Impact of Mutual Fund Charact

Impact of mutual funds characteristics on mutual funds return 1

Abstract

This research has explored the dynamic relationship between mutual fund characteristics,

managerial attribute and its return. Variables are including Fund Size, Net Asset Value, Price to

Earning, price to Book Value, Turnover and impact variable is Return. The data for this study is

gathered through secondary sources since the fund has been launched except some funds.

Multiple Regression analysis is used to determine the impact mutual fund characteristics on its

return. The empirical results show that the managerial attribute, mutual fund characteristics and

its return have a significant relationship as well as the managerial attribute (Turnover) are the

key determinant of the mutual fund return movements.


Chapter # 1


I - Introduction

Different management companies are actually managing mutual fund money. The management

companies are having nominal resources so it is given advised to be as competent eligible

department. Portfolio Handler is the one who managed the portfolio of shared fund through his/

her capable skills which could easily satisfied the interest of the investors. In order to select

appropriate securities of finance for investors they first investigate about uncertainties, economic

conditions, market and business trends, political situation and regulations in order to forecast the

positive return on stocks, and income generated for these companies and investors too. In fact,

the system and procedure of management companies isn’t remained unchangeable so these

managers are responsible to organize the fund portfolio again in a way that could help them to

maximize the return as per situation required.

1.1 - Concept of Mutual Funds:

The concept of mutual fund is to spend the investor’s money into pool of public money by

money manager and partnering over promotion selection of money manager or portfolio trainer.

This application brings several benefits for the inconsistent investors who don’t rely easily on

saying of portfolio managers because these type of investors are not normally looking for

immediate buying of funds. This entire concept is related to mutual fund.

On daily basis, the portfolio manager look in to the money holding of investors, counts

the accumulated fund, and observe that how the shares bought by the shareholders, and in the

end the fund manager calculate the net asset value of the mutual fund but at the same day, the

payment is distributed among investor by money manager. If you’re required to buy new shares

then you have to give right to your fund administrator to further buy it at most recent cost. It is


fact that the net asset value (NAV) of your shares or fund would be bigger or increased if your

fund administrator is managing your fund appropriately. So the right choice of selection of

portfolio manager to manage the funds is really important.

1.2 – Types of Mutual Funds:

There are two types of mutual fund exist which are named as:

Open end mutual fund

Closed end mutual fund

1.2.1 – Open-Ended Mutual Funds:

Open end mutual funds are those funds which is subscribed and delivery of shares done on

continuous basis. The net asset value is find out for the rescue of shares open end assets and

subscribed at the mention terms by money manager after adjusting sales or repurchase fee

responsibility. Whereas there is thirteen undecided end shares finances exist in Pakistan named

as; Human venture (Investment) unit, Swear (National Investment trust; NIT) in people

perspective & Titan earnings Money, Histrion agamid fund, Faysal counterpoised ontogenesis.

Money, Dwawood money industry fund, Pakistan income fund, Pakistan inventory industry

Money, Metro Bank-Pakistan dominant fund, Meezan islamic fund, Organization Belief of

Pakistan, UTP income money, UTP Islamic fund and Fused money market in classified facet.

1.2.2 – Close- End Mutual Funds:

Close end funds are those funds in which the shares are issued openly in public in the beginning

and then buy and sell of shares traded as in additional activity. Whereas trading is commonly

done in case of weak decrease to net asset value (NAV). At the end of minute, the fund managers


assorted the needs of investors and mature the variety of investment products related to its shared

funds. This countenance includes:

growth funds

balanced funds

income funds

1.2.3 – Growth Funds:

In case of "development funds" it provide sufficient blessing during the dealing of shared funds,

but in such case, the current revenue (income) would be low. Whereas the inconsistency in asset

or funds value would be piercing. Specified finances equip is used in reserves stock & someone

authorized to perform better in new funds & another funds should be treated through different

phase of experience.

1.2.4 - Balanced Funds

In case of "ontogenesis and income funds" or "counterbalanced funds", message forecasts for

equally fairish approvals as in percentage quantity and substantially in case of circulating

income. In this situation, the inconsistency in assets or fund will be low. These funds are

commonly spent in stocks reserve, in case of corporate debts & governance packing.

1.2.5 - Income Funds

The "connectedness money" or "income finances", pay superior ongoing income but real little

potentiality for growth. Specified assets outfit in polity paper, issued bonds through municipal,

anesthetic organization, organized loan (debts) & stocks in case of usefulness business, content

prescribed convey.


1.3 – Sources of Profit Generation:

The profits can be generated through shared money from many ternary sources which are named as:

Bonus (Dividend)

Top (Increase) Gains

Perceptiveness of Acquire cost (price)

1.3.1 - Dividend:

The income generated through application of shared money from conventional dividends and

also from those whose funds are hold by shared support companies. These generated incomes

from mutual funds are further divided in to its own funds holders.

1.3.2 – Top Gains:

It is clearly evident that the portfolio of fund changes by the fund manager according to changes

made in business and economic condition. In fact, the investors of funds are given dividend

through purchase and sells transaction of shares in terms of generating capital gain in the

application of mutual funds.

1.3.3 - Perceptiveness of Acquire Price:

Mutual fund help to increase the investment of investor through appreciating the share price of

related fund. By considering an example i.e. let say the subscription price of fund is Rs.11 and

after passing the time of eight months, what if the subscription price of related fund goes up to

Rs.20, so the extra Rs.9 would show the profit earned by the fund manager for investor through

selling its mutual fund in the market.


1.4 - History of Mutual Funds in Pakistan:

The concept of mutual fund were initiated in history of Pakistan in 1962 through public offering

of NIT (National Investment Trust) that is considered as open end mutual fund in public sector.

Similarly, it was focused and followed the same approach by the ICP (Investment Corporation

Pakistan) in 1966 through initiating the series of offers of closed end mutual fund in the history.

There is only one open end fund exist presently i.e. NIT mutual fund in the public sector.

Whereas there are twelve open end mutual fund and fourteen closed end mutual fund exist in

Pakistan under the management of private sector. In addition to, there are many mutual funds

related to closed an open end fund are lying in the channel.

