6 30

Historical Simulation 5 30

Backtest 4 30

Others 2 30


Fig No: 5.20

From the above data it is clear that Monte-Carlo Simulation and Historical Simulation are the

two most used techiques by the respondents to measur VAR.



- 116 -

5.21: Qualification of the investors and their awareness towards Financial modeling

techniques

Table No:5.21 shows the qualification of the investors and their level of awareness towards

Financial Modeling Techniques.

TABLE NO:5.21

Qualification

Total Graduate Postgraduate Professional

Awareness Yes 0 0 9 9

No 8 10 3 21

Total 8 10 12 30

Ho : There is no relation between the qualification of the investors and their level of

awareness towards Financial Modelling techniques.

H1 : There is no relation between the qualification of the investors and their level of

awareness towards Financial Modelling techniques.

TABLE NO:5.23

Chi-Square Tests

Value df

Asymp. Sig.

(2-sided)

Pearson Chi-Square 19.286a 2 .000

Likelihood Ratio 23.156 2 .000

Linear-by-Linear

Association

14.386 1 .000

N of Valid Cases 30

Since the table value is greater than the computed value. Ho is rejected,ie; there is a relation

Between the qualification of the investors and their level of awareness towards the Financial

Modelling techniques.



- 117 -

CHAPTER 6

FINDINGS, SUGGESTIONS AND

CONCLUSION



- 118 -

66..11::FFIINNDDIINNGGSS

SSEECCUURRIITTYY AANNAALLYYSSIISS

Return of Securities:

HCL has the maximum return (33.74%) ONGC has the minimum return

(9.86%)

Beta Value of the Securities:

YES BANK has the maximum beta value, which means maximum sensitivity to

market (1.32). The minimum sensitivity to market is for ASIAN PAINTS (0.28).

Alpha Value of the Securities:

ASIAN PAINTS has the maximum Alpha (30.23) indicating that it has

maximum extra return and ONGC has the minimum Alpha (4.06) which indicate

its earning is below market return

Risk of Securities:

i. Systematic Risk Of Securities:

YES BANK has the maximum systematic risk (1247.17%) and ASIAN PAINTS

has minimum systematic risk (55.46 %)

ii. Unsystematic Risk of Securities:

LUPIN LTD has maximum residual variance or unsystematic risk (2202.48) and

HDFC has minimum unsystematic risk (507.02)

ii. Risk Of Securities:

YES BANK has maximum risk (50.50 %) and ASIANPAINTS has minimum

risk (26.82%)

PORTFOLIO ANALYSIS

Portfolio return:

The return of optimal portfolio is highest with return (28.96%) and the return of 2nd portfolio

based on PE ratio has the least return of (24.65)

Portfolio risk:

The risk of equal weight portfolio is highest with risk (24.15) and the risk of 2nd portfolio

based on PE ratio has the least risk (23.02)



- 119 -

Portfolio evaluation:

The portfolio is tested for optimality by comparing its performance against the four other

portfolios using Sharpe’s ratio, Treynor ratio and Jensen ratio Tangency. In all cases except the

performance of the optimal portfolio is found to be superior

VALUE AT RISK:

Monte Carlo simulation:

Value at Risk At 99% of confidence level =191274.86

At 99% confidence level the maximum daily loss or gain of the portfolio will be Rs.191274.86.;

that is portfolio value will lie between 6808183.39

and 7190733.11

Value at Risk at 95% of confidence level=123742.83

At 95% confidence level the maximum daily loss or gain of the portfolio will be Rs.123742.83;

that is portfolio value will be lie between Rs. 6875715.42

and 7123201.08

Back testing:

The back test result shows at 5 % level significant day loss is stipulated by 5% historical

simulation value, at the same time 1% level significant day loss not stipulated but it very near to

1% level of confidence

Variance covariance model

At 5% significant level the maximum daily loss or gain of the portfolio will

be Rs.216545.70 , that is portfolio value will lie between Rs. 6782912.51

and Rs.7216003.99.

At 25 % significant level the maximum daily loss or gain of the portfolio

will be Rs.305788.83, that is portfolio value will lie between Rs.

6693669.418 and Rs. 7305247.08.

.

FINDINGS FROM PRIMARY DATA

Most of the investors are not aware of Financial Modelling techniques.

Most of the investors are not aware of VaR technique’s for risk management.

Qualification of the investors do affect their level of awareness of investors towards

Financial Modelling techniques. It can be observed those who are professionally

qualified are more aware of Financial Modelling techniques.



- 120 -

6.2: SUGGESTIONS

The investor should calculate the cost and benefit of each risk management

strategy with the conditions prevailing in the market while he is opting a risk

reduction

Even though the investor can use any type of models for optimization and risk

management, he has to consider the present state of securities market before his

investment.

MMoosstt ooff tthhee iinnvveessttoorrss aarree nnoott aawwaarree ooff tthheessee tteecchhnniiqquueess tthheeyy sshhoouulldd iimmpprroovvee tthheeiirr

kknnoowwlleeddggee..



- 121 -

CCOONNCCLLUUSSIIOONN

Financial modelling is the task of building an abstract model of a financial decision making

situation. In Today’s complex and dynamic investment environment it is necessary for any

investment manager to device and apply different kind of financial modeling strategies. Due to

the increased volatility and upswings in the capital market, every investment manager must be

careful regarding his investment decisions. Increased complexity of financial instruments and the

economic conditions such as recession, boom, etc. makes it difficult for any investment manager

to plan his investments. In these conditions, financial modeling strategies will help him to

effectively manage his assets. Every investment decision is based on an efficient risk-return

trade-off. Modern financial management offers different kind of financial models which will

enable an investment manager to strike an optimal balance between risk and return.

A portfolio is not a simple aggregation of a random group of securities. It is a combination of

carefully selected securities, combined in a specific way so as to reduce the risk of investment to

the minimum. A good portfolio selection through Sharpe’s optimization model & Markowitz

theory along with VaR techniques like Monte Carlo Simulation and variance covariance method

will assist an individual investor to select a good portfolio which maximizes his return by

keeping his portfolio risk at a minimum level.



- 122 -

BIBLIOGRAPHY

David A. Dubofsky and Thomas W, Miller J R.,Derivates Valuation and Risk

Management,Oxford University Press.

Ederington,W. T.(1979),The Hedging Performance of the New Futures Market,

The Journal of Finance

Punithavathy Pandian,Security Analysis and Portfolio Management,Vikas Publishing

House Pvt. Ltd.

Dr.Krishna Swami O.R,Research Methods,Himalaya Publishing House.

Kevin S,Portfolio Management, Pearson Education

WEBSITES

www.nseindia.com

www.rbi.org

www.investopedia.com

http://www.nseindia.com/

http://www.rbi.org/

http://www.investopedia.com/



- 123 -

ANNEXURE

FINANCIAL MODELLING FOR PORTFOLIO SELECTION AND

RISK MANAGEMENT

QUESTIONNAIRE

INSTRUCTIONS

Read all the questions carefully and put tick mark on appropriate box.

All the information collected is only for academic purpose and will be kept confidential.

1. Name (optional):__________________

2. Gender: Male Female

3. Age group: Below 25 25-35yrs 35-45 yrs

45-55yrs 55 & Above

4. Qualification: Undergraduate Graduate

Postgraduate Professional

5. Occupation: Entrepreneur Business

Professional Others

6. Annual income: Below 2 lakh 2 - 5 lakhs

5-10 lakhs Above 10 lakhs

7. How many years of Investment experience do you have?

Less than 1 year 2-5 years

5-10 More than 10 years

8. What type of investments do you have? Please tick all appropriate

Stock Bond ETF Gold Bank deposit

Mutual fund Life insurance Real estate

9. Which sector do you prefer invest your money?

Private sector Government sector Public sector

Foreign sector Diversify

10. Which type of analysis do you use for taking investment decisions?

Fundemental Analysis Technical Analysis Both

None

11.What is your investment objective?

Income and capital preservation Long term growth Safety

Short term growth Liquidity

12. At what rate do you want your investment to grow?

Steadily Average rate Fast

13. What percentage of your income do you invest in stock market securities?

0-15% 15-30%

30-50% More than 50%

14. Do you believe that investment in selected sectors is a successful strategy for

maximizing returns and minimizing risks?

Yes No

15. Do you have a financial advisor?

Yes No

16.What is your knowledge regarding portfolio management?

Expert knowledge High knowledge Moderate knowledge

Basic knowledge No knowledge

17.Which technique would you use to balance the risk and return of the investment?

Portfolio optimization Portfolio diversification Both

18.Which technique would you use for portfolio diversification?

Investing in different securities

Including more securities in portfolio

19. Are you familiar with financial modeling techniques?

Yes No

20. Which of the following techniques you use for evaluation of portfolio?

Sharpe’ ratio Treynor’s ratio

Jenson’s ratio Information ratio

21. Are you aware of VAR concepts in the field of risk management?

Yes No

22. .If yes which method is used by you for measuring VAR?

Monte-Carlo Simulation Historical Simulation

Others

Thank you for your valuable time

Appendix No: 2 Monte Carlo Simulation

SLN

O

ASIANPAINTS MINDTREE LUPINLTD HCL HUL YESBANK HDFC BANK

SIMULATED

PRICE

VALUE SIMULA

TED

PRICE

VALUE SIMULATED

PRICE

VALUE SIMULA

TED

PRICE

VALUE SIMULATED

PRICE

VALUE SIMULATED

PRICE

VALUE SIMULATED

PRICE

VALUE

1 178.2 3104101.4 914.4 1313992.9 647.1 1032117.0 774.8 868541.7 473.7 435301.5 446.0 302409.5 632.5 48071.2

2 178.4 3108700.4 877.6 1261154.6 616.4 983134.5 786.5 881643.0 484.7 445395.5 414.6 281088.8 616.8 46873.6

3 173.2 3017884.3 932.7 1340263.1 627.5 1000904.5 796.1 892441.6 462.1 424676.4 442.4 299948.6 619.6 47089.7

4 170.6 2972352.2 944.2 1356836.8 624.7 996420.5 759.8 851758.5 478.4 439663.7 445.9 302346.0 596.3 45318.7

5 171.4 2985680.1 907.3 1303777.1 668.7 1066644.7 785.0 880023.6 474.2 435752.2 460.7 312387.1 632.6 48075.6

6 173.9 3029960.4 924.2 1328095.1 610.9 974441.4 839.4 940917.5 476.9 438231.1 434.6 294672.4 619.5 47083.5

7 180.8 3150318.8 917.4 1318325.7 616.1 982621.9 770.4 863634.0 482.2 443140.3 429.0 290895.3 622.5 47308.1

8 173.5 3022688.4 907.6 1304189.1 603.4 962422.5 775.8 869629.0 466.3 428544.8 440.5 298648.4 626.1 47586.3

9 175.6 3060031.1 908.6 1305697.4 630.5 1005667.5 813.0 911404.6 486.3 446933.7 421.8 286005.6 631.4 47984.0

10 172.4 3003493.2 918.9 1320492.2 642.2 1024330.9 764.8 857350.2 487.0 447528.7 441.1 299046.7 636.7 48388.0

11 176.7 3079029.5 874.9 1257164.3 674.2 1075301.6 803.8 901101.1 458.1 421006.2 420.9 285342.4 607.9 46202.2

12 179.9 3134597.6 916.6 1317197.2 599.2 955763.2 782.6 877303.8 480.0 441134.7 427.0 289529.7 602.0 45751.9

13 174.8 3044627.2 887.2 1274888.7 672.2 1072128.4 816.3 915039.9 474.1 435715.1 436.8 296156.1 624.1 47431.6

14 172.7 3009316.4 911.5 1309850.7 651.6 1039349.5 830.3 930727.1 466.3 428558.9 434.3 294449.2 639.6 48605.9

15 175.8 3062274.5 869.5 1249484.9 618.1 985885.0 728.2 816330.6 473.2 434867.3 437.5 296636.1 615.4 46772.4

16 171.8 2992934.8 955.3 1372720.9 657.8 1049201.3 820.2 919439.1 467.3 429439.1 411.9 279241.9 612.1 46521.8

17 173.8 3028696.8 918.8 1320327.8 645.2 1029030.3 761.7 853913.1 481.5 442461.3 427.9 290137.5 609.6 46326.0

18 174.9 3047206.3 922.9 1326238.5 654.5 1043883.4 806.8 904379.2 471.6 433414.6 414.5 281036.2 616.6 46863.7

19 172.7 3009312.0 892.2 1282162.2 621.4 991053.7 787.7 883001.6 459.2 422017.9 444.5 301401.5 637.7 48467.5

20 171.7 2991860.5 897.5 1289767.5 664.2 1059376.0 811.3 909510.2 466.0 428250.7 419.6 284472.8 622.6 47320.2

21 173.9 3029757.3 929.9 1336325.1 627.3 1000546.2 750.5 841290.6 479.0 440229.7 424.6 287896.8 620.0 47117.6

22 176.8 3080089.9 911.4 1309649.2 571.6 911625.3 798.7 895366.8 472.5 434203.8 449.9 305010.5 633.4 48138.8

23 173.4 3021212.0 884.3 1270667.5 610.0 972969.0 816.0 914758.9 449.7 413276.0 433.4 293843.2 626.5 47613.9

24 176.4 3072424.7 905.5 1301252.9 658.8 1050712.1 785.0 879944.4 482.2 443136.1 419.1 284121.8 616.5 46851.3

25 170.0 2961009.8 871.0 1251640.4 624.0 995216.6 809.8 907804.6 473.2 434877.6 427.2 289629.8 632.0 48029.0

26 176.1 3067643.8 929.0 1334911.0 644.7 1028334.1 825.3 925123.8 467.3 429486.3 418.5 283768.0 627.9 47723.3

27 175.4 3055484.8 898.7 1291410.3 561.5 895524.9 784.7 879650.1 485.1 445809.5 432.9 293473.5 605.4 46009.7

