FINANCIAL PERFORMANCE AND CHARACTERISTICS OF PHARMACEUTICAL AND CHEMICAL INDUSTRY IN BANGLADESH: MULTINATIONAL VERSUS DOMESTIC CORPORATIONS by Shoeb Ahmed ID # 0330056 An Internship Report Presented in Partial Fulfillment of the Requirements for the Degree Bachelor of Business Administration INDEPENDENT UNIVERSITY, BANGLADESH May 2008
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FINANCIAL PERFORMANCE AND CHARACTERISTICS OF PHARMACEUTICAL AND CHEMICAL INDUSTRY IN BANGLADESH:
MULTINATIONAL VERSUS DOMESTIC CORPORATIONS
by
Shoeb Ahmed ID # 0330056
An Internship Report Presented in Partial Fulfillment of the Requirements for the Degree
Bachelor of Business Administration
INDEPENDENT UNIVERSITY, BANGLADESH May 2008
FINANCIAL PERFORMANCE AND CHARACTERISTICS OF PHARMACEUTICAL AND CHEMICAL INDUSTRY IN BANGLADESH:
MULTINATIONAL VERSUS DOMESTIC CORPORATIONS
FINANCIAL PERFORMANCE AND CHARACTERISTICS OF PHARMACEUTICAL AND CHEMICAL INDUSTRY IN BANGLADESH:
MULTINATIONAL VERSUS DOMESTIC CORPORATIONS
by
Shoeb Ahmed ID # 0330056
has been approved May 2008
_________________ Dr. Osman Goni
Assistant Professor School of Business
May 18, 2008 Dr. Osman Goni
Assistant Professor
School of Business,
Independent University, Bangladesh.
Dear Sir:
I, hereby, submit you the report on “Financial Performance and Characteristics of
Pharmaceutical and Chemical Industry in Bangladesh: Multinational versus Domestic
Corporations”, which has been prepared as a partial fulfillment of the degree Bachelors of
Business Administration.
This is the first time a study was performed comprehensively on my part and I have tried my
level best to complete the study in a proper way despite having limitations. It is hoped that proper
assessment will be done on my report considering the limitations of this study. Your benign and
authoritative advice will encourage me to conduct further flawless research in future.
Yours’ sincerely
____________ Shoeb Ahmed.
ID # 0330056
ACKNOWLEDGEMENT
In preparing the long and rigorous internship report, I acknowledge the encouragement and
assistance given by a number of people and institution. I am most grateful to the management of
GlaxoSmithKline Bangladesh Limited for gave me the opportunity to complete my internship in
their organization.
I would like to express my gratitude to my supervisor Dr. Osman Goni for providing me
detailed feedback and technical advice on this report. He always gave me his suggestions in
making this study as flawless as possible.
I would also like to render my sincere thanks to Mr. Sarwar Azam Khan (Finance Director),
Mr. Anisuzzaman (Finance Operation Manager) of GlaxoSmithKline Bangladesh Limited
providing me guidance, inspiration and above all flexibility of work.
Finally, I would like to thank Mr. A.N.M Giasuddin (Deputy Inspector), Law department,
Bangladesh Bank who had given me appointment from his precious time to collect data for my
report also helped me to understand many related matters.
I
Table of Content
Page
List of Tables III
List of Figures III
Executive Summary IV
1.0 Introduction 1
1.1 Purpose of the Study 2
1.2 Problem Statement 2
1.3 Methodology 3
1.3.1 Research Approach 3
1.3.2 Sampling Procedure 3
1.3.3 Instrument 4
1.3.4 Data Collection 5
1.3.5 Data Analysis 5
1.4 Limitations 6
1.5 Significance of the Study 6
1.6 Research Timeline 7
2.0 Literature Review 7
2.1 Capital Asset Pricing Model 8
2.2 The Sharpe Measure 10
2.3 Standard Deviation 10
2.4 The Treynor Measure 11
2.5 Beta Coefficient 12
II
2.6 The Jensen Measure 13
2.7 Systematic Risk 15
2.8 Geometric Mean 16
2.9 Calculation of Geometric Mean 17
2.10 Portfolio 17
2.11 The Risk Free Rate 18
2.12 Capitalization Ratio 18
3.0 Analysis of Performance 19
3.1 Financial Performance 19
3.1.1 Sharpe Measure 19
3.1.2 Treynor Measure 19
3.1.3 Jensen Measure 20
3.2 Financial Characteristic 21
3.2.1 Debt Equity Ratio 21
3.2.2 Average Standard Deviation of Equity 22
3.2.3 Frequency Distribution of Beta 23
3.2.4 Average Total Assets 24
4.0 Summary and Discussion 26
5.0 Conclusion 28
References 29
Bibliography 30
Appendix 32
III
List of tables
1. Sharpe Measure of MNC and DMC 19
2. Treynor Measure of MNC and DMC 19
3. Jensen Measure of MNC and DMC 20
4. Debt equity ratio of MNC and DMC 21
5. Average Standard Deviation of Equity of MNC and DMC 22
6. Frequency Distribution of Beta of MNC and DMC 23
7. Average Total Assets of MNC and DMC 24
8. Correlational Matrix of MNC and DMC 25
9. Financial Performance Comparison of MNC and DMC 26
10. Systematic Risk (β) Comparison of MNC and DMC 26
11. T-bill Rate Comparison of Bangladesh and U.S Government 27
List of Figure
1. Graph of Markowitz Portfolio Selection 7
2. Graph of Capital Market Line 9
3. Diagram of Debt equity ratio of MNC and DMC 22
IV
Executive Summary
The pharmaceutical and chemical industry is known as the fastest growing industry in
Bangladesh. At the side of multinational, domestic corporations have been improved range and
quality of their product. Multinational corporations (MNC) have established domineering
presence with advanced technological, financial and administrative base over domestic
corporations (DMC) in pharmaceutical and chemical industry. On the other hand, domestic
corporations have production cost advantage over multinationals operating in developed
countries. This research intends to evaluate systematically the differences of financial
characteristics and performance between multinational and domestic corporations utilizing
risk-adjusted performance measuring tools on the pharmaceutical and chemical industry in
Bangladesh. The risk-adjusted performance measuring tools are Sharpe, Treynor, Jensen
measure and debt equity ratio, average standard deviation of equity, frequency distribution of beta
