“Factors influencing equity fund performance: evidence from Indonesia”

This study aims to discover the factors that affect equity fund performance in compa- nies listed on the Indonesia Stock Exchange (IDX) during 2015–2018. This research is quantitative. Past performance, stock selection skills, market timing abilities, fund size, fund age are independent variables, while fund performance is the dependent variable. The population in this study was 73 equity funds. A total of 21 equity funds were selected as the sample by the purposive sampling method. The analytical method used is panel data regression analysis using the EViews program. Hypotheses were tested using a t -test with a significance level of alpha 0.05. The results show that equity fund past performance, stock selection skill, market timing ability, fund size, fund age and IDX composite index simultaneously have a significant effect on equity fund performance. Stock selection skill and IDX composite index partially have a positive and significant effect on equity fund performance. However, past performance, market timing ability, fund size and fund age have no positive and significant effect on equity fund performance. growth included the number of mutual fund products, Net Asset Value (NAV) of mutual fund, and mutual fund participation units. In 2014, there were 894 mutual fund products with NAV of IDR 241,571 trillion and participation units of 142.73 billion, whereas in 2018, there were 2,099 total mutual fund products, NAV of IDR 505,390 trillion, and investment units amount-ing to IDR 373.75 billion. However, if we pay attention to mutual fund returns, there is a decline.


INTRODUCTION
Investment in mutual fund is the right step for people who want to start investing in the capital market because it is easier and inexpensive. However, the mutual fund is not always efficient (Khorana, Servaes, & Tu fa no, 2005). Mutual fund is a opportunity for managing the fund for the public to invest in investment instruments available in the capital market by buying participation units. These funds are then managed by investment managers (IM) into investment portfolios, whether in the form of shares, bonds, money markets, or other securities.
The data from the Financial Services Authority regarding the development of mutual funds in Indonesia always experience growth from year to year starting from 2014-2018. The growth included the number of mutual fund products, Net Asset Value (NAV) of mutual fund, and mutual fund participation units. In 2014, there were 894 mutual fund products with NAV of IDR 241,571 trillion and participation units of 142.73 billion, whereas in 2018, there were 2,099 total mutual fund products, NAV of IDR 505,390 trillion, and investment units amounting to IDR 373.75 billion. However, if we pay attention to mutual fund returns, there is a decline.
Mutual fund decreased quite sharply in 2018. Rate of return reached its highest point in 2017 of IDR 35.06 trillion in the past five years. However, in the following year, the rate of return has decreased and reached its lowest point of IDR 10.47 trillion in the last five years. This shows an imbalance between the development of mutual fund management and returns. The increase in Net Asset Value (NAV) or Asset Under Management (AUM) is not accompanied by an increase in return. This is caused by the lack of investors' ability to choose the right mutual fund. On the other hand, the evaluation of mutual fund performance could not provide optimal benefits. Investors seem to only make an arbitrary assessment or gambling in investing. Interestingly, previous studies by Cuthbertson, Nitzsche, and O'Sullivan (2008) found some evidence that returns from mutual funds are not caused by stock selection skills of investment manager (IM); however, there are luck factors.
There are five types of mutual fund that are on the Indonesia Stock Exchange (IDX): equity fund, capital protected fund, fixed income fund, money market fund, and discretionary fund. Most investors who choose stock equity funds, but investors are less able to analyze mutual funds that have good prospects, as well as the lack of information obtained regarding the analysis of factors affecting mutual fund performance. To understand the factors that affect equity fund performance, in this research, equity past performance, stock selection skills, market timing ability, fund size, fund age and IDX composite index are used as predictor variables. This is because the mapping of previous studies obtained the gap phenomenon from the results of the study.
This research showed that stock selection skill plays an important role regarding the mutual fund performance. Manager expertise in the stock selection will determine the sustainability of the mutual fund itself. The rise of the IDX composite index means a capital market with high stock demand. Both of these can provide high return funds and also reduce the risk of default.