28 170.8 2976168.2 971.4 1395892.6 636.0 1014454.2 767.0 859808.0 459.0 421863.2 411.0 278629.1 633.9 48179.1

29 181.9 3168767.1 911.9 1310364.3 617.7 985152.0 755.2 846545.4 463.8 426189.7 434.5 294600.5 593.8 45126.6

30 174.0 3031334.2 925.4 1329811.2 622.3 992604.5 769.9 863060.7 476.6 437984.1 435.3 295133.0 625.4 47533.2

31 179.3 3123182.8 907.8 1304507.0 679.3 1083494.2 813.2 911641.0 477.9 439168.9 418.3 283602.9 631.6 47999.7

32 174.9 3046983.3 921.9 1324752.9 635.0 1012827.0 818.3 917361.6 476.6 438029.5 438.2 297080.3 621.7 47247.4

33 173.7 3026738.5 884.5 1271093.0 615.5 981691.5 765.5 858168.2 467.2 429322.5 456.1 309218.1 624.8 47485.2

34 179.4 3126237.4 918.1 1319247.2 641.7 1023433.4 821.1 920402.1 476.0 437466.8 446.1 302441.2 616.5 46857.0

35 169.7 2957127.5 935.0 1343635.5 630.0 1004897.5 780.0 874408.2 470.6 432493.8 409.6 277714.4 623.5 47384.1

36 175.3 3054136.4 898.9 1291763.3 593.1 946023.7 794.5 890627.8 454.9 418098.2 437.7 296779.0 614.6 46710.9

37 171.8 2992745.6 889.1 1277634.5 648.3 1034101.7 790.2 885772.5 467.3 429469.9 414.9 281316.7 638.8 48545.3

38 173.5 3023442.3 882.5 1268086.9 612.9 977540.4 793.9 889919.9 462.6 425125.8 449.4 304711.7 615.3 46761.4

39 172.7 3008381.3 908.7 1305784.6 643.1 1025807.1 752.4 843424.2 473.0 434700.1 414.4 280996.1 630.1 47886.7

40 176.1 3067480.3 943.8 1356285.1 591.8 943867.7 781.2 875760.3 463.0 425538.3 438.9 297559.1 631.6 48001.7

41 175.7 3061672.3 929.1 1335148.0 665.2 1061069.7 767.3 860166.3 481.7 442669.1 409.1 277375.6 603.7 45877.7

42 171.6 2989325.5 886.3 1273589.6 615.4 981485.7 821.8 921189.0 482.4 443321.1 437.2 296451.4 606.0 46057.0

43 177.6 3094391.1 903.2 1297954.9 675.3 1077076.0 767.9 860780.6 458.2 421122.7 423.1 286829.1 629.5 47839.8

44 171.6 2990353.8 918.6 1320092.0 614.2 979576.4 779.7 874061.2 470.3 432192.6 418.0 283385.3 619.2 47058.1

45 173.8 3027170.2 919.6 1321485.2 682.0 1087834.4 817.1 916013.0 465.6 427913.1 434.7 294743.1 620.9 47186.7

46 170.7 2973083.4 919.4 1321181.8 674.7 1076165.0 829.7 930066.4 463.5 425916.9 437.1 296368.6 618.7 47019.1

47 174.2 3034073.0 910.3 1308161.5 577.2 920563.2 785.1 880044.3 469.4 431338.7 433.3 293803.9 640.6 48683.1

48 175.2 3052516.3 919.6 1321480.8 638.7 1018698.2 789.3 884784.7 479.0 440242.8 449.0 304426.3 612.8 46573.7

49 175.9 3064789.8 880.8 1265738.1 602.8 961478.4 761.5 853653.2 456.2 419206.5 396.1 268548.5 623.5 47389.7

50 171.8 2993612.3 886.6 1274046.6 636.5 1015262.1 807.9 905629.7 468.2 430294.0 425.2 288310.5 649.4 49353.0

51 172.3 3002532.3 896.4 1288181.6 599.1 955634.2 797.9 894447.4 470.4 432284.9 431.0 292243.0 629.0 47804.3

52 176.3 3072042.1 903.4 1298245.8 586.5 935515.5 800.1 896945.6 460.6 423335.2 411.0 278677.7 630.4 47910.9

53 182.4 3178378.3 911.8 1310275.3 623.8 994932.7 756.5 848061.7 472.0 433802.6 458.8 311043.3 625.0 47501.7

54 175.8 3061934.0 900.5 1294083.5 610.3 973443.3 779.9 874273.2 468.9 430923.3 450.9 305705.5 634.9 48253.9

55 172.8 3011148.3 922.7 1325910.1 625.7 998040.9 745.3 835474.6 475.3 436792.1 450.9 305737.0 600.6 45642.7

56 170.5 2970310.2 934.7 1343173.0 643.0 1025599.0 783.4 878193.4 486.5 447125.1 426.7 289269.4 612.6 46558.2

57 169.5 2952882.6 924.9 1329033.3 621.2 990781.3 784.9 879903.2 473.2 434914.1 432.4 293166.7 628.2 47739.4

58 177.9 3099416.1 906.2 1302247.9 636.5 1015150.4 730.4 818755.2 471.5 433298.3 428.6 290580.3 621.4 47223.5

59 179.4 3125012.9 898.3 1290920.2 643.5 1026425.1 744.0 833970.8 463.0 425469.8 453.5 307479.4 623.7 47404.9

60 174.5 3040854.7 905.9 1301755.8 659.9 1052501.1 768.6 861648.9 477.7 439000.6 460.5 312197.7 618.0 46964.3

61 174.4 3037730.7 891.8 1281566.6 623.8 994981.4 775.9 869764.3 479.6 440721.0 410.1 278029.3 615.0 46743.5

62 178.8 3114632.2 927.6 1332947.7 628.2 1001929.1 766.0 858721.6 464.7 427029.2 435.9 295558.3 608.1 46218.5

63 175.7 3061156.9 884.9 1271625.6 659.3 1051567.9 780.2 874651.4 478.6 439851.1 424.2 287584.4 599.0 45522.7

64 175.8 3061944.8 867.4 1246413.9 634.9 1012692.0 789.7 885271.7 444.4 408426.9 450.2 305248.9 632.3 48053.3

65 170.7 2974303.5 929.5 1335709.1 674.5 1075759.1 762.5 854763.6 464.8 427127.3 453.6 307511.6 614.2 46677.3

66 173.6 3025057.8 887.4 1275258.1 574.9 916940.1 797.5 893990.6 471.2 433018.5 457.8 310387.1 622.9 47337.3

67 173.0 3013946.9 883.5 1269615.1 667.0 1063889.2 795.7 892010.2 473.5 435110.8 445.7 302204.3 628.6 47772.7

68 177.8 3098457.4 943.2 1355401.0 640.8 1022004.6 814.8 913338.9 460.2 422914.5 401.9 272457.0 610.2 46372.8

69 178.1 3102288.4 849.7 1220977.4 638.2 1017915.0 752.9 843981.0 474.1 435724.2 429.6 291239.6 631.0 47957.3

70 177.2 3086418.1 886.5 1273959.8 561.8 896140.4 814.9 913472.4 474.7 436220.2 437.1 296372.2 650.6 49448.3

71 172.9 3012406.8 896.6 1288361.9 619.3 987851.0 755.8 847256.6 463.6 426036.1 448.0 303717.1 612.4 46544.4

72 174.8 3045181.6 923.8 1327520.0 644.1 1027333.7 806.0 903511.5 468.6 430623.1 426.9 289444.9 615.6 46788.4

73 168.9 2942724.0 910.3 1308063.3 621.6 991470.0 786.1 881226.2 470.5 432425.0 430.4 291800.6 644.7 48994.6

74 175.1 3050771.6 860.6 1236709.4 666.0 1062204.3 790.3 885947.4 451.2 414620.1 434.5 294615.4 621.1 47204.5

75 169.2 2948585.1 885.4 1272257.6 638.1 1017838.1 785.8 880849.1 474.3 435871.4 452.6 306896.7 622.2 47286.9

76 171.1 2980428.2 886.2 1273498.4 668.5 1066333.6 798.5 895117.3 470.0 431889.4 431.4 292522.1 634.8 48244.4

77 175.9 3064038.8 863.5 1240864.1 659.8 1052451.5 783.6 878421.7 468.3 430388.4 457.2 309981.9 612.1 46516.4

78 171.6 2989958.6 925.4 1329757.8 634.1 1011357.4 797.0 893409.6 475.0 436541.3 433.9 294213.1 632.5 48067.1

79 171.3 2984510.4 906.4 1302429.5 583.3 930438.7 784.3 879255.0 466.0 428238.8 420.0 284786.4 623.4 47376.4

80 182.1 3173409.4 915.6 1315735.4 604.2 963772.7 780.0 874363.7 462.9 425422.7 416.2 282194.1 639.0 48566.7

81 176.7 3079156.4 907.6 1304196.7 672.5 1072703.2 763.2 855494.1 474.4 435939.2 443.0 300327.9 631.1 47961.5

82 174.3 3036375.1 902.2 1296456.8 624.7 996402.3 796.8 893160.1 458.0 420867.0 434.6 294661.0 621.6 47240.6

83 177.1 3084600.4 929.7 1335958.7 640.3 1021235.3 799.5 896255.7 453.7 416944.1 462.9 313823.1 602.5 45792.6

84 171.7 2991021.9 953.0 1369458.6 661.6 1055183.1 809.6 907551.4 467.8 429941.1 410.9 278593.1 600.8 45657.8

85 174.9 3047032.8 830.1 1192903.7 629.6 1004195.4 769.1 862205.8 459.8 422515.4 435.9 295570.9 635.0 48256.2

86 176.7 3078699.6 878.1 1261812.7 700.5 1117261.5 771.3 864673.7 456.2 419274.8 427.1 289586.8 607.4 46158.7

87 176.1 3068190.7 882.7 1268501.0 640.6 1021702.5 786.2 881377.5 468.4 430503.8 427.7 290009.5 634.3 48206.4

88 173.6 3024457.8 915.8 1315966.2 609.7 972411.9 788.6 884056.8 480.9 441924.6 448.8 304299.4 648.5 49285.4

89 174.3 3037367.6 924.1 1327894.7 632.9 1009467.0 809.6 907598.8 468.7 430776.1 413.4 280270.3 634.1 48195.1

90 177.5 3091726.6 905.4 1301116.0 661.6 1055188.7 755.1 846442.9 465.4 427744.0 415.4 281651.1 618.4 46998.0

91 176.0 3066332.5 879.3 1263549.4 646.9 1031816.4 761.4 853531.1 458.4 421260.8 425.9 288730.6 635.1 48267.2

92 174.5 3039441.2 866.3 1244819.4 621.5 991292.6 774.3 868021.6 471.3 433152.9 447.5 303396.4 609.7 46337.3

93 172.5 3006023.6 896.5 1288335.8 601.6 959628.4 789.3 884799.0 473.7 435295.5 429.8 291429.0 624.3 47443.1

94 167.7 2920985.6 883.4 1269439.9 636.5 1015295.2 765.5 858086.1 483.0 443866.7 431.1 292310.6 637.2 48427.3

95 172.6 3007177.2 941.3 1352617.2 669.1 1067171.2 790.3 885886.1 472.7 434414.4 426.4 289112.0 628.4 47757.3

96 173.7 3026521.3 907.2 1303692.3 619.6 988206.9 774.3 867999.2 479.0 440216.0 421.0 285464.6 623.8 47410.9

97 173.6 3024997.8 861.4 1237885.3 623.2 993967.6 783.9 878791.7 458.3 421210.9 422.7 286581.4 624.3 47449.2

98 174.0 3031058.5 936.1 1345156.5 621.9 991991.9 800.4 897271.4 466.3 428575.2 441.7 299501.1 609.0 46286.9

99 173.0 3013978.3 914.5 1314195.7 628.5 1002388.7 835.5 936589.0 471.0 432876.0 439.3 297855.3 636.9 48408.0

100 178.5 3110675.9 894.5 1285396.8 642.6 1024882.5 809.8 907773.2 474.8 436365.6 438.0 296968.7 645.5 49061.7

101 178.8 3114747.9 907.9 1304658.8 686.3 1094580.3 818.2 917210.2 471.3 433100.0 443.3 300575.9 629.9 47872.4

102 180.4 3143162.1 909.1 1306314.1 537.2 856868.0 801.5 898432.5 478.5 439731.6 439.7 298092.0 623.5 47389.6

103 170.7 2974553.4 934.3 1342574.9 630.8 1006136.7 783.1 877855.3 467.6 429678.8 442.9 300315.0 631.0 47956.9

104 176.9 3081768.2 921.5 1324210.6 613.2 978109.1 772.1 865530.5 469.7 431689.4 442.2 299800.0 626.9 47646.4

105 165.6 2885473.1 901.8 1295902.8 618.6 986711.8 805.3 902740.7 483.7 444482.1 437.4 296529.5 615.8 46800.4

106 173.1 3015923.9 899.0 1291862.5 597.5 953082.0 797.8 894290.2 463.3 425770.6 400.7 271663.2 619.2 47058.0

107 173.4 3021474.2 921.6 1324375.0 622.7 993144.8 785.3 880345.1 475.7 437147.8 427.7 289953.3 626.5 47615.4

108 174.5 3039609.1 921.3 1323847.4 655.4 1045287.5 770.1 863336.7 475.2 436748.0 440.1 298403.2 646.4 49125.8

109 175.7 3060480.7 894.1 1284848.6 629.4 1003901.5 795.5 891786.0 461.4 424062.3 435.6 295347.1 616.5 46854.4

110 177.0 3083071.6 888.5 1276798.7 723.3 1153690.4 738.1 827432.5 465.0 427302.6 425.1 288217.1 632.2 48050.8

111 179.9 3133675.8 888.1 1276174.5 651.7 1039515.6 814.3 912832.5 477.8 439083.0 415.4 281629.5 627.7 47706.2

