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Thesis final bilal n saif 222 (2010 2011) Thesis final bilal n saif 222 (2010 2011) Document Transcript

  • Performance and evaluation of portfolioThe information ratio performance measures (PROJECT- THESIS) BBA - 8 Foundation University Institute of Engineering and Management Sciences 1
  • RESEARCH PROPOSAL SUBMITTED BY SAIFULLAH MALIK BILAL AHMAD RAHEEM ANSER SUBMITTED TO Mr. NAVEED ANJUM 2
  • □ 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. 3
  • CHAPTER #1INTRODUCTION 4
  • □ 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). 5
  • Currently, this is the only open ended mutual fund operatingin public sector. The formation of the ICP(Investment Corporation of Pakistan) in 1966 offered a seriesof close-ended mutual funds which was afterwards divided intotwo lots in June 2000 and was then privatized. In the privatesector, there are forty-three open-ended and twenty-twoclosed-ended mutual funds. Although Pakistani mutual fundshave experienced a phenomenal growth during the period understudy (1999-2005) with net asset value grown from Rs. 16 billion to Rs.137 billion till June 30, 2005. However, comparing Pakistanimutual fund industry internationally it is of a tiny size.Pakistan holds only 1.33% mutual fund assets to primarysecurities, in contrast to India with 3.7%, Malaysia 4.0%,Hong Kong 20.3%, and South Korea 16.5%. These facts indicatethat mutual fund industry in Pakistan has significant room togrow. Paid-up capital may look substantial but the size isstill too small as compared to international standard.(Khorana etal (2005).In order top measure the performance of some mutual fund thatwe used in the study we are using information ratio analysis. The information ratio (IR) measures a portfolio managersability to generate excess returns relative to a benchmark 6
  • and also attempts to identify the consistency of theinvestor. This ratio will identify if a manager has beatenthe benchmark and that benchmark is KSE-100 INDEX. The higherthe IR the more consistent a mutual fund is. Information ratio = Rp- Ri/ Sp-iRp = Return of the portfolioRi = Return of the index or benchmarkSp-i = Tracking error (standard deviation of thedifference between returns of the portfolio and the returnsof the index)It explains Information Ratio-IRA high IR can be achieved by having a high return in theportfolio, a low return of the index and a low trackingerror. 7
  • a)SIGNIFICANCE OF THE STUDYThis study is significant because it will produce data on themutual funds performance and their ranking in the market. Itis 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 whocarry 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. 8
  • c) PROBLEM STATEMENTTo analyze the mutual funds performance with respect tobenchmark by using information ratio. d) OBJECTIVESThe focus of the research is to analyze and evaluate thedifference between performances of the mutual funds and torank them accordingly. The projects objectives aresummarized 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. 9
  •   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 followsi. Mutual fund performance ∞ market returnii. Mutual fund performance ∞ diversification 10
  • CHAPTER # 2LITERATURE REVIEW 11
