Dynamic asset allocation strategy

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Department of Finance,
University of Dhaka
Report on
Portfolio Management:
Dynamic Asset Allocation Strategy
Submitted to
Dr. Mahmood Osman Imam, FCMA
Professor
Department of Finance
University of Dhaka
Course Name: Financial Derivatives
Course Code: F- 503
Submitted by
Md. Monjurul Ahsan
Id No: 19-099 (BBA)
20-376 (MBA)
Section-A
MBA 20th
Batch
University of Dhaka
Date of Submission: 30-01-2019

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Letter of Transmittal
January 30, 2019
To
Dr. Mahmood Osman Imam
Professor
University of Dhaka
Sir,
Here is the report of the group term paper that you assigned us to work on “Portfolio Management:
Dynamic Asset Allocation Strategy” fixing the date of submission on January 30, 2019.
The topic that you have given us is really an important & interesting fact for the finance students
in acquiring practical orientation of dynamic asset allocation strategy.
We thank you for choosing us for working on this topic.
Yours sincerely
…………………………………
Md. Monjurul Ahsan
ID: 19-099 (BBA)
20-376 (MBA)
Section-A
20th Batch
University of Dhaka

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Acknowledgement
I express my thanks to our dear course teacher Dr. Mahmood Osman Imam for assigning me the
report dealing with dynamic asset allocation strategy.
The presentation of this report is of a great expectation in our MBA program and I am quite happy
to submit it dully applying that I think should have to be included. Theoretical knowledge is valued
when it is successfully applied in practical scenario. In this respect I found this report a great
opportunity to deal with some knowledge about dynamic asset allocation strategy.
So lastly I would again like to express our heartfelt thanks to our course teacher for providing the
theoretical knowledge and valuable guidelines related to the topic assigned.

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Executive Summary
Portfolio insurance is a dynamic trading strategy designed to protect a portfolio from market
declines while preserving the opportunity to participate in market advances. Several portfolio
insurance methods exist and are used in practice. The best-known strategy involves trading in
“real” and /or “synthetic” options. With the introduction of exchange-traded index put options, it
seemed theoretically possible for an investor to use these contracts to insure well-diversified
portfolios, especially index funds. For some reasons, most investors prefer not to use the option
market for insuring the portfolios. Hence it calls for the dynamic trading strategy replicating the
option strategy to insure the portfolio. In this strategy, the manager replicates an option through a
process of continually revising, in a prescribed manner, the proportions of a portfolio consisting
of the underlying the asset and the riskless asset. Besides the complex nature of the underlying
option pricing theory, the dynamic strategy calls for buying more stock when the market is going
up and selling off some stock as the market goes down. In this report there is thorough analysis of
the economy, industry and selected companies in order to develop a well-diversified optimum
portfolio of 10 stocks. The ten selected companies are from 10 different industries. The portfolio
is constructed of Tk 10, 00,000 and in dynamic asset allocation. The proportions allocated to the
underlying portfolio and the riskless asset change every period, so that the dynamic insurance
strategy requires a significant amount of trading. As in Bangladesh there is no market for derivative
securities, I assumed a hypothetical option market for this dynamic asset allocation strategy.

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Table of Contents
Executive summary....................................................................................................................4
Introduction............................................................................................................................. -9
Asset Class Selection........................................................................................................ 17-18
Dynamic Asset Allocation Strategy.................................................................................. 19-23
5.1 Delta Calculation ................................................................................................... 23-24
5.2 Insured Portfolio ..........................................................................................................25
5.3 Put Option Dynamics.............................................................................................. 25-26
5.4 Call Option...................................................................................................................27
6. Dynamic Asset Allocation............................................................................................. 28-39
7. Comparison.................................................................................................................... 40-41
8.Conclusion ...........................................................................................................................42

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Introduction
Origin of the report
For the partial fulfillment of the study, our honorable course teacher, Dr. Mahmood Osman Imam
assigned me to report on “Portfolio Management: Dynamic Asset Allocation Strategy”. To conduct
the report at first I wanted to know the procedures of constructing the portfolios with given amount
of initial investment which will provide knowledge about how insurance can be achieved.
Background of the Report
To the investor, insurance of portfolio is crucial. Options in the market of Bangladesh are not
available, but we can replicate them to construct insured portfolio which will provide a certain
return. Without dynamic asset allocation, there have been some strategies that don’t provide
portfolio insurance though the return is higher, but, the investor is always at risk and risk-averse
investors might not come in the market out of this scenario.
Objective of the Report
To be honest, the objective of the study is to fulfill the requirement of our course on International
Business. Other objectives behind conducting this study are as follows:
 To enhance our practical knowledge
 To know how Dynamic asset allocation strategy works
 To acquire knowledge about the procedures constructing insured portfolio.
 To compare dynamic asset allocation strategy with other methods.
 To explore how portfolio insurance provides cushion to investors.
Methodology
To accomplish the task we take help from our text book, articles, Dhaka Stock Exchange, and
different web sites.
Limitation of the Report
The major limitations encountered are as follows:
 Lack of adequate information
 Nonexistent options market in Bangladesh

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 Lack of Experience
 Lack of adequate time relative to the volume of the report
 Limitation of Knowledge
Dynamic Asset Allocation
One of the active asset allocation strategies is dynamic asset allocation, with which one constantly
adjust the mix of assets as markets rise and fall, and as the economy strengthens and weakens.
With this strategy one sell assets that are declining and purchase assets that are increasing, making
dynamic asset allocation the polar opposite of a constant-weighting strategy. For example, if the
stock market is showing weakness, investors sell stocks in anticipation of further decreases; and if
the market is strong, investors purchase stocks in anticipation of continued market gains.
In this strategy, the manager replicates an option through continuously revising the proportions of
a portfolio consisting of the underlying asset (stock/bond) and the riskless asset (bond/T-bill) to
insure portfolio’s value. This strategy requires buying more stock when the market is going up and
selling off some stock as the market goes down. The proportions allocated to the underlying risky
asset & the riskless asset change every period, so this strategy requires a significant amount of
trading. The number of units of the underlying risky asset that must be held long at any given
moment will be given by the call option’s “Delta”. The amount of riskless asset to hold is
determined by subtracting the value of the units held in the underlying asset from the total value
of the insured portfolio.
Many experts believe that what an investor buys or sells is more important than when he or she
buys or sells it. This is the essence of asset allocation. Because many asset classes tend to rise and
fall together, a portfolio’s overall return is much more affected by how the portfolio is allocated
rather than the specific securities chosen. A well-known 1986 study by Brinson, Hood and Bee
bower confirmed that 95% of the time, asset allocation determined a portfolio’s returns rather than
the specific securities chosen.
A dynamic asset allocation strategy is a mix of active and passive investing. On one hand the
investor keeps a consistent, long-term asset allocation and does not alter that based on short-term
market swings or stock fads. On the other hand, the investor buys and sells securities in his
portfolio occasionally in order to keep the portfolio aligned with the original weightings.

