BPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
Thesis final bilal n saif 222 (2010 2011)
1. Performance and evaluation of portfolio
The information ratio performance measures
(PROJECT- THESIS)
BBA - 8
Foundation University Institute of
Engineering and Management Sciences
1
2. RESEARCH PROPOSAL
SUBMITTED BY
SAIFULLAH MALIK
BILAL AHMAD
RAHEEM ANSER
SUBMITTED TO
Mr. NAVEED ANJUM
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3. □ ABSTRACT
Our thesis is comprised of measuring the performance and
evaluation of portfolio of mutual fund by using information
ratio and to rank them accordingly, out of 12 companies we
have selected five different companies of mutual funds which
register with stock exchange and their data available in the
financial websites. We evaluated mutual funds by using
information ratio analysis and by finding their R-squared.
This study showed that no effort has been made related to
this specific topic in the past, as mutual fund market is
still in developing phase in Pakistan. We found that the fund
which has higher information ratio that mutual fund performed
better in the market, and R-squared values tell us how much a
fund is diversified. As we have taken only five companies
data of five years and process them buy using only
information ratio analysis, but results would be more
specified and authentic if more mutual fund had taken and
data for more time period of these mutual fund .It may
produced more informative results if we used more analysis
techniques i-e Sharpe ratio, Treynor ratio and the alpha
ratio formulas. But data related to the topic was limited and
was not easily accessible. We also come to know the research
related to the topic was also very limited. As mutual fund
market in Pakistan is still in developing phase so there are
very limited institutes were available.
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5. □ INTRODUCTION
Increasing number of mutual funds in the developed financial
markets indicate investor preference for this mode of
investment (Huhmann, 2005). We observed that mutual fund
industry has experienced tremendous growth, but it is still a
recent phenomenon in some of the developing countries.
Because of its rapid growth mutual funds are growing
vigorously. Mutual funds are of two types open ended and
closed ended, closed ended are those whose shares are
initially offer to public and then traded in the secondary
market between various investors where as open ended funds
are those whose subscription and redemption of shares are
allowed on continually bases (Talat Afza, Ali Rauf).
Mutual funds are institutions established for the purpose of
benefiting those investors who cannot afford to invest
directly in various type of securities.
For these small investors asset management companies plays a
vital role by facilitating them with providing expert
professional management in the stock market.
Mutual Funds were introduced in Pakistan in 1962, with the
public offering of NIT (National Investment Trust).
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6. Currently, this is the only open ended mutual fund operating
in public sector. The formation of the ICP
(Investment Corporation of Pakistan) in 1966 offered a series
of close-ended mutual funds which was afterwards divided into
two lots in June 2000 and was then privatized. In the private
sector, there are forty-three open-ended and twenty-two
closed-ended mutual funds. Although Pakistani mutual funds
have experienced a phenomenal growth during the period under
study (1999-
2005) with net asset value grown from Rs. 16 billion to Rs.
137 billion till June 30, 2005. However, comparing Pakistani
mutual fund industry internationally it is of a tiny size.
Pakistan holds only 1.33% mutual fund assets to primary
securities, in contrast to India with 3.7%, Malaysia 4.0%,
Hong Kong 20.3%, and South Korea 16.5%. These facts indicate
that mutual fund industry in Pakistan has significant room to
grow. Paid-up capital may look substantial but the size is
still too small as compared to international standard.
(Khorana etal (2005).
In order top measure the performance of some mutual fund that
we used in the study we are using information ratio analysis.
The information ratio (IR) measures a portfolio manager's
ability to generate excess returns relative to a benchmark
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7. and also attempts to identify the consistency of the
investor. This ratio will identify if a manager has beaten
the benchmark and that benchmark is KSE-100 INDEX. The higher
the IR the more consistent a mutual fund is.
Information ratio = Rp- Ri/ Sp-i
Rp = Return of the portfolio
Ri = Return of the index or benchmark
Sp-i = Tracking error (standard deviation of the
difference between returns of the portfolio and the returns
of the index)
It explains Information Ratio-IR
A high IR can be achieved by having a high return in the
portfolio, a low return of the index and a low tracking
error.
