1. Index Fund returns v Closet index mutual funds
MBA 512- Dr Edmonds
Summer 2017
Brian Leemoon

2. Project overview Introduction to Mutual Funds Literature review
Data & Methodology
Data Analysis
Conclusion
Project overview

3. Introduction
A mutual fund is an investment vehicle that is derived from a pool of funds collected primarily from individual investors for the purpose of investing in securities such as stocks, and bonds. (Investopedia, n.d.).
Two types of mutual funds are index mutual funds that track the performance of a particular market index benchmark such as the S&P 500 index as closely as possible and actively managed mutual funds that try to outperform their benchmarks and peer group averages. (Vanguard Group Inc., n.d.).

4. Most experts agree than Index funds have both higher returns and lower fees than actively managed funds. However there is evidence that most highly active funds and funds with the highest management fees are exceptions.

5. Investor Allocation shift
Since 2015, there has been a seismic shift in investor allocation of funds, away from actively managed funds and into index funds. Blackrock estimate that “equity investments through index vehicles, … represent approximately 34% of global equity assets under management by external managers” Blackrock (2017). Index funds offer market-wide diversification, and low fund cost, due to operational simplicity.
The trend of lower fund costs has also been driven by regulation and transparency, with funds forced to report their fee structures and equity holdings

6. Index fund performance v managed mutual funds
Studies over the last two decades have also shown index fund performance beating actively managed mutual funds, and this has also been a key driver for the increased popularity of index funds.
Finally, diversification of equity funds via mutual funds is also encouraged by Modern Portfolio Theory (MPT), that states that it is not enough to look at the expected risk and return of one particular stock. By investing in more than one stock, an investor can reduce the riskiness of his portfolio Blackrock (2017).

7. Advantages of Index/ Active funds
Index Funds
Provide diversification
Lower costs
Target the desired market
Are less risky & provide superior funds
Active mutual funds
Provide diversification & Choice
Can provide higher returns (Highly active funds)
Can reduce overall risk as part of a portfolio

8. What are Closet Index funds and why they matter
Closet Index funds appear to be active mutual funds and charge commensurate management charges. However the bulk of the funds are invested in index equivalents and a smaller portion actively traded.
Closet Index Mutual funds therefore potentially offer equal or sub par Index fund returns at higher costs.
Arriving at an approach to avoid or recognize potential closet index funds is a useful investor tool in the quest for higher returns

9. Morningstar Active/Passive Barometer Findings
Active/Passive Barometer finds that actively managed funds have generally underperformed their passive counterparts, especially over longer time horizons, and experienced higher mortality rates (i.e. many are merged or closed).
Failure tends to be positively correlated with fees (i.e. higher cost funds are more likely to underperform or be shuttered or merged away and lower-cost funds were likelier to survive and enjoyed greater odds of success). orningstarActive-PassiveBarometerJune2015.pdf
Our testing does not validate the 2nd point

10. Morningstar Active/Passive Barometer Findings
U.S. Large Caps In the U.S. large-blend category, more than three-quarters of active managers lagged the equal- weighted composite of their passive peers during the ten year period ending December 31, 2014.
The average active large-blend fund’s returns trailed return of the average passive by around 0.82% per year.
Only 50.2% of the actively managed U.S. large-blend funds that existed as of December 31, 2004 survived the entire ten-year period. Survivorship rates amongst the highest-cost quartile of actively-managed large-blend and large-growth funds were particularly poor. Nearly two-thirds of these funds did not survive over the trailing 10 years through December 2014
The average lowest-cost fund also generated 0.7% higher net-of-fee annualized returns than the average highest-cost fund (3.6% higher on an asset-weighted basis)

11. The two funds selected using our methodology had high costs but also comparatively high returns

12. Literature Review
It is well known that the equal weighting of the S&P 500 skews standard cap-weighted portfolios towards smaller sized firms and increases overall beta. (Dubil, March 2015, p. 49)
Dubil, R. (March 2015). How Dumb is smart Beta ?Analyzing the Growth of Fundamental Indexing . Journal of Financial planning ,

13. Holmes, M. (January 2007). Improved study finds Index management usually outperforms active management. Journal of financial planning ,
Several studies contain basic flaws …past studies did not make accurate asset class or style comparisons rather they compared all actively managed funds with one large cap blended index the S&P Another flaw involved the comparison of actively managed funds with indices rather than with index funds …many funds have not successfully replicated their index. (Holmes, January 2007)
We Include the S&P index and an index fund (Vanguard 500.). Compare to suspected closet index funds (Not asset class) for real world comparison.