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Merits of Dynamic Asset Allocation Strategy
 Often cheaper than active trading
 The strategy requires less in trading commissions and advisory fees.
 Reduced downside risk as investments are avoid on declining markets
 Better exploitation of changing economic scenarios and
 Benefit of diversification of investments.
Disadvantages of Dynamic Asset Allocation Strategy
 The need of active management of portfolio
 Chance of loss because of wrong market interpretation and wrong investing decisions
 High risk when compared to strategic and tactical methods.
Process of dynamic asset allocation
There are some steps by which dynamic asset allocation strategy can be made successful. In a flow
chart all the relevant step is given below:
1. Put Option Dynamics
2. Insured Portfolio Dynamics
3. Call Option Deltas
4. Asset Allocation

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1. Put option dynamics
In this step all the put prices of each step have to be finding out from the strike prices. It helps to
find out the deltas of call which is very much essential for constructing a new portfolio.
2. Insured portfolio dynamics
The total value of risky and risk free investment will be combined which is known as insured
portfolio. In each of the time period this amount will be find out. Basically it represents the new
portfolio amount.
3. Call option delta
To construct new portfolio call option delta helps very much. The difference between up and down
movement stock price will be divided by the respective put option value difference to find out the
delta value.
4. Asset allocation
Due to the changes in call option delta value in each period asset allocation also changes.
According to call option delta shares may be bought or sold out. If delta increases then some new
risky shares have to buy and with the same amount risk free asset have to sell. On the other hand
if delta decreases than the previous time step then some risky shares have to sell and with the same
amount some risk free asset have to include. In each step risk free asset will be increased at the
risk free rate. Through this way asset allocation has been done and new portfolio has been formed.

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Three Steps Analysis
Economy Analysis:
The economy of Bangladesh is a rapidly developing market-based economy. Its per capita income
in 2018 was estimated to be US$ 1314 (adjusted by GDP Per Capita). According to the
International Monetary Fund, Bangladesh ranked as the 44th largest economy in the world in 2018
in PPP terms and 57th largest in nominal terms, among the Next Eleven (N-11) of Goldman Sachs
and D-8 economies, with a gross domestic product of US$306 billion in PPP terms and US$115.6
billion in nominal terms.
Bangladesh's economy has grown roughly 6% per year since 1996 despite political instability, poor
infrastructure, corruption, insufficient power supplies, slow implementation of economic reforms,
and the 2008-09 global financial crisis and recession. Although more than half of GDP is generated
through the service sector, almost half of Bangladeshis are employed in the agriculture sector with
rice as the single-most-important product. Garment exports, the backbone of Bangladesh’s
industrial sector and 80% of total exports, surpassed $21 billion last year, 18% of GDP. The sector
has remained resilient in recent years amidst a series of factory accidents that have killed over
1,000 workers and crippling strikes that shut down virtually all economic activity. Steady garment
export growth combined with remittances from overseas Bangladeshis, which totaled almost $15
billion and 13% of GDP IN 2018, are the largest contributors to Bangladesh’s current account
surplus and record foreign exchange holdings.
Textile industry:
The textile and clothing (T&C) industries provide the single source of economic growth in
Bangladesh's rapidly developing economy. Exports of textiles and garments are the principal
source of foreign exchange earnings. Agriculture for domestic consumption is Bangladesh’s
largest employment sector. By 2002 exports of textiles, clothing, and ready-made garments (RMG)
accounted for 77% of Bangladesh’s total merchandise exports. By 2013, about 4 million people,
mostly women, worked in Bangladesh's $19 billion-a-year industry, export-oriented ready-made
garment (RMG) industry. Bangladesh is second only to China, the world's second-largest apparel
exporter of western brands. Sixty percent of the export contracts of western brands are with
European buyers and about forty percent with American buyers only 5% of textile factories are
owned by foreign investors, with most of the production being controlled by local investors. As

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Textile industry is not reached its maturity stage yet investment in these industries will generate a
good return for the investors and for this reason I have selected companies from these industries
in the portfolio.
Pharmaceutical industry:
Pharmaceutical is the core of Bangladesh’s Healthcare sector, and serves as one of the most
important manufacturing industry. With a history since 1950s, the industry has now turned one of
the most successful pharmaceuticals manufacturing industry among the developing countries.
Presently, the industry meets 97% of local demand and exports to more than 80 countries. The
industry has been experiencing robust growth over the last few years. A local industry supporting
drug policy and effective regulatory framework, along with TRIPS relaxations are the key reasons
for success of the industry. As Pharmaceutical industry is in a growth stage in industry life cycle
there is a probability of making better investment return in this industry.
Cement Industry:
Development of cement industry in Bangladesh dates back to the early-fifties but its growth in real
sense started only about a decade. The country has been experiencing an upsurge in cement
consumption for the last five years. Government gave permission for establishing cement
industries in Bangladesh in FY1995. Initially the cement industry took place without the proper
analysis of the demand and supply of cement in the country. Within the span of the two to three
years, industry attained expanded capacity of the product with stable growth rate of consumption.
Considering the “Life cycle of the industry‟, currently cement industry of Bangladesh is in the
growth stage. Sales of cement are increasing due to an enormous demand for cement in both the
local and foreign markets. The industry realized about 30% and 21% growth in 2009 and 2010
respectively after suppressed demand from previous years.
Food and Allied Industry:
The food processing industry in Bangladesh represents one of the major potential sectors within
the industrial segments in terms of contribution to value addition and employment. The sector
accounts for over 22% of all manufacturing production and employs about 20% of labor forces.
All food processing enterprises account for 2% of the national GDP. The food processing sector