and average total assets are used to define financial characteristic. The origin of the sample list is
the Dhaka Stock exchange’s industry wise company list. Secondary data like: DSE general index,
risk free rate, stock price etc. have been used for the research. The researcher employed t-test to
find out the significant difference of financial characteristics and performance of two groups. The
researcher also employed correlation and regression analyses to explore any existing relationship
between the size and financial performance tools in context of Bangladesh. The result shows
MNCs are more risk-adjusted with lower returns and DMCs are less risk-adjusted with higher
returns. The report will help investors for better understanding the nature of MNCs and DMCs for
investment in pharmaceutical and chemical industry in Bangladesh. Few unusual findings are
observed and those would be issues for future research.
1.0 Introduction
Pharmaceutical and chemical Industry has grown in Bangladesh in the last two decades at a
significant rate. The national companies account for more than 65% of the pharmaceutical and
chemical business in Bangladesh (www.pharmabiz.com). Following the Drug (Control)
Ordinance of 1982, some of the local pharmaceutical companies improved range and quality of
their products considerably. Square, Beximco, Acme, Incepta, Opsonin, ACI, General Pharma,
Ibn Sina are quite strong and enjoying good market share. Square currently is the number one
company in the industry and enjoys over 12% market share. (www.pharmabiz.com). However,
among the top 20 companies of Bangladesh six are multinationals including GlaxoSmithKline,
Sanofi-aventis, Reckitt Benckiser and Novartis. Almost all the life saving imported products and
new innovative molecules are channeled-into and marketed in Bangladesh through these
multinational companies. According to major economic indicator (2007), the export of
pharmaceutical and chemicals rose to US$ 123.47 million in 2005-06 financial years while it was
US$106.31 million in 2004-05 financial years. The country can expand its economic growth by
investing in their fast growing pharmaceutical and chemical industry which has an annual average
growth rate of 16% and a market size of BDT 30 billion in 2005 according to International
Management System (IMS). In Bangladesh, the production cost of drugs is much lower than that
of large MNCs operating in developed countries. This will give the local products a price
advantage in developed markets as well. On the other hand the multinationals are taking the
advantages of insufficient infrastructures, technological, financial and administrative base over
domestic corporations of pharmaceutical and chemical industry. Bangladesh’s rapid expansion in
pharmaceuticals and chemicals was accompanied by huge investments mainly locally (Firdousi,
2005). Limited foreign investments flowed in through the setup of various multinational
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
2
pharmaceutical and chemical companies (MNCs) that have established a domineering presence in
the local market today. At present, the multinationals have a market share of 15% (Hossain,
2003). This is a favorable trend for Bangladesh since the multinationals have not capitalized on
the local market but have just enough influence to transfer their technology and hire national
employees creating jobs. The establishment of the multinationals is prospective for Bangladesh. It
gives the local companies the opportunity to create partnerships and mergers with the MNCs.
Since the local companies can produce drugs at a cheaper rate due to low production costs, the
MNCs can outsource their export drug production to the local companies. This is an option that
Bangladesh should consider in order to maximize its growth potential. Therefore, the
multinational and domestic or national pharmaceuticals and chemical companies’ performances
are playing different role for the economy of Bangladesh. As a result, it is important how
multinational corporations (MNCs) and domestic or national corporations (DMCs) are
performing and differs from each other.
1.2 Purpose of the study
The main purpose of this study is to evaluate systematically the differences of financial
characteristics and performance between multinational and domestic corporations utilizing
risk-adjusted performance measuring tools on the pharmaceutical and chemical industry in
Bangladesh.
1.2 Problem Statement
According to Michel and Shaked (1986), if markets are not perfectly integrated, the
multinational corporations are performing a valuable function for investors. It has been frequently
argued that imperfections in the market for products translate into opportunities for MNCs. For
example, Hirsch (1979) suggested a cost saving that permits an increase in the export of
intermediate products as well as entry to markets of new products sharing production economies,
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
3
this incremental value of being able to arbitrage tax regimes (Agmon & Lessard, 1977). But the
most frequently cited disadvantage of MNCs is that they operate in a more complex environment
than their counterparts, DMCs. MNCs are always exposed to the criticism that they siphon funds
out of countries in which they do business. So, governments are liable to limit the company’s
freedom to repatriate any of its profits. The performances of MNCs’ and DMCs’ were compared
by Gughes, Louge and Sweeney (1975) through various risk measures, such as systematic (β) risk
and unsystematic risk to find out whether MNC provides substantial diversification benefits.