112 171.3 2984000.7 940.8 1351964.3 663.2 1057854.7 789.2 884650.3 486.3 446922.6 456.1 309232.0 621.9 47261.2

113 176.0 3065909.3 876.3 1259290.8 638.8 1018809.3 771.0 864241.7 462.8 425288.6 401.8 272427.0 641.9 48781.3

114 169.5 2952517.9 911.2 1309394.6 602.0 960133.2 789.2 884640.0 474.5 436046.6 434.1 294305.3 622.6 47319.5

115 179.9 3135009.5 906.6 1302791.4 655.3 1045195.4 767.9 860775.2 472.0 433736.7 429.3 291047.1 644.1 48953.7

116 173.6 3024968.2 868.0 1247292.7 638.5 1018481.1 784.9 879854.8 461.0 423682.1 416.4 282316.8 608.2 46220.7

117 170.5 2970890.7 928.6 1334409.2 635.0 1012885.1 783.1 877847.7 475.3 436787.4 430.3 291736.7 631.4 47988.8

118 174.1 3032759.6 883.9 1270201.1 671.4 1070899.8 798.6 895209.5 482.6 443497.8 425.5 288500.9 624.7 47478.3

119 175.0 3048317.2 849.3 1220500.6 642.9 1025389.5 794.3 890430.3 465.4 427704.7 439.1 297738.2 649.7 49380.6

120 173.1 3016422.9 858.8 1234025.1 605.9 966456.4 754.6 845921.0 466.1 428330.4 413.1 280064.4 632.1 48038.9

121 170.6 2971818.2 901.0 1294767.4 650.1 1036926.5 776.1 870011.8 467.9 429992.2 471.6 319756.4 635.6 48307.5

122 175.0 3049687.6 901.6 1295544.0 630.2 1005129.2 790.1 885702.8 471.3 433100.8 437.0 296319.5 636.4 48367.6

123 171.6 2990210.7 921.8 1324619.2 607.8 969443.4 837.4 938711.5 484.7 445454.3 436.4 295867.5 615.1 46751.2

124 175.5 3057160.8 897.9 1290329.9 609.6 972305.0 749.3 839999.5 485.2 445899.9 435.7 295395.7 643.3 48889.4

125 177.9 3099199.5 883.4 1269410.4 664.9 1060465.5 811.8 909971.8 477.3 438635.8 417.0 282712.9 610.7 46415.8

126 175.9 3064424.9 927.6 1333012.7 603.9 963281.0 779.8 874128.5 468.7 430758.3 414.8 281226.8 622.9 47339.4

127 175.3 3053681.1 904.1 1299258.4 613.5 978537.7 772.9 866383.8 468.0 430071.8 420.3 284953.8 604.8 45964.0

128 175.9 3064534.3 893.4 1283862.8 650.8 1038035.6 794.9 891106.8 479.0 440238.6 428.8 290737.3 631.4 47986.1

129 175.3 3053581.1 898.8 1291575.0 666.4 1062962.4 776.3 870273.3 457.9 420783.1 418.5 283761.6 628.2 47744.7

130 172.0 2997088.1 897.9 1290262.8 653.4 1042183.8 772.2 865661.2 472.1 433872.8 417.7 283182.2 606.8 46117.8

131 176.9 3082712.6 942.1 1353741.5 653.0 1041572.7 765.6 858288.5 458.7 421515.8 440.3 298550.0 593.0 45065.8

132 173.5 3022416.8 894.8 1285777.0 658.1 1049649.9 797.4 893917.4 464.5 426916.7 432.0 292911.8 629.9 47871.4

133 171.8 2992324.2 911.4 1309729.6 631.5 1007320.1 777.0 871054.2 463.5 425923.9 425.9 288771.5 634.3 48209.9

134 172.1 2999055.4 917.3 1318132.8 621.2 990756.4 829.5 929864.2 465.1 427423.1 453.4 307423.5 603.0 45826.2

135 173.5 3022328.1 936.3 1345450.2 630.0 1004902.9 802.4 899543.3 469.4 431361.5 418.9 283988.9 602.7 45803.7

136 173.8 3027736.3 886.1 1273392.7 644.9 1028657.5 780.2 874565.6 472.1 433822.5 454.3 308036.2 599.1 45532.5

137 178.1 3103642.7 914.5 1314105.0 689.0 1098950.3 786.0 881120.5 468.1 430213.1 415.1 281463.1 635.1 48266.1

138 170.8 2975925.6 922.7 1325979.5 625.9 998330.0 810.9 909053.9 469.5 431514.9 442.1 299753.3 620.5 47155.5

139 169.5 2953107.1 886.3 1273601.0 597.1 952441.6 774.9 868612.9 478.8 440027.1 432.9 293522.9 649.2 49341.3

140 174.8 3045634.2 923.3 1326788.4 658.6 1050487.1 824.4 924204.2 484.3 445039.6 421.3 285672.4 638.8 48549.1

141 178.1 3102532.2 871.4 1252254.7 617.2 984373.6 773.5 867066.8 461.4 423990.9 438.6 297397.5 624.1 47433.0

142 172.0 2996041.8 925.2 1329520.0 585.7 934249.5 759.7 851679.2 470.9 432765.5 423.2 286935.1 630.1 47888.7

143 174.0 3032090.0 874.0 1255875.2 630.0 1004859.3 752.8 843935.9 475.6 437122.2 441.9 299640.3 621.3 47218.7

144 173.2 3017562.1 874.8 1257135.2 638.6 1018529.1 777.5 871618.2 455.2 418296.8 422.8 286635.9 639.4 48594.4

145 171.5 2988250.7 920.4 1322580.5 637.4 1016630.3 788.6 883981.0 468.4 430465.5 438.1 297030.8 617.5 46929.7

146 176.5 3074938.8 925.9 1330561.6 645.1 1028863.0 813.1 911482.8 471.5 433335.3 418.1 283501.0 617.2 46908.2

147 171.7 2991349.4 900.9 1294558.2 661.1 1054455.0 817.0 915901.4 469.0 431034.5 442.1 299767.3 621.4 47225.8

148 171.4 2985351.5 908.0 1304795.9 714.4 1139398.7 775.2 869054.5 475.1 436600.3 424.1 287509.1 621.5 47233.0

149 176.0 3066052.8 886.3 1273673.5 618.5 986437.8 768.8 861770.1 479.4 440528.6 424.8 288032.9 643.1 48875.9

150 171.9 2995285.3 904.9 1300319.3 594.5 948262.2 750.6 841423.8 465.7 427998.9 431.6 292642.6 636.2 48350.8

151 171.6 2989094.6 901.9 1296066.1 606.7 967739.6 784.2 879068.4 474.4 436002.4 419.4 284383.1 642.4 48822.0

152 177.1 3084929.8 902.0 1296219.6 622.3 992497.3 814.8 913392.8 482.8 443724.4 414.8 281257.1 626.6 47624.3

153 176.3 3070861.1 913.1 1312090.6 627.5 1000858.3 812.8 911197.4 479.0 440173.7 427.2 289649.0 628.0 47729.9

154 174.0 3032244.6 889.5 1278242.4 608.2 970109.6 750.2 841013.7 476.7 438125.7 431.5 292588.5 661.9 50302.5

155 178.3 3106460.7 873.8 1255657.8 624.2 995658.0 740.2 829751.6 467.6 429703.8 405.9 275221.1 623.9 47419.0

156 173.7 3026120.2 900.0 1293345.6 664.3 1059617.0 809.1 906992.2 475.5 436966.7 430.6 291953.9 620.5 47155.3

157 174.6 3041433.6 903.5 1298388.2 674.2 1075364.7 798.0 894515.6 469.1 431077.8 431.4 292474.1 628.3 47753.1

158 168.2 2930865.2 919.8 1321792.6 721.2 1150352.9 814.9 913483.2 473.2 434852.7 439.2 297763.0 623.9 47415.9

159 173.0 3013154.2 906.8 1303007.2 636.8 1015746.2 805.4 902811.0 480.0 441157.1 426.9 289406.2 630.5 47920.1

160 175.3 3054254.4 909.4 1306847.2 617.4 984780.8 762.0 854244.8 462.3 424814.8 450.2 305269.0 657.4 49961.6

161 175.9 3064584.4 923.6 1327234.3 617.3 984562.9 784.4 879339.9 471.4 433199.1 448.6 304183.2 630.3 47899.8

162 173.3 3018695.5 913.4 1312581.7 631.4 1007157.0 763.6 855961.9 476.6 437957.7 408.9 277224.8 619.9 47109.6

163 176.9 3081450.9 892.5 1282468.9 637.1 1016252.7 778.2 872390.4 463.8 426271.3 428.7 290632.6 615.2 46756.6

164 173.8 3027489.6 874.2 1256205.1 634.8 1012517.9 745.0 835138.7 466.0 428241.9 437.0 296292.5 636.6 48383.0

165 178.5 3110296.6 927.8 1333260.9 623.2 993996.8 782.6 877317.8 462.0 424597.9 426.6 289266.8 636.3 48359.8

166 174.3 3036661.2 886.8 1274304.0 622.4 992664.6 760.9 852954.1 472.3 434001.3 436.7 296113.8 623.5 47385.6

167 178.7 3113170.1 906.4 1302469.7 634.4 1011901.0 804.8 902187.3 461.9 424457.0 437.1 296324.4 639.5 48604.4

168 170.3 2966934.6 950.0 1365203.1 646.0 1030373.4 767.1 859906.4 468.1 430144.8 448.4 304005.2 628.6 47772.2

169 175.4 3054968.6 944.1 1356727.5 631.6 1007440.0 794.5 890652.3 458.2 421083.9 446.7 302894.5 621.9 47265.3

170 173.0 3013640.4 932.6 1340109.4 625.6 997807.9 769.0 862009.3 457.6 420580.1 459.9 311834.6 627.9 47717.6

171 176.6 3076076.2 912.6 1311353.7 638.1 1017827.5 740.5 830075.0 477.0 438353.8 439.5 298006.3 618.3 46991.9

172 175.5 3057589.4 911.0 1309044.4 611.7 975586.4 800.5 897395.2 465.9 428197.7 458.1 310618.0 606.2 46068.3

173 174.5 3039634.9 951.4 1367099.9 618.1 985912.7 801.0 897886.4 474.0 435563.0 413.6 280437.9 619.4 47077.9

174 172.2 3000255.5 895.8 1287272.9 602.6 961165.1 789.3 884857.5 473.0 434723.3 435.2 295046.9 628.9 47795.3

175 177.5 3092102.9 928.3 1333908.8 623.3 994140.5 799.8 896526.8 487.7 448191.8 420.0 284783.8 625.7 47549.6

176 176.7 3077934.2 907.4 1303895.8 699.5 1115734.3 766.1 858847.1 468.2 430287.9 421.7 285911.2 611.4 46469.0

177 170.0 2960879.6 921.8 1324598.0 621.1 990585.1 788.0 883366.6 469.3 431248.6 450.3 305277.1 636.7 48392.8

178 169.4 2951337.8 927.8 1333270.2 659.6 1052101.1 774.8 868594.0 471.0 432852.8 433.3 293745.4 606.9 46120.8

179 167.0 2908699.7 923.0 1326325.9 639.5 1020016.9 737.3 826568.0 471.1 432931.4 426.8 289359.4 654.8 49761.2

180 173.8 3028794.5 908.9 1306159.3 614.9 980716.4 813.5 911906.1 475.2 436708.1 412.4 279637.2 645.4 49046.8

181 173.3 3019469.5 895.9 1287455.1 620.9 990388.3 756.1 847543.3 479.5 440680.5 435.9 295546.4 618.9 47038.0

182 173.0 3013431.1 886.6 1274032.2 673.9 1074945.9 758.0 849690.4 471.6 433411.3 427.9 290108.4 630.6 47922.8

183 170.6 2972978.7 942.1 1353786.9 657.8 1049163.5 834.1 934998.0 475.0 436510.9 438.0 296937.0 652.3 49572.4

184 177.3 3089276.1 934.6 1343003.7 673.7 1074566.4 821.2 920534.1 489.4 449734.5 418.3 283590.4 604.3 45929.8

185 172.2 3000589.3 894.7 1285637.4 598.4 954372.1 774.4 868098.4 478.2 439479.6 421.2 285588.0 642.5 48827.3

186 166.4 2898751.5 891.4 1280963.3 661.2 1054615.3 780.0 874396.9 465.1 427421.5 441.3 299181.3 626.8 47635.4

187 171.9 2995191.6 898.1 1290523.8 585.0 933055.6 816.7 915488.7 477.1 438486.0 439.4 297920.9 644.2 48962.8

188 176.0 3065439.7 865.8 1244209.2 576.9 920086.7 812.0 910218.5 479.2 440415.8 423.1 286865.5 608.5 46245.8

189 173.5 3022082.1 919.6 1321411.1 633.4 1010249.8 788.2 883609.6 480.8 441828.5 432.6 293324.7 630.4 47907.5

190 177.2 3086810.9 929.9 1336282.6 629.3 1003809.3 779.4 873736.1 473.2 434914.1 434.4 294492.8 618.8 47030.3

191 175.2 3052387.2 894.4 1285270.6 633.2 1009967.2 783.7 878556.1 490.6 450853.0 407.0 275972.7 621.8 47254.0

192 177.2 3087823.9 929.3 1335399.0 678.5 1082285.7 774.3 867963.9 468.5 430542.0 452.6 306895.5 626.7 47627.9

193 174.2 3034789.9 844.2 1213137.1 621.6 991408.7 811.5 909675.8 475.4 436889.7 415.0 281392.2 619.0 47040.7

194 172.6 3007254.4 958.9 1377936.9 651.9 1039838.9 732.2 820828.7 458.1 420967.7 430.1 291639.2 624.7 47476.2

195 172.5 3005234.6 953.4 1370105.6 546.3 871276.0 803.2 900439.4 468.9 430923.1 449.2 304549.6 621.7 47246.2