14. Kaushik, A. , & Barnhart, S. (2009)
Kaushik, A., & Barnhart, S. (2009). Do mutual funds with few holdings outperform the market. Journal of Asset Management Vol. 9, 6, 398–408,
Following definitions in the financial press and in mutual fund-specific investment objective statements, we limit our investigation to funds that are concentrated in 10–30 stocks.
Our results indicate that, on average, fund portfolios with few holdings do not outperform the S&P 500 index. On average, small portfolios under-perform the market on a risk and investment style adjusted basis by about 2.40 per cent per year.
The two large cap funds selected had approx holdings. By comparison an S&P 500 fund will have 500 holdings

15. Haas, E. (2004). Mutual Fund Expense ratios :How high is too high
Haas, E. (2004). Mutual Fund Expense ratios :How high is too high. Journal of financial planning , p54-63.
One of the principal attractions of passively managed mutual funds (for example index funds) is their low expense ratios. All else being equal, a fund with lower expenses must have higher performance.
There is strong evidence that there exists a significant negative correlation between expense ratio and performance for actively managed funds. Carhart (1997) estimated that, for every 100 basis points of expense ratio, performance decreased by 153 basis points. MalkieI (1995) found that 100 basis points of expense ratio decreased performance by 192 basis points.

16. 1
Fama and French bring up the point that mutual funds do not easily disclose their trading (Share purchase & Sales costs) 2
Funds do not report trading costs, & estimates are subject to large errors. Trading costs are likely to vary across funds because of differences in style trading skill, and timing 3
Useful in deriving the Null Hypothesis: “active mutual funds do not produce gross returns above (or below) those of passive benchmarks. “
Implication consider excluding loading costs. Gross returns
Implication, review to assit crafting in Hypothesis statement
Fama, E., & French, K. (2010). Luck versus Skill in the Cross-Section of Mutual Fund Returns. Retrieved from The Journal of Finance, 65(5), :

17. Research Overview & Methodology
An approach outlined by Huebscher (2017) was used to create a mutual fund screening tool to identify potential closet index mutual funds
Two funds identified by the Huebscher (2017) study were also tested along with the S&P 500 Vanguard Index fund for a total of 5 funds
Monthly pricing data was collected for 54 months for all 6 Funds and index.
A correlation study and regression analysis was used to determine the relationship between the Mutual fund and S&P 500 index. An R –sq score of above 0.95 was used as to determine whether we would classify the fund as a closet index fund. This means that 95% of the increase in the fund return is attributable/explained by a 1 unit increase in the S&P 500 index
The total 10 year average annual return gap between the closet mutual funds and the index was calculated to determine if the gap exceeded the annual management free.

18. Data Selection & Analysis
In this section, we describe our data selection
Basis of Mutual fund selection- How the funds were selected
Graph of annual performance
Correlation tests
Regression hypothesis testing
Hypothesis review
Data Selection & Analysis

19. Basis of Mutual fund selection
The data for this analysis was downloaded from Morningstar & Yahoo Finance. The criteria I used to identify those funds were the following:
The fund was classified by Morningstar as a U.S. large-cap fund (Blended) and had at least ten years of performance history and 10 years of the same management team. To ensure consistency of management and performance. Where more than one class of the same fund exist only one class was used.
The fund was not classified by Morningstar as an index fund
The sharpe ratio was at least 0.6 (Risk adjusted return). This was used to weed out funds with excessive risk variance.
The five-year average expense ratio was more than 1.4%, which is above the average expense ratio of all U.S. equity funds (0.70%).
The basis of selection was derived from the Huebscher (2016) and Holmes (2007) studies
Filtered from 1000 mutual funds, 5 mutual funds that meet all criteria.

20. Fund Category is Large Cap US equity, Blended , Growth Fundamental & dividend. High Expense ratio (Compared to Average 0.75 or less). Large fund size over $20, Billion. Neutral Sharpe ratio. (Risk adjusted return ratio)
Iterations of fund size were performed until the final 5 funds were reached (Down from over 1000 funds). This resulted in 2 usable mutual funds (As the others were classes of the same funds). 2 Mutual funds from the Huebscher 2016 study were selected along with the 5th fund the Vanguard S&P 500 Index fund