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includes processing of cereals, pulses & oilseeds, bakery & confectionary, fruits and vegetables,
dairy, carbonated beverages and various other food items.
Food industry is a rapidly growing sector in Bangladesh, employing a significant portion of the
labor force in the country. Between 2004 and 2010, the food processing industry in Bangladesh
grew at an average 7.7 percent per annum. Bangladesh Bureau of Statistics, in its 25006 Economic
Census, reported that there were approximately 246 medium sized food processing industries
employing 19 percent of the industrial manufacturing workforce in Bangladesh or 8 percent of the
total manufacturing labor force. The industry employs 2.45 percent of the country's total labor
force and its share in the GDP was 2.01 percent in 2010. There are also numerous small scale
factories and domestic units engaged in food processing throughout the country. According to
some industry analysts, the food processing sector in Bangladesh is a 4.5 Billion US Dollar
industry. In 2010, Bangladesh exported over $700 million worth of processed food and beverages,
over 60 percent of them were shrimp and fish products.
Fuel and power industry:
Electricity is a key ingredient for the socio-economic development of the country. The government
has given top priority to development of the sector considering its importance in the overall
development of the country. The government has set the goal of providing electricity to all citizens
by 2021. Adequate and reliable supply of electricity is an important pre-requisite for attracting
both domestic and foreign investment.
As the power sector is a capital-intensive industry, huge investments are required in order to
generate addition to the capacity. Competing demands on the government resources and declining
levels of external assistance from multilateral and bilateral donor agencies constrained the
potential for public investment in the power sector. Recognizing these trends, the government of
Bangladesh amended its industrial policies to enable private investment in the power sector.
Fuel & power industry are oligopolistic in nature. These two industries have been making a lot of
profit. The current state of our power sector is very poor. So it has huge scope of growth. That’s
why I included companies from this industry.

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Tannery industries:
In Bangladesh the leather industry is well established and ranked fourth in terms of earning foreign
exchange. In consideration of being a value added sector the (Government of Bangladesh (GoB),
Ministry of Industry (MoI) has declared it as a priority sector. The leather products sector have
huge opportunities in generating employment , entrepreneurship and investment by increasing
export of higher value added products rather than finished leather and by utilizing locally made
raw material (finished leather) to convert into more value added leather products (including
footwear and other leather goods).
Statistics prepared by Export Promotion Bureau of Bangladesh for the Financial Year 2011-12,
the leather sector grew by 17.5 percent and earned $765 million in revenue. Of this $434.8 million
was attributed from leather products, accounting for approximately 57 percent of the total revenue.
The leather sector includes 220 tanneries, 3,500 MSMEs and 110 large firms2 of leather products
controlling more than 90% of the export market. Most of the enterprise enterprises are located in
Dhaka, followed by two big clusters at Bhairab and Chittagong . The sector generates direct and
indirect employment for about 850,000 3 people, including a significant number of women
particularly in the leather products industries.
Banking industry:
Banking sector of Bangladesh is one of the major sectors, which contributes significantly to the
national economy. The sector comprises a number of banks in various categories such as:
Nationalized Commercial Banks, Specialized Banks, Private Commercial Banks and Trans-
National Banks. The Banking Industry of Bangladesh at present is in the growth stage. Almost
every year new private banks are coming up, new branches are opening within two to three months,
and new customers are coming to open an account in different banks. As a result, according to July
30, 2016 there are 6 nationalized commercial banks, 2 specialized banks, 40 local private
commercial banks and 9 foreign commercial banks operating in this country.
Moreover, as on July 30, 2016 there are 60,881,322 numbers of deposit accounts and 10,462,785
numbers of advance accounts in the banks.

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Nonbanking Financial Institution:
Financial sector is the most important sector of any economy. Currently, 44 life and general
insurance companies and 21 NBFIs listed in DSE. These two industries are the most consistent
performer since many years. These are also in the growth stage, so they have very high future
profit potentiality. Therefore investment in these industries will generate a good return for the
investors and for this reason I have selected companies from these industries in the portfolio.
Engineering Industry:
The light engineering industry in Bangladesh continues to grow each year. This labor-intensive
sector produces a diverse range of items, including import substitute machinery spares, plant
machineries, small tools, toys, consumer items and paper products for the domestic market. Most
of these enterprises are located in and around Dhaka metropolis. In the Export policy 2003-2006,
the Government of Bangladesh had identified the following five sectors to have the High Priority:
Light Engineering Products (including auto-parts and bi-cycles), Software & ICT products, Agro-
products & Agro-processing products, Leather goods and High value-added readymade garments.
Insurance Industry:
However, though the global insurance market declined but Bangladesh has seen a significant
growth over last year. Growth in the industrialized countries was -- 2.8% for life and -- 0.6% for
non-life insurance, however, emerging markets grew at a rate of 4.2% for life and 2.9% for non-
life insurance.
Company Analysis:
I have chosen 10 companies from those 10 industries. I tried to diversify as much as possible. As
banking sector’s contribution was 7.4% and 4.49% according to February 12 and 11 of the total
capital market I have taken two dominant and growing companies Islami Bank for portfolio
construction. Textile industry comprises about 8.64% and 7.08% of capital market so I chose
Square Textile which market share is almost 30% and making continuous profit and listed as A
category share in DSE. Pharmaceutical also comprises 13.84% and 13.24% of overall market so I
choose Square Pharma which is a growing multinational company operated in Bangladesh. From
Tannery industries I choose Bata Shoe which is a market leader and growing firm. As both
insurance and nonbanking finance institution comprises 4.77% and 3.72% of capital market I

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choose Prime insurance and Lanka Bangla Finance two renowned companies within their sector.
From food and allied sector I choose Bangas for its growth opportunities and positive profit making
and choose Padma oil from fuel and power sector which also comprises 16.25% of overall capital
market. From engineering sector I have chosen Singer BD Limited. From Cement Industry I have
chosen Heidelberg Cement which is a market leader in the cement industry and performing well.
From insurance industry which comprises a good amount in market composition I have selected
Prime Insurance.
Table 1: Sector wise P/E ratio
Sector name P/E
Ratio
Sector Cap Sector Earning
Bank 11.03 411,798,451,840 40,197,073,552
Cement 38.83 53,862,493,722 2,487,445,101
Ceramics Sector 20.37 21,975,535,682 606,053,639
Engineering 15.85 116,693,607,327 5,152,146,890
Financial Institutions 25.36 90,953,609,789 8,074,706,542
Food & Allied 15.66 225,704,358,664 7,189,690,168
Fuel & Power 12.93 269,910,804,296 21,394,730,606
Insurance 16 90,235,000,147 4,491,202,611
IT Sector 17.41 3,610,643,261 207,435,341
Jute 2086.88 646,592,400 3,449,280
Miscellaneous 23.92 69,909,936,693 2,131,790,043
Paper & Printing 20.5 2,076,476,000 151,138,400
Pharmaceuticals &
Chemicals
18.74 329,740,523,223 14,478,007,073
Services & Real Estate 18.38 20,058,576,564 547,189,254
Tannery Industries 25.70 25,934,584,533 1,009,161,308
Telecommunication 16.41 490,099,553,921 19,922,836,039
Textile 15.78 82,521,354,118 6,897,400,867
Travel & Leisure 20.29 27,130,328,960 1,601,240,261
We calculate P/E excluding :
Z category.
Shares of OTC.
Shares which are not traded for a long time.