1.5 - Rules Control Shared Finances in Pakistan:

Mutual funds are governed by two basic rules in the context of Pakistan which are named as;

Asset direction companies rules, 1995 (command open end mutual fund)

Investment companies and Asset advisor rules, 1971 (i.e. control closed end mutual fund)

1.6 - Mutual Funds in Pakistan:

There are two types of mutual fund operating in Pakistan i.e. open ended mutual fund and

closed ended mutual fund under the management of public and private sector. There is only one

open ended mutual fund operating in public sector i.e. NIT mutual fund whereas there are twelve

open ended mutual fund operating in private sector of Pakistan. Similarly, there are eighteen

closed ended mutual fund operating in Pakistan under the public and private sector management

which is clearly shown through figure (1-1) of mutual fund in Pakistan mentioned in appendix B.

From theses fact, I move forward to the record of mutual funds in Pakistan, and rules governed


for mutual asset in Pakistan. In portion of methodology, I have explained the reviewed literature,

sample size selection of mutual assets (funds), collection and analyzing of data, selection of

statistical technique for application of mutual fund and lastly checked validity and reliability of

the data.

In chapter of context of reference I have explained the theoretical background related to

testable assumption (hypothesis) of efficient market and fund portfolio management, attributes of

funds that affect the financial performances of mutual funds. Afterwards, I went for application

of mutual fund through illustration of empirical results by using multivariate regression analysis

and that’s how it helps me to do final conclusion to support of my study and further it provides

guidance in case of future research of studies.

1.7 - Background

In March 2000, the stock market was dramatically busted almost in every country due to incident

of terrorist activity; held on USA on Sept. 11, 2001 by falling down of twin towers and even

faced because of IT bubble in the economy. This may not only causes the result of decline in

stock market return but also it hampered the raising growth occurred in stock market. In past few

years and even at present situation, it also revealed the severe downturns have been seen faced in

stock market after the occurrence of 9/11 incident on USA. That’s how the consequences of

inflation have been floated in specially developing and transitional economy across the many

countries and different regions.

In fact there is no doubt that equity stocks purely invested in stocks return but also this

decision comes under the supervision and authorization of portfolio of fund manager. As

authorized by the portfolio management, the fund manager is deemed to responsible for holding


fixed income and other type of securities in the application of mutual fund. In order to meet the

required liquidity situation and potential redemption of shares, the funds is usually hold around 4

to 5 % of total assets in case of money market securities.

Accordingly Elton and Gruber, (1995); the mutual funds brought lots of diversification in

investment through funds collection from many investors in order to further invest it in different

securities across the countries of world. There are two types of investment strategies followed by

fund manager in application of mutual fund i.e. firstly active strategies which is all about

investment in variety financial products, and secondly; passive strategies which is all about do

investment in a market index. According to Jack Treynor1 et al (Bodie Investments 2002) who

briefly described that idea of diversification is remained quite older after occurrence of modern

finance theory so they wanted to emphasize on the quote that “do not pull all your legs in one

basket” because it won’t fruitful to implement diversification every time.

According to views of Harry Markowitz (1952); he has given model of portfolio selection

for representing the diversification principles. This model is deeply well presentable and

considered as beginning step for portfolio management, and even commonly it is referred as

efficient set of portfolios of risky assets. This model revealed the fact that the investor are

looking for greater return if he goes for maximum risk and in such situation he is willing to

receive the expected return against bearing the greater risk of mutual funds (assets). In order to

adjust the risk performance evaluation method, there would be using two criteria i.e. model of

capital asset pricing method (CAPM) is used with another evaluation method i.e. mean variance

criteria for adjusted risk performance evaluation.

1.8 – Contextual Frame Work


In past couple years, there were many research took place in mutual funds by different economic

researchers. It is true that most of the time, individual investor doesn’t have required knowledge

and information about different investment firms and lacking investment vision and criteria in

the available securities of Pakistan. It is the requirement of financial instrument in case of foreign

& local capital and money markets that the individual investor must have the specialized

knowledge about securities in case of capital and money markets in order to have the increased

profitability and improved performance of financial instrument. That’s how the individual

investor are far behind in comparison of others and lacks in doing investment in such financial

markets due to having incomplete and correct information related to securities. That is reason

they are unable to modify and expand their portfolio of mutual fund. There is no doubt that there

are many investment funds are available in Pakistani financial market out of which many of

them, are offering various type of investment, level of risk, the prices (fees).There have been

seen many establishment related to several new Pakistani fund management companies and

foreign fund management companies.

1.9 - Problem Discussion

The past study of mutual fund deny the fund manager ability for market portfolio of adjusted risk

while support the efficient market reported by Jensen (1968), Sharpe (1966), Treynor (1965), but

the view of Inppolito (1993) was totally opposite about it. Although, lots of academic research

have been done in past and recent too, but it is difficult to identify the superior performance

funds because it is unpredictable to assess the performance of individual mutual fund in the

financial market. It is fact that the investors are able to make successful investment strategies in

order to beat the market but sometimes remained unsuccessful because of efficient market.

According to past studies, the fund returns may change from year to year because the objective


of investment funds by individual investor may changed and that’s how it affects the fund returns

significantly due to change of investment decision by investors; reported by Laurie Prather,

William J. Bertin, Thomas Henker (2002).

Lehmann, Blake, Timmerman (1999) reported that the asset allocation is an important

factor to achieve total returns for multiple class portfolios by fund manage. It is disclosed by

Wermers (2000) that stock picking ability is considered an important factor for improving

overall performance in case of mutual funds by fund manager. Measuring fund performances and

error tracking is a critical process, which could be done through portfolio configuration which in

fact explains the portfolio’s composition, reported by Keim D. (1999). Through this study, I

wanted to find out does the return equity of mutual funds got affected through fund’s

characteristics. There is no doubt that the funds attributes (characteristics) is considered an

important source for selecting top performing funds, and leaving worst funds, in short, it is cleary

mentioned in academic research that fund characteristics could help to differentiate among top

and worst funds in case of mutual funds. Accordingly to past researchers named as Laurie

Prather, Thomas Henker, & William J Bertin (2002); the fund attributes have been divided or say

categorized into four variables i.e. Popularity Variables, Growth Variables, and Management

Variables & Cost Variables.

1.9.1 - Popularity Variables

This measures for responsibility for money or fund aggregation which reflects the purchase and

merchandising somaesthesia and the funds noesis to alter that somesthesia. The popularity of

assets may be dependent proportionate to its recent action; either it meets the investment


objectives distinct in its catalogue. Thusly the popularity variables permit amount money size,

funds marketplace estimation and net quality appreciate (NAV).