196 172.3 3001919.3 939.3 1349726.9 573.5 914685.1 778.7 872954.9 475.5 436991.5 439.0 297670.5 617.1 46898.9

197 174.6 3041590.5 885.4 1272317.7 658.2 1049815.2 840.9 942628.8 482.8 443649.4 432.0 292900.6 615.6 46783.4

198 170.9 2977041.0 926.7 1331675.0 585.8 934293.5 757.4 849060.6 456.5 419486.2 461.0 312562.5 636.2 48353.8

199 174.3 3036631.1 917.6 1318633.2 637.7 1017169.9 783.8 878641.6 483.3 444146.4 411.3 278850.1 621.6 47238.4

200 173.7 3026249.7 909.7 1307287.2 559.7 892768.6 815.6 914318.8 488.5 448908.8 448.1 303803.5 635.9 48330.7

201 177.2 3087184.0 911.8 1310211.4 614.7 980420.8 752.8 843927.2 473.9 435517.1 424.5 287779.8 608.5 46246.8

202 180.5 3144180.9 880.8 1265663.3 686.7 1095360.3 792.2 888026.3 461.4 424024.7 425.9 288760.4 627.0 47651.2

203 177.0 3083911.7 927.9 1333359.2 654.7 1044205.4 812.6 910900.3 466.0 428278.6 451.7 306263.4 626.0 47578.8

204 173.7 3026957.0 806.8 1159396.5 632.5 1008795.0 790.4 886013.3 481.8 442808.2 423.2 286925.9 608.0 46205.3

205 174.8 3045323.4 877.9 1261538.0 629.7 1004372.4 770.0 863193.7 476.4 437804.6 428.1 290220.8 626.3 47598.1

206 171.1 2980879.3 898.7 1291463.7 622.9 993468.4 834.6 935639.3 475.5 436997.1 429.4 291122.4 636.2 48353.3

207 178.0 3100764.3 891.5 1281084.5 634.9 1012623.9 765.2 857764.2 474.6 436143.7 422.7 286608.3 636.3 48356.1

208 170.4 2968447.2 904.8 1300142.4 662.9 1057336.2 805.2 902583.2 474.9 436464.5 447.2 303199.3 634.1 48193.4

209 171.3 2984721.4 887.6 1275498.1 614.0 979315.3 840.6 942302.2 494.5 454481.1 439.5 297949.7 634.8 48247.8

210 171.5 2988567.2 888.5 1276788.2 673.5 1074215.1 825.8 925742.6 470.7 432548.9 450.6 305502.4 612.6 46560.9

211 175.7 3061889.8 903.5 1298393.8 684.6 1091871.5 792.4 888275.6 471.0 432819.4 431.0 292190.3 621.4 47230.1

212 172.6 3006693.4 864.8 1242756.3 672.5 1072577.8 803.5 900697.3 469.3 431291.0 432.8 293445.0 622.4 47299.8

213 179.9 3134397.5 885.6 1272567.9 629.8 1004526.7 812.7 911053.0 475.2 436683.4 433.5 293894.0 657.6 49975.2

214 171.7 2991661.3 901.5 1295422.4 603.5 962609.7 792.8 888726.4 479.6 440735.9 455.5 308811.6 616.7 46867.5

215 174.3 3036771.2 893.0 1283222.8 611.6 975532.9 817.8 916805.3 462.8 425330.9 445.3 301908.4 613.8 46650.1

216 175.2 3052572.8 901.8 1295933.1 619.5 988102.5 776.6 870622.4 466.8 429012.7 420.7 285217.2 636.6 48383.8

217 175.1 3049852.7 886.0 1273157.4 709.1 1131074.3 772.4 865862.6 465.9 428180.2 434.8 294811.6 624.0 47421.8

218 172.0 2996915.4 866.4 1244998.6 675.8 1077935.3 768.2 861182.9 462.8 425288.2 427.7 289989.3 623.8 47409.6

219 173.4 3021360.6 873.5 1255228.0 631.2 1006696.8 834.1 935004.2 469.4 431344.8 438.2 297090.5 623.1 47352.8

220 177.8 3097116.9 889.4 1278049.8 595.9 950421.5 789.4 884962.7 483.7 444477.9 425.0 288179.3 605.3 46002.2

221 174.5 3040961.7 863.3 1240556.6 648.2 1033871.3 819.6 918810.0 490.0 450353.7 428.8 290759.2 621.4 47228.5

222 178.6 3111736.4 869.4 1249364.3 639.7 1020290.9 787.5 882773.8 469.9 431878.4 422.9 286749.5 630.8 47937.7

223 178.2 3103800.1 928.0 1333604.9 708.4 1129928.7 808.7 906570.1 479.3 440453.0 428.9 290776.5 636.1 48339.8

224 176.6 3077203.1 864.5 1242220.1 576.7 919800.6 777.5 871631.2 463.8 426238.4 427.7 290008.2 634.5 48223.6

225 169.8 2957802.7 886.0 1273149.2 650.9 1038189.1 775.0 868758.1 468.3 430360.5 438.2 297096.0 631.3 47977.6

226 179.3 3123882.6 903.8 1298808.2 651.5 1039108.9 786.8 881977.1 471.8 433571.1 433.7 294050.6 599.3 45543.1

227 178.2 3104517.0 981.0 1409690.4 674.2 1075341.8 781.3 875826.6 462.0 424553.6 399.8 271037.3 613.5 46628.7

228 173.8 3028041.8 903.7 1298630.0 650.4 1037391.1 784.5 879400.2 493.1 453136.2 416.3 282219.7 625.1 47510.8

229 175.1 3050794.4 894.5 1285426.5 606.1 966706.7 793.6 889659.7 468.7 430720.9 398.0 269863.4 622.2 47285.0

230 176.4 3073589.3 905.4 1301062.0 616.0 982490.4 753.4 844606.3 464.9 427250.0 425.0 288166.4 617.3 46915.4

231 175.6 3059208.0 882.1 1267618.9 512.8 817880.5 778.1 872274.2 467.9 430010.3 431.8 292759.4 616.0 46819.7

232 173.5 3022041.8 900.2 1293543.2 596.9 952051.0 808.6 906425.8 470.6 432446.3 439.8 298201.3 636.7 48390.2

233 171.8 2992422.3 924.4 1328339.2 617.7 985269.3 761.4 853491.5 480.5 441566.5 415.1 281413.6 592.2 45008.5

234 175.6 3059515.0 911.2 1309327.6 648.8 1034787.6 793.7 889700.3 474.0 435594.9 444.7 301539.2 626.9 47648.1

235 173.7 3025413.2 937.0 1346513.8 667.9 1065357.2 771.0 864303.5 465.3 427611.0 415.3 281562.9 609.1 46291.2

236 170.4 2968565.6 896.1 1287763.5 620.6 989838.8 829.5 929819.4 489.0 449406.2 446.5 302711.0 624.4 47453.5

237 175.6 3058707.8 900.9 1294616.2 661.8 1055544.1 739.9 829467.2 459.2 422039.0 422.1 286211.0 629.0 47805.9

238 177.6 3093541.6 919.3 1321047.3 573.1 914067.3 785.3 880297.8 450.5 413997.8 435.8 295504.9 638.3 48512.8

239 173.1 3016441.7 935.5 1344363.7 668.0 1065380.3 789.0 884415.5 459.3 422140.4 429.4 291118.2 607.9 46202.2

240 177.3 3088791.6 894.2 1284895.7 643.2 1025854.4 800.2 897044.5 457.1 420073.5 431.5 292529.0 610.6 46408.1

241 169.0 2945113.2 905.0 1300509.3 608.3 970187.5 773.7 867285.7 465.5 427750.8 453.1 307169.0 627.4 47685.3

242 175.4 3055139.4 947.0 1360784.4 630.0 1004880.9 784.2 879075.3 474.7 436247.9 421.6 285866.3 624.7 47479.9

243 172.9 3011753.7 928.1 1333727.4 593.7 946902.7 777.3 871347.5 483.9 444659.5 417.8 283287.9 631.4 47983.2

244 180.9 3152126.7 921.7 1324516.6 561.5 895528.9 775.5 869327.3 485.4 446085.4 442.0 299672.2 633.4 48139.8

245 172.9 3012411.9 903.9 1298964.9 643.1 1025731.4 801.7 898723.1 470.5 432393.7 438.7 297407.0 625.3 47522.8

246 172.5 3005570.4 886.7 1274249.1 703.9 1122785.4 769.5 862579.9 467.4 429543.2 433.4 293824.5 626.6 47624.1

247 174.8 3044738.8 917.3 1318218.8 651.1 1038544.6 815.6 914258.1 470.9 432757.1 428.5 290490.7 601.7 45730.3

248 174.6 3042641.0 892.8 1282958.2 647.0 1031979.7 773.8 867393.7 477.7 438965.7 454.0 307808.3 614.1 46674.5

249 175.6 3059670.4 888.3 1276525.4 631.4 1007137.4 736.7 825874.6 472.7 434411.8 430.1 291618.5 615.2 46757.0

250 178.3 3106263.9 908.5 1305525.0 624.1 995518.0 777.4 871442.2 471.9 433667.0 419.7 284531.2 612.0 46510.7

251 174.5 3039562.8 916.5 1316969.2 635.1 1013013.6 781.7 876320.8 482.4 443283.0 460.2 311989.3 624.8 47485.1

252 171.2 2982907.9 925.9 1330503.2 647.2 1032306.2 799.1 895816.8 461.8 424363.7 427.1 289598.2 636.0 48337.5

253 173.9 3029581.8 921.7 1324508.9 627.6 1001046.8 812.5 910833.3 472.3 434057.3 411.8 279179.1 604.0 45901.3

254 172.2 3000856.5 887.3 1274992.3 658.8 1050722.5 773.1 866619.8 465.5 427801.3 452.3 306632.3 636.2 48348.3

255 177.2 3088012.1 873.9 1255824.1 627.4 1000759.5 749.0 839603.1 480.0 441149.4 435.9 295563.7 647.2 49185.2

256 175.4 3055530.4 933.7 1341723.8 650.1 1036899.6 771.4 864770.3 471.2 433044.1 434.7 294737.5 616.4 46842.8

257 173.3 3019577.3 880.2 1264915.9 661.3 1054758.1 781.5 876075.8 465.0 427372.7 442.3 299887.6 613.8 46646.2

258 178.6 3111722.5 929.7 1335940.6 653.7 1042625.7 790.3 885959.0 467.2 429349.3 446.3 302610.1 620.6 47167.2

259 172.8 3010713.1 920.5 1322749.6 625.4 997522.8 781.5 876086.4 469.1 431080.7 415.6 281782.3 638.9 48559.2

260 172.9 3012584.8 925.8 1330313.8 617.7 985162.7 768.7 861768.4 476.8 438143.5 427.0 289477.0 601.1 45682.0

261 175.9 3065023.6 895.0 1286136.2 610.1 973118.1 802.7 899855.5 467.5 429656.2 429.5 291192.0 640.0 48638.8

262 179.3 3124483.2 918.4 1319781.5 620.3 989405.0 819.6 918751.4 488.4 448795.7 428.5 290553.5 643.1 48876.0

263 177.4 3089820.4 913.0 1312023.9 639.2 1019489.3 744.5 834601.5 477.7 438999.7 435.0 294920.3 610.4 46389.3

264 179.2 3121369.6 887.7 1275593.6 649.6 1036164.2 785.0 879937.1 486.8 447371.8 421.6 285825.4 632.9 48099.2

265 178.0 3101836.7 937.3 1346833.4 663.5 1058262.4 760.1 852061.5 476.8 438220.5 448.8 304297.0 609.2 46297.8

266 172.7 3009374.4 921.6 1324405.6 629.3 1003721.5 744.8 834911.0 478.4 439668.7 425.3 288368.8 627.4 47683.7

267 171.0 2978419.7 906.1 1302135.1 661.1 1054429.5 780.8 875298.2 473.1 434755.7 436.1 295659.2 625.3 47524.9

268 173.1 3016561.9 909.3 1306705.0 620.6 989825.4 766.2 858940.5 476.9 438269.8 433.3 293786.9 622.4 47300.4

269 175.6 3058724.5 886.9 1274407.9 605.1 965180.7 786.3 881497.2 467.4 429572.2 407.3 276125.1 609.1 46292.0

270 174.0 3031173.2 871.7 1252683.9 664.6 1059964.6 775.8 869687.5 482.4 443318.4 448.6 304182.2 630.1 47884.9

271 173.2 3016891.5 931.7 1338895.0 622.1 992324.8 784.5 879399.3 479.8 440954.6 444.5 301354.6 608.5 46249.0

272 171.9 2994479.4 910.8 1308819.0 648.1 1033712.8 843.7 945763.9 465.7 427962.9 468.6 317743.1 619.5 47082.4

273 171.2 2982352.0 921.4 1324038.5 645.0 1028840.8 791.1 886798.4 476.8 438170.8 431.6 292641.9 633.6 48154.7

274 169.0 2944574.1 903.4 1298122.6 689.8 1100206.4 769.1 862146.7 471.7 433493.4 432.3 293129.7 636.2 48354.8

275 177.1 3085336.0 862.4 1239252.1 617.0 984116.2 804.0 901300.6 474.1 435653.7 424.4 287714.4 648.9 49318.0

276 178.5 3110111.9 928.1 1333697.7 643.0 1025662.7 815.5 914166.9 479.8 440923.7 418.0 283404.7 628.7 47778.1

277 171.2 2982176.7 912.2 1310873.5 600.6 957933.1 841.6 943428.0 483.7 444474.6 429.5 291232.2 602.7 45804.1

278 171.1 2981572.5 917.9 1318984.8 631.8 1007794.5 814.7 913334.6 477.0 438368.4 431.5 292544.7 661.3 50256.3

279 171.2 2982438.7 926.2 1330892.8 637.7 1017184.4 757.4 849057.9 488.6 449013.2 436.8 296154.5 610.9 46429.8