  • □ LITERATURE REVIEW The idea underlying the information ratio (or IR) – alsocalled the appraisal ratio – proposed by Grinold [1989] is toget the performance relative to a given reference portfolio.It measures the excess return of the fund over a givenbenchmark, divided by the standard deviation of the excessreturn – or more concretely, the degree of regularity inoutperforming the benchmark. The excess return over thebenchmark results from the choices made by the manager tooverweight assets that he hopes will exceed that of thebenchmark. A passive management gives a null ratio. Thedenominator, also called “tracking error”, reflects the costof an active management. This ratio has some major drawbacks.First, it requires much data to assess its significance. Thesensitivity to the selected benchmark is also a concern: 12
  • 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 trackingerror, little changes in excess return swing the informationratio from largely positive to largely negative or viceversa. As for the Sharpe ratio, Israelsen [2005] partiallytackles this issue by introducing Israelsen’s modifiedinformation ratio where the tracking error is exponentiated.Finally, this ratio also considers equally positive andnegative variations from the index: an issue solvedconsidering an information ratio based on semi-variance[Gillet and Moussavou, 2000]. Cameron Clement, CFA he interpreting The InformationRatio is a widely used and powerful tool for evaluatingmanager skill, The Information Ratio was established toaddress the shortcomings of the reward-to-variability ratio,modern form of the IR is widely credited to Trey nor andBlack (1973). It measures the manager’s excess return over anappropriate benchmark relative to the standard deviation ofthose excess returns. By computing risk on a relative returnbasis, the IR effectively eliminates market risk, showingonly risk taken from active management, currently a great 13
  • amount of performance analysis is relative to a benchmark.Sometimes this is done because it is deemed reasonable, butother 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 theinformation ratio is the risk-adjusted return of a portfolioor security versus a benchmark. To calculate the informationratio, an asset’s excess return is divided by its trackingerror relative to the benchmark.(The Sharpe ratio is actuallyan information ratio that uses the risk-free return as thebenchmark.) Georges Hübner Affiliate Professor of Finance, EDHECBusiness School. The performance measures for managedportfolios with directional strategies developed in theframework of the capital asset pricing Model proposed by Treynor (1961), Sharpe (1964) and Lintner (1965), three of themdirectly relate to the beta of the portfolio through thesecurity market line (SML). Jensen’s (1968) alpha is definedas the portfolio excess return earned in addition to therequired average return, while the Trey nor (1965) ratio andthe information ratio (IR) are defined as the alpha dividedby the portfolio beta and by the standard deviation of the 14
  • 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 moresophisticated, investment managers are using benchmark indicesin an increasingly complex fashion—as the baseline along whichthe manager intends to add value and manage risk, fordetermining which factor bets have most influenced overallportfolio returns(Attribution analysis), and for determiningthe extent to which the manager added value (through use ofthe information ratio Arun S. Muralidhar. Many papers onactive management argue for maximizing information ratiosusing a risk budgeting framework. Recent innovations in risk-adjusted performance measures show why maximizing informationratios could be the wrong policy and also provide a differenttwist to the discussion on separating alphas from betas. The 15