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Asset class selection
Industries selected to make this portfolio:
 Bank
 NBFI
 Textile
 Food and allied
 Cement
 Fuel and power
 Telecommunication
 General Insurance
 Engineering
 Pharmaceuticals and Chemical
I have selected these industries because of the growth rate of industries & diversification of risk.
Selection Criteria of Assets:
Criteria are followed to select individual security. These are:
 Listed in Dhaka Stock Exchange
 Listed before January 01, 2006
 ‘A’ category share.
 Growth firm.
 Having significant market share on underlying sector.

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Selection of Individual Asset:
The securities selected are as follows:
Sector Company
Bank AB Bank
Textile APEX SPINNING & KNITTING MILLS LIMITED
Engineering Aftab Automobiles
Pharmaceuticals IBNSINA Pharmaceuticals
Telecom GP
NBFI Lankabangla
Cement Lafarge Surma Cement
Fuel and power Jamuna oil
Ceramic RAK Ceramics
Food & Allied BATBC
Risk free asset selection:
There may be 100% risk free asset or some combination of risky and risk free asset in the portfolio
that’s why risk free asset should be determined. I have taken 91-day T-bill as the risk free asset for
constructing new portfolio. The rate in each quarter has been used to calculate the growth of risk
free asset.
Data collection:
Data have been collected from DSE stock and Bangladesh bank. The opening, closing .highest and
lowest price of the shares has been taken from the daily share price statement. Dividend
information also has taken from the exchanges. Risk free rate has been determined in quarter basis.
Portfolio construction:
Now after getting all the required information I have determined dividend adjusted price in each
quarter. Then with considering the investment and situation I have determined the value of risky

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and risk free investment. In this case initial, higher, lower and closing values are multiplied by the
respective number of shares. Then the total closing values have been distributed among the 10
companies equally. Again by following this strategy I have got the total closing values at the end
of second quarter. After following this strategy, I have got all quarter’s total closing values. These
values have been used as strike price. Put option values have been determined by considering either
option will be exercised or not. If it will be exercised, then value of the put option will be zero
otherwise the difference between stock price and strike price.
With the help of stock price and put option value the call option delta has been calculated.
Continuous compounding has been used in the growth of risk free asset. After determining cal
option delta dynamic asset allocation has been formed for the equal weight of the both risky and
risk free asset. So with the changes of the delta new portfolio has been formed by buying or selling
risky or risk free asset. Through this I have got the insured portfolio value in each of the quarter
end.

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Dynamic asset allocation strategy
At first some assumption has been taken before constructing dynamic asset allocation. These
are given below-
 Investment amount is 1000000 Tk.
 Initial distribution of total fund between Risky securities and T-bills is
considered to be 50:50
 The amount of investment in shares will be distributed among the 10
securities equally
 Continuous compounded risk free rate is assumed.
 Call and Put option strike prices are assumed 1080000 Tk.
Now step by step dynamic asset allocation strategy is given below:
Standard deviation determination
All the closing prices of the company have been taken in daily basis. After this dividend also been
adjusted after the record that. Return has been calculated through the log normal basis. And by
giving the equal weight portfolio standard deviation for daily basis for every quarter have been
calculated. In this case daily portfolio standard deviation has been converted into quarter through
the following formula-
Quarter portfolio standard deviation = daily standard deviation × √ number of days
Based on this formula the following portfolio standard deviation has been gotten.