Previous research conducted by Michel and Shaked (1986) compared standard MNCs’ and
DMCs’ performances through performance measures such as Sharpe, Treynor and Jensen
measures.
Therefore, the researcher intends to investigate the differences of financial characteristics and
performance between multinational corporations (MNCs) and domestic corporations (DMCs) in
context of pharmaceutical and chemical industry in Bangladesh.
1.3 Methodology
1.3.1 Research approach
Here in this study two portfolios group were formed. One was for MNCs and another was for
DMCs. After that portfolios’ performances were compared.
1.3.2 Sampling Procedure
As the previous research conducted by Michel and Shaked (1986) included only publicly held
company, so the researcher followed the procedure for the sampling. It facilitates of accounting
data accesses which is most reasonable and standardized information. The genesis of the sample
was the Dhaka Stock Exchange (DSE) industry-wise company list. There were total 25
pharmaceutical and chemical companies listed. There were other large MNCs operating in
Bangladesh, but they were not enlisted in DSE. Those companies are registered and operating in
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
4
more than one country is selected as sample for multinational companies. As only two
multinational companies (GlaxoSmithKline, Reckitt Benckiser) were there, so they were selected.
According to market share position of year 2006 top three DMCs were selected. They are Square
(15.01%), Beximco (10.28%) and ACI (3.31%).
1.3.3 Instrument
In this study the researcher tries to measure financial performance of MNC and DMC
portfolios through Sharp, Treynor and Jensen performance measurement tools and differentiate
their characteristics through capitalization ratio (debt equity ratio), standard deviation of equity
and frequency distribution beta. The measure tools are as follows:
Sharpe Measure,
Where,
RiG
= Geometric average return on stock i
Rf G = Geometric average return on risk free Security
σi = Standard deviation of yearly rates of return
Treynor Measure,
Where,
RiG
= Geometric average return on stock i
RfG
= Geometric average return on risk free security
βi = Security’s beta
RiG
- RfG
σi Si =
Ti = βi
RiG
- RfG
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
5
Jensen Measure,
Where,
RiG
= Geometric average return on stock i
RfG
= Geometric average return on risk free security
βi = Security’s beta
RmG = Geometric average market return
1.3.4 Data collection
For completing the study, secondary data were utilized. For secondary data collection:
companies annual reports, daily trading price of stock and DSE general index, Dhaka stock
exchange’s library was used. The risk free rate (Rf), estimated by the monthly T-bill returns was
obtained from Bangladesh Bank’s website and online published report, like: Major Economic
indicator. Dhaka stock exchange’s web site was also used to collect companies’ yearly
performance data.
1.3.5 Data analysis
For data analysis, the researcher adopted t-test to find out the significant differences of
risk-adjusted performances and financial characteristics of the two groups, MNCs and DMCs.
Financial characteristics of MNC and DMC portfolios were evaluated by some selected variables
like capitalization ratio (debt equity ratio), standard deviation of equity and frequency distribution
of beta. To find out whether average performance measures are influenced only because of their
size or not, regression analysis was performed. For regression analysis, performance measure
used as the dependent variable, size as independent variable. Other calculations like: standard
αi = RiG
- [ RfG + βi ( Rm
G - RfG )]
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
6
deviation, stock returns etc. Microsoft Excel was used. SPSS version 12 was used for statistical
analysis
1.4 Limitations
Pharmaceutical and chemical industry is so oversaturated and the number of market players is
so intense that it limits the opportunity to work extensively on the proposed research subject
during the internship period.
The limitations confronted while conducting the research were:
• Availability of data was limited for which data of only six years has been incorporated.
• There are good numbers of multinational and domestic pharmaceutical and chemical
companies are not listed under DSE but those are also key players in the market. Exclusion of
those companies for the study can be attributed not to reflect the real differences between them.
• The proposed model of Michel and Shaked (1986) was measured on basis of monthly
return, but unavailability data of dividend and DSE general index on monthly or quarterly this
research study moved to the yearly return.
• Only three DMCs are included for DMCs’ portfolio and equal weight method was used for
portfolio of both groups, which could be a limitation.
1.5 Significance of the study
The present research is remarkable in various aspects. First of all, it will help investors to
identify the nature of MNCs and DMCs and will also help to take decision regarding investment.
Secondly, future researcher would be able to extent the research by including other indicator.
Further more, for government or authorized department like Drug administration, Board of
Investment etc. it facilitate better understanding of the potentiality of the pharmaceutical and
chemical industry to contribute in development of an economy of a country like Bangladesh.
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
7
1.6 Research Timeline
2008 March Writing Research Proposal
2008 April Developing Literature Review
2008 April Developing financial model
2008 April Collecting pertinent data
2008 April Analyzing data and interpret findings
2008 May Preparing draft and finalize research paper
2.0 Literature Review
Any discussion of the theory of stock price behavior has to start with Markowitz (1952,
1959). The Markowitz model is a single-period model, where an investor forms a portfolio at the
beginning of the period. The investor's objective is to maximize the portfolio's expected return,
subject to an acceptable level of risk (or minimize risk, subject to an acceptable expected return).