1.9.2 - Growth Variables

Ontogeny (essay) shifting measures those factors which effect the hereafter show or grown

prospects of a money with the plain mean existence that ontogeny factors positively affect

performance. We included value earnings ratios (PE), soprano to volume ratio (PB) and cost to

interchange ratio (PC), there are some different factors of diversification train and individual

holdings can also be thoughtful. Value earning, toll to assemblage, and terms to change rate

alikeness the assets damage to value-impacting accounting versatile, such as earnings,

accumulation amount and cash line.

1.9.3 - Cost Variable

Outlay variables measures the expenses of the finances incurred during the sane bed of

performing. These measures let the expenses ratio (TKA), front most end burden, deferred

encumbrance and assets of finances gordian. Expenses ratio represents the pct of fund assets paid

as direction fee including trainer's compensation and operating expenses much as explore proof,

administrative fees and all new asset-based outlay incurred by the fund excluding workplace

charges.

1.9.4 - Managerial Variable

Managerial variables attempt to usurp managerial and administration attributes as vessel as

monitoring mechanism that adhere manager to stated funds promotion objectives which


ultimately relate the execution of money. Managerial attributes includes bulk, finances under

direction, management term, fund age, extremum initial get, and direction artifact.

1.10 - Problem Identification/ Statement

We have discussed about the background, current situation of Pakistani funds market and

variables which are affecting the mutual funds performance. Managerial attributes affecting the

mutual funds performance has been studied by different academics and they have suggested how

efficiently investment strategies can be made to gain a profit on stocks and mutual funds.

Although past performance is not indicating the future gains, but the previous studies shows that

fund characteristics affect the performance of mutual funds. Some academics have studied the

Pakistani mutual fund industry performance. We also have added our research analysis since the

fund has been launched of funds industry and special focus is on the mutual fund characteristics

affecting the performance. We have tried to answer the following question.

1.11 - Research Questions

The research proven to fulfill the mass interrogative

How the mutual funds characteristics affect the Pakistani mutual fund industry?

1.12 - Hypothesis Testing

In our research dependent variable is mutual fund return and factors affecting (popularity, growth

and managerial variables) the performance are independent variables.

H0: Fund size has insignificant impact on performance of mutual funds.

H1: Fund size has significant impact on performance of mutual funds.

H0: NAV has insignificant impact on impact the return.


H2: NAV has significant impact the return.

H0: Growth variables (PE and PB has insignificant impact on the return of mutual funds.

H3: Growth variable has significant influence the return.

H0: Turnover has insignificant impact on the return of mutual funds.

H4: Turnover has significant influence the return.

We will accept the null hypothesis if managerial attributes has insignificant impact on the

performance and alternatively reject the null hypothesis if these managerial attributes impact the

return of mutual funds.

1.13 - Purpose of the Research/study

Our intention is to probe whether managerial attributes and mutual assets characteristics touching

the assets execution and either it unexcelled point the incoming action. Contrary variables are

utilized and proved by using the abnormality analysis.

1.14 - Justification/ Significance of the Research

This research analyzed how these finances characteristics influencing the shared assets, their

reciprocity, and comparability with the old investigate studies.

1.15 - Limitations

Time limitations and Resources not allow me to take samples of all mutual fund companies of Pakistan.

This study only focuses open-end mutual funds of Pakistani mutual fund industry.

1.16 - Scope of the Research


This investigate included 20 shared assets companies operative in Pakistan which jazz 77 open-

end assets. The accumulation is included since fund has been launched roughly the returns and

different characteristics i.e. Turnover, Fund size, Net asset value, etc.

Chapter # 2


II - Literature Review

The construct of portfolio "execution" has at minimal two separate dimensions: The tailing

dimensions were highlighted by Michael C. Author in his studies in May 1968 "The Action of

Mutual Funds in the Period 1945-1964".

The noesis of the portfolio trainer or security analyst to process returns on the

portfolio through successful prediction of succeeding instrument prices.

The ability of the portfolio administrator to inform (through "efficacious"

diversification) the total of "insurable risk" dropped by the holders of the portfolio.

Different articles and thesis had been studied for conducting this research thesis mainly

financial research studies. Digital library of Jstor, Mutual Fund Association of Pakistan and

Google scholar was used for searching the literature relevant to the topic. Composed information

is used in the opening parts. Mostly the intelligent text are portfolio execution, finances

characteristics, mutual assets, justice mutual finances, finances size, mass ratio, efficient

markets. Whatsoever articles bibliography was old spell studying the articles for references.

Dissimilar scientist has conferred different results for their extent of investigate but we jazz used


only content related to our expanse of portion. Considerable search meditate was acquirable in

our area of search but academics know attained dissimilar results. We make used attributes in our

hypothesis, which has already been utilized in our literature retrospect.

As sort of educator work on finances show enhanced due to the fast ontogeny in shared

assets industry. Initially treatment with timing/investment abilities of finances handler there are

added factors too which may fighting the fund action including assets expenses, economies of

scale and administrator aim characteristics. Despite the development in the mutual fund literature

over the once various decades, academics soothe arrive to the contradictory conclusions

regarding the knowledge of money managers to constantly outperform the marketplace and

managerial attributes and fund peculiar characteristics that effect show.

Aboriginal mutual finances studies (i.e. Jensen (1968) Traynor (1965) validation the

economic markets by denying the ability of fund managers to oscillation a risk-adjusted

marketplace portfolio; however these were challenged by Ippolito's (1993) which reaches the

opposition finish. Bers and Madura (2000), Grinbalatt and Titman (1992), Goetzmann and

Ibbotson (1994), Hendricks, Patel and Zeckhauser (1993), Ibbotson and Patel (2002), Volkman

and Wohar (1995, 1996), strengthener this concept of marketplace inefficiency by find evidence

of repeated winners among fund managers and formal execution continuation.

Wermers (2000) finds that funds' capital production cognition enables them to raiment their

costs, patch oppositeness perspective bestowed and bust show durability among small-cap assets.

Detzel and Weigand (1998) encounter that investment name and the filler of stocks held by

finances explains the enduringness observed during their reflect period. In shared fund literature

there is other disputable topic nearly the interrelationship and scrap of expenses, volume and

weight on money execution. Sharpe (1966) finds that assets with berth expenses savvy wagerer


show, and much late, Golec (1996) suggests that fees are mostly associated with counter

relationship between show, after expenses, and assets fees and turnover, piece in a read of

alluviation and no concern funds, Hooks (1996) concludes that low cost laden finances

sufficiently outperform middling disbursement no-load finances. In oppositeness, Dellva and

Olson (1998) hit that assets with front-end weight charges earn minify risk-adjusted returns,

whereas Droms and Writer (1996) conclude no someone between action and loads, but a

supportive relation between fund expenses and returns.