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Quarter 4 (2017)
Quarter 1 (2018)
Company ABBank Apex Spinning Aftab IBNSINA GP LankabanglaLafarge Jamunaoil RAK BATBC
Weight 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10
Sector Company Covariance Covariance Covariance Covariance Covariance Covariance Covariance Covariance Covariance Covariance Weight
Bank ABBank 0.0005783 -0.0001137 -0.0000242 0.0000221 0.0004962 0.0007327 -0.0000373 -0.0001009 -0.0000189 0.0001501 0.10
Textile Apex Spinning -0.0001137 0.0005620 -0.0000498 0.0001084 -0.0001432 0.0002103 -0.0000131 0.0000061 -0.0000051 -0.0000877 0.10
Engineering Aftab -0.0000242 -0.0000498 0.0003267 -0.0000668 0.0000647 -0.0016628 0.0000043 0.0000198 0.0000007 0.0000518 0.10
Pharmaceuticals IBNSINA 0.0000221 0.0001084 -0.0000668 0.0002429 -0.0000495 0.0002729 0.0000352 -0.0000289 -0.0000149 0.0000189 0.10
Telecom GP 0.0004962 -0.0001432 0.0000647 -0.0000495 0.0095434 0.0001546 -0.0001200 -0.0023467 -0.0001845 0.0000576 0.10
NBFI Lankabangla 0.0007327 0.0002103 -0.0016628 0.0002729 0.0001546 0.0195649 0.0001645 -0.0001188 0.0000464 -0.0000141 0.10
Cement Lafarge -0.0000373 -0.0000131 0.0000043 0.0000352 -0.0001200 0.0001645 0.0005075 0.0000543 0.0000228 0.0000246 0.10
Fuel and power Jamunaoil -0.0001009 0.0000061 0.0000198 -0.0000289 -0.0023467 -0.0001188 0.0000543 0.0007092 0.0000536 0.0000311 0.10
Ceramic RAK -0.0000189 -0.0000051 0.0000007 -0.0000149 -0.0001845 0.0000464 0.0000228 0.0000536 0.0000905 -0.0000482 0.10
Food &Allied BATBC 0.0001501 -0.0000877 0.0000518 0.0000189 0.0000576 -0.0000141 0.0000246 0.0000311 -0.0000482 0.0008377 0.10
Portfolio Return -0.000122488
Portfolio Variance 0.0002807
Portfolio Standard Deviation 0.016754948 0.1297833
Company AB Bank Apex Spinning Aftab IBNSINA GP LankabanglaLafarge Jamunaoil RAK BATBC
Weight 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10
Bank AB Bank 0.0008691 0.0000163 0.0001508 0.0000806 0.0001136 0.0003419 0.0001140 0.0000231 0.0004974 -0.0000260 0.10
Textile Apex Spinning 0.0000163 0.0007210 0.0000647 0.0001096 -0.0000151 0.0002680 -0.0000238 0.0000692 -0.0001519 -0.0000716 0.10
Engineering Aftab 0.0001508 0.0000647 0.0003592 0.0000362 0.0001247 0.0001696 0.0005290 0.0003934 0.0001065 -0.0000558 0.10
Pharmaceuticals IBNSINA 0.0000806 0.0001096 0.0000362 0.0001318 0.0000278 0.0001317 0.0000058 0.0000219 0.0001621 -0.0000226 0.10
Telecom GP 0.0001136 -0.0000151 0.0001247 0.0000278 0.0023079 0.0000809 0.0000690 0.0000694 0.0000820 -0.0002120 0.10
NBFI Lankabangla 0.0003419 0.0002680 0.0001696 0.0001317 0.0000809 0.0116248 0.0001458 0.0000743 0.0040828 -0.0042552 0.10
Cement Lafarge 0.0001140 -0.0000238 0.0005290 0.0000058 0.0000690 0.0001458 0.0010664 0.0006830 0.0001978 -0.0000726 0.10
Fuel and power Jamunaoil 0.0000231 0.0000692 0.0003934 0.0000219 0.0000694 0.0000743 0.0006830 0.0005690 0.0001806 -0.0000313 0.10
Ceramic RAK 0.0004974 -0.0001519 0.0001065 0.0001621 0.0000820 0.0040828 0.0001978 0.0001806 0.0099927 -0.0015072 0.10
Food & Allied BATBC -0.0000260 -0.0000716 -0.0000558 -0.0000226 -0.0002120 -0.0042552 -0.0000726 -0.0000313 -0.0015072 0.0019094 0.10
Portfolio Return -0.00095636
Portfolio Variance 0.0003511
Portfolio Standard Deviation 0.018737118 0.1475362

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Quarter 2 (2018)
Quarter 3 (2018)
Weight 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10
Bank ABBank 0.0005644 0.0000511 0.0000942 0.0000133 -0.0000003 0.0001405 0.0000156 0.0000310 0.0000066 0.0000020 0.10
Textile Apex Spinning 0.0000511 0.0001109 0.0000320 0.0000224 -0.0000061 -0.0000035 -0.0000053 0.0000171 0.0000102 0.0000014 0.10
Engineering Aftab 0.0000942 0.0000320 0.0001611 0.0000224 0.0000157 0.0001354 0.0000188 0.0000477 0.0000382 0.0000151 0.10
Pharmaceuticals IBNSINA 0.0000133 0.0000224 0.0000224 0.0001895 0.0000281 0.0000556 0.0000633 -0.0000113 0.0000475 0.0000178 0.10
Telecom GP -0.0000003 -0.0000061 0.0000157 0.0000281 0.0000416 0.0000223 0.0000340 0.0000023 0.0000256 0.0000034 0.10
NBFI Lankabangla 0.0001405 -0.0000035 0.0001354 0.0000556 0.0000223 0.0008332 -0.0000377 0.0000221 0.0000800 0.0000176 0.10
Cement Lafarge 0.0000156 -0.0000053 0.0000188 0.0000633 0.0000340 -0.0000377 0.0002924 0.0000137 0.0000522 0.0000135 0.10
Fuel and power Jamunaoil 0.0000310 0.0000171 0.0000477 -0.0000113 0.0000023 0.0000221 0.0000137 0.0000557 0.0000102 0.0000042 0.10
Ceramic RAK 0.0000066 0.0000102 0.0000382 0.0000475 0.0000256 0.0000800 0.0000522 0.0000102 0.0001141 0.0000288 0.10
Food &Allied BATBC 0.0000020 0.0000014 0.0000151 0.0000178 0.0000034 0.0000176 0.0000135 0.0000042 0.0000288 0.0001901 0.10
PortfolioReturn -0.000641803
PortfolioVariance 0.0000497
PortfolioStandardDeviation 0.007050716 0.0541576
Weight 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10
Bank ABBank 0.0001859 0.0000030 -0.0000495 -0.0000264 -0.0000340 0.0001004 -0.0000239 0.0000083 -0.0000034 0.0000121 0.10
Textile Apex Spinning 0.0000030 0.0005497 0.0000515 0.0001768 0.0000270 -0.0000748 0.0000467 -0.0000184 0.0000236 -0.0000246 0.10
Engineering Aftab -0.0000495 0.0000515 0.0004928 0.0002682 -0.0000072 0.0000869 0.0000903 0.0000043 0.0001448 -0.0000653 0.10
Pharmaceuticals IBNSINA -0.0000264 0.0001768 0.0002682 0.0008971 -0.0000215 -0.0000774 -0.0000115 -0.0000399 0.0000112 -0.0000785 0.10
Telecom GP -0.0000340 0.0000270 -0.0000072 -0.0000215 0.0001622 -0.0000033 0.0000182 0.0000030 -0.0000408 -0.0000215 0.10
NBFI Lankabangla 0.0001004 -0.0000748 0.0000869 -0.0000774 -0.0000033 0.0004021 0.0000577 0.0000759 0.0000922 0.0000135 0.10
Cement Lafarge -0.0000239 0.0000467 0.0000903 -0.0000115 0.0000182 0.0000577 0.0005498 0.0003295 0.0008815 -0.0000046 0.10
Fuel and power Jamunaoil 0.0000083 -0.0000184 0.0000043 -0.0000399 0.0000030 0.0000759 0.0003295 0.0004412 0.0007291 0.0000134 0.10
Ceramic RAK -0.0000034 0.0000236 0.0001448 0.0000112 -0.0000408 0.0000922 0.0008815 0.0007291 0.0023376 -0.0000073 0.10
Food &Allied BATBC 0.0000121 -0.0000246 -0.0000653 -0.0000785 -0.0000215 0.0000135 -0.0000046 0.0000134 -0.0000073 0.0000850 0.10
PortfolioReturn 0.000740908
PortfolioVariance 0.0001137
PortfolioStandardDeviation 0.010665142 0.0832974