21. Total Returns %
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
YTD
10 year Average Return
Last 5 Years average return
Included Annual Exp
Gross 5 Year after mngt fee ad back
R-Sq Value
S&P 500 TR USD
5.49
-37
26.46
15.06
2.11 16
32.39
13.69
1.38
11.96
11.59
8.754
14.202
VFINX
5.39
-37.02
26.49
14.91
1.97
15.82
32.18
13.51
1.25
11.82
11.49
8.632
14.05
0.18
14.23
100%
AFICX
12.65
-40.16
32.26
13.13
-2.67
16.21
30.45
8.08
2.56
11.65
12.39
8.416
13.026
1.42
14.446
95.2%
ETTGX
4.32
-33.04
22.79
12.42
0.42
15.05
31.92
12.33
2.15
8.68
10.97
7.704
13.21
0.847
14.057
98.3%
CICCX
4.99
-35.31
26.09
9.91
-2.62
14.59
31.29
11.13
-2.3
13.61
9.53
7.138
12.652
1.47
14.122
93.4%
PLVIX
-3.76
-40.81
19.07
13.01
-2.92
15.91
31.56
12.4
-1.86
13.17
7.75
5.577
12.604
0.77
13.374
94.7%
Total returns do account for management, administrative, and 12b-1 fees and other costs automatically deducted from fund assets.
Total returns do not include purchase or sales fees. Source- Morningstar
Key
American Funds Fundamental Invs C
AFICX
American Funds Invmt Co of Amer 529C
CICCX
Principal Large Cap Value III Inst
PLVIX
Eaton Vance Tx-Mgd Growth 1.1 A
ETTGX
Vanguard 500 Index Investor
Over the last 10 and 5 year periods the index and VFNIX, the index mutual fund have out performed the suspected closet indexing mutual funds. Adding back the Gross management fees we see that the fund returns on three out of the 4 non index funds are similar to the index return. This is consistent with studies that have suggested that Closet indexing mutual funds have a lower return than index funds due to their management fees.

22. Mutual Fund performance (To July 31st 2017)
Visually just looking at the barchart, the S&P 500 index (Dark Blue) seems each year to be the best or 2nd best performing fund. Also mutual fund AFICX had two spectacular years 2007 and 2009.

23. Data Analysis

24. All 5 mutual funds have low p values (<0.05 alpha). We accept H1
Is there a relationship between the S&P 500 index and the mutual fund?
95% confidence
Ho rho correlation Coeff =0 (no correlation)
H1: rho Correlation Coeff not equal to 0 (correlation)
Assumptions: Continuous data, there are no significant outliers, variables approximately normally distributed

25. Suspected closet index fund
Index tracking Fund
Suspected closet index fund

26. Suspected closet index fund
There is sufficient evidence that there exists a linear relationship between each of the mutual funds: AFICX, CICCX, PLVIX, ETTGX and VFINX the S&P 500 index tracker as all Correlation coefficients were above We move on to compute the regression . Note in Minitab the p-value actually means p<0.0005, which is less than the cut off for statistical significance of p<0.05

27. Reject the Null. Accept the Alternative
Reject the Null. Accept the Alternative. There is a relationship between the S&P 500 index returns and AFICX.
Also AFIC is a closet index fund, as over 95% (R-sq) of changes in AFICZ can be explained by changes in the S&P 500 index

28. Regression –Hypothesis AFICX

29. CICCX
Histogram appears to be normally distributed
Reject the Null. Accept the Alternative. There is a relationship between the S&P 500 index returns and CICCX.
Also AFIC is a closet index fund, as over 95% (R-sq) of changes in AFICZ can be explained by changes in the S&P 500 index

30. Reject the Null. Accept the Alternative.
Regression –Hypothesis PLVIX
Reject the Null. Accept the Alternative.

31. Reject the Null. Accept the Alternative.
Regression –Hypothesis CCICX
Reject the Null. Accept the Alternative.

33. Reject the Null. Accept the Alternative.
Regression –Hypothesis ETTGX
Reject the Null. Accept the Alternative.

34. Reject the Null. Accept the Alternative
Reject the Null. Accept the Alternative. There is a relationship between the S&P 500 index returns and ETTGX.
Also ETTGX is a closet index fund, as over 98% (R-sq) of changes in ETTGX can be explained by changes in the S&P 500 index

35. The residuals do not look random
The residuals do not look random. (difference between the observed value of the dependent variable (y) and the predicted value (ŷ) )

36. Reject the Null. Accept the Alternative.
Regression –Hypothesis VFINX
Reject the Null. Accept the Alternative.

37. Original Hypothesis: Index funds (Vanguard 500 Index) exceed the returns on large closet index mutual funds due to lower fund charges.
Investment Industry moving away from actively managed funds to passive index funds.
Closet Index funds-achieve returns similar to those of their benchmark index, without exactly replicating the index.
Brian Leemoon MBA 512-Professor Edmonds

38. Null Hypothesis: There is no relationship between the S&P 500 Index and a closet index fund
Closet Index funds-achieve returns similar to those of their benchmark index, without exactly replicating the index.
Investment Industry moving away from actively managed funds to passive index funds.
Hypothesis changed, when it was realized that the Vanguard S&P 500 index fund itself might vary against the underlying index.
We use the Null hypothesis test and Alternative Hypothesis to establish whether there is a relationship between the Index and suspected closet index funds