Laurie Prather, et al (2004) yield umbrella touch of past shared fund execution by

analyzing a monstrous set of both mutual funds and fund attributes in an endeavour to nexus

action to fund-specific characteristics. The results present that the hypothesized relationships

between show and the explanatory variables are mostly upheld. After attractive into

consideration overall market conditions and money finance objective, the symptomatic variables

that think to fund popularity, maturation, outlay, and management also inform show. Eventually,

after controlling for survivorship and benchmark misconception as good as fund-specific factors,

the results controvert the action strength phenomenon. Anders G. Ekholm, Micheal Sound

(2007) canvass the personalty of 17 various shared money characteristics on shared money

action, including both publically accessible substance and non-public information equanimous

through a questionnaire among fund managers in Finland. We label that an hyperbolic limit of

investors love an adverse issue on mutual money show, and that indicant finances perform their

actively managed peers. Moreover, we uncovering that shared assets that are trading against in-

house brokerages underperform their peers, probably due to soft-commission arrangements. This

object potentially has restrictive implications for the mutual money industry.


Arturo Bris, et al (2006) examine a take of 125 justness shared finances that tight to new

assets between 1993 and 2004. They feat that assets intimate masses a stop of leading

performance and brachydactylic money inflows. Fund managers cite their fees when they

approximate to correct managers for losses in income due to the restrictions in size imposed by

the money end resoluteness. Managers reopen when fund size declines. However, they do not get

lake around majestic money managers. Marcin Kacperczyk , Writer Sialm, Lu Zheng (2003)

Despite wide revelation requirements, mutual money investors do not discover all actions of

money managers. We computation the upshot of undetected actions on fund returns using the

instrument gap-the disagreement between the reportable money key and the appearance on a

portfolio that invests in the previously revealed fund holdings. We credit that undetected actions

of any finances persistently create see, while such actions of additional funds defeat duration.

Our water conclusion shows that the reappear gap predicts money execution.

Massimo Massa and Rajdeep Patgiri (1998) calculable the modify of contractual

incentives on the execution of shared funds. We get that high-incentive contracts make managers

to position many danger and throttle the assets' chance of action. Yet, finances with high-

incentive contracts speak higher risk-adjusted key, and the prime execution remains lasting. The

top inducement quintile of funds outperforms the nether quintile by 2.70% per assemblage.

Moreover, high-incentive mortal finances from one period eff a optimistic alpha of 0.41% per

period in the people twelvemonth. Focusing on assets' holdings, we line through which

incentives gain execution. Nicolas P. B. Bollen , Jeffrey A. Busse (2004) calculation parameters

of touchstone support selection and activity timing models using daily shared money returns and

quarterly measure periods. We then excel assets quarterly by atypical key and decide the

performance of apiece decile the pursuing rear. The common abnormal recall of the top decile in


the post-ranking poop is 39 basis points. The post-ranking atypical travel disappears when funds

are evaluated over yearner periods. These results inform that arch.

Thomas Kalsson and Marina Persson (2005) were old a number of shared money

investors and can be a large plus in the assets resolution. They chance that the financial advisors

we surveyed use a much informed determination impact than somebody investors. The use of

individualist search sources and the thoughtfulness of a author oblique set of fund characteristics

demonstrate that advisors incline to alter the decision-making touch for investors. Though

advisors do not reckon money disbursal ratios as burning as most academics would upgrade, they

clearly engage see to clients. Not astonishingly, advisors who pass the superlative noesis and use

the most objective info free.

Jhon C. Bogle(1970) vindicate the action of money groups (stable, income/growth,

development, and invasive maturation are the categories utilised) bears a highly invariable

relationship to the proceeding of the industry and has, in fact, been rather rigidly certain. (It

should be emphasised that it is unit being performance that is predictable, not organism fund

performance, nor unquestioning show.) Several confirmable studies person explored the holdfast

between a fund's risk-adjusted proceeds and cost ratio as excavation as numerous otherwise

collateral issues. Sharpe (1966) reports that funds with decrease expenses possess higher reward-

to-risk ratios. But Ippolito (1989) finds fund returns to be misrelated to expenses. In acquisition

to these typewrite totality, other papers summarized here are those addressing another money

characteristics and execution. Among these are Dellava and Olson (1998), who investigate the


relationship of money execution and fund characteristics specified as fees, bulk, and enatic

variables. Their results mostly present that choice assets acquire.

Addressing the bulk payoff, the beforehand wreak of Mortal; still, both Malkiel (1995)

and Carhart (1997) inform a destructive outcome for portfolio bulk and complete money

expenses on fund returns. Grinblatt and Titman (1994) and Wermers (2000) shew a certain

relation between action and bulk, suggesting that those assets reserved in more progressive

trading may be judgement low priced securities. Thusly the shared fund literature oftentimes

reaches opposed conclusions regarding the noesis of money managers to disturb the marketplace

and the fight of volume and expenses on fund thin centering may encourage to the inconsistent

findings.


Chapter # 3


III - Methodology

In this chapter; the strategy taken to conduct this research as well as a suitable framework for this

study will be presented, including research approach, its design, population and sampling, data

collection methods and its analysis techniques with the justification of the specific choices we

made for this study. The aim is to simplify the understanding of each step taken to complete the

study (See figure 3-1 method of research work in appendix one).

3.1 - Research Approach

In this study, quantitative research approach has been taken to investigate the relationship among

managerial attributes, mutual fund characteristics and its performance. According to the nature of

the research, a quantitative research approach is suitable with descriptive research purpose to

examine the association between the variables i.e. Fund size, NAV, price to Earning, Price to

Book, Turnover and Return because this research has to explore the relationship as well as

developing a mathematical model between these numeric variables. However in this study

analytical methods will be performed. While designing this research, it is considered that it

should serve the purpose practically and should be in line with the objective of the study.

3.1.1 - Quantitative Research

Burns and Grove (1991) quantitative research is a formal, objective, systematic process in which

numerical data are utilized to obtain information about the world. Quantitative methods are research

practices that are used to collect quantitative facts - information dealing with numbers and

anything that is quantifiable. Tables, graphs and statistics, are frequently applied to present the


outcomes of these methods. The core objective of quantitative research methods is to extend and

utilize theories, mathematical models and/or hypotheses pertaining to phenomena. The procedure

of measurement is vital to quantitative research because it gives the fundamental association

between mathematical expression and empirical observation of quantitative relationships.