LITERATURE REVIEW
The performance of a portfolio cannot be enough just to pay attention to the level of return that the portfolio produces, but one must also pay attention to other factors such as the risk level of the portfolio. Some previous studies have examined the factors that affect mutual fund performance. Grinblatt and Titman (1992), Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Ben and Hellara (2011) have examined the relationship between mutual fund performance and past performance. Da, Gao, and Jagannathan (2010) and Nallareddy and Ogneva (2017) have examined the mutual fund performance and stock selection skills. Cuthbertson, Nitzsche, and O'Sullivan (2010), Sherman, O'Sullivan, and Gao (2017), and Tchamyou and Asongu (2017) have examined the relationship between mutual fund performance and market timing ability.
Several portfolio performance measures have included return and risk factors in their calculations, e.g., Sharpe ratio (Sharpe, 1966), Treynor-Mazuy measure (Treynor & Mazuy, 1966), and Jensen ratio (Jensen, 1968). Sharpe ratio is used to measure the equity fund performance in this research.
Sharpe ratio gives better appropriate measures for high return and all portfolio than others (Scholz & Wilkens, 2005). A higher portfolio Sharpe ratio shows better performance than the others. The Sharpe method is formulated as follows: where rd S is Sharpe ratio value, rd R is return of portfolio, rf R is risk-free rate, σ is standard deviation of the portfolio excess return.
Equity fund past performance will affect future performance because investment managers obtained data and information and then take several actions to improve future equity fund performance ( deviation of the portfolio excess return past period. Stock selection skill is the ability of IM to pick the right stocks to be included in their portfolio and has the potential to produce returns as expected by investors. Stock selection skill components play an important role in growth-oriented funds and income-oriented funds (Da et al., 2010). Previous studies by Nallareddy and Ogneva (2017) have shown that skilled investment manager can avoid investing in low-grade fundamental companies. Interestingly, previous studies by Hsu, Kalesnik, and Myers (2010) found the relationship between positive performance and stock picking-skills on top rank equity income, whereas no relationship was found among small equity funds. The stock selection skill model is developed by Trenor and Mazuy (1966), then, Henrikson and Merton (1981) developed another model. In this research, stock selection skill was calculated using the Treynor-Mazuy method (Treynor & Mazuy, 1966). To measure the ability of micro forecasting (stock selection) of investment managers, this can be seen through the value of .
α If the investment manager has ( ) 0, α > it means that investment manager has a superior selection ability, and vice versa, it means the inferior ability of stock selection.
This model also explains the manager's market timing ability. Previous studies by Cuthbertson et al. (2010) showed that just a small number have successfully implemented market timing ability among income equity in the UK. The research has the same results as the research conducted by Sherman et al. (2017) with Chinese mutual funds as the research object. In this study, we not only measure market timing ability but also examine their relationship with performance. Previous studies by Ferson and Mo (2016) stated that the IM performance depends on market timing, volatility timing, and security selection. Tchamyou and Asongu (2017) found that evidence of a consistent positive threshold of market volatility and return in market timing. The symbol of γ represents the investment manager's ability to perform market timing and is categorized as having this ability when γ is positive, this indicates that the investment manager produces an excess return on the investment fund portfolio that is higher than the market excess return, formulated as follows: where α is intercept, which shows the indications regression coefficient for excess market return or slope when the market falls (bearish), γ is regression coefficient, which indicates the market timing ability of the investment manager, p ε random error.
The company's total assets generally indicate the economies of scale. The size of the mutual fund will be represented in the total market capitalization of the investment fund. Mutual fund must reach a minimum fund size to gain sufficient returns for their transaction costs ( where Size is fund size, TNA is total net asset.
Many investors disagree that the age of the mutual fund reflects its performance. The longer the equity fund's life, the better the mutual fund performance. The old mutual fund products usually have also been tested for their performance even in difficult times. Some previous studies showed fund age have a significant effect on mutual fund performance (

METHODS
The independent variables used are past performance (X 1 ), stock selection skill (X 2 ), market timing ability (X 3 ), fund size (X 4 ), fund age (X 5 ), and IDX composite index (X 6 ). The dependent variable is equity fund performance (Y).
The data used are secondary data, i.e., financial statements that have been published in 2015-2018, monthly NAV, and costs. The sample was determined using the purposive sampling method. The criteria in determining the sample are as follows: (1) equity fund, which is active and available on IDX in 2015-2018, (2) mutual fund has some data requirements, e.g., prospectus data and monthly NAV for December 2015 -December 2018. Based on the criteria, 21 mutual funds were selected as the sample.

RESULT AND DISCUSSION
Descriptive statistics are shown in  Table 3 and Table 4. Based on EViews output for the F-Test in Table  3, which is statistically significant at probability 0.000 < 0.05. Value of F-statistic > F To test the effect of the independent variable on dependent variable partially, t-test was performed. The result of t-test is shown in Table 4. For H 1 , past performance prob. is 0.0008 < 0.05, t-statistic > t table (-3.4831 > 1.991). Past performance has a negative and significant effect on equity fund performance. H 1 is rejected. This result is the same as previous research by Berk and Green (2004). Information from past performance is unable to predict future returns; gathering information about performance is unnecessary. From this result, IM's should not be satisfied with past success. We found past performance is not able to reflect future performance.
For H 2 , stock selection skill prob. is 0.0000 < 0.05, t-statistic > t Stock selection skill of IM plays a crucial role in equity fund performance. IM with great selection will allocate assets in superior fundamentals companies or appropriate industrial sectors. Companies with inferior fundamentals will be able to avoid it. Moreover, IM invest not only for short-term returns but also for long-term returns.
For H 3 , market timing ability prob. is 0.1159 > 0.05, t-statistic < t Past performance is cannot reflect future performance. IM should not be highly satisfied with past performance. Superior performance in the past was not followed by better achievement in the following year. Stock selection skill plays a crucial role in achieving better performance of equity funds. IM must be able to select the right stocks, companies, or appropriate sectors to allocate funds so that the perfor-mance of equity funds always increases. IDX composite index movement affects overall equity fund performance. IM can take the opportunity from this fluctuation to review and reconsider its portfolio and ensure the appropriate asset allocation and fund strategy in the selection of equity fund in accordance with the characteristics and investment objectives of investors.   Note: Lagrange multiplier test is the third step. The result showed that Breusch-Pagan prob. is 0.0474, which means that random effect is better than fixed effect. Random effect selected as the best to estimate panel data regression.   Note: Jarque-Bera Probability is 0.186967 > 0.05. The data distribution is normal.