  • literature on maximizing information ratios focuses only onthe active management process and ignores two actions used byclients or managers to improve risk-adjusted performance:passive management and leverage/deleverage using cash. Itdemonstrates the impact of maximizing the wrong objectivefunction and shows the benefit of maximizing risk-adjustedreturns for the entire fund, rather than the information ratioon the active component.In 1989, Richard Grinold introduced the fundamental law ofactive management that detailed how to measure the efficiencyof a manager, as measured by the information ratio.1 Roger Clarke, Harindra de Silva, and Steven Thorleyrevisited this research and published Portfolio Constraintsand the Fundamental Law of Active Management. They determinedGrinold’s work did not factor in portfolio. Constraints andtheir impact on the information ratio. To address this issue,Clarke, de Silva, and Thorley’s research included a measure ofa manager’s ability to forecast future securities’ returns andthe ability then to implement investment ideas.Richard C. Grinold and Ronald N. Kahn, Information is thevital input into any active management strategy. Informationseparates active management from passive management.Information, properly applied, allows active managers tooutperform their information less benchmarks. Analyses go 16
  • beyond this to investigate statistical significance, value-added, and skill. These more sophisticated analyses rely onthree important statistics describing. Investment performance:t-statistics, information ratios, and informationcoefficients.The information ratio in particular, however, most directlycaptures the investment value added offered by theinformation, and so is the most important statistic forinvestment information analysis.Gordon Bodnar and Charles Smithson, Discusses the evolution ofrisk allocation, contrasting it with asset allocation andexamining its advantages in the modern market and portfoliostructuring. 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. 17
  • With the rise in benchmarking, the task of an activeportfolio manager was to “beat the index”. Clearly, one wayto beat the index was to take on more risk than in the index– a tactic not necessarily in line with the wishes of theinvestor. CHAPTER # 3 METHODOLOGY 18
  • □ METHODOLOGIESa) 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. 19
  • 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 SFWFc) MODEL 20
  • We used information ratio for the analysis ofmutual funds and we rank them accordingly by using thefollowing formula:Rp = Return of the portfolioRi = Return of the index or benchmarkSp-i = Tracking error (standard deviation of thedifference between returns of the portfolio and the returnsof the index). 21
  • CHAPTER #4 DATA ANALYSIS & MEASURES □ DATA ANALYSIS & MEASURESa) DATA ANALYSIS We find an information ratio by implementing the data of benchmark/mutual fundsb) MEASURE 22
  • 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 ratioi. 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 23