3.1.1.1 - Steps in the quantitative approach

The amount the most cardinal steps of a quantitative search, nonetheless it is seldom observed in

its clear conformation. Level so, the personage can be old to apprehension the concept and

outgrowth of a denary learn (Bryman, 2004). The noesis starts with theory, which is an speech of

the deductive study on the relationship between theory and explore, a conception is derivable

from theory and proven to sustain or spurn the theory. The hypothesis is not at all an unavoidable

manoeuvre and is most commonly observed in experimental studies. An large move of all valued

studies are conducted without strictly formulated construct, instead researchers often formulates

numeric explore questions as a batter for the theory. Steps 3 through 8 transact with the design

and implementation of investigate tools. Choices here are oftentimes essential for obtaining a

good construction of reliability and rigor. The lastly steps, 9 through 11, is where the scientist

psychoanalyse and compare is to possess any result at all opposite than for the investigator

himself the results of the scrutiny has to be prefab people, and once its public it becomes a

portion of theory and the junction is fulfilled (Bryman, 2004).

3.2 - Research Design

This research is design to illuminate the relation in between managerial attributes, mutual fund

characteristics ant its performance, so a correlational research design is appropriate for this

study.

Table 3-2: Symbolic Presentation of variables


3.2.1 - Correlational Research Design

A correlational research design is a quantitative technique of research in which researcher has

two or more quantitative variables from the similar group of subjects, & the researcher is trying

to conclude if there is an association (or co-variation) between the two variables (a similarity

between them, not a difference between their means). Theoretically, any two quantitative

variables can be correlated; however, it is probably a waste of time to collect & analyze data

when there is little reason to think these two variables would be related to each other1.

3.3 - Population & Sampling

The target population in this study is mutual fund industry of Pakistan. As there are twenty two

companies of which twenty companies data available, so we can say that the whole population

has been taken as a sample for analysis.

3.4 - Research Variables

To see cause and affect relationship this research is focusing on two types variables

Dependent Variables Symbols Independent Variables Symbols

Monthly Return MR Fund Size FS

Net Asset Value NAV

Price to Earning PE

Price to Book PB

Turnover T

1 http://www.capilanou.ca/programs/psychology/students/research/correlation.html


3.5 - Data Collection

The data used in this study is monthly from January-2001 to July-2010. In this study the data has

been gathered through secondary sources including monthly fund manager reports issued by

companies their financial statements, different research reports, magazines and different web-

sites (MUFAP)2.

3.6 - Data Analysis

Data analysis will be conducted by using SPSS. The following well-known statistical technique

is used for tabulating, interpreting and the analyzing the data for this research study.

Karl Pearson’s Correlation coefficient

Regression Analysis

3.6.1 - Karl Pearson’s Correlation Coefficient

Correlation refers to the degree of relation between two numerical variables. It is denoted by "r", which is

typically known as Correlation Coefficient.

The Correlation coefficient gives the mathematical value for measuring the strength of the linear

relation between two variables. Mathematically the value of "r" always lay between -1 and 13.

3.6.2 - Regression Analysis

Regression is the relationship between selected values of independent variable and observed

values of dependent variable, from which the most probable value of dependent variable can be

predicted for any value of independent variable. The regression equation is

2 http://mufap.com.pk/33http://www.mba-tutorials.com/statistics/452-correlation-analysis.html

http://www.mba-tutorials.com/statistics/452-correlation-analysis.html


y=α+βx1+βx2+ βx3+ε

MR=α +β1 FS+β2NAV +β3 PEandPB+ β4 T+ε

The use of regression to formulate quantitative predictions of one variable from the

values of another variable is called regression analysis4.

4 http://www.audioenglish.net/dictionary/regression_analysis.htm


Chapter # 4


IV - Data Analysis

This chapter comprises of empirical results, which is used in order to find out the hypothesis

values. For testing purpose the approach which is used; is quantitative research approach in

which historical quantitative data of selected samples were used in order to check the impact of

different mutual fund characteristics, managerial attribute on its return. The statistical technique

used in this study to test the hypothesis is Karl Pearson Correlation Coefficient and Regression

Analysis. This chapter also presented the basic assumptions for Regression analysis before

applying the test; all using SPSS.

Firstly, the hypothesis is tested through Karl Pearson Correlation coefficient to find out

the degree of relationship between each dependent variable with independent variables.

Secondly, the hypothesis is being tested through Linear Regression analysis to determine the

extent of relationship between dependent and independent variables because in this study; one

dependent variables is present so we setup regression models for dependent variable.

4.1 - Summary Statistics

The summary below highlights the descriptive statistics for each variable.

Table 4-1: Summary StatisticsVariables N Minimum Maximum Mean Std Dev

Monthly return 77 -2.29 16.55 6.79 4.54

Fund Size 77 112.02 41741.41 2923.72 6689.76

Net Asset Value 77 9.07 122.96 65.18 36.55

Price to Earning 77 6.20 11.40 8.47 1.22

Price to Book 77 1.40 3 2.41 0.24

Turnover 77 -0.21 1.51 0.69 0.46


This table presents a summary statistics for the variables as monthly return minimum -2.29 and

maximum 16.55 due to global financial crisis and environmental instability, Fund size minimum

112.02 and maximum 41741.41 due to different strategy of companies, Net asset value minimum

9.07 and maximum 122.96, Price to earnings minimum 6.20 and maximum 11.40, Price to book

minimum 1.40 and maximum 3. In turnover minimum -0.21 and maximum 1.51 rest of four due

to impact of return.

Table 4-1 is showing that mostly variables have their mean lie between minimum and

maximum value some close to minimum value and some close to maximum value. As monthly

return has mean 6.79 which is lie between minimum and maximum value, Fund size has mean

41741.41 lie between minimum and maximum value, Net asset value has mean 65.18 lie between

minimum and maximum value, Price to earning has mean 8.47 which is close to minimum value

which refers to low earnings, Turnover has mean 0.69 and standard deviation 0.46 here is mean

value close to minimum value with less volatility and price to book has mean 2.41 and standard

deviation 0.24 here is mean value close to maximum value which shows that larger number of

observations are close to the maximum value as price to book was less volatile or it can say that

it was constant therefore mean is close to maximum value.