280 176.1 3068636.5 922.5 1325654.9 642.0 1023975.6 776.3 870246.2 467.3 429438.5 422.8 286674.9 613.1 46591.9

281 175.9 3063795.5 914.4 1313957.5 627.9 1001494.8 805.4 902891.9 467.1 429238.8 442.2 299817.9 625.3 47523.4

282 173.8 3028166.4 877.7 1261204.3 632.4 1008621.8 802.2 899314.3 477.1 438481.8 438.4 297253.4 637.0 48410.5

283 177.3 3088489.8 888.6 1276933.9 668.2 1065735.7 761.5 853697.4 485.5 446136.9 443.9 300991.7 618.0 46971.2

284 173.1 3016189.8 880.0 1264582.4 617.8 985388.3 750.1 840907.2 487.1 447672.3 439.7 298124.9 634.1 48193.5

285 171.5 2987959.4 879.2 1263398.6 654.7 1044325.4 770.3 863475.4 472.0 433795.2 436.1 295693.9 603.1 45839.2

286 175.9 3063912.5 897.8 1290166.2 586.1 934822.7 817.1 915943.2 460.8 423495.9 441.7 299440.1 611.3 46458.4

287 182.8 3185369.3 890.0 1278888.4 598.1 954005.2 798.8 895476.8 478.9 440132.4 417.3 282949.8 619.2 47059.9

288 173.3 3018906.5 920.4 1322622.1 665.7 1061773.9 822.4 921897.3 472.8 434535.4 430.7 292022.2 637.6 48457.9

289 175.2 3051509.1 900.1 1293467.7 600.0 957058.0 853.7 957021.8 476.5 437906.4 437.0 296268.4 612.6 46558.9

290 173.6 3025246.2 906.4 1302562.9 633.4 1010302.8 756.7 848304.3 465.4 427679.7 448.0 303767.2 632.5 48071.3

291 178.2 3104300.6 919.8 1321730.7 619.8 988518.7 776.4 870371.1 480.2 441302.4 433.3 293808.2 622.5 47307.1

292 175.0 3049250.7 908.7 1305770.9 650.2 1037080.9 793.3 889293.8 463.5 425985.1 444.6 301442.8 628.3 47749.5

293 175.2 3052425.0 890.3 1279391.0 596.6 951623.2 797.5 893964.0 459.7 422421.4 430.3 291709.7 603.6 45876.3

294 172.5 3005309.6 931.5 1338534.9 646.4 1030938.4 776.4 870331.4 490.1 450370.5 449.8 304975.8 642.6 48840.1

295 173.8 3027303.4 917.8 1318950.1 627.4 1000703.3 793.9 889954.1 458.8 421645.2 422.3 286323.4 620.4 47151.9

296 173.7 3026808.1 928.3 1333979.0 636.2 1014791.8 787.6 882947.4 469.4 431416.0 452.3 306664.4 638.5 48526.0

297 176.3 3071811.0 951.7 1367597.2 567.3 904881.3 798.2 894808.8 455.4 418527.6 421.3 285660.9 610.9 46426.8

298 172.0 2997204.4 867.7 1246886.6 697.6 1112628.3 809.4 907376.5 473.6 435271.2 437.9 296872.6 619.3 47067.8

299 173.3 3020009.3 946.2 1359693.3 595.9 950411.5 803.6 900873.0 480.2 441284.7 432.6 293271.9 638.5 48527.2

300 168.8 2940969.9 937.1 1346668.8 598.0 953860.0 799.5 896275.2 467.6 429710.7 425.1 288219.9 615.6 46788.5

301 171.5 2987899.4 874.4 1256500.8 582.2 928540.0 762.7 855032.1 476.0 437451.8 441.1 299086.8 633.0 48108.6

302 175.9 3065360.8 872.7 1254017.9 658.1 1049737.3 767.9 860864.0 477.5 438812.3 432.4 293159.2 646.7 49146.7

303 176.7 3079195.3 929.3 1335466.0 622.2 992421.1 797.1 893597.3 482.0 442969.4 463.8 314469.4 620.6 47168.0

304 178.3 3107091.5 889.5 1278268.0 562.2 896673.6 823.2 922852.0 474.1 435728.4 424.3 287694.4 616.1 46821.9

305 174.4 3038708.6 877.4 1260799.1 597.0 952158.1 755.5 846954.5 480.4 441514.8 429.0 290859.7 618.6 47017.2

306 174.1 3032773.2 909.8 1307413.6 664.5 1059839.9 765.3 857951.2 482.6 443521.2 443.8 300880.3 606.0 46055.8

307 175.6 3059752.8 930.0 1336480.1 577.9 921779.9 776.8 870809.9 481.0 442015.1 429.1 290913.3 621.3 47215.1

308 173.7 3026880.7 896.4 1288172.2 661.3 1054784.6 752.7 843738.4 477.6 438882.7 437.5 296598.2 610.2 46374.1

309 175.9 3064298.7 901.7 1295780.2 665.5 1061501.5 790.0 885583.4 471.5 433351.3 473.8 321212.1 634.6 48231.8

310 169.8 2957996.8 885.0 1271790.8 662.4 1056513.3 774.4 868150.3 473.8 435381.3 433.3 293782.6 619.8 47104.6

311 167.6 2919354.5 862.9 1239963.4 566.7 903943.9 732.9 821569.2 471.2 433039.2 429.1 290913.3 609.0 46285.4

312 176.6 3076086.9 906.1 1301994.5 638.6 1018533.9 797.3 893790.6 467.9 430005.7 420.6 285138.1 625.4 47531.0

313 178.3 3106198.4 869.9 1250082.5 610.5 973816.2 793.1 889053.2 472.4 434144.7 436.3 295816.3 614.0 46666.1

314 169.2 2947969.0 888.2 1276309.2 637.5 1016781.8 791.2 886976.9 468.2 430291.4 451.8 306297.0 635.2 48272.0

315 173.2 3018328.0 906.4 1302492.4 617.4 984784.0 789.2 884688.6 472.6 434338.7 436.7 296111.6 643.9 48934.1

316 169.7 2956321.5 911.2 1309451.8 611.1 974698.3 810.9 909073.7 472.7 434450.2 408.8 277196.3 627.3 47671.8

317 169.9 2959677.7 882.5 1268216.6 608.2 970078.1 755.2 846598.9 464.6 426932.7 438.7 297437.3 620.3 47146.5

318 174.6 3042278.5 895.0 1286161.1 577.9 921693.9 798.0 894534.8 464.3 426653.5 412.8 279861.5 637.2 48429.6

319 172.1 2997904.5 893.9 1284507.8 679.4 1083719.8 802.5 899564.4 476.1 437519.9 424.6 287847.0 644.9 49014.1

320 180.0 3136708.5 909.1 1306435.1 603.1 961899.3 770.4 863634.4 471.2 433065.6 438.1 297012.6 623.4 47378.3

321 178.0 3101825.9 860.6 1236673.2 668.7 1066629.4 799.8 896609.4 478.3 439569.2 422.9 286722.4 620.8 47178.8

322 172.6 3006480.6 914.7 1314424.6 656.8 1047529.2 782.3 876942.9 471.7 433526.7 420.0 284769.8 635.3 48281.6

323 176.8 3079747.7 905.0 1300447.2 551.4 879431.5 804.4 901719.6 468.8 430846.0 423.3 286964.4 630.4 47908.4

324 176.6 3076680.6 899.8 1292976.1 601.0 958592.3 792.2 888026.4 478.6 439808.8 427.6 289931.9 626.6 47620.0

325 176.6 3077277.5 876.2 1259028.4 634.6 1012134.3 778.5 872684.7 476.2 437646.5 437.6 296724.4 638.5 48522.7

326 175.0 3048886.6 899.5 1292608.1 621.8 991785.8 771.2 864555.8 464.6 426942.6 439.1 297704.3 641.1 48722.5

327 172.0 2997038.5 919.4 1321138.0 663.0 1057529.7 763.0 855319.3 461.9 424482.7 435.6 295311.1 638.1 48493.1

328 173.3 3018770.8 918.6 1320051.3 650.3 1037194.9 804.8 902200.6 461.4 424025.7 452.9 307058.8 623.8 47410.5

329 172.1 2998611.1 901.6 1295616.3 641.9 1023820.7 812.8 911172.8 472.2 433965.6 433.9 294212.5 594.8 45202.7

330 175.8 3062057.0 855.6 1229494.3 618.2 986040.0 776.9 870910.6 473.6 435203.9 438.2 297123.2 639.8 48624.3

331 177.6 3094410.7 890.2 1279169.7 603.2 962041.8 820.5 919769.1 474.2 435828.5 414.7 281141.6 617.9 46964.0

332 171.4 2986210.3 906.7 1302975.6 630.5 1005581.5 784.3 879239.7 478.0 439325.4 462.8 313798.0 636.6 48378.0

333 174.8 3044566.7 943.1 1355269.4 624.7 996379.1 753.2 844316.6 473.3 434992.0 423.7 287235.2 611.2 46448.1

334 175.2 3052578.5 927.5 1332814.9 670.0 1068715.2 814.5 913029.4 463.9 426358.5 439.3 297827.4 634.5 48220.4

335 169.3 2949155.6 943.2 1355324.5 622.8 993305.6 783.4 878156.6 469.6 431595.8 430.3 291750.8 633.2 48122.6

336 175.4 3055743.2 916.3 1316757.8 646.7 1031473.9 820.9 920250.8 480.3 441432.8 432.6 293299.6 626.8 47640.3

337 170.3 2966567.3 910.3 1308135.2 588.3 938332.7 781.4 875993.4 474.1 435721.7 455.4 308734.6 606.6 46098.7

338 177.3 3088144.6 928.3 1333901.1 637.3 1016537.0 763.0 855318.5 480.3 441378.1 425.5 288510.7 632.7 48082.7

339 174.5 3039636.2 917.3 1318217.7 607.2 968544.0 789.0 884491.5 473.0 434732.5 433.4 293850.4 624.5 47463.2

340 175.3 3054458.8 898.8 1291565.5 605.0 965037.2 744.8 834968.3 473.9 435503.7 436.4 295872.2 622.5 47312.5

341 175.4 3055810.9 896.1 1287691.2 593.4 946464.2 779.1 873348.0 486.2 446774.7 437.6 296685.7 638.3 48509.2

342 174.1 3032675.8 904.4 1299579.5 631.5 1007300.9 798.7 895394.8 473.4 435049.7 460.5 312250.7 632.8 48090.7

343 175.6 3058939.9 900.7 1294313.4 600.5 957837.9 819.8 918969.4 474.5 436053.9 423.4 287092.1 625.7 47555.0

344 174.3 3036285.2 926.9 1331902.8 611.5 975296.7 814.8 913351.3 476.1 437537.1 451.0 305783.9 634.8 48243.0

345 176.1 3068177.9 919.3 1321007.5 552.6 881363.8 802.5 899575.1 475.0 436510.1 432.9 293496.2 626.6 47620.4

346 176.5 3075327.8 912.4 1311050.9 633.7 1010678.4 771.2 864474.6 471.7 433526.6 453.3 307363.8 617.4 46923.5

347 179.1 3120779.9 891.5 1281140.4 689.4 1099549.7 807.5 905161.1 444.0 408024.2 434.7 294735.2 614.3 46690.5

348 169.5 2953777.4 921.7 1324542.8 569.7 908624.6 815.4 914116.9 460.8 423457.9 426.6 289212.7 627.6 47700.2

349 169.8 2957779.9 863.3 1240600.6 646.0 1030331.2 786.0 881116.9 467.1 429265.2 432.0 292924.3 626.8 47637.5

350 175.8 3063241.6 907.9 1304609.1 620.4 989478.6 797.2 893665.9 474.5 436022.8 420.0 284772.1 596.7 45346.7

351 179.3 3123423.1 891.4 1280956.1 638.7 1018651.2 777.6 871660.6 474.8 436312.0 434.6 294630.1 627.1 47659.8

352 174.1 3033271.5 880.4 1265078.6 641.8 1023727.6 779.7 874003.5 473.7 435375.2 442.9 300317.7 625.1 47507.0

353 171.4 2986524.4 891.0 1280324.0 640.3 1021343.5 766.0 858702.6 470.6 432470.8 422.0 286100.5 604.7 45960.9

354 171.4 2986208.9 879.1 1263335.5 642.1 1024138.8 803.6 900807.3 490.0 450320.0 433.8 294146.8 628.4 47757.1

355 177.3 3088762.8 921.9 1324822.2 598.2 954122.9 804.9 902244.3 478.9 440128.5 432.1 292979.5 629.5 47844.8

356 179.6 3129114.7 932.9 1340589.0 642.7 1025177.6 788.1 883493.4 475.6 437086.0 418.0 283373.4 646.9 49167.8

357 176.2 3069507.0 891.4 1281003.0 652.9 1041365.6 766.4 859135.9 460.9 423581.1 436.4 295845.9 608.7 46257.8

358 176.3 3071490.1 918.4 1319771.6 695.6 1109536.8 758.9 850676.2 461.0 423681.1 397.4 269463.6 627.3 47676.1

359 172.3 3001282.4 939.9 1350689.3 587.8 937542.9 805.7 903175.1 476.8 438173.4 443.6 300761.7 614.8 46721.4

360 172.9 3012167.8 923.8 1327536.0 656.9 1047824.9 766.6 859381.2 469.0 431045.1 424.4 287766.2 616.2 46827.6

361 179.1 3121003.1 917.3 1318228.2 623.7 994824.6 791.1 886806.9 465.6 427880.3 437.4 296549.9 631.1 47962.8

362 177.0 3083087.2 877.8 1261406.9 658.2 1049790.7 785.0 879979.9 467.2 429391.0 435.5 295281.9 626.4 47604.8

363 176.4 3073001.2 925.7 1330169.3 553.5 882841.9 783.4 878192.5 476.7 438088.3 421.0 285446.0 611.5 46472.7