39. Summary/ Outcomes
After a review of the literature, a methodology for closet index fund identification was developed.
There were several iterations of the Hypotheses as knowledge of the subject became deeper.
Mutual funds meeting set criteria were screened resulting in a total of 5 funds being analyzed against the S&P 500 index. There were 54 months of data x 6 funds
The analysis revealed that there was a high correlation to the S&P 500 for each of the five funds, well into the range, 0.70 is considered is strong)
Using regression analysis we were able to validate the variation in each fund is between 93%-99%, explained by changes in the S&P 500 index
We establish as rule from the regression analysis that funds with R-Sq of >=95% are closet index funds as 95% of their varation can be explained by movement in th eS&P 500 index.
We had sufficient evidence to reject the null hypothesis. That there was no relationship between the S&P 500 index and the selected mutual funds.

40. Summary of Mutual funds performance and R sq values
Use R-Sq >= 95% as the cut off point, all funds above this level are closet index funds
We establish that 3 of the funds with R-sq values above 95% are closet index funds

41. Conclusions/ Further work
It was surprising that after adding back the annual average Gross management fees to arrive at each funds Gross annual return we see that the fund returns on three out of the 4 non index funds are slightly better than the index total return. This results tend to support other studies that have indicated that index funds exceed the returns on Closet index funds due to lower fund charges.
More mutual funds can be tested for their correlation to the Vanguard S&P 500 by reducing the mutual fund screener fund size. The objective would be to identify mutual funds with high returns that do not correlate or have low correlation to the S&P 500 index. This would indicate funds that are not closet index funds.
We were able to detect potential closet index funds using criteria from the available literature. And we were able to use statistical testing to validate which suspected funds were in our opinion closet index funds. Finally we established a threshold of R sq 95% as the “cut off rule”.

42. Final thoughts active and passive assets are both necessary
Most traditional portfolios contain an active component and a passive component. Stock purchases are based on expectations of an abnormal return, and enter the active part of a portfolio. Once the market accepts the investor's point of view, with the market price meeting shareholder expectations the asset is not immediately sold but continues to be held at least until a better investment is identified. Assets held beyond this point can be considered to comprise the passive part of his portfolio.
Viewpoint, E. (MAY-JUNE 1976). Index Funds and Active Portfolio Management. FINANCIAL ANALYSTS JOURNAL . Retrieved from Index Funds and Active Portfolio Management

43. Thank You

44. Bibliography
Anderson, T. (2015, June 26). Index funds trounce actively managed funds: Study. Retrieved from CNBC.com:
Brown, J. (2016, April 14). Do Actively Managed Funds Really Pay Off for Investors? Retrieved from USnews.com: pay-off-for-investors
Budiono, D. (2009, August). The Analysis of Mutual Fund Performance Evidence from U.S. Equity Mutual Funds. Retrieved from Erasmus Research Institute of Management:
Chang, C. E., & Krueger, T. (December 2015). Do Fundamental Index funds outperform Traditional Index funds? Journal of financial planning,
Dubil, R. (March 2015). How Dumb is smart Beta ?Analyzing the Growth of Fundamental Indexing . Journal of Financial planning ,
Fama, E., & French, K. (2010). Luck versus Skill in the Cross-Section of Mutual Fund Returns. Retrieved from The Journal of Finance, 65(5), :
Haas, E. (2004). Mutual Fund Expense ratios :How high is too high. Journal of financial planning ,

45. Bibliography
Holmes, M. (January 2007). Improved study finds Index management usually outperforms active management. Journal of financial planning ,
Huebscher, R. (2016, 12 29). The 10 Largest Clost-Index funds. Retrieved from Advistor Perspectives:
Jagric, T., Podobnik, B., Strasek, S., & Jagric, V. (2007). Risk Adjusted performance of mutual funds some tests. South East Europe Journal of Economics,
Kaushik, A., & Barnhart, S. (2009). Do mutual funds with few holdings outperform the market. Journal of Asset Management Vol. 9, 6, 398–408,
Ptajisto, A. (2013). Active share and mutual fund performance Financial Analysts Journal, Volume 69 Number 4. Retrieved from Active Share Mutual fund performance.
Umemoto, A. M. (2006, January 21st). Journal of Financial Service Professionals . Retrieved from
Vanguard Group Inc. (n.d.). Retrieved from Compare index vs. actively managed funds:
Viewpoint, E. (MAY-JUNE 1976). Index Funds and Active Portfolio Management. FINANCIAL ANALYSTS JOURNAL . Retrieved from Index Funds and Active Portfolio Management