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8. a)SIGNIFICANCE OF THE STUDY
This study is significant because it will produce data on the
mutual funds performance and their ranking in the market. It
is also useful to financial analysts, Stock exchange dealers,
Staff of the organization, Perspective investors of the firm,
Managers and top executive of the organization, Students who
carry a research in the same issue.
b) SCOPE AND LIMITATION OF THE STUDY
The broad problem areas of the project are
To analyze the performance of mutual funds of the
selected institute.
The numbers of institutes are limited.
We are analyzing mutual funds only by using
information ratio.
Data was not easily accessible.
Research related to topic was limited.
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9. c) PROBLEM STATEMENT
To analyze the mutual funds performance with respect to
benchmark by using information ratio.
d) OBJECTIVES
The focus of the research is to analyze and evaluate the
difference between performances of the mutual funds and to
rank them accordingly. The project's objectives are
summarized as follows.
Relationship between mutual funds and benchmark
by using information ratio.
How to calculate an information ratio, how to
interpret it.
How useful is the Information Ratio to Evaluate the
Performance of Portfolio Managers.
e) RESEARCH QUESTIONS/HYPOTHESIS
H1.High value of information ratio predict excess
portfolio return relative to the benchmark
H2.Higher the diversification the better will be the
performance of the fund.
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10.
H0.Higher the diversification poor will be the
performance of the fund.
f) CONCEPTUAL FRAME WORK/THEORITICAL FRAMEWORK
DEPENDANT VARIABLE INDEPENDENT VARIABLE
MUTUAL FUND 1.MARKET RETURN 2.DIVERSIFICATION
PERFORMANCE
In our study there is one dependent variable that is mutual
fund performance and we have two independent variables those
are market return and diversification, and in it we are not
considering any intervening and moderating variables.
The relationship between variables is as follows
i. Mutual fund performance ∞ market return
ii. Mutual fund performance ∞ diversification
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12. □ LITERATURE REVIEW
The idea underlying the information ratio (or IR) – also
called the appraisal ratio – proposed by Grinold [1989] is to
get the performance relative to a given reference portfolio.
It measures the excess return of the fund over a given
benchmark, divided by the standard deviation of the excess
return – or more concretely, the degree of regularity in
outperforming the benchmark. The excess return over the
benchmark results from the choices made by the manager to
overweight assets that he hopes will exceed that of the
benchmark. A passive management gives a null ratio. The
denominator, also called “tracking error”, reflects the cost
of an active management. This ratio has some major drawbacks.
First, it requires much data to assess its significance. The
sensitivity to the selected benchmark is also a concern:
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13. Goodwin [1998] estimate that is has a notable impact,
which is contradicted by Gillet and Moussavou [2000]. Next,
if a fund tracks an index closely, with a small tracking
error, little changes in excess return swing the information
ratio from largely positive to largely negative or vice
versa. As for the Sharpe ratio, Israelsen [2005] partially
tackles this issue by introducing Israelsen’s modified
information ratio where the tracking error is exponentiated.
Finally, this ratio also considers equally positive and
negative variations from the index: an issue solved
considering an information ratio based on semi-variance
[Gillet and Moussavou, 2000].
Cameron Clement, CFA he interpreting The Information
Ratio is a widely used and powerful tool for evaluating
manager skill, The Information Ratio was established to
address the shortcomings of the reward-to-variability ratio,
modern form of the IR is widely credited to Trey nor and
Black (1973). It measures the manager’s excess return over an
appropriate benchmark relative to the standard deviation of
those excess returns. By computing risk on a relative return
basis, the IR effectively eliminates market risk, showing
only risk taken from active management, currently a great
13
14. amount of performance analysis is relative to a benchmark.
Sometimes this is done because it is deemed reasonable, but
other times for lack of an alternative.
A good discussion of the use and abuse of benchmarks is.