The assumption of a single time period, coupled with assumptions about the investor's attitude
toward risk, allows risk to be measured by the variance (or standard deviation) of the portfolio's
return. Thus, as indicated by the arrow in Figure 1, the investor is trying to go as far northwest as
possible.
Figure 1: Markowitz Portfolio Selection
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
8
As securities are added to a portfolio, the expected return and standard deviation change in
very specific ways, based on the way in which the added securities co-vary with the other
securities in the portfolio. The best that an investor can do (i.e., the furthest northwest a portfolio
can be) is bounded by a curve that is the upper half of a hyperbola, as shown in Figure 1. This
curve is known as the efficient frontier. According to the Markowitz model, investors select
portfolios along this curve, according to their tolerance for risk. An investor who can live with a
lot of risk might choose portfolio A, while a more risk-averse investor would be more likely to
choose portfolio B. One of the major insights of the Markowitz model is that it is a security's
expected return, coupled with how it co-varies with other securities, that determines how it is
added to investor portfolios (http://www.dfaus.com/library/articles/explaining_stock_returns).
2.1 Capital Asset Pricing Model
Building on the Markowitz framework, Sharpe (1964), Lintner (1965) and Mossin (1966)
independently developed what has come to be known as the Capital Asset Pricing Model
(CAPM). This model assumes that investors use the logic of Markowitz in forming portfolios. It
further assumes that there is an asset (the risk-free asset) that has a certain return. With a risk-free
asset, the efficient frontier in Figure 1 is no longer the best that investors can do. The straight line
in Figure 2, which has the risk-free rate as its intercept and is tangent to the efficient frontier, is
now the northwest boundary of the investment opportunity set. Investors choose portfolios along
this line (the capital market line), which shows combinations of the risk-free asset and the risky
portfolio M. In order for markets to be in equilibrium (quantity supplied = quantity demanded),
the portfolio M must be the market portfolio of all risky assets. So, all investors combine the
market portfolio and the risk-free asset, and the only risk that investors are paid for bearing is the
risk associated with the market portfolio. This leads to the CAPM equation:
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
9
CAPM equation:
E(Rj) = Rf + βj [E(Rm) - Rf]
E(Rj) and E(Rm) are the expected returns to asset j and the market portfolio, respectively, Rf is
the risk free rate, and βj is the beta coefficient for asset j. βj measures the tendency of asset j to co-
vary with the market portfolio. It represents the part of the asset's risk that cannot be diversified
away, and this is the risk that investors are compensated for bearing. The CAPM equation says
that the expected return of any risky asset is a linear function of its tendency to co-vary with the
market portfolio. So, if the CAPM is an accurate description of the way assets are priced, this
positive linear relation should be observed when average portfolio returns are compared to
portfolio betas. Further, when beta is included as an explanatory variable, no other variable
should be able to explain cross-sectional differences in average returns. Beta should be all that
matters in a CAPM world.
Figure 2: Capital Market Line
Based on the capital market theory and recognizing the necessity to incorporate return and
risk into the analysis, three researchers – William Sharpe, Jack Treynor, and Michael Jensen
developed measures of portfolio performance in the 1960s. These measures are often referred as
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
10
the composite (risk-adjusted) measures of portfolio performance, meaning they incorporate both
realized return and risk into the evaluation (Jones, 2004).
2.2 The Sharpe Measure
William Sharpe, introduce a risk-adjusted measure of portfolio performance called the reward-
to-variability ratio (RVAR) based on his work in capital market theory, dealing specially with the
capital market line (CML). The Sharpe portfolio performance measure (designated by S) is stated
as follows:
Sharpe Measure,
Where,
Ri = Average return on stock i
Rf = Average return on risk free Security
σi = Standard deviation of monthly/yearly rates of return
Shape’s measure divides average portfolio excess return (or the return above the risk free rate)
over the sample provided by the standard deviation of returns over that period (Shapre, 1966). In
other words it seeks to measure the total risk of portfolio by including the standard deviation of
returns.
The Sharpe ratio is used to measure how well the return if an asset compensates the investor
for the risk taken. When comparing tow assets each with the average return against the same
benchmark with return Rf , the asset with higher Sharpe ratio gives more return for the same risk.
2.3 Standard Deviation
Standard deviation (σ) is the statistical measure of the degree to which an individual value in a
probability distribution tends to vary from the mean of the distribution.
In finance, standard deviation is a representation of the risk associated with a given security
(stock, bonds, property, etc.) or the risk of a portfolio of securities. Risk is an important factor in
Ri - Rf
σi Si =
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
11
determining how to efficiently manage a portfolio if investments because it determines the
variations in returns on the assets and/or portfolio and gives investors a mathematical basis for
investment decisions. The overall concept of risk is that as it increases, the expected return on the
asset will increase as a result of the risk premium earned - in other words, investors should expect
a higher return on an investment when said investment carries a higher level of risk. As this study
is on historical data of stocks so, historical returns has been calculated and then standard
deviation or the returns has been calculated.