  • 30-Nov-05 52 8346.11 -0.05882 0.009376 -0.068229-Dec-05 49.75 9078.2 -0.04327 0.087716 -0.1309931-Jan-06 51.95 9570.05 0.044221 0.054179 -0.0099628-Feb-06 45.25 10542.92 -0.12897 0.101658 -0.2306331-Mar-06 41.5 11525.33 -0.08287 0.093182 -0.1760528-Apr-06 40.4 11535.98 -0.02651 0.000924 -0.0274331-May-06 34.4 11339.63 -0.14851 -0.01702 -0.1314930-Jun-06 31.8 9895.4 -0.07558 -0.12736 0.0517831-Jul-06 34.6 9959.24 0.08805 0.006451 0.08159931-Aug-06 31.15 10489.48 -0.09971 0.053241 -0.1529529-Sep-06 31.8 10035.58 0.020867 -0.04327 0.06413931-Oct-06 31.75 10532.29 -0.00157 0.049495 -0.0510730-Nov-06 29.15 11243.3 -0.08189 0.067508 -0.149429-Dec-06 28 10587.9 -0.03945 -0.05829 0.01884131-Jan-07 33 10057.68 0.178571 -0.05008 0.22864928-Feb-07 33.35 11301.53 0.010606 0.123672 -0.1130730-Mar-07 31.4 11196.28 -0.05847 -0.00931 -0.0491630-Apr-07 33.35 11282.28 0.062102 0.007681 0.05442131-May-07 33.6 12419.17 0.007496 0.100768 -0.0932729-Jun-07 34.3 13016.76 0.020833 0.048118 -0.0272931-Jul-07 34.9 13829.97 0.017493 0.062474 -0.0449831-Aug-07 27.4 13753.38 -0.2149 -0.00554 -0.2093628-Sep-07 29.1 12124.69 0.062044 -0.11842 0.18046531-Oct-07 29.2 13560.37 0.003436 0.11841 -0.1149730-Nov-07 28.05 14330.9 -0.03938 0.056822 -0.0962131-Dec-07 30 13999.3 0.069519 -0.02314 0.09265831-Jan-08 28.1 13633.04 -0.06333 -0.02616 -0.0371729-Feb-08 30.6 14016.05 0.088968 0.028094 0.06087431-Mar-08 28.85 14964.56 -0.05719 0.067673 -0.1248630-Apr-08 28.33 15114.25 -0.01802 0.010003 -0.0280330-May-08 23 15186.82 -0.18814 0.004801 -0.1929430-Jun-08 23.77 12088.59 0.033478 -0.20401 0.23748631-Jul-08 18.21 12212.81 -0.23391 0.010276 -0.2441829-Aug-08 14.97 10498.14 -0.17792 -0.1404 -0.0375224-Sep-08 14.97 9207.87 0 -0.1229 0.122905 6-Oct-08 14.97 9179.68 0 -0.00306 0.003062 4-Nov-08 14.97 9182.88 0 0.000349 -0.0003531-Dec-08 5.36 9187.1 -0.64195 0.00046 -0.6424130-Jan-09 7.25 5753.16 0.352612 -0.37378 0.7263927-Feb-09 7.19 5373.38 -0.00828 -0.06601 0.05773731-Mar-09 8.8 5730.21 0.223922 0.066407 0.15751530-Apr-09 9.51 6907.74 0.080682 0.205495 -0.1248129-May-09 9.19 7222.85 -0.03365 0.045617 -0.0792730-Jun-09 8.45 7289.14 -0.08052 0.009178 -0.089731-Jul-09 10.71 7174.47 0.267456 -0.01573 0.28318731-Aug-09 11.17 7748.95 0.042951 0.080073 -0.0371230-Sep-09 14.42 8737.98 0.290958 0.127634 0.16332430-Oct-09 16.41 9380.49 0.138003 0.073531 0.06447226-Nov-09 14 9182.4 -0.14686 -0.02112 -0.1257431-Dec-09 14.38 9136.6 0.027143 -0.00499 0.032131 24
  • AVERAGE RETURN -0.00812 0.011266 STANDARD DEVIATION 0.187448 INFORMATION RATIO -0.10344 ANNULIZED INFORMATION RATIO -0.35831ii. ASIAN STOCK FUND LIMITED ( ASFL ) DATE ASFL KSE R ASFL R KSE ER 31-Jan-05 10.5 6232.5 25-Feb-05 10.5 6764.31 0 0.085329 -0.08533 29-Mar-05 8.6 8303.32 -0.18095 0.227519 -0.40847 28-Apr-05 8.25 7606.67 -0.0407 -0.0839 0.043203 30-May-05 8.15 7128.54 -0.01212 -0.06286 0.050735 30-Jun-05 10.65 6895.75 0.306748 -0.03266 0.339405 26-Jul-05 10.25 7489.29 -0.03756 0.086073 -0.12363 31-Aug-05 10 7217.97 -0.02439 -0.03623 0.011837 29-Sep-05 11 7802.83 0.1 0.081028 0.018972 19-Oct-05 10.8 8268.58 -0.01818 0.05969 -0.07787 30-Nov-05 9.7 8346.11 -0.10185 0.009376 -0.11123 29-Dec-05 9.95 9078.2 0.025773 0.087716 -0.06194 31-Jan-06 10 9570.05 0.005025 0.054179 -0.04915 24-Feb-06 7.5 10542.92 -0.25 0.101658 -0.35166 8-Mar-06 8 11525.33 0.066667 0.093182 -0.02652 26-Apr-06 9 11535.98 0.125 0.000924 0.124076 22-May-06 8.95 11339.63 -0.00556 -0.01702 0.011465 25
  • 17-Jun-06 8.95 9895.4 0 -0.12736 0.127361 13-Jul-06 8.95 9959.24 0 0.006451 -0.00645 8-Aug-06 8 10489.48 -0.10615 0.053241 -0.15939 21-Sep-06 7 10035.58 -0.125 -0.04327 -0.08173 9-Oct-06 6 10532.29 -0.14286 0.049495 -0.19235 30-Nov-06 5.8 11243.3 -0.03333 0.067508 -0.10084 29-Dec-06 5.5 10587.9 -0.05172 -0.05829 0.006568 22-Jan-07 4.95 10057.68 -0.1 -0.05008 -0.04992 20-Feb-07 5.9 11301.53 0.191919 0.123672 0.068248 29-Mar-07 6 11196.28 0.016949 -0.00931 0.026262 3-May-07 6 11282.28 0 0.007681 -0.00768 31-May-07 5.05 12419.17 -0.15833 0.100768 -0.2591 28-Jun-07 4.65 13016.76 -0.07921 0.048118 -0.12733 26-Jul-07 4.8 13829.97 0.032258 0.062474 -0.03022 30-Aug-07 3.1 13753.38 -0.35417 -0.00554 -0.34863 28-Sep-07 4 12124.69 0.290323 -0.11842 0.408744 25-Oct-07 5.35 13560.37 0.3375 0.11841 0.21909 29-Nov-07 5.4 14330.9 0.009346 0.056822 -0.04748 24-Dec-07 7.2 13999.3 0.333333 -0.02314 0.356472 30-Jan-08 6.5 13633.04 -0.09722 -0.02616 -0.07106 28-Feb-08 5.8 14016.05 -0.10769 0.028094 -0.13579 20-Mar-08 5.75 14964.56 -0.00862 0.067673 -0.07629 21-Apr-08 5.5 15114.25 -0.04348 0.010003 -0.05348 19-May-08 5.2 15186.82 -0.05455 0.004801 -0.05935 27-Jun-08 5.7 12088.59 0.096154 -0.20401 0.300162 4-Jul-08 5.7 12212.81 0 0.010276 -0.01028 8-Aug-08 5.7 10498.14 0 -0.1404 0.140399 13-Sep-08 5.7 9207.87 0 -0.1229 0.122905 21-Oct-08 6.17 9179.68 0.082456 -0.00306 0.085518 24-Nov-08 6.17 9182.88 0 0.000349 -0.00035 28-Dec-08 2.5 9187.1 -0.59481 0.00046 -0.59527 31-Jan-09 2.5 5753.16 0 -0.37378 0.373778 1-Feb-09 2.5 5373.38 0 -0.06601 0.066012 31-Mar-09 2.5 5730.21 0 0.066407 -0.06641 1-Apr-09 4.87 6907.74 0.948 0.205495 0.742505 6-May-09 4.87 7222.85 0 0.045617 -0.04562 29-Jun-09 4.87 7289.14 0 0.009178 -0.00918 27-Jul-09 1.92 7174.47 -0.60575 -0.01573 -0.59002 31-Aug-09 2.43 7748.95 0.265625 0.080073 0.185552 30-Sep-09 5.19 8737.98 1.135802 0.127634 1.008168 29-Oct-09 2.62 9380.49 -0.49518 0.073531 -0.56871 16-Nov-09 1.83 9182.4 -0.30153 -0.02112 -0.28041 31-Dec-09 3.2 9136.6 0.748634 -0.00499 0.753622AVERAGE RETURN 0.016722 0.011266STANDARD DEVIATION 0.28525INFORMATION RATIO 0.019129 26
  • ANNULIZED INFORMATION RATIO 0.066265iii. AL MEEZAN MUTUAL FUND ( AMMF ) DATE PRICE KSE_PRICE R_AMMF R_KSE ER 1/7/2005 12.95 6232.5 2/8/2005 13 6764.31 0.003861 0.085329 -0.08147 3/1/2005 14.6 8303.32 0.123077 0.227519 -0.10444 4/11/2005 10.5 7606.67 -0.28082 -0.0839 -0.19692 5/2/2005 10.05 7128.54 -0.04286 -0.06286 0.02 6/10/2005 10.7 6895.75 0.064677 -0.03266 0.097333 7/4/2005 10.35 7489.29 -0.03271 0.086073 -0.11878 8/1/2005 10.5 7217.97 0.014493 -0.03623 0.05072 9/8/2005 10.05 7802.83 -0.04286 0.081028 -0.12389 10/7/2005 10.9 8268.58 0.084577 0.05969 0.024887 11/8/2005 11.65 8346.11 0.068807 0.009376 0.059431 12/1/2005 12.45 9078.2 0.06867 0.087716 -0.01905 1/9/2006 13.9 9570.05 0.116466 0.054179 0.062287 2/1/2006 15 10542.92 0.079137 0.101658 -0.02252 3/9/2006 14.3 11525.33 -0.04667 0.093182 -0.13985 4/19/2006 15.65 11535.98 0.094406 0.000924 0.093482 5/8/2006 15.65 11339.63 0 -0.01702 0.017021 6/7/2006 15 9895.4 -0.04153 -0.12736 0.085828 7/3/2006 14.9 9959.24 -0.00667 0.006451 -0.01312 8/4/2006 14.85 10489.48 -0.00336 0.053241 -0.0566 9/5/2006 15.15 10035.58 0.020202 -0.04327 0.063474 10/2/2006 12.1 10532.29 -0.20132 0.049495 -0.25082 27
  • 11/6/2006 12.35 11243.3 0.020661 0.067508 -0.04685 12/5/2006 12.3 10587.9 -0.00405 -0.05829 0.054244 1/3/2007 12.85 10057.68 0.044715 -0.05008 0.094793 2/9/2007 12.35 11301.53 -0.03891 0.123672 -0.16258 3/6/2007 11.6 11196.28 -0.06073 -0.00931 -0.05142 4/4/2007 12.8 11282.28 0.103448 0.007681 0.095767 5/10/2007 13 12419.17 0.015625 0.100768 -0.08514 6/1/2007 14.75 13016.76 0.134615 0.048118 0.086497 7/10/2007 14.95 13829.97 0.013559 0.062474 -0.04891 8/1/2007 15.4 13753.38 0.0301 -0.00554 0.035638 9/6/2007 11.15 12124.69 -0.27597 -0.11842 -0.15755 10/5/2007 12.7 13560.37 0.139013 0.11841 0.020604 11/12/2007 12.85 14330.9 0.011811 0.056822 -0.04501 12/3/2007 12.95 13999.3 0.007782 -0.02314 0.030921 1/4/2008 12.95 13633.04 0 -0.02616 0.026163 2/11/2008 12.6 14016.05 -0.02703 0.028094 -0.05512 3/7/2008 12.85 14964.56 0.019841 0.067673 -0.04783 4/11/2008 12.8 15114.25 -0.00389 0.010003 -0.01389 5/2/2008 13.05 15186.82 0.019531 0.004801 