Scholarly article on topic 'Trade-off Study of Equity Mutual Fund for Small and Medium Enterprise'

Trade-off Study of Equity Mutual Fund for Small and Medium Enterprise Academic research paper on "Economics and business"

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Abstract of research paper on Economics and business, author of scientific article — Eric Marshall Ting Toyo, Sylviana Maya Damayanti

Abstract The purpose of this research is focused on equity mutual fund in Indonesia at 2007-2013. From equity mutual fund that active at 2007-2013 this research examined whether selected factors influence the performance of equity mutual fund. Then this research also investigated which equity mutual fund's performance exceeded performance of Indonesia stock index (IHSG). 5 equity mutual funds that exceed Indonesia stock index (IHSG) is panin dana maksima, schroder dana istimewa, pratama saham, batavia dana saham, dan BNP Paribas pesona. This research can provide recommendation for small and medium enterprise to allocate their fund in mutual fund. SMEs usually have a volatile revenue and income stream. In order to reduce the operational risk, SMEs allocates high cash position as a buffer during difficult situation. This paper aims to increase earning from this cash position through investment strategy.

Academic research paper on topic "Trade-off Study of Equity Mutual Fund for Small and Medium Enterprise"

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Procedía - Social and Behavioral Sciences 169 (2015) 249 - 257

The 6th Indonesia International Conference on Innovation, Entrepreneurship and Small Business,

12 - 14 August 2014

Trade-off Study of Equity Mutual Fund for Small and Medium Enterprise

Eric Marshall Ting Toyoa*, Sylviana Maya Damayantib

abSchool of Business and Management, Institut Teknologi Bandung, Jl. Ganesha 10, Bandung 40132, Indonesia

Abstract

The purpose of this research is focused on equity mutual fund in Indonesia at 2007-2013. From equity mutual fund that active at 2007-2013 this research examined whether selected factors influence the performance of equity mutual fund. Then this research also investigated which equity mutual fund's performance exceeded performance of Indonesia stock index (IHSG). 5 equity mutual funds that exceed Indonesia stock index (IHSG) is panin dana maksima, schroder dana istimewa, pratama saham, batavia dana saham, dan BNP Paribas pesona. This research can provide recommendation for small and medium enterprise to allocate their fund in mutual fund. SMEs usually have a volatile revenue and income stream. In order to reduce the operational risk, SMEs allocates high cash position as a buffer during difficult situation. This paper aims to increase earning from this cash position through investment strategy.

© 2015TheAuthors.PublishedbyElsevier Ltd.This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-reviewunderresponsibilityofCenter for Innovation,Entrepreneurship, and Leadership (CIEL), School of Business and Managements (SBM), Institut Teknologi Bandung (ITB).

Keywords: mutual fund, SMEs; performance mutual fund; variables mutual fund; sharpe ratio

* Corresponding author. E-mail address: eric.marshall@sbm-itb.ac.id

1877-0428 © 2015 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of Center for Innovation, Entrepreneurship, and Leadership (CIEL), School of Business and

Managements (SBM), Institut Teknologi Bandung (ITB).

doi:10.1016/j.sbspro.2015.01.308

1. Introduction

This research can provide recommendation to small and medium enterprise that want to allocate their fund to investment, especially in mutual fund. Specifically, this research is examining the factor that effect performance of mutual fund and compare the performance of mutual fund. Entrepreneurs ussually face volatility in their SMEs. Volatility in revenues, earnings, and cash flows. This paper are trying to see whether the earnings generated from the SMEs business can be enhanced certain specific investment strategy. So, the result of this research can provide insight to SMEs about factors that need to be considered and performance of mutual fund. With this investment strategy, entrepreneurs can choose their investment strategy apropriately. This is because mutual fund is one of investment instrumen that have low risk, because this investment is a portfolio. There are many types of mutual fund, so entrepreneurs need to know how to choose mutual fund appropriately. To choose a good mutual, entrepreneurs can look at the variables.

The current development of Mutual fund in Indonesia is rapidly increasing in line with the growth of economic and capital market. By investing in Mutual fund, ordinary people and individuals who do not have large funds could do investment in capital market and obtain the benefits of capital market development. The development of Mutual fund supported by the growth and development of investment products makes not every individual can understand the new investment products and has enough time to manage his / her investments. By utilizing the services of professional investment manager who have deep down knowledge on the securities, most people can catch up their lack of knowledge about investment.

One of Mutual fund investment benefits is the diversification on the money invested, because the money will be distributed to a variety of investment instruments, such as stocks and obligations. By diversification, investors can lower down the risks posed by their investments. For example, if one investment instrument loses, then it will be compensated by the returns of other investment instruments. (Evi Putri Winingrum, 2011).