2.4 The Treynor Measure
At approximately the same time as Sharpe’s measure was developed (the mid 1960s), Jack
Treynor presented a similar measure called the reward-to-volatility ratio (RVOL). Like Sharpe,
Treynor sought to relate the return on a portfolio to its risk. Treynor, however, distinguished
between total risk and systematic risk. He used as a benchmark the ex-post security line.
Treynor’s measure relates the average excess return on the portfolio during some period to its
systematic risk as measured by the portfolio’s beta. The Treynor portfolio performance measure
(designated T) is stated as follows:
Treynor Measure,
Where,
Ri = Average return on stock i
Rf = Average return on risk free security
βi = Security’s beta
In measuring portfolio performance Treynor introduce the concept of the characteristic line,
which uses to partition a security’s return into its systematic and no systematic components. The
Ti = βi
Ri - Rf
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
12
slope of the characteristic line measures the relative volatility of the fund’s returns. As we know,
the slope of this line is the beat coefficient, which is a measure of the volatility of the portfolio’s
returns in the relation to those of the market index (Treynor, 1965). A larger T value indicates a
larger slope and a better portfolio for all investors, regardless of their risk preferences. Because
the numerator of this ratio ( ) is the risk premium and the denominator is a measure of
risk, the total express indicates the portfolios risk premium return per unit of the risk. All risk-
averse investors would prefer to maximize this value.
2.5 Beta Coefficient
The beta coefficient (β) measures an investment's relative volatility or impact of a per-unit
change in the independent variable (market) on the dependable variable (portfolio) holding all
else constant.
The Beta coefficient, in terms of finance and investing, is a measure of volatility of a stock or
portfolio in relation to the rest of the financial market
(http://en.wikipedia.org/wiki/Beta_%finince%29). An asset with a beta of 0 means that its price is
not at all correlated with the market; that asset is independent. A positive beta means that the
asset generally follows the market. A negative beta shows that the asset inversely follows the
market; the asset generally decreases in value if the market goes up. By definition, the market
itself has an underlying beta of 1.0, and individual stocks are ranked according to how much they
deviate from the macro market (for simplicity purposes, the DSE general index is usually used as
a proxy for the market as a whole). A stock that swings more than the market (i.e. more volatile)
over time has a beta above 1.0. If a stock moves less than the market, the stock's beta is less than
1.0. More specifically, a stock that has a beta of 2 follows the market in an overall decline or
growth, but does so by a factor of 2; meaning when the market has an overall decline of 3% a
stock with a beta of 2 will fall 6%. (Betas can also be negative, meaning the stock moves in the
Ri - Rf
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
13
opposite direction of the market: a stock with a beta of -3 would decline 9% when the market
goes up 3% and conversely would climb 9% if the market fell by 3 %.)
The beta coefficient is a key parameter in the capital asset pricing model (CAPM). It
measures the part of the asset's statistical variance that cannot be mitigated by the diversification
provided by the portfolio of many risky assets, because it is correlated with the return of the other
assets that are in the portfolio. Higher-beta stocks mean greater volatility and are therefore
considered to be riskier, but are in turn supposed to provide a potential for higher returns; low-
beta stocks pose less risk but also lower returns. In the same way a stock's beta shows its relation
to market shifts, it also is used as an indicator for required returns on investment (ROI).
The beta movement should be distinguished from the actual returns of the stocks. For
example a sector may be performing well and may have good prospects, but the fact that its
movement does not correlate well with the broader market index may decrease its beta. However,
it should not be taken as a reflection on the overall attractiveness or the loss of it for the sector, or
stock as the case may be. Beta is a measure of risk and not to be confused with the attractiveness
of the investment.
2.6 The Jensen Measure
The measure was first used in the evaluation of mutual fund managers by Michael Jensen in
the 1970’s. In finance, Jensen’s alpha or Jensen’s measure 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. (http://en.wikipedia.org/wiki/Jensen_ratio).
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
14
Jensen Measure,
Where,
Ri = Average return on stock i
Rf = Average return on risk free security
βi = Security’s beta
Rm = Average market return
This equation indicate that the realized rate of return on a security or portfolio should be a
linear function of the risk free rate of return, plus a risk premium that depends on the systematic
risk of the security. By subtracting risk free return from both sides we get following equation:
Where,
= The risk premium on the stock i
In this form, it would not be expected any interception for the regression if all assets and
portfolio were in equilibrium. Alternatively, certain superior portfolio managers who could
forecast market turns or consistently select under valued securities would earn higher risk
premiums than those implied by this model. To detect and measure this superior and/ or inferior
performance Jensen agreed to add an intercept (a non-zero constant) term (alpha) that measures
any positive and/or negative differences from the model. Consistent positive difference would
case a positive intercept, whereas consistent negative differences cause a negative intercept. So
with an intercept the earlier equation becomes:
Superior performances will evident by significantly positive alpha and inferior performances
will evident by significantly negative alpha. If alpha is insignificantly different from zero, this
Ri - Rf
Ri - Rf = αi + βi [ Rm - Rf ]
Ri - Rf = βi [ Rm - Rf ]
Ri = Rf + βi [ Rm - Rf ]
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
15
evidence that the portfolio manager matched the market on a risk-adjusted basis. Now to better
demonstrate what αi (alpha) is, the above equation can be rearrange like bellow:
So finally the equation becomes as bellow:
A computable advantage of the Jensen measure is that it permits the performance measure to
be estimated simultaneously with the beta for a portfolio. That is by estimating a characteristic
line in risk premium form, estimates of both alpha and beta are obtained at same time (Jones,
2004). A positive alpha of 1.0 means the fund has outperformed its benchmark index by 1%.