0.01473 6/4/2008 12.05 12088.59 -0.07663 -0.20401 0.127379 7/4/2008 13.7 12212.81 0.136929 0.010276 0.126654 8/7/2008 8 10498.14 -0.41606 -0.1404 -0.27566 9/5/2008 8.15 9207.87 0.01875 -0.1229 0.141655 10/8/2008 8 9179.68 -0.0184 -0.00306 -0.01534 16-Nov-08 7 9182.88 -0.125 0.000349 -0.12535 12/17/2008 6 9187.1 -0.14286 0.00046 -0.14332 1/6/2009 5.09 5753.16 -0.15167 -0.37378 0.222112 2/18/2009 4.19 5373.38 -0.17682 -0.06601 -0.1108 3/17/2009 3.9 5730.21 -0.06921 0.066407 -0.13562 4/3/2009 5.29 6907.74 0.35641 0.205495 0.150915 5/4/2009 4.9 7222.85 -0.07372 0.045617 -0.11934 6/8/2009 4.85 7289.14 -0.0102 0.009178 -0.01938 7/1/2009 5.2 7174.47 0.072165 -0.01573 0.087897 8/11/2009 5.3 7748.95 0.019231 0.080073 -0.06084 9/3/2009 6.24 8737.98 0.177358 0.127634 0.049724 10/7/2009 6.24 9380.49 0 0.073531 -0.07353 11/13/2009 7.15 9182.4 0.145833 -0.02112 0.166951 12/4/2009 6.4 9136.6 -0.1049 -0.00499 -0.09991AVERAGE RETURN -0.00422 0.011266STANDARD DEVIATION 0.105375INFORMATION RATIO -0.14697ANNULIZED INFORMATION RATIO -0.50913 28
  • iv. INTERFUND MOD ( FIFM ) FIFM KSE R_FIFM R_KSE ER 31-Jan-05 1.1 6232.5 28-Feb-05 1.1 6764.31 0 0.085329 -0.08533 28-Mar-05 1.2 8303.32 0.090909 0.227519 -0.13661 27-Apr-05 1 7606.67 -0.16667 -0.0839 -0.08277 31-May-05 1.2 7128.54 0.2 -0.06286 0.262857 23-Jun-05 0.55 6895.75 -0.54167 -0.03266 -0.50901 15-Jul-05 0.75 7489.29 0.363636 0.086073 0.277563 30-Aug-05 0.55 7217.97 -0.26667 -0.03623 -0.23044 19-Sep-05 1 7802.83 0.818182 0.081028 0.737153 12-Oct-05 0.7 8268.58 -0.3 0.05969 -0.35969 16-Nov-05 0.5 8346.11 -0.28571 0.009376 -0.29509 29-Dec-05 1 9078.2 1 0.087716 0.912284 4-Jan-06 0.7 9570.05 -0.3 0.054179 -0.35418 10-Feb-06 0.9 10542.92 0.285714 0.101658 0.184057 25-Mar-06 0.5 11525.33 -0.44444 0.093182 -0.53763 4-Apr-06 0.5 11535.98 0 0.000924 -0.00092 7-May-06 0.55 11339.63 0.1 -0.01702 0.117021 19-Jun-06 0.95 9895.4 0.727273 -0.12736 0.854634 7-Jul-06 0.7 9959.24 -0.26316 0.006451 -0.26961 1-Aug-06 0.8 10489.48 0.142857 0.053241 0.089616 13-Sep-06 0.5 10035.58 -0.375 -0.04327 -0.33173 26-Oct-06 0.5 10532.29 0 0.049495 -0.04949 12-Nov-06 0.6 11243.3 0.2 0.067508 0.132492 5-Dec-06 0.25 10587.9 -0.58333 -0.05829 -0.52504 4-Jan-07 0.7 10057.68 1.8 -0.05008 1.850078 7-Feb-07 0.35 11301.53 -0.5 0.123672 -0.62367 13-Mar-07 0.9 11196.28 1.571429 -0.00931 1.580741 16-Apr-07 0.9 11282.28 0 0.007681 -0.00768 21-May-07 0.55 12419.17 -0.38889 0.100768 -0.48966 29
  • 24-Jun-07 0.95 13016.76 0.727273 0.048118 0.67915423-Jul-07 0.5 13829.97 -0.47368 0.062474 -0.5361629-Aug-07 1.65 13753.38 2.3 -0.00554 2.3055389/21/2007 0.8 12124.69 -0.51515 -0.11842 -0.39673 5-Oct-07 0.2 13560.37 -0.75 0.11841 -0.8684130-Nov-07 0.3 14330.9 0.5 0.056822 0.44317817-Dec-07 0.9 13999.3 2 -0.02314 2.02313930-Jan-08 0.85 13633.04 -0.05556 -0.02616 -0.0293914-Feb-08 0.85 14016.05 0 0.028094 -0.02809 4-Mar-08 0.8 14964.56 -0.05882 0.067673 -0.126521-Apr-08 0.75 15114.25 -0.0625 0.010003 -0.072529-May-08 0.3 15186.82 -0.6 0.004801 -0.604812-Jun-08 0.2 12088.59 -0.33333 -0.20401 -0.1293317-Jul-08 0.4 12212.81 1 0.010276 0.98972421-Aug-08 0.45 10498.14 0.125 -0.1404 0.26539925-Sep-08 0.9 9207.87 1 -0.1229 1.12290530-Oct-08 0.9 9179.68 0 -0.00306 0.00306213-Nov-08 0.06 9182.88 -0.93333 0.000349 -0.93368 4-Dec-08 0.06 9187.1 0 0.00046 -0.00046 4-Jan-09 0.05 5753.16 -0.16667 -0.37378 0.207112 5-Feb-09 0.05 5373.38 0 -0.06601 0.06601225-Mar-09 0.06 5730.21 0.2 0.066407 0.133593 9-Apr-09 0.06 6907.74 0 0.205495 -0.2055 9-May-09 0.06 7222.85 0 0.045617 -0.04562 8-Jun-09 0.06 7289.14 0 0.009178 -0.00918 4-Jul-09 0.06 7174.47 0 -0.01573 0.01573225-Aug-09 0.06 7748.95 0 0.080073 -0.0800720-Sep-09 0.06 8737.98 0 0.127634 -0.1276316-Oct-09 0.06 9380.49 0 0.073531 -0.0735311-Nov-09 0.06 9182.4 0 -0.02112 0.021117 7-Dec-09 0.1 9136.6 0.666667 -0.00499 0.671654 AVERAGE RETURN 0.126345 0.011266 STANDARD DEVIATION 0.656189 INFORMATION RATIO 0.175375 ANNULIZED INFORMATION RATIO 0.607519 30