The fund raised from investors is another advantage of Mutual fund. The amount of money managed is relatively higher than the money managed by individuals. Furthermore, the investment management is conducted by professional management team, i.e. investment manager (Ambarwati, 2007). Mutual fund company will issue stocks that in turn are offered to investors. After the money is pooled, then it will be invested in considered profitable securities. The returns reaped will be distributed back to investors (Anoraga dan Pakarti, 2003).

A news article in www.investor.co.id on 6 juli 2013 stated that the returns from Equity mutual funds exceeded the growth of Stock Index (IHSG / Indeks Harga Saham Gabungan). The returns of Equity mutual funds reached 12.66 %, while the growth of IHSG in IDX (Indonesian Stock Exchange) was 11.63% in the first semester of 2013 .

This phenomenon can be made as a reference for investors who do not have much time to obtain the investment returns higher than the returns of IHSG. Basically, Equity mutual funds are a Mutual fund by which at least 80% of its funds must be invested on stocks. Most of the returns obtained by Equity mutual funds come from investment on stocks. There is also possibility that specialization of investment manager who manages Equity mutual funds make the returns of Equity mutual funds are higher than those of IHSG. Therefore, the researcher will conduct a study whether specialization of investment manager has any impact on the returns of Equity mutual funds.

The second possibility is the impact of Mutual fund company age. It is possible that the more aged the Equity mutual funds, the better are the experiences of the investment manager of those Equity mutual funds. Thus, the researcher will study whether there is any impact of Mutual fund company age on the returns of Equity mutual funds.

The third possibility is that there is any cooperation (affiliation) that makes the performances of certain Equity mutual funds increasing. Therefore, the researcher would study whether there is any impact of affiliation between companies issuing Equity mutual funds with other companies to the performances of Equity mutual funds.

The objective of the research is to give information to public, investors and ordinary people, whether (or not) Equity mutual funds can give higher returns than those of markets stocks, so that they can choose which investment instruments are appropriate to them. The objectives of the research are stated as follows: (1) To measure the performances of Equity mutual funds by using Sharpe 's method so that this research can examine which Mutual fund products that show better performances. (2) To study whether there is any impact of specialization of investment manager on the performances of Equity mutual funds. (3) To study whether there is any impact of company age on the performances of Equity mutual funds. (4)To study whether there is any impact of affiliation

company on the performances of Equity mutual funds. (5) To study whether there is any impact of Net Asset Value (NAV) on the performances of Equity mutual funds. (6) To make comparison between the performances of Equity mutual funds to those of market stocks.

2. Theoretical Foundation

2.1. Research Variable

The variables used in this research are classified into two types: independent and dependent variables. The dependent variables in the research are Sharpe ratio of Equity mutual funds, whereas the independent variables are the age of Mutual fund, the specialization of investment managers, affiliation companies, and Net Asset Value (NAV) of Mutual fund.

2.2. Data Gathered

The research collects data to measure the performances on Equity mutual funds with the following criteria:

1. Equity mutual funds taken are conventional Equity mutual funds

2. Equity mutual funds taken are actively traded from January 2007 to December 2013 Based on those criteria, the19 Equity mutual funds data gathered in this study.

Table 1 Table of equity mutual fund used in this studies_

No Name of Equity mutual funds

1 Axa Citradinamis

2 Batavia Dana Stocks Optimal

3 Batavia Dana Stocks

4 BNP Paribas Ekuitas

5 BNP Paribas Pesona

6 CIMB-Principal Equity Aggressive

7 Dana Ekuitas Andalan

8 Dana Ekuitas Prima

9 Dana pratama ekuitas

10 Danareksa mawar

11 First State Indoequity Sectoral Fund

12 Mandiri Investa Atractive

13 Manulife Stocks Andalan

14 Panin Dana Maksima

15 Pratama Stocks

16 Rencana Cerdas

17 Schroder Dana Istimewa

18 Schroder Dana Prestasi Plus

19 Trim Capital

2.3. Data Collection Method

1. Monthly NAV data of every Equity mutual funds from January 2007 to December 2013 are retrieved from the official website of BAPEPAM.

2. The risk free rate (rf) for detemining Sharpe ratio is set by using the interest rate of SUN (government bonds) which are actively and continuesly traded from Januari 2007 to December 2013. The research is to study Equity mutual funds from Januari 2007 to December 2013 continuously so that the risk free rate used should be compatible to what is investigated.