Correspondingly, a similar negative alpha would indicate an underperformance of 1%. However,
unlike the Sharpe and Treynor measures, each period’s returns must be used in estimating process
rather than an average return for the entire period. Thus, if performance is being measured on an
annual return on Rf, Rm and Ri must be obtained.
2.7 Systematic risk
Systematic risk is a risk that cannot be diversified away, as opposed to "idiosyncratic risk”,
which is specific to individual stocks (http://en.wikipedia.org/wiki/Systemic_risk). It also called
market risk or undiversified risk. It refers to the movements of the whole economy. Even if we
have a perfectly diversified portfolio there is some risk that we cannot avoid and this is the
systematic risk. However, the systematic risk is not the same for all securities or portfolios.
Different companies respond differently to a recession or a booming economy. For an example
think of the automobile industry compared to the food industry in case of a recession. Both of
them will be affected negatively but food industry not as much as automobile industry.
αi = (Ri - Rf )– {βi [ Rm - Rf ]}
αi = Ri - [ Rf + βi ( Rm - Rf )]
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
16
2.8 Geometric Mean
Measuring the investment return generally arithmetic average is used but the pervious study
used geometric average. Though, the geometric average always gives lower value than arithmetic
average. The geometric average is used because the effect of the negative returns of a stock is
fully offsets by its calculation, which is not true for the arithmetic average. In general, the bad
returns have the grater influences on the averaging process in the geometric technique. So
geometric average will be appropriate for this study and finally the measure tools will be as
follows:
Sharpe Measure,
Where,
RiG
= Geometric average return on stock i
Rf G = Geometric average return on risk free Security
σi = Standard deviation of monthly/yearly rates of return
Treynor Measure,
Where,
RiG
= Geometric average return on stock i
RfG
= Geometric average return on risk free security
βi = Security’s beta
Jensen Measure,
Where,
RiG
= Geometric average return on stock i
RfG
= Geometric average return on risk free security
RiG
- RfG
σSi =
αi = RiG
- [ RfG + βi ( Rm
G - Rf
G )]
Ti = βi
RiG
- RfG
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
17
βi = Security’s beta
RmG = Geometric average market return
2.9 Calculation of geometric mean
The geometric mean, in mathematics, is a type of mean or average, which indicates the central
tendency or typical value of a set of numbers. It is similar to the arithmetic mean, which is what
most people think of with the word "average," except that instead of adding the set of numbers
and then dividing the sum by the count of numbers in the set, n, the numbers are multiplied and
then the nth root of the resulting product is taken (http://en.wikipedia.org/wiki/Geometric_mean).
But it is very obvious that returns of stock can be negative or zero. So to calculate the geometric
mean along with the negative return, it requires that the negative values be converted or
transformed to a meaningful positive equivalent value. For example, to calculate the geometric
mean of the values +12%, -8%, and +2%, instead calculate the geometric mean of their decimal
multiplier equivalents of 1.12, 0.92, and 1.02, to compute a geometric mean of 1.0167.
Subtracting 1 from this value gives the geometric mean of +1.67% as a net rate of population
growth (or financial return).
2.10 Portfolio
Portfolio means a combination of different securities with different returns and standard
deviations, which actually minimize the risk and maximize the return. Holding a portfolio is a
part of an investment and risk-limiting strategy called diversification (Investmentpedia.com). The
assets in the portfolio could include stocks, bonds, options, warrants, gold certificates, future
contracts or any other that is expected to retain its value.
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2.11 The risk-free rate
The risk-free rate is the current interest rate on a default-free bond in the absence of inflation.
The risk-free interest rate is the interest rate that it is assumed can be obtained by investing in
financial instruments with no default risk. However, the financial instrument can carry other types
of risk, e.g. market risk (the risk of changes in market interest rates), liquidity risk (the risk of
being unable to sell the instrument for cash at short notice without significant costs) etc. Though a
truly risk-free asset exists only in theory, in practice most professionals and academics use short-
dated government bonds of the currency in question. Usually government Treasury bills are used
for investment. The risk-free interest rate is thus of significant importance to modern portfolio
theory in general, and is an important assumption for rational pricing. It is also a required input in
financial calculations, such as the Sharpe, Treynor, and Jensen formula for measuring volatility of
portfolio. Note that some finance and economic theory assumes that market participants can
borrow at the risk free rate; in practice, of course, very few borrowers have access to finance at
the risk free rate.
2.12 Capitalization
Capitalization is a measure of a corporation's reliance on long-term debt. These ratios compare
debt to shareholders' equity and thus reflect the extent to which a corporation is trading on its
equity. This ratio is calculated by dividing debt by shareholders' equity. It also called debt to
equity ratio (www.investmentpedia.com/finance/cap_ratio).
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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3.0 Analysis of Performance
3.1 Financial Performance
The measures of financial performance are exhibited by three tables for the both MNC and
DMC portfolios. Several observations are promptly noticeable.