[Siegel, 2003]Frank j. Ambrosio, CFA.He said that the
information ratio is the risk-adjusted return of a portfolio
or security versus a benchmark. To calculate the information
ratio, an asset’s excess return is divided by its tracking
error relative to the benchmark.(The Sharpe ratio is actually
an information ratio that uses the risk-free return as the
benchmark.)
Georges Hübner Affiliate Professor of Finance, EDHEC
Business School. The performance measures for managed
portfolios with directional strategies developed in the
framework of the capital asset pricing Model proposed by Trey
nor (1961), Sharpe (1964) and Lintner (1965), three of them
directly relate to the beta of the portfolio through the
security market line (SML). Jensen’s (1968) alpha is defined
as the portfolio excess return earned in addition to the
required average return, while the Trey nor (1965) ratio and
the information ratio (IR) are defined as the alpha divided
by the portfolio beta and by the standard deviation of the
14
15. portfolio residual returns. There exists no other widely used
alternative measure that sticks to the SML. Indeed, most
recent performance measures developed along with the
increasing popularity of hedge funds, such as the Sortino
ratio (Sortino and Price [1994]), the M2 (Modigliani and
Modigliani [1997]) and the Omega (Keating and Shadwick
[2002]) focus on a measure of total risk, in the continuation
of the Sharpe (1966] ratio applied to the capital market
line.David E. Kuenzi Strategy (Benchmarks From the Investment
Manager’s Perspective).
The investment management industry becomes more
sophisticated, investment managers are using benchmark indices
in an increasingly complex fashion—as the baseline along which
the manager intends to add value and manage risk, for
determining which factor bets have most influenced overall
portfolio returns(Attribution analysis), and for determining
the extent to which the manager added value (through use of
the information ratio Arun S. Muralidhar. Many papers on
active management argue for maximizing information ratios
using a risk budgeting framework. Recent innovations in risk-
adjusted performance measures show why maximizing information
ratios could be the wrong policy and also provide a different
twist to the discussion on separating alphas from betas. The
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16. literature on maximizing information ratios focuses only on
the active management process and ignores two actions used by
clients or managers to improve risk-adjusted performance:
passive management and leverage/deleverage using cash. It
demonstrates the impact of maximizing the wrong objective
function and shows the benefit of maximizing risk-adjusted
returns for the entire fund, rather than the information ratio
on the active component.
In 1989, Richard Grinold introduced the fundamental law of
active management that detailed how to measure the efficiency
of a manager, as measured by the information ratio.
1 Roger Clarke, Harindra de Silva, and Steven Thorley
revisited this research and published Portfolio Constraints
and the Fundamental Law of Active Management. They determined
Grinold’s work did not factor in portfolio. Constraints and
their impact on the information ratio. To address this issue,
Clarke, de Silva, and Thorley’s research included a measure of
a manager’s ability to forecast future securities’ returns and
the ability then to implement investment ideas.
Richard C. Grinold and Ronald N. Kahn, Information is the
vital input into any active management strategy. Information
separates active management from passive management.
Information, properly applied, allows active managers to
outperform their information less benchmarks. Analyses go
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17. beyond this to investigate statistical significance, value-
added, and skill. These more sophisticated analyses rely on
three important statistics describing. Investment performance:
t-statistics, information ratios, and information
coefficients.
The information ratio in particular, however, most directly
captures the investment value added offered by the
information, and so is the most important statistic for
investment information analysis.
Gordon Bodnar and Charles Smithson, Discusses the evolution of
risk allocation, contrasting it with asset allocation and
examining its advantages in the modern market and portfolio
structuring.
Modern portfolio theory revolutionized investing by making
clear the importance of correlations of asset returns, in
addition to expected returns and the variance of returns. By
the 1970’s, the dominant investment style had become “asset
allocations”. Investors tried to hold “efficient portfolios”
– portfolios of assets with low correlations – so that all
but the market risk would be diversified away. This gave
rise to the common practice of managing to some benchmark
portfolio.