4.2 - Karl Pearson’s Correlation Coefficient

Correlation refers to the degree of relation between two numerical variables. It is denoted by "r", which is

typically known as Correlation Coefficient. The Correlation coefficient gives the mathematical value for

measuring the strength of the linear relation between two variables. Mathematically the value of "r"

always lay between -1 and 1 with:


+1 representing absolute positive linear relationship (as X increases, Y increases).

0 representing no linear relationship (X and Y have no pattern).

-1 representing absolute inverse relationship (as X increases, Y, Decreases).

Table 1 presented the test results for Karl Pearson’s Correlation Coefficient among Dependent

variable with every Independent variable.

Table 4-2: Pearson Correlation Coefficients

Variables Return Fund size Net Asset Value

Price to Earning

Price to book

Turnover

ReturnCorrelationP-Value 1

Fund sizePearson CorrelationP-Value

-0.122 (0.291)

1

Net Asset ValuePearson CorrelationP-Value

0.035(0.761)

-0.142(0.216)

1

Price to EarningPearson CorrelationP-Value

0.140(0.225)

-0.171(0.138)

0.016(0.892)

1

Price to bookPearson CorrelationP-Value

0.250*(0.028)

0.142(0.217)

0.035(0.760)

0.358*(0.001)

1

TurnoverPearson CorrelationP-Value

0.865*(0.000)

-0.093(0.421)

-0.022(0.853)

0.158(0.170)

0.260(0.170)

1

The table contains two rows; the first row shows the value of correlation coefficient,

second row shows the significance value and the row labeled as N presented the total number of

observations. All variables carry 77 observations and the p-value for the test is less than 0.05, so

we can reject our null hypothesis at 5% level of significance and admit that there is some


correlation present among the variables. The row labeled Pearson Correlation gives the values of

correlation. The value of 0.865 explains that there is a strong positive relationship between return

of mutual fund and turnover. While in the case of price to book, price to earning and net asset

value; there is a weak positive correlation with return and it is decreasing respectively. This

means that the change in turnover influenced more on the return than price to book, price to

earning and net asset value respectively. The impact of fund size is inversely proportional on net

asset value, price to earning and turnover than net asset value has also a negative impact on

turnover.

4.3 - Analysis of variances

The table A-1 gives the test results for the analysis of ANOVA. Here model, Error and Corrected

total, is breakdown of variance in the outcome variable, which we will examine. Model summary

gives the adequacy and accuracy of the fitted model. Degree of Freedom (DF) is associated with

the sources of variance. The total variance has n-1 degrees of freedom. The known degree of

freedom corresponds to the number of coefficients estimated minus 1. Including the intercept,

there are 6 coefficients, so the model has 6-1=5 degree of freedom. The unknown degree of

freedom is the DF total minus the DF model, 76-5 =71.

The value of adjusted-R2 is 0.745, which shows that the independent variables in the

model can accurately predict 75.4% of the total variance present in the dependent variable. F-

value and p-value comes from the test of ANOVA, which shows the sufficiency of adjusted-R2.

With respect to the p-value in our case the null hypothesis is rejected, so it means the

independent variables used in this study to predict the values of dependent variable can

accurately measures enough variance.


4.4 - Parameter Estimation OLS Method

This table 4.4 shows the dependent variables, constant, coefficients, t statistic, R-Square and

F-statistic. Constant referred as the Y intercept the height of the regression line when it crosses

the Y axis. In other words, this is the predicted value of dependent variable when all

independents variables are 0. R-Square which is called the coefficient of determination and it

gives the adequacy of the model. In this study, we have a dependent variables monthly return. In

order to fulfill our requirement, we setup a regression model for dependent variable. The general

model for regression analysis is given by:

MR=α +β1FS+β2 NAV +β3 PEandPB+ β4 T+ε

Where,

α = Regression Constant

β = Regression Coefficient ( β1 Regression Coefficient of FS, β2 Regression Coefficient of

NAV, β3 Regression Coefficient of PE and PB, β4 Regression Coefficient of T).

Dependent Variable = MR which is monthly return of Mutual funds

Independent Variables = FS (Fund size), NAV (Net Asset Value), PE (Price to Earning), PB

(Price to Book) and T (Turnover).

ε=

The value of R2 is 0.754, which shows that the independent variables in the model can

accurately predict 75.4% of the total variance present in the dependent variable. Coefficients

Standard error of residual


gives the regression coefficients and related statistics for all independent variables separately in

different rows. These regression coefficient and constant can be used to construct an ordinary

least squares (OLS) equation and also to test the hypotheses for each Independent variable.

According to p-value in this case, the p-value of Fund size, Net asset value, Price to earnings and

Price to book is shown as 0.482, 0.442, 0.792 and 0.568 respectively which is greater than 0.05,

this means that the change in the values of these variables has insignificant impact on the

monthly return of mutual fund and we should eliminate this variable from the OLS equation.

While the hypothesis for other independent variable is rejected. By using the regression

coefficient and the constant term; we can construct the OLS equation for predicting the monthly

return i.e.

Monthly Return = -0.332 + 8.342 (Turnover)

Table 4-3: Ordinary Least Square Estimation


Ordinary Least Square (OLS)

Intercept -0.332

C.I.* 95% [-5.983 ; 5.318]

T-Value -0.177

P-Value (0.907)

Fund size -3.0E-005

C.I. 95% [0.000 ; 0.000]

T-Value -0.707

P-Value (0.482)

Net Asset Value 0.006

C.I. 95% [-0.009 ; 0.021]

T-Value 0.773

P-Value (0.442)

Price to Earning -0.064

C.I. 95% [-5.74 ; 0.419]

T-Value -0.264

P-Value (0.792)

Price to Book 0.698

C.I. 95% [-1.726 ; 3.122]

T-Value 0.574

P-Value (0.568)

Turnover 8.342*

C.I. 95% [7.141 ; 9.543]

T-Value 13.853

P-Value (0.0001)

R2 0.754

F 43.455*

(0.0001)

C.I: Confidence interval

4.5 - Testing OLS Assumptions


Before applying the Regression analysis, we first check the following basic assumptions of

regression analysis in order to ensure that the given data provides reliable and valid outcomes.