3. The age data, specialization of investment managers, and affiliated company are obtained from the websites of each Mutual fund companies

2.4. Data Processing 2.4.1. Sharpe Ratio

The processing of NAV data is using the Sharpe ratio formula as follows:

Where:

rx = portfolio return rf = Risk free rate

stdDev(x) = portfolio standard deviation

The above NAV data are processed monthly using MS Excel, so that this research can determine the value of Sharpe ratio of each companies issuing Equity mutual funds

2.4.2. Multiple Linear Regression Text

If there are two or more independent variables, this research can determine the impact of correlation between dependent and independent variables by using Multiple linear regression analysis (Ghozali, 2005). The regression equation is formulated as follows:

Y = a + b1X1 + b2X2 + b3X3 + b4X4 Where:

Y = Sharpe Ratio a = constant

b1 - b4 = regression coefficient of each independent variables X1 = company age

X2 = specialization of investment manager X3 = affiliation company X4 = the sums of NAV

3. Result

3.1. Multiple Linear Regression Analysis

3.1.1. Impact Company age (X1), Specialization (X2), Affiliation (X3) and Total NAV (X4) to Sharpe Index (Y)

To estimate the impact of company age (X1), specialization (X2), affiliation (X3) and Total NAV (X4) to Sharpe Index (Y), multiple linear regression analysis is applied with the following equation: Y = a + b1X1 + b2X2 + b3X3 + b4X4 Where :

Y = Sharpe Index X1 = company age X2 = specialization X3 = affiliation X4= Total NAV a = constant

b1; b2, b3, b4 = Regression Coefficient

The result of data processing by SPSS 13 software for multiple linear regression analysis is presented in the following table.

Table 2 Multiple Regression Analysis Variables Regression Coefficient Std. Error t Sig.

(Constant)_1,130_0,916_1,234_0,217

X1 -0,078 0,118 -0,665 0,506 X2 -0,111 0,109 -1,021 0,308 X3 -0,120 0,121 -0,990 0,323 X4_-0,056_0,022_-2,542_0,011

Based on the computation on the table above, the equations for multiple linear regression analysis are formulated as follows:

Y = 1,130 - 0,078 X1- 0,111 X2- 0,120 X3 - 0,056 X4 Y0 = 1,130 - 0,078 X1- 0,111 (0)- 0,120 (0)- 0,056 X4 Y0 = 1,130 - 0,078 X1- 0,056 X4 Y1 = 1,130 - 0,078 X1- 0,111 (1)- 0,120 (1)- 0,056 X4 Y1 = 0,899 - 0,078 X1- 0,056 X4 Where:

Y0 = Sharpe Index Equation with no specialization as an investment manager and affiliation to domestic company

Y1 = Sharpe Index Equation with specialization as an investment manager and affiliation to Foreign company The values of regression coefficient on the independent variables describe when independent variable rises one unit and the value of other independent variables are kept constant or equal to zero, then the values of the dependent variables are expected to go up or down in line with the plus or minus sign of the regression coefficient of its independent variables.

From the equation of multiple linear regression above, the constant value is calculated as 1,130. In other words, if Sharpe Index (Y) variable is not affected by the four independent variables - company age (X1), specialization (X2), affiliation (X3) and Total NAV (X4) equal to zero - then value of average Sharpe Index will be 1,130.

The sign of regression coefficient on independent variables shows the direction of the relation of corresponding variables with Sharpe Index. When coefficient of independent variables X1 is negative, it shows that the correlation is not in the same direction with company age (X1) and Sharpe Index (Y). For example, -0.078 coefficient of variables X1 means that for an increase for one unit on company age (X1) will affect on the decrease of Sharpe Index (Y) for 0.078.

Negative regression coefficient for independent variables X2 shows there is NO unidirectional correlation between Specialization (X2) and Sharpe Index (Y). Coefficient of -0.111 on variables X2 means that an increase for one unit on Specialization (X2) will take effect on a decrease of 0,111 on Sharpe Index (Y).

Negative regression coefficient for independent variable X3 shows there NO unidirectional correlation between Affiliation (X3) and Sharpe Index (Y). Coefficient of -0.120 on variable X3 means that for every increase for one unit on Affiliation (X3), there will be a decrease of 0.120 on Sharpe Index (Y)

Negative regression coefficient for independent variable X4 means there is NO unidirectional correlation between Total NAV (X4) and Sharpe Index (Y). Coefficient of -0,056 on variable X4 means that for every unit increase in Total NAV (X4) there will be a decrease of 0,056 on Sharpe Index (Y).