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18. With the rise in benchmarking, the task of an active
portfolio manager was to “beat the index”. Clearly, one way
to beat the index was to take on more risk than in the index
– a tactic not necessarily in line with the wishes of the
investor.
CHAPTER # 3
METHODOLOGY
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19. □ METHODOLOGIES
a) DATA COLLECTION
We collect the data of mutual fund from the electronic data
provided by Karachi stock exchange. We also collect some data
from different journals, websites and books.
b) SAMPLE SELECTION
We select five companies of mutual funds listed with KSE.
Following criteria are followed for sample selection.
1. All companies are public listed companies
2. The size of the companies varies.
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20. 3. The companies have a life of more then five years.
4. The data relating to these companies is available.
SERIAL NAME OF THE COMPANY SYMBOL
1 AL MIZAN MUTUAL FUND AMMF
2 PICIC GROWTH FUND PGF
3 INTERFUND MOD FIFM
4 ASIAN STOCKS ASFL
5 SAFEWAY MUTUAL FUND SFWF
c) MODEL
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21. We used information ratio for the analysis of
mutual funds and we rank them accordingly by using the
following formula:
Rp = Return of the portfolio
Ri = Return of the index or benchmark
Sp-i = Tracking error (standard deviation of the
difference between returns of the portfolio and the returns
of the index).
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22. CHAPTER #4
DATA ANALYSIS & MEASURES
□ DATA ANALYSIS & MEASURES
a) DATA ANALYSIS
We find an information ratio by implementing the data of
benchmark/mutual funds
b) MEASURE
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23. We find an information ratio by implementing the data of
benchmark/mutual funds, by using following formula in the
excel sheet
Rate of return (both mutual fund and KSE prices)
RP-RI=alpha
Average (both mutual fund and KSE return)
Standard deviation (STDEV)
Information ratio
Annualized information ratio
i. PICIC GROWTH FUND ( PGF )
DATE PGF KSE R PGF R KSE ER
31-Jan-05 52.95 6232.5
28-Feb-05 65.3 6764.31 0.233239 0.085329 0.14791
30-Mar-05 45.45 8303.32 -0.30398 0.227519 -0.5315
29-Apr-05 45 7606.67 -0.0099 -0.0839 0.073999
31-May-05 46.8 7128.54 0.04 -0.06286 0.102857
30-Jun-05 53.65 6895.75 0.146368 -0.03266 0.179024
29-Jul-05 52.4 7489.29 -0.0233 0.086073 -0.10937
31-Aug-05 50 7217.97 -0.0458 -0.03623 -0.00957
30-Sep-05 52.45 7802.83 0.049 0.081028 -0.03203
31-Oct-05 55.25 8268.58 0.053384 0.05969 -0.00631
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33. □ FINDINGS
RANKING OF MUTUAL
FUND
ANNULIZED
MUTUAL INFORMATION R R Squared
FUND INFORMATION RATIO RATIO RANKING Squared %
1 AMMF -0.14697 -0.509131437 5 0.283797 28.3 %
2 SFWF -0.13972 -0.47777 4 0.000286 0.0286 %
3 PGF -0.1344 -0.35831 3 0.019655 1.96%
4 FIFM 0.17535 0.607519 1 0.002561 0.25%
5 ASFL 0.019129 0.066265 2 0.025562 2.25%
RANKING BASED ON R SQUARED VALUES
R Squared Ranking Criteria Ranking
80% and above 1 4
28.3 %
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34. 60%_80% 0
2
0.0286 %
40%_60% 5
3
1.96%
20%_40% 0
4
0.25%
1%_20% 5
5
2.25%
_ 0% and below _
0
So from the findings we concluded that higher the information
ratio more efficient the mutual fund would be. So according
to findings the results shows that FIFM is at the top of
these above five mutual funds as it got the higher
information ratio. And when we use R squared we come to know
that from all these above mutual funds none of the mutual
fund is as much as diversified as it has to be. AMMF is the
fund from all these five which is diversified 28.3% but it
does not shows any response in its efficiency. According to
our ranking criteria on the basis of R squared none of the
mutual fund is at the position of 1, 2 or 3 position. So
these mutual funds need more diversification as well as they
should take some valuable steps to increase their returns.