364 175.0 3048163.6 908.4 1305405.8 655.0 1044715.3 823.4 923055.6 466.9 429066.3 441.0 299021.9 610.6 46408.6

365 179.2 3121821.1 907.6 1304208.7 620.7 990052.6 768.4 861329.7 472.5 434220.0 468.3 317510.3 639.5 48602.9

366 170.9 2977927.5 902.0 1296194.1 690.4 1101245.1 746.4 836726.4 459.3 422100.3 426.1 288899.6 632.4 48060.2

367 171.4 2986591.4 919.6 1321488.0 608.6 970714.6 837.1 938337.8 471.3 433082.1 411.6 279055.9 625.1 47510.5

368 175.1 3050433.8 886.1 1273258.5 620.9 990387.4 785.9 880985.0 466.2 428444.9 427.8 290020.9 599.0 45526.5

369 172.9 3013098.8 904.9 1300300.4 646.7 1031561.8 819.7 918865.2 469.5 431432.9 421.2 285578.1 621.8 47259.2

370 174.0 3031531.8 862.5 1239402.3 597.0 952223.0 819.2 918349.4 468.2 430309.3 440.7 298814.5 643.4 48902.0

371 174.7 3043672.7 892.0 1281859.6 669.5 1067889.8 786.1 881266.1 473.2 434840.8 415.4 281672.8 621.8 47259.1

372 175.1 3051394.3 888.0 1276127.6 620.0 988877.2 831.5 932068.1 476.1 437509.3 442.5 299988.8 612.6 46559.9

373 178.2 3103742.7 903.2 1297879.0 651.8 1039586.2 759.6 851551.4 454.9 418008.5 439.4 297888.7 645.5 49059.5

374 175.1 3050897.7 880.1 1264765.4 595.6 950034.5 798.1 894636.7 486.5 447130.2 443.1 300435.0 623.3 47372.1

375 170.4 2969164.5 917.9 1319052.5 570.9 910653.9 791.1 886773.1 463.7 426139.3 466.6 316374.3 625.8 47557.8

376 174.7 3042776.6 909.4 1306868.6 629.7 1004418.4 757.6 849292.4 461.5 424095.2 431.5 292580.8 631.9 48022.5

377 170.6 2972910.7 915.8 1315974.6 636.4 1015131.8 782.2 876838.5 472.0 433748.4 433.1 293623.3 633.9 48174.2

378 169.5 2952575.0 933.8 1341917.0 628.6 1002616.1 759.3 851218.3 492.6 452662.3 440.9 298957.4 605.4 46006.7

379 178.2 3104016.6 901.4 1295257.7 592.7 945340.0 799.2 895924.9 478.2 439438.1 414.9 281305.6 633.5 48148.4

380 176.2 3069990.8 935.9 1344960.1 631.1 1006624.3 761.4 853544.3 472.9 434604.8 416.6 282460.3 612.5 46551.9

381 175.0 3048729.9 896.6 1288388.1 636.5 1015178.3 832.0 932643.4 467.4 429494.8 427.4 289756.0 612.3 46533.0

382 170.3 2966208.5 908.8 1305988.1 670.2 1069002.8 800.2 897032.6 475.6 437051.5 423.3 287006.4 600.7 45653.2

383 174.5 3040170.7 898.1 1290635.9 578.6 922919.5 789.4 884926.2 483.1 443940.1 437.0 296301.4 630.7 47935.0

384 173.2 3018032.5 908.8 1305949.1 603.3 962273.1 815.7 914383.6 476.9 438312.7 440.7 298812.0 625.5 47535.0

385 182.5 3179037.9 897.3 1289352.5 646.8 1031642.0 807.0 904642.4 467.5 429644.7 433.4 293849.7 628.8 47786.0

386 167.1 2910797.6 849.9 1221291.4 614.1 979480.6 798.4 894974.4 469.3 431297.8 432.0 292863.9 638.6 48531.0

387 173.5 3021974.7 911.9 1310446.0 609.5 972144.8 809.7 907675.8 469.4 431399.3 430.5 291856.6 640.6 48687.3

388 177.9 3099835.9 898.9 1291732.0 656.1 1046431.8 746.8 837107.6 463.0 425496.8 428.9 290779.8 613.4 46619.6

389 173.5 3023050.5 918.5 1319935.6 633.5 1010469.1 755.7 847131.5 477.3 438633.8 447.3 303264.0 630.6 47924.8

390 175.5 3057461.1 928.5 1334244.4 631.7 1007615.8 802.4 899510.2 469.8 431774.7 442.7 300165.5 625.0 47502.3

391 176.7 3077735.1 935.9 1344922.8 641.0 1022451.9 778.6 872865.7 462.3 424861.7 415.7 281868.2 659.2 50099.5

392 172.4 3003767.4 928.1 1333632.1 599.9 956899.2 807.4 905080.6 480.2 441278.2 445.1 301758.4 626.6 47621.3

393 175.4 3056275.2 919.0 1320538.1 655.0 1044683.5 782.7 877457.0 476.6 438033.3 443.2 300489.9 627.8 47714.0

394 172.1 2998508.2 909.7 1307198.1 625.4 997466.6 805.3 902713.6 473.9 435475.8 421.2 285578.6 607.3 46153.9

395 177.0 3083168.0 928.3 1333929.4 547.0 872467.6 793.4 889368.9 475.4 436865.8 408.5 276933.7 605.3 46000.2

396 178.2 3105348.5 859.6 1235316.7 583.4 930530.6 781.0 875481.3 466.3 428525.1 424.7 287932.4 615.3 46765.7

397 176.7 3078548.4 904.7 1300112.5 708.8 1130531.8 800.8 897651.8 466.9 429076.9 410.7 278456.7 626.3 47602.3

398 178.5 3110698.0 880.5 1265325.2 637.9 1017398.4 799.8 896593.5 461.6 424226.6 430.8 292059.6 639.5 48600.1

399 174.1 3033778.3 900.7 1294250.5 625.8 998124.5 786.8 881980.4 474.1 435674.8 446.6 302770.1 617.7 46943.2

400 172.9 3012786.4 929.8 1336132.0 661.7 1055488.1 814.0 912441.0 487.3 447817.2 437.8 296808.3 607.8 46194.1

401 172.3 3002168.0 897.9 1290282.4 642.3 1024457.7 748.6 839179.1 477.2 438592.7 435.4 295205.8 612.1 46519.6

402 175.7 3061236.7 933.6 1341582.2 617.0 984088.2 775.8 869630.1 483.3 444113.9 426.2 288975.5 614.4 46694.2

403 170.9 2978165.1 921.6 1324271.4 666.7 1063454.0 792.7 888578.1 469.5 431494.1 428.5 290554.4 632.8 48092.4

404 173.1 3016110.5 896.4 1288160.9 620.2 989247.6 826.9 926899.1 451.2 414685.4 449.6 304852.0 631.5 47996.1

405 172.8 3011046.3 925.2 1329466.4 575.7 918166.7 776.4 870372.3 460.6 423259.9 440.5 298684.7 648.8 49310.5

406 178.9 3116860.7 897.8 1290119.6 592.8 945507.7 795.9 892181.5 471.9 433698.0 430.7 292036.5 621.8 47257.2

407 169.4 2950894.5 907.2 1303665.7 635.4 1013517.5 791.2 886989.2 471.1 432979.7 422.8 286673.8 628.4 47761.4

408 172.4 3004215.3 914.8 1314532.3 632.0 1008017.1 749.9 840614.2 465.0 427296.3 432.6 293303.9 645.7 49072.7

409 175.1 3049760.0 876.1 1258971.6 679.6 1083912.5 802.4 899513.6 469.6 431586.5 421.2 285607.0 614.7 46718.4

410 175.0 3048449.1 930.4 1336983.2 664.0 1059012.7 762.0 854231.9 469.3 431310.2 432.1 292938.5 618.7 47019.1

411 178.1 3102392.2 923.3 1326844.5 603.9 963218.3 773.3 866833.2 468.0 430099.7 456.4 309450.3 609.6 46330.9

412 172.3 3001448.0 930.8 1337572.8 660.6 1053713.0 782.5 877208.2 476.0 437419.8 421.1 285500.2 600.1 45607.1

413 174.8 3044773.1 896.7 1288494.1 660.6 1053669.4 835.4 936494.4 470.8 432658.3 400.8 271720.5 607.2 46147.0

414 176.4 3073709.4 918.2 1319431.7 589.4 940039.3 780.1 874532.6 454.9 418009.6 440.7 298801.7 623.9 47413.4

415 183.5 3196570.1 871.9 1252910.4 629.7 1004299.7 735.2 824215.2 449.4 413013.5 444.3 301252.1 622.2 47288.2

416 173.0 3013843.7 895.4 1286626.4 608.3 970287.2 793.1 889115.9 457.3 420295.9 440.1 298390.0 612.1 46523.1

417 178.3 3107130.6 907.5 1304061.7 607.1 968300.8 789.3 884807.5 470.8 432649.3 427.0 289531.0 595.3 45240.0

418 173.2 3016807.2 905.2 1300790.1 546.7 871960.4 784.9 879838.4 480.7 441738.4 452.0 306425.1 612.4 46542.7

419 174.6 3041103.5 901.1 1294835.4 603.4 962426.3 792.0 887863.5 465.8 428092.5 426.7 289303.4 630.3 47906.2

420 178.7 3112976.9 870.9 1251429.9 680.6 1085489.5 819.7 918931.3 467.6 429737.9 436.3 295833.4 613.7 46644.3

421 172.0 2997309.0 910.5 1308406.2 611.2 974844.1 789.9 885492.8 460.9 423592.4 429.2 290994.7 625.0 47500.1

422 172.8 3009839.9 924.6 1328662.2 614.2 979603.4 809.4 907310.4 476.6 437950.9 426.8 289356.3 623.0 47345.1

423 175.1 3050487.3 891.4 1280932.8 663.8 1058768.9 774.0 867653.1 473.0 434677.8 423.0 286791.3 624.4 47453.3

424 177.4 3090644.0 906.1 1302076.4 680.4 1085170.1 791.6 887359.2 470.6 432445.8 419.2 284208.2 627.0 47652.3

425 179.8 3132233.6 914.8 1314528.3 627.9 1001541.7 816.8 915623.8 480.1 441229.9 448.3 303966.2 599.1 45532.6

426 175.1 3051450.5 904.3 1299424.9 646.5 1031129.0 775.0 868801.0 486.2 446818.9 418.6 283805.5 644.8 49001.1

427 179.0 3117811.2 900.5 1294088.1 654.8 1044363.1 771.4 864772.6 468.4 430492.5 439.5 297947.2 629.7 47859.0

428 170.5 2970574.0 903.0 1297627.6 650.6 1037700.9 804.9 902272.9 457.2 420129.0 424.1 287545.2 596.9 45366.7

429 173.3 3019268.5 925.8 1330432.3 617.7 985180.8 772.4 865903.0 473.3 434969.4 421.0 285444.7 632.9 48102.8

430 174.8 3045924.9 947.0 1360870.3 649.1 1035271.4 786.6 881784.3 469.5 431464.5 422.1 286183.1 618.0 46969.3

431 173.7 3026436.8 885.5 1272392.4 610.6 973870.1 766.0 858696.9 462.8 425268.5 439.9 298275.2 633.2 48120.8

432 175.0 3048490.9 865.2 1243266.1 627.0 1000011.1 793.0 888994.2 478.5 439709.3 432.1 292940.3 587.4 44642.6

433 174.0 3031627.2 881.9 1267354.5 581.6 927721.1 784.3 879169.4 468.4 430500.6 429.3 291047.3 643.5 48902.6

434 181.3 3158692.9 925.4 1329842.4 636.9 1015923.4 800.9 897776.5 475.4 436914.4 424.4 287754.9 637.4 48439.0

435 174.5 3039495.9 882.4 1268042.5 656.1 1046434.5 816.4 915194.0 463.5 425938.8 433.6 293973.2 619.4 47075.0

436 176.7 3078558.1 915.7 1315818.1 609.6 972272.2 807.5 905192.7 478.4 439671.8 428.7 290679.7 627.1 47660.5

437 171.7 2990628.7 960.7 1380581.1 607.9 969526.8 815.9 914634.3 469.5 431470.3 439.2 297796.3 638.1 48491.9

438 173.4 3020996.6 929.3 1335446.6 588.1 938069.6 773.4 866960.2 460.3 422981.8 417.1 282774.2 627.0 47648.6

439 174.5 3039631.7 892.8 1282916.4 647.1 1032105.9 793.6 889670.5 482.8 443657.3 421.5 285774.5 632.6 48080.7

440 173.3 3019803.2 918.8 1320355.6 598.8 955007.1 806.8 904370.6 459.3 422110.9 422.9 286740.5 617.7 46944.8

441 173.1 3016129.1 923.3 1326758.3 632.3 1008439.4 792.7 888579.3 468.9 430895.7 428.7 290677.8 613.2 46604.0

442 173.0 3013924.4 944.0 1356518.7 646.0 1030429.7 815.4 914117.6 467.5 429669.4 435.7 295392.3 631.2 47973.6

443 173.5 3022961.9 910.4 1308295.2 620.1 989107.8 815.8 914558.4 463.8 426247.1 408.4 276905.7 628.0 47727.9

444 176.6 3077110.4 898.4 1290977.6 640.0 1020728.7 755.4 846818.5 465.3 427575.1 435.3 295125.5 629.6 47846.3

445 173.5 3021987.9 848.9 1219812.5 660.1 1052835.1 799.3 896003.0 464.4 426764.1 428.7 290660.6 610.3 46381.4

446 173.4 3020514.3 858.6 1233773.1 587.5 936999.5 801.3 898278.0 472.8 434485.0 413.8 280564.1 618.7 47022.4

447 174.5 3040605.0 934.9 1343395.5 611.9 976025.4 811.7 909887.2 458.8 421678.0 417.6 283129.2 628.7 47780.9