It can be inferred that average Sharpe Index on no specialization as investment manager with affiliation to Domestic company is higher than average Sharpe Index on specialization as an investment manager with affiliated to Foreign company.

3.1.2. Significance Test on Regression Coefficient

3.1.2.1. Overall Hypothesis Test (F-Test)

To examine the significance impact of independent variables simultaneously on dependent variables, F-Test is used as follows:

Ho : There is NO significant impact of company age (X!), specialization (X2), affiliation (X3) and Total NAV (X4) on Sharpe Index (Y).

Ha : There is significant impact of company age (X!), specialization (X2), affiliation (X3) and Total NAV (X4) on Sharpe Index (Y). a = 5% Statistic Test:

Test Criteria: 1. Accept Ho if Ftest < F table 2. Reject Ho if F test > F table F table = F a ; (dfl, df2) ; df! = k , df2 = n-k-1

The result of F-Test is calculated by SPSS software and is presented in the following table.

Table 3 Overall Hypothesis Test (F-Test)

F test df F table Sig Explanation Conclusion

1,783 dfl = 4 ■ 2,382 0,130 Ho is accepted No impact

df2= 924 (not significant)

From the table above, this research can obtain that the value of F test is 1,783. Since the value of F test (1,783) < F table (2,382), then Ho is accepted. Thus, it can be inferred that simultaneously there is NO significant impact of company age (X1), specialization (X2), affiliation (X3) and Total NAV (X4) on Sharpe Index (Y).

3.1.2.2. Partial Hypothesis Test (T-Test)

To examine the significance impact of independent variables partially on particular independent variables, T-Test is used as follows:

Hypothesis:

• Hoi :Pi = 0 Company age^) has NO significant impact on Sharpe Index (Y).

Ha! : Pi Ф 0 company age (Xi) has significant impact on Sharpe Index (Y).

• Ho2 :p2 = 0 specialization (X2) has NO significant impact on Sharpe Index (Y).

Ha2 : p2 Ф 0 specialization (X2) has significant impact on Sharpe Index (Y).

• Ho3 :p3 = 0 Affiliation (X3) has NO significant impact on Sharpe Index (Y).

Ha3 : p3 Ф 0 Affiliation (X3) has significant impact on Sharpe Index (Y).

• Ho4 :p4 = 0 Total NAV (X4) has NO significant impact on Sharpe Index (Y).

Ha4 : p4 Ф 0 Total NAV (X4) has significant impact on Sharpe Index (Y).

a = 5% Statistic Test :

thit " ЗД

independent degree = n-k-1

Test Criteria: 1. Accept Ho if -t table < t test < t table

2. Reject Ho if t test < -t table or t test > t table The result of T-Test computed by SPSS is presented on the following table.

Table 4 Hypothesis test (T-Test)

Variables t test df t table Sig. Keterangan Conclusion

Xi -0,665 0,506 Ho is accepted not significant

X2 -1,021 -0,990 924 ±1,963 0,308 Ho is accepted not significant

X3 0,323 Ho is accepted not significant

X3 -2,542 0,011 Ho is rejected significant

Based on the table above, this research can see that:

• Variable Xi has -t test value which is higher than -t table value. Because the value of -t test (-0,665) > -t table (1,963), then Ho is accepted. Therefore, it can be concluded that partially there is NO significant impact of company age (Xi) on Sharpe Index (Y).

• Variable X2 has -t test value which is higher than -t table value. Because the value of -t test (-1,021) > -t table (1,963), then Ho is accepted. Thus, it can be inferred that partially there is NO significant impact of specialization (X2) on Sharpe Index (Y).

• Variable X3 has -t test value which is higher than -t table value. Because the value of -t test (-0,990) > -t table (1,963), then Ho is accepted. Consequently, it can be concluded that partially there is NO significant impact of affiliation (X3) on Sharpe Index (Y).

• Variable X4 has -t test value which is lower than -t table value. Since the t test (-2,542) < -t table (-1,963), then Ho is rejected. Hence, it can be inferred that partially there is NO significant impact of Total NAV (X4) on Sharpe Index (Y).

3.1.3. Multiple Correlation Analysis

To determine the simultaneous correlation between company age (Xi), Specialization (X2), Affiliation (X3) and Total NAV (X4) on the Sharpe Index (Y), this research can perform multiple correlation analysis (R).