Test for Normality

Test for Multi-Collinearity

Test for Autocorrelation

4.5.1 - Test for Normality

Statistical methods are based on various underlying assumptions. One common assumption is

that a random variable is normally distributed. In many statistical analyses, normality is often

conveniently assumed without any empirical evidence or test. But normality is critical in many

statistical methods. When this assumption is violated, interpretation and inference may not be

reliable or valid. There are two ways of testing normality (1) Graphical Methods (2) Numerical

Methods. Graphical methods visualize the distributions of random variables or differences

between an empirical distribution and a theoretical distribution (e.g., the standard normal

distribution). Numerical methods present summary statistics such as skewness and kurtosis, or

conduct statistical tests of normality. In this study, we used both of these methods to find out the

normality of the data. In numerical method, we used Shapiro-Wilk statistics to conclude the

results and also setup several histograms to determine normality graphically. All The variables

are supposed to be normally distributed with mean 0 and Standard Deviation 1 (See the

Appendix for details).

Table A-2 gives the test results for Shapiro-Wilk Statistics. The Shapiro-Wilk W is the

ratio of the best estimator of the variance to the usual corrected sum of squares estimator of the


variance (Shapiro and Wilk 1965)5. The statistic is positive and less than or equal to one. Being

close to one indicates normality.The above table clearly shows that the Shapiro-Wilk Statistics

for dependent and independent variables used in this study are very close to 1, this ensure the

data being used has come from normally distributed population.

4.5.2 - Test for Multi-Collinearity

Multi-Collinearity is a statistical phenomenon in which two or more predictor variables in a

regression model are highly correlated. In this situation the coefficient estimates may change

inconsistently in response to small changes in the model or the data. Tolerance and the Variance

Inflation Factor (VIF) are two Collinearity diagnostic factors that can help identifying Multi-

Collinearity. The value of tolerance must be greater than 0.50, while the value of VIF is less than

2.50.

Table 4-4: Multi-Collinearity Statistics

Independent VariablesCollinearity Statistics

Tolerance VIF

Fund size 0.887 1.128

Net Asset Value 0.973 1.028

Price to Earning

Price to Book

Turnover

0.819

0.776

0.911

1.221

1.289

1.098

5 Shapiro, S. S. and Wilk, M. B. (1965). "An analysis of variance test for normality (complete samples)", Biometrika, 52, 3 and 4, pages 591-611.


Table 4 shows the Collinearity statistics for independent variables used in the study. The

tolerance value for all IVs is greater than 0.50 and VIF is less than 2.50, this indicates that the

correlation among the IVs are very low and hence no Multi-Collinearity factor exist in the

regression model.

4.5.3 - Test for Auto Correlation

Auto Correlation is the relationship between values of a variable taken at certain times in a time

series and values of a variable taken at other, usually earlier times. The term also referred to as

“Lagged Correlation” or “Serial Correlation” the hypotheses usually considered in the Durbin-

Watson test are;

Ho : ρ=0

Ho : ρ>0

Here null hypothesis is showing there is autocorrelation exist and alternative hypothesis

showing there can be +ve, -ve and autocorrelation exist. The statistical technique used to identify

the existence of Autocorrelation in the residuals from a regression analysis is called Durbin-

Watson statistics calculate through following formula;

d=∑t=2

T(e t−e t−1 )

2

∑t−1

Te

t2

. The value of Durbin-Watson must be greater than 1.20 and less than 2.00, which

indicates very low (negligible) or No Autocorrelation. If Durbin-Watson is less than 1.20 or

greater than 2.00, there may be cause for alarm. In regressions, this can imply an under/over

estimation of the level of statistical significance.


Table 4-5: Durbin-Watson Statistics

Monthly return

Durbin-Watson 1.88

As shown in the above Table, the values of Durbin-Watson statistics for dependent

variables in our case are nearest to 2.00, this indicates that there is no autocorrelation exists in

our study and the regression models assume that the error deviations are uncorrelated.

4.6 - Result of Analysis

A relationship between return and independent variables can be check in the scatter plot

Appendix II. All scatter plots indicates some kind of linear relationship. Our regression analysis

give us results that either will accept the null hypothesis if managerial attribute does not

influence the performance and alternatively reject the null hypothesis if the managerial attribute

impact the return of mutual fund.

H0: Fund size has insignificant impact on performance of mutual funds.

H1: Fund size has significant impact on performance of mutual funds.

H0: NAV has insignificant impact on the return.

H2: NAV has significant impact on the return.

Among the popularity variables the null hypothesis stating that fund size does not influencing the

performance of mutual fund. There is a positive relationship with return. Thus the fund size

influences the fund performance because larger fund have more diversification of investment and


economies of scale and a negative relationship indicates that the fund size may impact on its

ability to implement a particular investment style.

H0: Growth variables (PE and PB) has insignificant impact on the return of mutual funds.

H3: Growth variables has significant impact on the return.

Within the growth variables the coefficient estimates for PE and PB are positive and negative

respectively and statically significant. Impact of these variables reflects a positive influence of

growth opportunities. So we found that growth variables influences the mutual fund return.

H0: Turnover has insignificant impact on the return.

H4: Turnover has significant impact on the return.

Within managerial variables earlier studies by Friend et al (1970), Grinblatt and Titman (1994),

wermers (2000), Arshad ali javeed and Azhar iqbal (2008) finds a positive relationship between

turnover and return which is consistent with our analysis.


Chapter # 5


V - Conclusion

The research gives a detailed and incorporated analysis of mutual funds performance, history and

current trends of mutual fund industry of Pakistan and fund characteristics impacting the mutual

funds. We select different kinds of categories of popularity, growth and managerial variables

which influencing the performance. These include detail discussion of the relationship between

mutual funds performance and fund related factors with a recent data of mutual funds and fund

characteristics.

Our research builds upon earlier research and provides investor a framework which

factors should they consider while investing in mutual funds. We select 77 mutual funds, the

fund attributes shows the relationship with return how it is affected by the fund size , net asset

value, price to earnings, price to book and turnover. The research provides a significant update to

the previous literature by examining mutual funds industry recent conditions and rapid growth of

mutual fund industry. The relationship between mutual fund performance and fund specific

factors shows the results are generally consistent with the studies conducted by previous

researchers.

5.1 - Findings

Turnover reacts positively to the rise in performance of mutual fund industry of

Pakistan.

The impact of Net asset value and Price to book variable is very little on the

performance of mutual fund industry of Pakistan.

While Fund size and Price to Earning influences the performance of Pakistani mutual

fund industry negatively.