The table 1 is presenting Sharpe measure of MNC and DMC portfolio, where DMC portfolio
is higher than MNC portfolio almost each of the five time periods. Therefore DMC portfolio is
obtaining higher return than MNC portfolio. In other word, DMC portfolio is compensating in a
good way of the risk taken by the investors.
3.1.2 Treynor Measure
Table 2 Treynor Measure of MNC and DMC Treynor Measure 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006
MNCs 0.76 0.89 2.74 2.5 4.38
DMCs -2.76 -1.02 -2.16 12.10 17.21
Treynor measure is demonstrated by Table 2. All the risk-averse investors would prefer to
maximize the Treynor value. But the denominator (β) of the Treynor equation measures the
volatility of the portfolio in relation to the rest of the market. The T value of the DMC portfolio is
greater than the MNC portfolio almost over each of the five time periods. Though, the T values of
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
20
the DMC portfolio are greater than the MNC, the DMC portfolio is inversely correlated to the rest
of the market. The beta of the DMC portfolio is negative over 2000 to 2004 time periods.
Therefore, the DMC portfolio is much more volatile than the MNC portfolio, hence they are
considered more risky than the MNC portfolio. Some of that high return can be explained by their
higher volatility.
3.1.3 Jensen Measure
In table 3 Jensen measure of MNC and DMC portfolio is displayed. Here in Jensen measure
the value of DMC portfolio is superior to MNC portfolio almost over the each time periods. As
the Jensen model adjust the level of risk for the level of beta and that’s why the riskier portfolios
are expected to have higher excess returns. Therefore, DMC portfolio is riskier as well as giving
higher excess returns.
Table 3 Jensen Measure of MNC and DMC Jensen Measure 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006
MNCs 2.94 2.71 2.55 2.50 3.54
DMCs 6.04 5.26 4.81 3.35 3.55
The previous researchers Michel and Shaked (1986) conclude that domestic corporations’
(DMC) performances have a superior risk-adjusted performance. While Hughes, Logue and
Sweeney (1975) showed that multinational corporations’ (MNC) performances are more risk-
adjusted with higher return than domestic corporations (DMC). Interestingly, this study reveals
that domestic corporations (DMC) are less risk-adjusted with higher returns whereas
multinational corporations (MNC) are more risk-adjusted with lower returns. T-test is performed
separately for each performance measure. The result does not show any significant differences
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
21
between the groups for both Sharpe and Jensen measure. The result of t-test of Treynor
measurement of the two samples significantly differs at a level of p < 0.001.
3.2 Financial Characteristic
The Financial characteristic of two groups is presented by four tables. The selected variables
for the financial characteristic are debt equity ratio as a capitalization ratio, average standard
deviation of equity, frequency distribution of beta and average total asset.
3.2.1 Debt equity ratio
Table 4 Debt equity ratio of MNC and DMC 2006 2005 2004 2003 2002 2001 2000
MNCs 0.115 0.085 0.095 0.115 0.115 0.120 0.095
DMCs 0.221 0.303 0.323 0.254 0.095 0.125 0.135
The table 4 is demonstrating debt equity ratio of MNC and DMC portfolios. The previous
study demonstrates that MNCs are highly leveraged than DMCs. But the present study finds out
that DMCs are more leveraged rather than MNCs. The higher debt equity ratio of DMCs reflects
the higher borrowed fund in the capital structure. This might be an explanation of the higher
volatility of DMCs portfolio than MNCs. Further more, MNC can reduce the total risk:
operational and financial risk, by diversifying internationally at the corporate level. The range of
the debt equity ratio of MNC is 0.085 to 0.12, whereas the range of DMC is 0.095 to 0.303.
Result of the t-test indicates that the debt equity ratio of the two samples significantly differs at a
level of p < 0.001.
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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Figure 3: Debt equity ratio
3.2.2 Average Standard Deviation of Equity Table 5 Average Standard Deviation of Equity of MNC and DMC 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006
MNCs 0.005 0.010 0.070 0.070 0.02
DMCs 0.986 0.290 0.531 1.214 1.625
The above table provides the average standard deviation of equity for the two groups. As
indicated by the results, the average standard deviation of equity of the DMCs is consistently
higher than MNCs. A t-test was performed which indicate the average standard deviation of the
two samples are significantly differs at a level of p < 0.05. The lower equity-variability reported
for the MNC portfolio is consistent with the theoretical hypothesis on total risk reduction. The
result of the standard deviation of equity of the present study similar with the empirical findings
reported by Hughes et al. (1975) as well as with the previous research reported by Michel and
Shaked (1986).
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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3.2.3 Frequency Distribution of Beta
Table 6 Frequency Distribution of Beta of MNC and DMC
Range MNC DMC
-4 - -3 - 0.20
-2 - -1 - 0.40
-1 - 0 0.20 0.40
1 - 2 0.40 -
3 - 4 0.40 -
Mean beta 2.05 -1.69
The table 6 is presenting the frequency distribution of beta. After frequency distribution of
betas of the two portfolios, it reveals that 60 percent of DMC portfolio’s beta is under negative
range and 80 percent of MNC portfolio’s beta is under positive range. Furthermore the mean of
betas of MNC and DMC portfolios are respectively 2.05 and -1.69. The results are clearly
suggestive. As most of the values of beta of MNC portfolio falls under positive range and close to
market’s beta, they should have lower systematic risk. On the other hand most of the value of
beta of DMC portfolio falls under negative range; they should have higher systematic risk.