448 168.5 2936136.2 936.7 1345969.9 625.4 997535.7 790.0 885631.3 465.9 428164.6 432.8 293413.3 601.6 45725.0

449 173.1 3015937.4 913.2 1312204.3 605.7 966082.2 813.8 912235.1 475.5 436984.5 415.5 281719.1 640.7 48696.6

450 173.4 3020638.3 932.9 1340534.5 640.5 1021572.1 784.3 879247.7 470.0 431958.0 440.1 298405.6 620.9 47191.6

451 176.0 3065769.7 906.9 1303283.1 625.5 997638.0 783.9 878801.0 465.2 427511.7 425.8 288699.7 618.4 46998.3

452 177.6 3094158.4 925.0 1329178.1 629.0 1003235.0 818.7 917739.1 472.9 434555.0 424.9 288088.2 633.8 48166.7

453 177.4 3090624.8 911.4 1309619.6 641.2 1022773.9 788.0 883359.8 473.8 435467.0 432.0 292922.6 629.8 47866.4

454 176.6 3077399.4 904.0 1298983.8 653.7 1042592.1 807.9 905697.9 470.1 432001.6 423.8 287313.3 617.0 46889.6

455 173.3 3018607.1 860.4 1236402.6 617.5 984833.0 793.5 889512.9 465.2 427533.5 423.6 287201.1 634.1 48190.5

456 175.3 3053410.4 892.9 1283156.8 591.7 943779.5 815.8 914488.5 472.0 433732.0 452.0 306460.1 646.4 49129.8

457 173.4 3021278.4 894.2 1284945.2 603.0 961715.7 777.7 871813.8 478.0 439295.7 452.9 307041.6 602.7 45807.4

458 176.0 3066767.6 881.9 1267332.4 657.5 1048748.0 769.2 862229.2 459.3 422084.5 426.7 289289.3 642.4 48825.1

459 175.2 3051881.9 931.4 1338458.7 679.5 1083859.3 773.8 867438.1 481.8 442776.3 461.8 313101.4 633.4 48137.7

460 174.1 3033649.7 908.6 1305700.6 616.5 983243.0 827.6 927745.4 476.2 437593.0 442.1 299751.8 609.8 46346.2

461 173.3 3018819.0 926.2 1330924.0 649.5 1035874.5 790.5 886165.4 476.9 438302.7 413.3 280237.1 619.2 47061.5

462 172.8 3010070.7 873.4 1255034.5 590.5 941869.6 805.7 903244.5 472.4 434126.3 429.4 291146.8 621.5 47237.2

463 177.1 3085255.1 909.9 1307532.1 630.6 1005865.6 782.8 877530.5 460.3 423057.4 410.6 278391.7 606.8 46113.3

464 172.0 2995978.0 921.7 1324456.4 540.6 862330.5 758.5 850257.5 468.7 430762.0 440.8 298865.1 599.1 45533.8

465 176.5 3075838.7 890.6 1279862.6 593.3 946383.8 789.1 884555.0 470.8 432688.2 448.5 304108.1 618.6 47010.6

466 169.2 2948284.8 947.1 1361010.6 617.0 984143.7 797.9 894462.3 463.2 425702.8 435.2 295096.0 608.4 46236.6

467 173.1 3015772.5 889.3 1277937.0 619.1 987455.3 767.6 860528.1 476.5 437875.5 454.2 307948.0 640.1 48645.2

468 172.5 3005737.7 914.9 1314745.1 615.8 982254.2 749.1 839722.6 467.8 429885.9 438.9 297595.4 637.5 48448.9

469 171.3 2984758.7 896.8 1288704.6 649.2 1035478.7 764.4 856887.6 476.5 437923.4 425.8 288658.9 595.1 45231.1

470 175.7 3061812.8 913.5 1312700.6 621.6 991474.6 822.6 922164.1 464.8 427141.8 440.1 298389.6 650.9 49466.0

471 177.5 3092650.6 911.4 1309617.1 621.9 991998.2 767.7 860537.9 473.5 435192.3 418.1 283465.6 614.8 46722.4

472 178.2 3103805.5 917.8 1318809.8 661.1 1054488.1 754.6 845937.7 471.9 433707.1 444.5 301339.4 625.0 47498.9

473 170.1 2963999.2 892.2 1282126.0 621.0 990441.2 773.2 866765.2 473.7 435346.5 439.3 297834.8 628.2 47739.6

474 173.6 3023910.1 903.6 1298525.9 588.1 938015.2 812.8 911163.5 463.4 425865.9 444.8 301574.4 612.8 46574.8

475 168.7 2938884.7 886.8 1274288.8 680.4 1085179.7 844.8 947002.0 480.9 441959.8 421.0 285450.1 640.6 48687.4

476 176.5 3074829.7 903.1 1297760.4 625.3 997323.5 774.4 868109.6 480.7 441745.2 443.0 300341.1 615.8 46802.9

477 174.9 3047259.9 895.9 1287424.7 653.0 1041575.4 759.2 851117.7 479.4 440534.0 427.2 289617.7 623.7 47402.0

478 173.3 3020077.4 930.6 1337283.2 581.4 927382.2 761.7 853812.8 462.2 424724.6 428.9 290794.6 609.1 46289.6

479 175.5 3057157.7 939.9 1350587.5 598.8 955105.0 795.5 891733.0 472.0 433737.0 434.7 294693.2 628.4 47761.4

480 173.7 3026000.5 903.3 1298046.4 608.5 970592.0 789.6 885111.2 463.3 425788.8 417.0 282737.2 634.4 48217.8

481 173.0 3014801.2 900.5 1294029.7 634.5 1012045.8 782.3 876966.0 477.7 439024.8 420.2 284862.5 651.7 49529.8

482 174.2 3034903.3 857.4 1232022.2 608.8 971019.4 788.2 883617.2 481.3 442339.9 457.0 309818.3 647.7 49226.6

483 176.6 3077138.2 878.8 1262789.1 642.2 1024274.2 845.0 947260.1 472.4 434155.3 414.9 281303.4 620.5 47159.6

484 173.1 3015428.6 905.8 1301593.1 654.4 1043709.2 812.9 911240.2 462.6 425116.8 408.5 276954.1 618.4 46994.7

485 172.2 3000734.0 881.9 1267340.3 651.3 1038857.1 740.4 829953.3 469.2 431239.1 431.8 292763.3 626.0 47572.5

486 174.5 3040926.1 890.8 1280041.4 623.9 995128.2 737.6 826820.1 480.4 441479.3 422.2 286269.9 620.5 47157.0

487 171.5 2988099.3 929.5 1335646.3 667.4 1064541.8 790.6 886316.3 477.2 438588.0 455.2 308630.5 626.1 47585.3

488 170.2 2965062.1 876.0 1258820.2 574.2 915783.7 789.3 884788.6 478.4 439618.1 451.3 305981.9 624.6 47466.3

489 177.2 3087968.1 919.9 1321900.5 619.7 988370.4 762.0 854216.3 470.2 432124.4 433.3 293797.1 627.8 47716.2

490 167.5 2917819.6 881.4 1266570.5 632.9 1009423.8 798.1 894659.4 465.7 427994.7 424.9 288079.1 623.0 47345.8

491 173.7 3025564.5 912.2 1310791.5 640.7 1021925.7 789.7 885266.2 457.4 420339.4 433.0 293588.7 630.0 47876.4

492 175.7 3061510.1 918.8 1320379.2 621.9 991881.3 793.9 889942.3 477.3 438617.1 456.5 309478.8 629.1 47810.9

493 176.2 3069228.8 871.2 1251901.8 666.4 1062978.5 787.7 883022.5 476.6 437990.4 456.9 309762.0 642.3 48818.6

494 169.6 2955196.6 850.7 1222434.5 590.0 941113.0 809.5 907481.3 463.5 425971.9 433.1 293660.9 590.2 44858.4

495 178.3 3105785.6 902.5 1296852.5 606.4 967176.7 784.9 879838.9 469.7 431655.3 405.1 274652.0 643.3 48887.5

496 174.9 3046403.0 935.2 1343871.2 616.2 982896.9 720.9 808143.2 468.8 430790.9 440.3 298510.4 656.2 49874.0

497 176.4 3073511.1 917.3 1318162.9 640.3 1021238.3 806.4 903939.6 468.4 430425.2 447.5 303426.4 628.1 47736.9

498 172.0 2996396.3 914.3 1313789.1 658.0 1049542.1 805.3 902753.4 468.0 430101.6 436.0 295581.3 606.0 46058.9

499 180.1 3138561.1 866.2 1244698.3 658.5 1050367.9 774.5 868159.2 480.8 441883.3 426.8 289390.0 627.2 47666.6

500 167.1 2910636.7 912.9 1311851.5 613.9 979138.2 781.7 876230.9 476.7 438066.3 474.8 321903.5 626.0 47572.3

Date

PORTFOLIO VALUE

Change in Value ASIANPAINTS MINDTREE LUPINLTD HCL HUL YESBANK HDFC

2-Apr-12 56854954.8 713686.05 858827.8 561901.25 372792.35 252927.9 40154.6 1622532.3

3-Apr-12 58475200.8 718571.85 852368 566553.4 371046.25 253741.5 40295.2 -569491.15

4-Apr-12 57902017 723026.55 852447.8 570645.05 366864.8 253266.9 40017.8 -770526.4

9-Apr-12 57127609.1 727122 860422.8 558594.3 371735.5 252622.8 39653 -381499.85

10-Apr-12 56735614.1 723673.2 869354.8 550411 381339.05 255978.9 39888.6 -343334.05

11-Apr-12 56392400.7 707075.85 886501 549290 382855.4 254792.4 40010.2 331459.55

12-Apr-12 56719934.3 713901.6 877090.5 554222.4 387082.8 251843.1 40310.4 789282.9

13-Apr-12 57511764.2 708297.3 897985 536902.95 390712.85 247775.1 40230.6 935436.3

16-Apr-12 58442970.1 702261.9 903009.3 543460.8 387128.75 250012.5 40261 -419240.65

17-Apr-12 57984771.5 761178.9 884906 539032.85 388001.8 251673.6 40299 -287012.85

18-Apr-12 57686855.3 758879.7 882752.8 554110.3 388599.15 250792.2 40861.4 327072.2

19-Apr-12 57995224.7 767573.55 880280.5 564367.45 391034.5 249334.5 42107.8 216718.35

20-Apr-12 58199062.1 783596.1 879802 566497.35 388737 247063.2 41883.6 2246091.25

23-Apr-12 60471762 782015.4 875415.8 555511.55 383314.9 243266.4 41446.6 -149380.55

24-Apr-12 60314964 784817.55 860343 571934.2 386439.5 243673.2 41180.6 -663510.25

25-Apr-12 59623310.6 789559.65 883071.8 569019.6 385152.9 248181.9 41545.4 1015601.85

26-Apr-12 60663404 800911.95 864888.8 561564.95 381109.3 242486.7 41078 749448.75

27-Apr-12 61382932.6 832525.95 857631.5 572774.95 381752.6 236147.4 41127.4 421280.65

28-Apr-12 61814127.1 819736.65 859306.3 571093.45 383774.4 236825.4 41309.8 -317821.2

30-Apr-12 61443909.6 847255.2 881078 574008.05 383774.4 237096.6 41230 91793.15

2-May-12 61513597.6 864068.1 872544.8 581182.45 390575 236384.7 41792.4 1229440.3

3-May-12 62781919.2 839136.15 860263.3 577595.25 399535.25 229028.4 42107.8 214703.35

4-May-12 62986627.7 834753.3 880838.8 575297.2 399673.1 226248.6 40850 514694.8

7-May-12 63492736.8 858104.55 879722.3 562629.9 395124.05 230214.9 40451 131129.1

8-May-12 63686992.1 835831.05 872385.3 536622.7 395951.15 223163.7 39166.6 928934.1

9-May-12 64613842.5 836118.45 869833.3 545478.6 397513.45 217299 38961.4 -980731.9

10-May-12 63657374.7 838848.75 832829.3 550747.3 398156.75 221028 39330 -541578.2

11-May-12 63134714.7 833675.55 821425 547664.55 397053.95 223401 38801.8 1342246.2

14-May-12 64413489.5 866654.7 862336.8 543741.05 398708.15 216010.8 38041.8 1246388.55

15-May-12 65646967.1 883108.35 857073.3 548112.95 397421.55 214756.5 37931.6 -261380.25

16-May-12 65408285.7 871253.1 863214 544693.9 393102.25 205806.9 37635.2 -1006020.55

17-May-12 64375161.1 892017.75 868876.3 543965.25 395124.05 204993.3 37832.8 79199.2

18-May-12 64479693.1 874127.1 854521.3 541891.4 397053.95 211841.1 38041.8 938248.85

21-May-12 65406543.5 876138.9 867201.5 537463.45 391677.8 218587.2 37806.2 -1336210.65

22-May-12 64060694 877791.45 869354.8 546655.65 389518.15 218010.9 37183 -7630.45

Appendix No:3 Back Test

23-May-12 64069405 872905.65 858987.3 543404.75 392413 217434.6 37027.2 1255263.05

24-May-12 65328144.5 871756.05 851809.8 544469.7 390299.3 222384 37977.2 292829

25-May-12 65608638.7 890149.65 846307 546039.1 386761.15 223773.9 38000 1003101.35

28-May-12 66599950.5 888928.2 851331.3 551027.55 383636.55 229231.8 38665 358411.9

29-May-12 66944906.1 890940 848460.3 566497.35 382533.75 229469.1 38376.2 -449984.05

30-May-12 66490191.9 897693.9 843834.8 570813.2 388231.55 222384 38049.4 3602335.85

31-May-12 70063444.1 905597.4 864011.5 565040.05 393332 223638.3 38471.2 -4251543.8

1-Jun-12 65851675.6 903585.6 858668.3 546039.1 385520.5 219231.3 37270.4 -1688437.1