□ DISCUSSION
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35. Our above findings and theoretical analysis – we ranks the
mutual funds portfolio according to their performance then
apply R squared regression , and then ranks them according to
the ranking criteria, we further investigate the following
points such as
The Higher the ratio the more efficient the fund
would be.
Return will be better if IR > 0.5.
R squared tells how much portfolio is diversified.
□ GRAPHS
Here is some graphical representation of results of the
findings.
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36. i. G-1
RANKING OF MUTUAL FUND
4 1 2 3 4 5
5
0.002561
0.025562
2
0.000286 3
0.019655
1
0.283797
ii. G-2
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37. INFORMATION RATIO OF MUTUAL FUNDS
ASFL, 0.019129
AMMF, -0.14697
FIFM, 0.17535
SFWF, -0.13972
PGF, -0.1344
AMMF SFWF PGF FIFM ASFL
iii. G-3
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43. Our research provides an overview of the Pakistani mutual
fund industry and investigates the mutual funds risk adjusted
performance using information ratio. Mutual fund industry in
Pakistan is still in growing phase. Result shows that on
overall basis, funds industry needs to improve their risk
diversification and take measures to increase returns. Where
as results also show some of the funds under perform, these
funds are facing the diversification problem. If we see as a
whole all the selected funds in our research we come to know
that all are facing diversification problem to some extent.
Worldwide there had been a tremendous growth in this
industry; this growth in mutual funds worldwide is because of
the overall growth in both the size and maturity of many
foreign capital markets, we are far behind. The need of an
hour is to mobilize saving of the individual investors
through the offering of variety of funds (with different
investment objectives).
The funds should also disclose the level of risk associated
with return in their annual reports for the information of
investors and prospective investors. This will enable the
investors to compare the level of return with the level of
risk. The success of this sector depends on the performance
of funds industry and the role of regulatory bodies.
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44. Excellent performance and lenient regulations will increase
the popularity of mutual funds in Pakistan.
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46. We recommend those people who want to continue research on
this topic that they make take more companies to get more
precise results about the mutual fund market as we have taken
only 5 companies out of 12.
We have only use information ratio to measure the mutual
funds portfolio performance and their evaluations. Mutual
funds performance should also be further measured by using
Sharpe ratio, trenyor ratio, and alpha ratio formulas we
should find different or better results and more
diversifications in our findings.
Due to certain limitation of institutions and availability of
data we find limited results, as we have taken only data of
five years, if we have more data results would be more
precise. But as we have seen the data is not easily
accessible, if it is so the results could be more precise and
accurate. Not only data but mutual fund market is also
limited in Pakistan and is still in slow growing phase, it
need more efforts to produce better results, and to make more
people aware of its use and benefits.
We should need numerous companies’ data to know the market
conditions in Pakistan, how companies should actively
diversified the risk and gives appropriate return from the
mutual funds portfolios.
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48. i. Richard C. Grinold and Ronald N. Kahn /information
analysis.
ii. Philippe Cogneau /Researcher, University of Liege, HEC
Management School/The 101 Ways to Measure Portfolio
Performance.
iii. Georges Hübner/Affiliate Professor of Finance, EDHEC
Business School. How Do Performance Measures Perform?
iv. FRANK J. AMBROSIO, CFA/ an evaluation of risk Metrics.
v. Goodwin [1998] /article on performance evaluation of Mutual
Funds.
vi. Patrick Burns/Performance Measurement via Random Portfolios.
vii. David E. Kuenzi Vice President, Investment
Analytics/Strategy Benchmarks— From the Investment
Manager’s Perspective.
viii. Arun S. Muralidhar / Why Maximizing Information Ratios is
Incorrect.
SEARCH ENGINES
a. www.google.com
b. www.scribd.com
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