Our finding indicates that there is no Autocorrelation and Multi Collinearity factors exists

in the model, therefore the results are authentic and reliable. The impact of turnover is more

severe on the performance of Pakistani mutual fund industry because turnover has a strong

positive correlation with return. 1% increases in the turnover increases more than 8% value of

the return of mutual funds. Thus, investors who are interested in investing in mutual funds

should pay more attention to the managerial attributes represents turnover.

5.2 - Future Research Proposal

We studies different research papers, thesis related to mutual fund performance which has given

us an idea for future studies. We include sample size of 77 open end mutual funds and only a few

variables influencing the performance of the mutual funds. The future study can be done close-

end mutual funds and variables such as fund age, management tenure, diversification level,

number of holdings etc. Do these variables influence the performance of mutual funds?


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Appendix


VII – Appendix A

Table A-1: Analysis of Variance (ANOVA)

Source DFSum of Squares

Mean Square F-Value P-Value

Monthly return

Model 5 1182.468 236.499 43.455* (0.0001)

Error 71 386.400 5.442

Corrected Total 76 156.868

Table A-2: Test for Normality

VARIABLES

Shapiro-Wilk

Statistic df

Monthly Return 0.911 77

Fund size 0.388 77

Net Asset Value 0.856 77

Price to Earning 0.957 77

Price to Book 0.906 77

Turnover 0.858 77


Appendix BFigure 1 – 1 Mutual Funds in Pakistan

Open-End Mutual Funds1 ABL Income Fund 52 IGI Income Fund2 ABL Stock Fund 53 IGI Islamic Income Fund3 AKD Income Fund 54 IGI Money Market Fund4 AKD Index Tracker Fund 55 IGI Stock Fund5 AKD Opportunity Fund 56 JS Aggressive Asset Allocation6 Meezan Capital Protected Fund 57 JS Aggressive Income Fund7 Meezan Cash Fund 58 JS Capital Protected Fund8 Meezan Islamic Fund 59 JS Capital Protected Fund IV9 Meezan Islamic Income Fund 60 JS Cash Fund

10 Meezan Sovereign Fund 61 JS Fund of Funds11 Alfalah GHP Alpha Fund 62 JS Income Fund12 Alfalah GHP Cash Fund 63 JS Islamic Fund (Formerly UTP Islamic Fund)

13 Alfalah GHP Income Multiplier Fund 64 JS KSE 30 Index Fund (14 Alfalah GHP Islamic Fund 65 JS Principal Secure Fund I15 Alfalah GHP Principal Protected Fund 66 JS Principal Secure Fund II16 Alfalah GHP Principal Protected Fund II 67 Unit Trust of Pakistan17 Alfalah GHP Value Fund 68 KASB Balanced Fund18 MetroBank Pakistan Sovereign Fund (12/12) 69 KASB Capital Protected Gold Fund19 MetroBank Pakistan Sovereign Fund (Perpetual) 70 KASB Cash Fund20 Pakistan Capital Market Fund 71 KASB Islamic Income Fund21 Pakistan Capital Protected Fund (FIS) 72 KASB Liquid Fund22 Pakistan Cash Management Fund 73 KASB Stock Market Fund23 Pakistan Income Enhancement Fund 74 Lakson Equity Fund24 Pakistan Income Fund 75 Lakson Income Fund25 Pakistan Int'l Element Islamic Fund 76 Lakson Money Market Fund26 Pakistan Stock Market Fund 77 MCB Cash Management Optimizer Fund27 Askari Asset Allocation Fund 78 MCB Dynamic Allocation Fund28 Askari Income Fund 79 MCB Dynamic Cash Fund29 Askari Islamic Asset Allocation Fund 80 MCB Dynamic Stock Fund30 Askari Islamic Income Fund 81 NAFA Cash Fund31 Askari Sovereign Cash Fund 82 NAFA Government Securities Liquid Fund32 Atlas Income Fund 83 NAFA Income Fund33 Atlas Islamic Income Fund 84 NAFA Islamic Income Fund34 Atlas Islamic Stock Fund 85 NAFA Islamic Multi Asset Fund35 Atlas Money Market Fund 86 NAFA Multi Asset Fund36 Atlas Stock Market Fund 87 NAFA Saving Plus Fund37 BMA Chundrigar Road Saving Fund 88 NAFA Stock Fund38 BMA Empress Cash Fund 89 National Investment Trust (GBF)39 Crosby Dragon Fund 90 National Investment Trust (IF)40 Crosby Phoenix Fund 91 National Investment Trust (LOC)41 Dawood Islamic Fund 92 National Investment Trust (Non LOC)42 Dawood Money Market Fund 93 Pak Oman Advantage Islamic Fund43 Faysal Asset Allocation Fund 94 Pak Oman Advantage Islamic Income Fund44 Faysal Balanced Growth Fund 95 Pak Oman Advantage Stock Fund45 Faysal Income & Growth Fund 96 Pak Oman BOP Advantage Plus Fund46 Faysal Savings Growth Fund 97 UBL Liquidity Plus Fund


47 First Habib Income Fund 98 United Composite Islamic Fund48 First Habib Stock Fund 99 United Growth & Income Fund49 HBL Income Fund 100 United Islamic Income Fund50 HBL Multi Asset Fund 101 United Stock Advantage Fund51 HBL Stock Fund

Close-End Mutual Funds1 Golden Arrow Selected Stock Fund 10 JS Large Cap Fund 2 Pakistan Capital Protected Fund 1 11 JS Value Fund Limited3 Pakistan Premier Fund Limited 12 Pak Oman Advantage Fund4 Pakistan Strategic Allocation 13 PICIC Energy Fund5 Atlas Fund of Funds 14 PICIC Growth Fund6 Al Meezan Mutual Fund 15 PICIC Investment Fund7 Meezan Balanced Fund 16 Asian Stocks Fund8 First Capital Mutual Fund 17 Safeway Mutual Fund9 JS Growth Fund 18 UBL Capital Protected Fund

1.00.80.60.40.20.0

Observed Cum Prob

1.0

0.8

0.6

0.4

0.2

0.0

Expected Cum Prob

Dependent Variable: Monthly Return

Figure 4-2 : Normal P-P Plot of Regression Standardized Residual


6420-2-4

20

15

10

5

0

Mean = -3.76E-16Std. Dev. = 0.967N = 77

Figure 4-1: Normal Curve for Monthly Return

Frequency


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Impact of Mutual Fund Charact