4-Jun-12 64186132.4 889503 849975.5 553605.85 378995.6 217671.9 37669.4 630224.75

5-Jun-12 64791546.9 903441.9 862017.8 555287.35 374308.7 219061.8 38114 1886104.45

6-Jun-12 66622599.1 913500.9 880599.5 562854.1 386025.95 224790.9 39512.4 374926.7

7-Jun-12 67034629.4 876641.85 874538.5 559435.05 389426.25 229265.7 40872.8 -383447.6

8-Jun-12 66644376.6 882030.6 869673.8 555567.6 394526.7 234215.1 40971.6 152717.3

11-Jun-12 66834276.4 887994.15 836497.8 540882.5 400821.85 232418.4 41188.2 819119.45

12-Jun-12 67663563.6 896688 814247.5 543404.75 397513.45 236011.8 41769.6 -78025.3

13-Jun-12 67556418.3 899059.05 822382 550186.8 411298.45 234655.8 41173 -152230.05

14-Jun-12 67433593.2 899130.9 822701 536678.75 405095.2 225129.9 40614.4 267974.85

15-Jun-12 67704505.3 881886.9 818394.5 544749.95 413044.55 226723.2 41613.8 -425526.65

18-Jun-12 67318608 868810.2 819989.5 526757.9 410287.55 220282.2 40656.2 413187.3

19-Jun-12 67703634.2 882964.65 830277.3 529055.95 412814.8 219061.8 40770.2 21971.2

20-Jun-12 67685341.1 884904.6 839927 545646.75 418696.4 225435 40599.2 201690.9

21-Jun-12 67888307.4 874917.45 842000.5 540153.85 422877.85 232723.5 41260.4 -113458.75

22-Jun-12 67793357.5 869385 841123.3 529840.65 423015.7 230689.5 41370.6 -1461409.85

25-Jun-12 66342976 877144.8 832669.8 521096.85 422785.95 229909.8 40789.2 -849582.45

26-Jun-12 65489298 887563.05 837295.3 516668.9 414193.3 231469.2 41302.2 329172.3

27-Jun-12 65788085.3 913069.8 834663.5 526589.75 415801.55 227028.3 41724 -462935.1

28-Jun-12 65315949.1 920973.3 850932.5 514595.05 415066.35 224824.8 41686 2470351.8

29-Jun-12 67746318.1 926577.6 856754.3 534100.45 417685.5 230113.2 42829.8 625510.2

2-Jul-12 68314275.3 967316.55 867680 543068.45 410425.4 233503.2 43620.2 365029

3-Jul-12 68647035.5 1011001.35 856594.8 543180.55 405600.65 237740.7 43764.6 -1190387.75

4-Jul-12 67465823.9 1005900 857392.3 541947.45 402476.05 237062.7 43928 -1574157.1

5-Jul-12 65875195.3 999217.95 861938 552036.45 405141.15 242452.8 44391.6 -1195918.95

6-Jul-12 64713147.9 950791.05 871747.3 549794.45 409919.95 244859.7 44194 -552143.5

9-Jul-12 64173065.9 947198.55 870391.5 545814.9 407990.05 243910.5 43939.4 194825.55

10-Jul-12 64341188.2 955030.2 873581.5 558650.35 410241.6 243707.1 44737.4 -16945.65

11-Jul-12 64355125.8 940660.2 872146 552428.8 405646.6 239571.3 44612 480561.35

12-Jul-12 64865590.4 914363.1 880440 539425.2 407071.05 239774.7 44087.6 -227719.65

13-Jul-12 64605131.5 944180.85 884826.3 542115.6 405370.9 236791.5 44615.8 -265261.7

16-Jul-12 64338574.9 921619.95 910984.3 539593.35 405416.85 237300 44281.4 -517142.55

17-Jul-12 63811559.4 933259.65 908990.5 536678.75 408173.85 237639 44327 32097.25

18-Jul-12 63849887.8 928086.45 908033.5 533876.25 410149.7 238079.7 44612 -788465.15

19-Jul-12 63052831.3 925715.4 912340 537519.5 410471.35 240588.3 44794.4 1730401.25

20-Jul-12 64761929.5 952587.3 908113.3 537855.8 409919.95 239978.1 44277.6 -2024189.35

23-Jul-12 62763626.1 940588.35 909708.3 535613.8 407071.05 230316.6 43548 -568471.15

24-Jul-12 62140789.6 942025.35 927891.3 538976.8 437627.8 231062.4 43627.8 -643505.7

25-Jul-12 61470913.7 932469.3 934191.5 575689.55 426829.55 234621.9 43779.8 -1104266.3

26-Jul-12 60438660.2 898053.15 902052.3 573671.75 424440.15 234350.7 43000.8 657921.95

27-Jul-12 61083274.2 893526.6 903328.3 580341.7 426967.4 240283.2 44429.6 1279058.3

30-Jul-12 62310654.1 902651.55 941767.8 579332.8 428024.25 244147.8 44631 1173475.05

31-Jul-12 63456150.6 907034.4 958435.5 581294.55 429494.65 247605.6 44669 -254452.05

1-Aug-12 63188722.9 921763.65 950301 584993.85 432067.85 247809 44574 417879.1

2-Aug-12 63612948.6 921907.35 943681.8 588412.9 430505.55 246385.2 44270 1815334.15

3-Aug-12 65458809.5 909692.85 926455.8 585610.4 428805.4 249368.4 44703.2 -139213.2

6-Aug-12 65299398.2 913500.9 941767.8 586507.2 429494.65 247944.6 45619 -61923.35

7-Aug-12 65224483.6 916446.75 938179 594690.5 431838.1 251063.4 45607.6 -224548.4

8-Aug-12 65008450.8 905956.65 927971 602369.35 438500.85 248995.5 45516.4 331669

9-Aug-12 65333371.1 904160.4 929725.5 601640.7 448701.75 245876.7 45953.4 -638480.6

10-Aug-12 64694854.8 903154.5 926296.3 601752.8 457386.3 241740.9 45763.4 1030842.45

13-Aug-12 65727108.3 895682.1 928290 608590.9 450585.7 245368.2 46166.2 198544.25

14-Aug-12 65889132.9 925499.85 918640.3 617166.55 455732.1 247944.6 46219.4 -1240362.85

16-Aug-12 64669592.9 933547.05 886899.8 625574.05 454675.25 244080 45603.8 -558534.7

17-Aug-12 64087698.1 927511.65 909947.5 624789.35 462624.6 243639.3 45227.6 288595.7

21-Aug-12 64358610.2 934265.55 911702 625237.75 471998.4 242893.5 45326.4 84.50000001

22-Aug-12 64322895.1 966957.3 921351.8 620025.1 471309.15 242215.5 45364.4 162052.75

23-Aug-12 64461400 977088.15 922627.8 627031.35 478247.6 240351 45425.2 -386800.35

24-Aug-12 64052854.1 1004894.1 927891.3 624845.4 475996.05 233571 45318.8 -302463.5

27-Aug-12 63803719.5 967316.55 914014.8 626134.55 478844.95 227706.3 45170.6 1078968.05

28-Aug-12 64913500.9 938935.8 910505.8 624957.5 481647.9 227536.8 44790.6 -423169.6

29-Aug-12 64500599.5 934193.7 920873.3 613803.55 480223.45 224282.4 44729.8 -64032.35

30-Aug-12 64397809.7 949138.5 940172.8 612682.55 485875.3 223706.1 45288.4 -981703.85

31-Aug-12 63428275.4 946911.15 945994.5 610272.4 473376.9 222892.5 45246.6 193204.15

3-Sep-12 63607722 956467.2 938577.8 622771.55 473376.9 222384 44874.2 760486.7

4-Sep-12 64342930.4 956036.1 948785.8 629441.5 478844.95 225774 44847.6 -721784.45

5-Sep-12 63613819.7 973495.65 934590.3 630058.05 488172.8 219739.8 44999.6 920642.15

6-Sep-12 64465755.5 1004175.6 968165 637344.55 483807.55 221570.4 44699.4 1254007.4

7-Sep-12 65689651 1004247.45 971514.5 646817 495295.05 227130 44870.4 -175311.1

8-Sep-12 65471876 1032700.05 984992.3 643734.25 497133.05 228858.9 44919.8 -340203.9

10-Sep-12 65134760.3 1023575.1 999985.3 643117.7 491802.85 225841.8 44927.4 648907.5

11-Sep-12 65788085.3 1037729.55 982759.3 646760.95 488770.15 223638.3 45174.4 1268409.35

12-Sep-12 66994558.8 1074085.65 988979.8 652702.25 497179 228282.6 45539.2 47540.7

13-Sep-12 67065989 1069199.85 956601.3 658923.8 502738.95 229875.9 45539.2 844184

14-Sep-12 67970190.8 1039956.9 918002.3 653374.85 503657.95 241300.2 46569 -356885.95

17-Sep-12 67676630.1 999720.9 912499.5 636335.65 488770.15 255978.9 46230.8 261073.45

18-Sep-12 67954511 988153.05 904923.3 643061.65 489275.6 251300.7 46014.2 -66023.65

20-Sep-12 67871756.5 1001445.3 923824 636840.1 484772.5 246453 46124.4 891906.85

21-Sep-12 68757665.2 990595.95 930283.8 638801.85 486794.3 251470.2 47511.4 548669.75

24-Sep-12 69337817.8 987721.95 919996 626302.7 476087.95 255606 48260 -742768.05

25-Sep-12 68581703 975004.5 930124.3 633701.3 485599.6 254487.3 48404.4 -767245.4

26-Sep-12 67826459.3 958335.3 933314.3 637680.85 484175.15 253877.1 47937 -356132.05

27-Sep-12 67428366.6 951796.95 951018.8 654047.45 494192.25 258284.1 47940.8 1123572.9

28-Sep-12 68552085.6 950791.05 950540.3 647321.45 501636.15 259029.9 47815.4 105998.5

1-Oct-12 68636582.3 957401.25 956282.3 651469.15 498879.15 267267.6 47336.6 -535177.2

3-Oct-12 68086047.1 948491.85 953172 662903.35 510504.5 271844.1 47078.2 -643864.35

4-Oct-12 67492828 930601.2 923824 660325.05 510504.5 270115.2 47978.8 -1121047.6

5-Oct-12 66399597.5 932684.85 906199.3 642949.55 519602.6 266793 47302.4 1350693.3

8-Oct-12 67768966.7 945114.9 902052.3 626358.75 514685.95 261470.7 47173.2 67387.3

9-Oct-12 67799455.2 949713.3 917842.8 628600.75 522773.15 267267.6 47557 76893.7

10-Oct-12 67876112 964227 904285.3 633701.3 518224.1 266589.6 46964.2 -32067.85

11-Oct-12 67863916.6 949497.75 876213.3 646648.85 525070.65 269199.9 47488.6 110194.25

12-Oct-12 67928378 960562.65 903248.5 652029.65 528470.95 267572.7 47967.4 -421056.55

15-Oct-12 67490214.7 979459.2 895512.8 654327.7 531687.45 267776.1 48195.4 168538.05

16-Oct-12 67685341.1 973926.75 886102.3 655224.5 527735.75 259470.6 47910.4 391409.15

17-Oct-12 68099113.6 929667.15 911941.3 650796.55 526632.95 261233.4 47735.6 308403.45

18-Oct-12 68358701.4 948348.15 913616 673721 528976.4 263809.8 48351.2 -747748.45

19-Oct-12 67626977.4 939223.2 914573 678597.35 520659.45 259979.1 47766 859922.1

22-Oct-12 68453651.3 965807.7 908831 685099.15 523324.55 262419.9 48564 -345443.25

23-Oct-12 68123504.4 955389.45 897905.3 682352.7 524151.65 270759.3 48191.6 -230206.35

25-Oct-12 67878725.3 947845.2 913616 682969.25 518270.05 282183.6 48438.6 449092.85

26-Oct-12 68354345.9 945043.05 902929.5 682913.2 507471.8 280014 48423.4 143429.4

29-Oct-12 68495464.1 951868.8 901653.5 683810 501819.95 281268.3 48685.6 -767259.2

30-Oct-12 67735864.9 948491.85 902770 679774.4 506001.4 276251.1 48157.4 -291277.25

31-Oct-12 67444046.4 947342.25 903487.8 681568 502325.4 279064.8 48199.2 111200.85

1-Nov-12 67572969.2 937858.05 903328.3 681680.1 493916.55 279708.9 47773.6 464457.3

2-Nov-12 68003292.6 942815.7 924541.8 688518.2 489827 284793.9 47902.8 940384

5-Nov-12 68938854 942025.35 931240.8 688125.85 489827 283743 48260 2438412.9

6-Nov-12 71349187.7 967747.65 937939.8 682016.4 489689.15 285302.4 48605.8 468861.2

7-Nov-12 71786479.9 988512.3 938896.8 690704.15 491251.45 284861.7 48643.8 984411.05

8-Nov-12 72790858.2 975076.35 931320.5 693338.5 490148.65 284454.9 48564 -1114543.8

9-Nov-12 71679334.6 975076.35 932596.5 689078.7 486288.85 288251.7 48590.6 -434050.05

12-Nov-12 71249011.2 963149.25 933553.5 695020 486886.2 288048.3 49498.8 -85918.75

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31-Jan-13 78419035.3 1133361.9 963858.5 771248 435560.05 354017.7 48871.8 743064.6

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21-Feb-13 78636810.3 1223749.2 947270.5 807344.2 430321.75 330152.1 50635 419109.55

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21-Mar-13 85589059.4 1278139.65 996476.3 866645.1 423475.2 292963.8 46132 676535.3

22-Mar-13 86303361.4 1237759.95 1000863 860871.95 421912.9 298659 45999 -1257758.45

25-Mar-13 85002809.1 1277852.25 1005807 859919.1 423934.7 295031.7 46314.4 453089.5

26-Mar-13 85424421.5 1311549.9 990096.3 869223.4 434411.3 288353.4 46702 278960.2

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