  • v. SAFEWAY MUTUAL FUND ( SFWF ) SFWF KSE_PRICE R_SFWF R_KSE ER 27-Jan-05 23.2 6232.5 24-Feb-05 23 6764.31 -0.00862 0.085329 -0.09395 28-Mar-05 19.9 8303.32 -0.13478 0.227519 -0.3623 28-Apr-05 19.8 7606.67 -0.00503 -0.0839 0.078875 26-May-05 20.8 7128.54 0.050505 -0.06286 0.113362 30-Jun-05 24.85 6895.75 0.194712 -0.03266 0.227368 21-Jul-05 19 7489.29 -0.23541 0.086073 -0.32149 30-Aug-05 19 7217.97 0 -0.03623 0.036228 27-Sep-05 19.5 7802.83 0.026316 0.081028 -0.05471 21-Oct-05 19.5 8268.58 0 0.05969 -0.05969 30-Nov-05 15.65 8346.11 -0.19744 0.009376 -0.20681 29-Dec-05 16 9078.2 0.022364 0.087716 -0.06535 26-Jan-06 15 9570.05 -0.0625 0.054179 -0.11668 24-Feb-06 15.7 10542.92 0.046667 0.101658 -0.05499 30-Mar-06 14.9 11525.33 -0.05096 0.093182 -0.14414 27-Apr-06 14 11535.98 -0.0604 0.000924 -0.06133 30-May-06 13.1 11339.63 -0.06429 -0.01702 -0.04727 5-Jun-08 13 9895.4 -0.00763 -0.12736 0.119728 26-Jul-06 12.5 9959.24 -0.03846 0.006451 -0.04491 7-Aug-06 11.95 10489.48 -0.044 0.053241 -0.09724 15-Sep-06 11.95 10035.58 0 -0.04327 0.043272 31-Oct-06 12 10532.29 0.004184 0.049495 -0.04531 17-Nov-06 9.1 11243.3 -0.24167 0.067508 -0.30917 29-Dec-06 6.8 10587.9 -0.25275 -0.05829 -0.19445 31-Jan-07 6.35 10057.68 -0.06618 -0.05008 -0.0161 21-Feb-07 6.55 11301.53 0.031496 0.123672 -0.09218 29-Mar-07 7.5 11196.28 0.145038 -0.00931 0.154351 25-Apr-07 7.75 11282.28 0.033333 0.007681 0.025652 28-May-07 8.05 12419.17 0.03871 0.100768 -0.06206 28-Jun-07 11.15 13016.76 0.385093 0.048118 0.336975 31-Jul-07 13 13829.97 0.165919 0.062474 0.103445 29-Aug-07 10 13753.38 -0.23077 -0.00554 -0.22523 28-Sep-07 10.5 12124.69 0.05 -0.11842 0.168421 11-Oct-07 10.9 13560.37 0.038095 0.11841 -0.08031 27-Nov-07 9.7 14330.9 -0.11009 0.056822 -0.16691 31-Dec-07 11.5 13999.3 0.185567 -0.02314 0.208706 31
  • 24-Jan-08 11.5 13633.04 0 -0.02616 0.02616327-Feb-08 11.7 14016.05 0.017391 0.028094 -0.010710-Mar-08 12.4 14964.56 0.059829 0.067673 -0.0078424-Apr-08 12.9 15114.25 0.040323 0.010003 0.0303226-May-08 12 15186.82 -0.06977 0.004801 -0.0745727-Jun-08 11.9 12088.59 -0.00833 -0.20401 0.19567429-Jul-08 12.2 12212.81 0.02521 0.010276 0.01493430-Aug-08 12.5 10498.14 0.02459 -0.1404 0.16498910-Sep-08 13 9207.87 0.04 -0.1229 0.16290515-Oct-08 13 9179.68 0 -0.00306 0.00306230-Nov-08 12.6 9182.88 -0.03077 0.000349 -0.0311212-Dec-08 12 9187.1 -0.04762 0.00046 -0.0480815-Jan-09 11.5 5753.16 -0.04167 -0.37378 0.332112 6-Feb-09 11 5373.38 -0.04348 -0.06601 0.022534 2-Mar-09 10.5 5730.21 -0.04545 0.066407 -0.1118617-Apr-09 9.6 6907.74 -0.08571 0.205495 -0.2912128-May-09 8.75 7222.85 -0.08854 0.045617 -0.1341629-Jun-09 9.75 7289.14 0.114286 0.009178 0.10510829-Jul-09 8.9 7174.47 -0.08718 -0.01573 -0.0714531-Aug-09 5.5 7748.95 -0.38202 0.080073 -0.462130-Sep-09 8.28 8737.98 0.505455 0.127634 0.3778229-Oct-09 6.31 9380.49 -0.23792 0.073531 -0.3114526-Nov-09 5.04 9182.4 -0.20127 -0.02112 -0.1801531-Dec-09 6.02 9136.6 0.194444 -0.00499 0.199432 AVERAGE RETURN -0.01256 0.011266 STANDARD DEVIATION 0.172764 INFORMATION RATIO -0.13792 ANNUALIZED INFORMATION RATIO -0.47777 32
  • □ 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 % 33
  • 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 34