22
Up factor and down factor determination:
After getting all the quarterly standard deviation we can calculate the up and down factor for all
the quarter by following the below formula:
U= 𝒆^𝝏√𝒕
d= 𝟏/𝒖
Finally, the up factor and down factor has been calculated for every period which has been given
below-
u d
Q4(2016) 1.13858149 0.878286
Q1(2017) 1.158975145 0.862831
Q2(2017) 1.055650897 0.947283
Q3(2017) 1.086864958 0.920078
Portfolio value and option price determination
As the initial investment is Tk 1000000 so multiplying by the up factor value of up can be made and
multiplying by the down factor value of portfolio down can be determined. This strategy has been
followed for every node of every quarter according their up and down factor.
Now the value of portfolio and option price are given below-
Portfolio value for each quarter

23
Q4(2017) 1.13858149 0.878286 1514029
Q1(2018) 1.158975145 0.862831 1393024
Q2(2018) 1.055650897 0.947283 1281690
Q3(2018) 1.086864958 0.920078 1319588
1358606
1250023
1150118
1138581
1127161
1037075
954189.7
982403.7
1011452
930614.2
856237.2
1000000
1167901
1074559
988677.7
1017911
1048010
964250.1
887184.8
878285.8
869476.1
799985.4
736048.6
757812.5
780219.9
717862.8
660489.4
Node Time Q0 Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)

24
Delta calculation
Through the call option value and portfolio value call delta can be calculated. Here it has been
assumed that closing price equal to strike price. Subtracting the K from portfolio value we get
option price. And after that probability and present value factor has been calculated to find out the
up and value of call option. Now for probability calculation the following formula has been used.
P = (𝒂−𝒅)/(𝒖−𝒅)
Here,
a=𝒆^𝒓Δ𝒕
u= up factor
d= down factor
So probability for down factor will be = 1- P
Finally value of call option has been calculated through the following formula
Value of call option = 𝑒^(−𝑟𝑡)(portfolio up ×p +portfolio down×1-p)
After finding out the value of call option delta value has been calculated through the following
formula-
Delta = (𝑓𝑢−𝑓𝑑)/(𝑆0𝑢−𝑆0𝑑)
Now the delta for each quarter is given below:

25
N/A
1
N/A
1.031449
N/A
1
N/A
0.898707
N/A
0.272652
N/A
0.320895
N/A
0
N/A
0.647382
N/A
0.490454
N/A
0.577237
N/A
0
N/A
0.181739
N/A
0
N/A
0
N/A
0
N/A
Node Time Q0 Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)

26
Insured Portfolio
1514029
1393024
1281690
1319588
1358606
1250023
1150118
1161105
1127161
1070458
1080000
1034517
1080000
1039643
1080000
1067368
1167901
1098791
1080000
1054534
1080000
1038585
1080000
1012610
1080000
1043751
1080000
1021118
1080000
1046334
1080000
Node Time Q0 Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)

27
Put Option Dynamics
Put option Strike price (1000000*1.08) tk.= 1080000
u d a p (1-p) T-bill rate C.C Rate PVF
Q4(2016) 1.13858149 0.878286 1.032898 0.593988 0.406012 Q4(03/10/2017) 3.25% 0.032369 0.99194
Q1(2018) 1.158975145 0.862831 1.030032 0.564594 0.435406 Q1(02/01/2018) 2.97% 0.02959 0.99263
Q2(2018) 1.055650897 0.947283 1.028295 0.747568 0.252432 Q2(10/04/2018) 2.80% 0.027902 0.993049
Q3(2018) 1.086864958 0.920078 1.042150 0.731906 0.268094 Q3(03/07/2018) 4% 0.04 0.989732
1514029 0
1393023.884
0 1281690 0
1319587.647
0 1358606 0
1250022.759
0 1150118 0
1138581
22523.22 1127161 0
1037075.365
33382.60027 954189.7 125810.3
982403.7166
52113.35669 1011452 68548.03
930614.2011
109028.9625 856237.2 223762.8
1000000
67368.47349 1167901 0
1074559.145
24231.5318 988677.7 91322.3
1017911.458
36622.95017 1048010 31990.38
964250.0763
74335.27202 887184.8 192815.2
878285.8
134324.3 869476.1 210523.9
799985.4345
243765.8754 736048.6 343951.4
757812.4894
263305.0627 780219.9 299780.1
717862.7813
328471.2053 660489.4 419510.6
Q0 Q4 (2016) Q1 (2018) Q2 (2018) Q3 (2018)

28
Call Option
91day
u d a p (1-p) T-bill rate C.CRate PVF
Q4(2016) 1.13858149 0.878286 1.032898221 0.593988 0.406012 Q4(03/10/2016) 3.25% 0.03236868 0.991940489
Q1(2017) 1.158975145 0.862831 1.030032404 0.564594261 0.435406 Q1(02/01/2017) 2.97% 0.029590282 0.992629729
Q2(2017) 1.055650897 0.947283 1.028295355 0.74756817 0.252432 Q2(10/04/2017) 2.80% 0.027902455 0.993048664
Q3(2017) 1.086864958 0.920078 1.042150 0.731906302 0.268094 Q3(03/07/2017) 4% 0.04 0.989731542
1514029 434028.8461
1393023.884
367923.0507 1281690 201689.9407
1319587.647
328391.0315 1358606 278605.934
1250022.759
220424.6806 1150118 70117.8221
1138581.49
195002.3717 1127161 47160.87365
1037075.365
34162.90078 954189.7 0
982403.7166
25361.56636 1011452 0
930614.2011
0 856237.2 0
1000000
125564.7413 1167901 87900.68019
1074559.145
63674.43991 988677.7 0
1017911.458
47270.09406 1048010 0
964250.0763
0 887184.8 0
878285.8398
26491.72291 869476.1 0
799985.4345
0 736048.6 0
757812.4894
0 780219.9 0
717862.7813
0 660489.4 0
Q0 Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)