This might be one of the explanations of low returns for MNCs and high returns for DMCs.
The result of lower systematic risk of MNC is also supported by Hughes et al (1975), Rugman
(1977) and Agmon and Lessard (1977).
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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3.2.4 Average Total Assets
Table 7 Average Total Assets of MNC and DMC 2000-2002 2001-2003 2002-2004 2003-2005 2004-2006
MNCs 6131.33 6562.16 6871.00 7448.87 7853.94
DMCs 4661.64 4254.13 4828.00 5807.56 6827.74
*million in TK
By using asset as a variable the size of the portfolios is measured. The above table indicates
the average size of multinational corporations (MNC) is higher compared to the domestic
corporations (DMC). As a consequence it is necessary to test whether average performance
measures of the two groups differ because of the size effect. Miller and Pras (1979) reported
through regression result that size is a significant explanatory variable for performances. The
pervious study conducted by Michel and Shaked (1986) reported that size is not a significant
variable in any case as well as for observed differences in the two groups’ performance.
Similarly, the present study reveals the size can not explain observed differences in the two
groups’ performance.
A correlation analysis has been conducted on all the performance tools and size as variables
to explore the relationship among variables. For interpreting the strength of relationships among
variables, the guideline suggested by Rowntree (1981) has been followed; and the classification
of the correlation coefficient (r) is as follows:
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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0.0 to 0.2 Very weak, negligible
0.2 to 0.4 Weak, low
0.4 to 0.7 Moderate
0.7 to 0.9 Strong, high marked
0.9 to 1.0 Very strong, very high
The bi-variate correlation procedure was a subject to a two tailed test of statistical significance
at two different levels highly significant (p<. 001) and significant (p<. 01) or (p<.05). The results
of the correlational analysis are shown in Table 8. The result shows that size has a moderate
correlation but not significantly.
Table 8 Correlational Matrix for Sharpe, Treynor, Jensen Measure and Size of MNC and DMC
Correlations
Sharpe Treynor Jensen size Sharpe Pearson Correlation 1 .536 -.220 .537 Sig. (2-tailed) . .110 .541 .110 N 10 10 10 10Treynor Pearson Correlation .536 1 .046 .437 Sig. (2-tailed) .110 . .899 .207 N 10 10 10 10Jensen Pearson Correlation -.220 .046 1 -.306 Sig. (2-tailed) .541 .899 . .390 N 10 10 10 10size Pearson Correlation .537 .437 -.306 1 Sig. (2-tailed) .110 .207 .390 . N 10 10 10 10
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
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4.0 Summary and Discussion
For better understanding of MNC and DMC portfolios performances the researcher have to
compare the return of measures. The comparison is given bellow:
Table 9 Financial Performance Comparison of MNC and DMC
Measurement Tool MNC (GOOD)
DMC (GOOD)
Sharpe Measure - √
Treynor Measure - √
Jensen Measure - √
The above table shows that returns of all measure of DMC portfolio are better than MNC
portfolio. Therefore DMC portfolio could be considered as attractive option if we disregard of
risk factor.
The following table illustrates the riskiness of the portfolios. As the result of frequency
distribution of beta shows that the DMC portfolio is more risky than MNC portfolio.
Table 10 Systematic Risk (β) Comparison of MNC and DMC
Less Risky More Risky
MNC √ -
DMC - √
It is obvious that the results and findings of the study could be momentary and even an
incident. According to Hassan, Islam and Basher (2000), the Dhaka Stock exchange is an
inefficient capital market. The present study collected the trade prices of stocks from DSE.
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
27
Therefore it would not be sensible to recommend which portfolio would be attractive or risky
between MNC and DMC portfolios. Moreover, the study observed a few negative betas of DMC
portfolio, which is unusual for the pharmaceutical and chemical industry. May be over short
periods luck can over shadowed all else, but luck can not be expected to continue.
Table 11 T-bill Rate Comparison of Bangladesh and U.S Government
Retrieved from http://en.wikipedia.org/wiki/Beta_%finince%29 Bodie, Z., Kane,A. & Marcus, A.J. (2003). Investments (5th ed.). McGraw-Hill: New Delhi. Dhaka stock exchange’s industry wise company list. Retrieved from: http://www.dsebd.org/industrylisting.php Jensen’s Alpha
Retrieved from http://en.wikipedia.org/wiki/Jensen_ratio Jones, C.P. (2004). Investment analysis and management. (9th ed.) John Wiley & Sons Inc. Major Economic Indicator (March, 2008).
Rahman, H. The Growth of the Pharmaceutical Sector. Retrieved from: http://www.ais-dhaka.net/School_Library/Senior%20Projects/
06_rahman_pharmaceuticals.pdf Sharp ratio
Retrieved from http://en.wikipedia.org/wiki/Sharpe_ratio Standard deviation Retrieved from http://en.wikipedia.org/wiki/Standard_deviation Systemic risk
Retrieved from http://en.wikipedia.org/wiki/Systemic_risk Treynor ratio
Retrieved from http://en.wikipedia.org/wiki/Treynor_ratio
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC
30
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Appendix
Financial Performance & Characteristics of Pharmaceutical & Chemical Industry in Bangladesh: MNC vs. DMC