  • 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. 35
  • 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 0.283797ii. G-2 36
  • INFORMATION RATIO OF MUTUAL FUNDS ASFL, 0.019129 AMMF, -0.14697 FIFM, 0.17535 SFWF, -0.13972 PGF, -0.1344 AMMF SFWF PGF FIFM ASFLiii. G-3 37
  • ANNULIZED INFORMATION RATIO 5 1 0.066265 1 4 -0.509131437 0.607519 2 3 4 2 5 3 -0.47777 -0.35831iv. G-4 38
  • R SQUARED 0.3 0.283797 0.25 0.2 0.15 0.1 0.05 0.019655 0.025562 0.000286 0.002561 0 1 2 3 4 5 R Squared 0.283797 0.000286 0.019655 0.002561 0.025562 1 2 3 4 5v. G-5 39
  • RANKING BASED ON R SQUARED VALUES 6 5 1.96% 2.25% 4 28.30% 3 RANKING 2 1 0 0.03% 0.25% _ -1 0 1 2 3 4 5 6 7 R SQUARED Rankingvi. G-6 40
  • RANKING BASED ON R SQUARED VALUES 5 4 3 2 1 0 28.30% 0.03% 1.96% 0.25% 2.25% _Ranking 4 0 5 0 5 0 41
  • Chapter # 5 CONCLUSION□ CONCLUSION 42
  • Our research provides an overview of the Pakistani mutualfund industry and investigates the mutual funds risk adjustedperformance using information ratio. Mutual fund industry inPakistan is still in growing phase. Result shows that onoverall basis, funds industry needs to improve their riskdiversification and take measures to increase returns. Whereas results also show some of the funds under perform, thesefunds are facing the diversification problem. If we see as awhole all the selected funds in our research we come to knowthat all are facing diversification problem to some extent.Worldwide there had been a tremendous growth in thisindustry; this growth in mutual funds worldwide is because ofthe overall growth in both the size and maturity of manyforeign capital markets, we are far behind. The need of anhour is to mobilize saving of the individual investorsthrough the offering of variety of funds (with differentinvestment objectives).The funds should also disclose the level of risk associatedwith return in their annual reports for the information ofinvestors and prospective investors. This will enable theinvestors to compare the level of return with the level ofrisk. The success of this sector depends on the performanceof funds industry and the role of regulatory bodies. 43
  • Excellent performance and lenient regulations will increasethe popularity of mutual funds in Pakistan. 44
  • CHAPTER # 6 RECOMMENDATIONS□ RECOMMENDATIONS 45
  • We recommend those people who want to continue research onthis topic that they make take more companies to get moreprecise results about the mutual fund market as we have takenonly 5 companies out of 12.We have only use information ratio to measure the mutualfunds portfolio performance and their evaluations. Mutualfunds performance should also be further measured by usingSharpe ratio, trenyor ratio, and alpha ratio formulas weshould find different or better results and morediversifications in our findings.Due to certain limitation of institutions and availability ofdata we find limited results, as we have taken only data offive years, if we have more data results would be moreprecise. But as we have seen the data is not easilyaccessible, if it is so the results could be more precise andaccurate. Not only data but mutual fund market is alsolimited in Pakistan and is still in slow growing phase, itneed more efforts to produce better results, and to make morepeople aware of its use and benefits.We should need numerous companies’ data to know the marketconditions in Pakistan, how companies should activelydiversified the risk and gives appropriate return from themutual funds portfolios. 46
  • ⇒ REFERENCES 47
  • 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 48