Table 5 Correlation Analysis

Model R R Square Adjusted R Square Std. Error of the Estimate

1 ,088a ,008 ,003 1,07374

a. Predictors: (Constant), total NAV, afiliasi, spesialisasi, umur perusahaan

Based on the output of SPSS software data processing this research can obtain that the value of correlation coefficient (R) is 0,088. It shows that there is very low correlation between company age (X^, specialization (X2), affiliation (X3) and Total NAV (X4) on the Sharpe Index (Y).

3.1.4. Determination Coefficient

The impact of company age (Xi), specialization (X2), affiliation (X3) and total NAV (X4) on the Sharpe Index (Y) is represented by determination coefficient calculated by the following formula: KD = R2 x 100%

= (0,088)2 x 100% = 0,8%

In other words, variables of company age (X1), specialization (X2), affiliation (X3) and Total NAV (X4) have an impact of 0,8% on the Sharpe Index. While the rest 99,2% of Sharpe Index can be explained by other variables which are not studied.

3.2. Analysis of Sharpe Ratio

Based on the result of MS Excel data processing, this research can see there are 5 Equity mutual funds having negative Sharpe Ratio. It implies that with certain risks to bear, the return of Equity mutual funds cannot exceed the return gained from SUN (government bonds) which is considered as risk-free or independent risk. It also implies that there are some Equity mutual funds which performances are still not too good.

Table 6 Sharpe Ratio

No Name of Equity Mutual Funds Overall Sharpe Index

1 Axa Citradinamis -1.74%

2 Batavia Dana Saham Optimal -0.73%

3 Batavia Dana Saham 3.77%

4 BNP Paribas Ekuitas 3.36%

5 BNP Paribas Pesona 3.60%

6 CIMB-Principal Equity Aggressive -3.06%

7 Dana Ekuitas Andalan 1.34%

8 Dana Ekuitas Prima 2.29%

9 Dana pratama ekuitas -1.23%

10 Danareksa mawar 1.11%

11 First State Indoequity Sectoral Fund 1.35%

12 Mandiri Investa Atractive -1.95%

13 Manulife Saham Andalan 1.60%

14 Panin Dana Maksima 11.16%

15 Pratama Saham 4.12%

16 Rencana Cerdas 0.06%

17 Schroder Dana Istimewa 5.37%

18 Schroder Dana Prestasi Plus 1.29%

19 Trim Capital 1.29%

20 IHSG 2.26%

Based on those 19 Equity mutual funds to be researched, there are 14 Equity mutual funds having positive Sharpe ratio. It implies that most Equity mutual funds studied have good performances. From these positive Sharpe-ratio Equity mutual funds, there are 7 Equity mutual funds having Sharpe ratio above Sharpe ratio of IHSG. It also implies that, with a certain risks to bear by investor, the return given by these 7 Equity mutual funds are better than those given by IHSG.

4. Conclusion

The objective of this research is to test whether there is any impact of Mutual fund age, specialization of investment manager, affiliation companies, and Net Asset Value (NAV) of Equity mutual fund on the performances of Equity mutual fund reflected in Sharpe ratio. Furthermore, the research is also intended to test whether the performances of Equity mutual fund can go beyond IHSG (stock price index).

Based on the overall hypothesis test (F-Test), this research can conclude that the age of Mutual fund company, specialization of investment manager, affiliation company, as well a NAV of Equity mutual fund do not have significant impact on the performances on Equity mutual fund. Based on the partial hypothesis test (T-Test), this research can also infer that the age of Mutual fund company, specialization of investment manager, and affiliation company do not have any impact (no significance) on the performances of Equity mutual fund, whereas its NAV of Equity mutual fund have significant impact on the performances of Equity mutual fund.

Based on multiple correlation analysis, this researchcan infer that there is only very low correlation between age of Mutual fund company, specialization of investment manager, affiliation company, and NAV of Equity mutual fund and the performances of Equity mutual fund. Based on the determination coefficient, this researchcan know that age of Mutual fund company, specialization of investment manager, affiliation company, and NAV of Equity mutual fund have an impact of 0,8% on the performances of Equity mutual fund. It implies that that the four factors to be researced have very little impact on the performances of Equity mutual fund.

Based ont the Sharpe test, there are 7 Equity mutual fund having Sharpe ratio beyond that of IHSG, i.e. Batavia Dana Saham, BNP Paribas Ekuitas, BNP Paribas Pesona, Dana Ekuitas Prima, Panin Dana Maksima, Pratama

Saham, and Schroder Dana Istimewa. Based on Sharpe ratio, this researchcan know that the highest value of Sharpe ratio is 11.16% while the the lowest one is -3.06%.

So, when entrepreneurs or owners of SMEs can use this investment strategy, they can gain more profit than put their fund on cash or savings.

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