29
Dynamic asset allocation
Each and every time new portfolio is formed according to delta. Over the period investment pattern
will not be same. If market goes up then investment will be made in new shares. On the other hand
if market goes down then investment will be made in risk free asset. Now according to our delta
dynamic asset allocation has been given below:
Quarter 0
Quarter 0
100% Equity portfolio 1000000
Insured portfolio 1067368
Initial Delta 0.647382
New Portfolio
Shares (0.843127*1000000) 647381.7
T-bill 419986.7
Total 1067368
Quarter 4(2017)
Shares (0.84313*1061250) 737096.9
T-bill 424007.9
Total 1161105
New Delta 0.898707
Sell (.097526102*1061250) Shares 286154
Buy T-bill 286154
New Portfolio
Shares (.94065*1061250) 1023251
T-bill 710161.8
Total 1733413

30
Quarter 4b (2017)
100% Equity portfolio 878285.8
Shares (0.84313*942285) 568586.2
T-bill 444023.9
Total 1012610
New Delta 0.181739
Sell (0.3693*942285) Shares 408967.5
Buy T-bill 408967.5
New Portfolio
Shares (0.47383*942285) 159618.7
T-bill 852991.4
Total 1012610
Quarter 1a (2018)
Shares (0.84313*1155791) 1185922
T-bill 133665.4
Total 1319588
New Delta 1.031449
Buy (0.18832*1155791) Shares 175165.1
Sell T-bill 175165.1
New Portfolio
Shares (1.03145*1155791) 1361087
T-bill -41499.7
Total 1319588
Quarter 1b (2018)
Shares (0.84313*974442) 882892.8
T-bill 151624.2
Total 1034517
New Delta 0.320895
Sell (0.33858*974442) Shares 567644
Buy T-bill 567644
New Portfolio
Shares (0..50455*974442) 315248.9
T-bill 719268.2
Total 1034517

31
Quarter 1c (2018)
Shares (0.84313*1026229) 184994.1
T-bill 869540.3
Total 1054534
New Delta 0.577237
Sell (0..08601*1026229) Shares -402582
Buy T-bill -402582
New Portfolio
Shares (0.92914*1026229) 587575.8
T-bill 466958.6
Total 1054534
Quarter 1d (2018)
Shares (0.84313*865209) 137724
T-bill 883393.6
Total 1021118
New Delta 0
Sell (0.84313*865209) Shares 137724
Buy T-bill 137724
New Portfolio
Shares 0
T-bill 1021118
Total 1021118
Quarter 2a (2018)
Shares (0.84313*1219549) 1436833
T-bill -43809.2
Total 1393024
New Delta 1
Buy Shares 218523.7
New Portfolio
Shares (1*1219549) 1393024
T-bill 0

32
Total 1393024
Quarter 2b (2018)
Shares (.84313*1095365) 1289335
T-bill -39312
Total 1250023
New Delta 1
Buy Shares 196091.1
New Portfolio
Shares (1*1095365) 1250023
T-bill 0
Total 1250023
Quarter 2c (2018)
Shares (0.50455*1028196) 332792.7
T-bill 737665.2
Total 1070458
New Delta 0.272652
Buy Shares -50032.4
Sell T-bill -50032.4
New Portfolio
Shares (0.54196*1028196) 282760.3
T-bill 787697.6
Total 1070458
Quarter 2d (2018)
Shares 298629.8
T-bill 741013.3
Total 1039643
New Delta 0
Sell Shares 298629.8
Buy T-bill 298629.8
New Portfolio
Shares 0

33
T-bill 1039643
Total 1039643
Quarter 2e (2018)
Shares 620274.9
T-bill 478515.7
Total 1098791
New Delta 0.490454
Buy Shares -93252.8
Sell T-bill -93252.8
New Portfolio
Shares (2.519892*1620038) 527022.1
T-bill 571768.5
Total 1098791
Quarter 2f (2018)
Shares 556600.5
T-bill 481984.8
Total 1038585
New Delta 0
Sell (0.512999*687346.8) Shares 556600.5
Buy T-bill 556600.5
New Portfolio
Shares 0
T-bill 1038585
Total 1038585
Quarter 2g (2018)
Shares 0
T-bill 1043751
Total 1043751
New Delta 0

34
New Portfolio
Shares 0
T-bill 1043751
Total 1043751
Quarter 2h (2018)
Shares 0
T-bill 1046334
Total 1046334
New Delta 0
New Portfolio
Shares 0
T-bill 1046334
Total 1046334
Quarter 3a (2018)
Insured portfolio 1514028.846
1 shares * 1288663.896 1514028.846
0 T-Bill 0
Total 1514028.846
Quarter 3b (2018)
1 shares * 1154141.364 1281689.941
0 T-Bill 0
Total 1281689.941
Quarter 3c (2018)

35
1 shares * 1157442.358 1358605.934
T-Bill 0
Total 1358605.934
Quarter 3d (2018)
1 shares*1036617.931 1150117.822
T-Bill 0
Total 1150117.822
Quarter 3e (2018)
0.64196 shares * 1086466.539 307322.2843
T-bill 819838.5894
Total 1127160.874
Quarter 3f (2018)
0.54196 shares * 973051.218 260161.4106
T-Bill 819838.5894
Total 1080000
Quarter 3g (2018)
0 shares*975834.2708 0
T-Bill 1080000
Total 1080000
Quarter 3h (2018)

36
0 Shares * 873967.7582 0
T-Bill 1080000
Total 1080000
Quarter 3i (2018)
0.99803 shares* 1144206.969 572801.8956
T-Bill 595098.7846
Total 1167900.68
Quarter 3j (2018)
0.99803 shares*1024764.174 484901.2154
T-Bill 595098.7846
Total 1080000
Quarter 3 k(2018)
0 shares*1027695.132 0
T-Bill 1080000
Total 1080000
Quarter 3L (2018)
0 shares*920414.9082 0
T-Bill 1080000
Total 1080000
Quarter 3m (2018)

37
0 shares * 964675.5761 0
T-Bill 1080000
Total 1080000
Quarter 3n (2018)
0 shares * 863973.9102 0
T-Bill 1080000
Total 1080000
Quarter 3p (2018)
0 shares*866444.9878 0
T-Bill 1080000
Total 1080000
Quarter 3q(2018)
0 shares * 775997.5298 0
T-Bill 1080000
Total= 1080000

38
Comparison of portfolios
I have done the comparison in terms of absolute portfolio value, return on investment and Q2Q
return. And I have calculated all these values in all the following four portfolios and then compare
the result between those and try to find out which provide the best result.
1) Static Portfolio
2) 100 % T-bill Portfolio
3) Dynamic Portfolio
4) 100% equity portfolio
1. Static Portfolio
2. 100% T-Bill Portfolio
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Stock 711394 878600 826439 893342
T-Bill 355483.2917 358122.7552 360629.6145 364371.1467
Total 1066877 1236722 1187069 1257713
ROI 6.69% 23.67% 18.71% 25.77%
Q2Q Return 6.69% 15.92% -4.01% 5.95%
Static Portfolio Value
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Stock 0 0 0 0
T-Bill 1008125 1015610.328 1022719.6 1033330.316
Total 1008125 1015610 1022720 1033330
ROI 0.81% 1.56% 2.27% 3.33%
Q2Q Return 0.81% 0.74% 0.70% 1.04%
100% T-bill Portfolio Value

39
3. 100% Equity Portfolio
4. Dynamic Portfolio
Comparison
Comparison in terms of absolute portfolio Value
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Static Portfolio 1066877 1236722 1187069 1257713
100% T-Bill portfolio 1008125 1015610 1022720 1033330
100% equity Portfolio 1098879 1357158 1276587 1379931
Dynamic Portfolio 852991 1021118 1046334 1080000
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Stock 1098879 1357158 1276587 1379931
T-Bill 0 0 0 0
Total 1098879 1357158 1276587 1379931
ROI 9.89% 35.72% 27.66% 37.99%
Q2Q Return 9.89% 23.50% -5.94% 8.10%
100 % equity Portfolio Value
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Stock 0 0 0 0
T-Bill 852991.4449 1021117.552 1046333.987 1080000
Total 852991 1021118 1046334 1080000
ROI -14.70% 2.11% 4.63% 8.00%
Q2Q Return -14.70% 19.71% 2.47% 3.22%
Dynamic Portfolio Value

40
In case of absolute portfolio value, dynamic portfolio keeps increasing in each quarter and it has
the highest value in each quarter. So dynamic provides the best solution in each quarter. And 100%
equity portfolio provides lowest performance amongst the four in every quarter.
Comparison in terms of absolute return
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Static Portfolio 6.69% 23.67% 18.71% 25.77%
100% T-Bill portfolio 0.81% 1.56% 2.27% 3.33%
100% equity Portfolio 9.89% 35.72% 27.66% 37.99%
Dynamic Portfolio -14.70% 2.11% 4.63% 8.00%
0
200000
400000
600000
800000
1000000
1200000
1400000
1600000
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Absolute portfolio Value
Static Portfolio 100% T-Bill portfolio 100% equity Portfolio Dynamic Portfolio

41
While I compared the among the four options, then I found out that 100% equity provides negative
return in each and every quarter. And static portfolio return was negative in the first two quarters
but it improves a little bit over the next two quarter. Both 100% T-bill and dynamic portfolio
provides positive return. 100% T-bill portfolio performs better than dynamic portfolio in the first
quarter but in the remaining three quarter dynamic portfolio provides more return.
Comparison in terms of Q2Q return
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Static Portfolio 6.69% 15.92% -4.01% 5.95%
100% T-Bill portfolio 0.81% 0.74% 0.70% 1.04%
100% equity Portfolio 9.89% 23.50% -5.94% 8.10%
Dynamic Portfolio -14.70% 19.71% 2.47% 3.22%
-20.00%
-10.00%
0.00%
10.00%
20.00%
30.00%
40.00%
50.00%
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Return on investment

42
In the first quarter both static and 100% equity portfolio provides negative result and 100% T-bill
and dynamic provides positive value. Here 100% T-bill is better than dynamic portfolio. In the
second quarter, all portfolios provide positive return and among those dynamic portfolio provides
more return. In the third quarter all the portfolios provide positive return but here 100% equity
provides the best result. In the fourth quarter dynamic portfolio provides the best result.
-20.00%
-15.00%
-10.00%
-5.00%
0.00%
5.00%
10.00%
15.00%
20.00%
25.00%
30.00%
Q4 (2017) Q1 (2018) Q2 (2018) Q3 (2018)
Q2Q Return

43
Conclusion
Dynamic asset allocation strategy is the better model of portfolio investment in comparison with
the static asset allocation strategy. This method provides the basis for adjustment in asset
proportion in the portfolio in terms of the changes in prices of the underlying securities. This is a
continuous process of changing the portfolio combination and structure which provides better
insurance of the portfolio value indicating the supremacy above all other methods of portfolio
construction.
Dynamic asset allocation is essential to construct new portfolio with the risky and risk free asset.
That means with the changes in delta either securities sell or buy to construct new portfolio. If
delta increases then new risky securities will be bought and if delta decreases then some securities
will be sold and risk free asset with the same amount will be bought to make new portfolio. So in
the above case by the shares of 10 companies and Treasury bill it can be possible to construct
portfolio with quarterly that’s why dynamic asset allocation strategy is used. Through this
approach investment can be hedge out as it is constructed by considering the delta of call option.
As every period portfolio construction can be changed that’s why it is dynamic asset allocation
strategy not static asset allocation strategy.
The basic dynamic trading approach involves replicating the insured portfolio’s price action with
an ever-changing combination of positions in the underlying portfolio and the risk less asset. The
proportions allocated to the underlying portfolio and the risk less asset change every period. The
dynamic insurance strategy requires a significant amount of trading. By dynamic asset allocation
it can be shown that how the same replication is accomplished (approximately) with either a stock
portfolio and short futures positions or the risk less futures.

44
References
1. Options, Futures and Other Derivative Securities by John Hull. Prantice-Hall International Inc.
2. Gibson R., Heinz Z. (1996). The Benefits and Risks of Derivative Instruments: An Economic
Perspective, Derivatives Use, Trading and Regulation. Geneva Paper.
3. World Federation of Exchanges, 2008c, “Equity derivatives and cash equity trading”, December
2008.
4. The case for Dynamic Asset Allocation by Mellon Capital Management Corporation Research
Team.
Websites
 www.dsebd.org
 www.secbd.org
 www.bb.org.bd
 www.mof.gov.bd
 www.stockbangladesh.com
 www.langkabanglaportal.com
 www.encyclopedia.com
Primary Data
 DSE Trade Information Archive
 DSE Dividend Archive

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