Funciones y medidas de control interno en una institución en el área de

This thesis has examined the performance of the U.S.-domiciled diversified equity mutual funds, their expense ratios and the relation between them. It distinguishes itself by using comprehensive and integrated approach to the examination of fund performance. In addition to using more recent survivor-bias-free data which covers the period of the extensive expansion in mutual fund industry, I also used three models to assess mutual fund performance: CAPM, Fama- French (1993) three-factor model and Carhart’s (1997) four-factor model. Examination includes the division of my sample into three periods and division into seven different investment objective groups. I show that each additional factor in the models stated above explains the variation in the returns better than the previous, for instance the intercept from one-factor model changes its sign from positive to negative with the employment of a more comprehensive model. I also update the existing literature by showing not only the relation between before-fee performance and expenses but also the relation between after-fee performance and expense ratio.

I document that, on average, domestic diversified equity mutual funds underperform compared to the market. I use the CRSP value-weighted market portfolio consisting of all U.S. companies listed on the NYSE, AMEX and NASDAQ which allows for the inclusion of more companies, but also corrects for the possible biases due to a benchmark error. Moreover, this underperformance only aggravates in the later period. Important conclusion based on my analysis is that there is a significant variation in abnormal return between investments objectives specified.

My results also demonstrate that there is negative relation between after-fee performance and expense ratio. I also support this finding by examining the determinants of the expense ratio and including performance variable itself. The coefficient for performance survives the robustness check and is negative and statistically significant. In many aspects my findings are similar to the previous studies discussed in this paper. The signs of the turnover, size and performance are in line with them. I also introduce the variable of the volatility of the monthly fund returns and it is positive and significant in all of the regressions employed. Suggesting that, on average, funds with high expense ratios experience higher variability in their returns.

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However, in the age variable did not survive the robustness check and the result contradicts the finding of Chance and Ferris (1991) who found negative effect of the age.

A possible problem with my research can be that the CRSP database may have an omission bias and thus it imposes limitation on my study and results produced. According Elton et al. (2001) in spite of the fact that CRSP mutual fund database includes almost all the funds in existence during the period of investigation, the return data is missing for some of them and their fund characteristics differ from those in the general population. Thus, by dropping these funds from my sample might result in upward bias in the result. Secondly, there can also be a problem of the performance-attribution model, since estimated risk-adjusted returns contain funds’ true abnormal return but they also include estimation error. Such as for example the residuals of the performance estimation may not be correct and thus it can affect my result by decreasing the probability of finding significant relationship.

A further research can be conducted on the effect on the age on the expense ratio. In two of the regressions employed the coefficient for it was negative and significant. However, when accounting for possible serial correlation of the residuals, the age variable changes it sign and proposes an interesting fact. This phenomenon can be further investigated in the papers to follow. Moreover, a further study can also be conducted on the effect of different fees and charges on the performance. There is no uniform way of calculating the loads and incorporating them in the “overall” expense ratio; it can also be a challenging topic to do a research on.

I showed that investors are better off choosing the funds with lower expense ratio, since beating a market is not an easy endeavor incurring extra costs while receiving the same or inferior return does not seem to be a sensible decision. However, the absence of any fees and too low expense ratios cannot be and should not be interpreted as a sign of a superior performance.

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References

Berk, J.B., & Green, R.C. (2004). Mutual fund flows and performance in rational markets. Journal of Political Economy, 112, 1269-1295.

Carhart, M.M. (1997). On persistence in mutual fund performance. Journal of Finance, 52(1), 57-82.

Chance, D., & Ferris, S. (1991). Mutual fund distribution fees: an empirical analysis of the impact of deregulation. Journal of Financial Services Research, 5, 25–42.

Dellva, W.L., & Olson, G.T. (1998). The relationship between mutual fund fees and expenses and their effects on performance. The Financial Review, 33, 85-104.

Elton, E.J., Gruber, J., & Blake, C.R. (2001). A first look at the accuracy of CRSP mutual fund database and a comparison of the CRSP and Morningstar mutual fund databases. Journal of Finance, 56, 2415–2430.

Fama, E.F., & French, K.R. (1993). Common risk factors in the returns on stocks and bonds. Journal of Financial Economics, 33, 3—56.

Ferris S. P., & Chance, D. M. (1987).The effect of 12b-1 plans on mutual expense ratios: a note. Journal of Finance, 42, 1077-1082.

Gil-Bazo, J. & Ruiz-Verdu, P. (2009). The relation between price and performance in the mutual fund industry. Journal of Finance, 64, 2153–2183.

Goetzmann, W.N. & Ibbotson, R.G. (1994). Do winners repeat? Patterns in mutual fund performance. Journal of Portfolio Management, 20, 9–17.

Grinblatt, M., & Titman, S. (1992). The persistence of mutual fund performance. Journal of Finance, 47, 1977–1984.

Investment Company Institute. (2013). Investment Company Fact Book. Washington DC. Investment Company Institute.

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Ippolito, R. (1989). Efficiency with costly information: a study of mutual fund performance, 1965-1984. The Quarterly Journal of Economics, 104, 1–23.

Jensen, M.C. (1968). The performance of mutual funds in the period 1945-1964. Journal of Finance, 23, 389–446.

Kennickell, A.B.,Starr-McCluer, M., & Surette B.J. (2000). Recent Changes in U.S. Family Finances: Results from the 1998 Survey of Consumer Finances. Federal Reserve Bulletin 86, 1-29.

Laderman, J., & Smith G. (1993). The power mutual funds. Business Week, 18, 62–68.

Malhotra, D.K., & McLeod R.W. (1997). An empirical analysis of mutual fund expenses. Journal of Financial Research, 20, 175–190.

McLeod R.W., & Malhotra, D.K. (1994). A re-examination of the effect of 12b-1 plans onmutual fund expense ratios. Journal of Financial Research, 17, 231–240.

Peterson, M.A. (2009). Estimating standard errors in finance panel data sets: Comparing approaches. Review of Financial Studies, 22, 435–480.

Sharpe, W. F. (1966). Mutual fund performance. Journal of Business, 39, 119–138.

Wermers, R. (2000). Mutual fund performance: An empirical decomposition into stock-picking talent, transaction costs, and expenses. Journal of Finance, 55, 1655–1703.

White, H. (1980). A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica, 48, 817–838.

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Appendix

Table 6 presents the results of equation (4) with an only exception that risk-adjusted return is estimated using Fama-French (1993) three-factor model. As it can be seen from the Panel A, in comparison with the four-factor alpha, the slope coefficient is 0.937 which less than 0.97 from the Table 4. This indicates that the relation is further from a unit slope. Reduced R- squared also points at the fact that the four-factor model better explains the relation between before-fee risk-adjusted return and expense ratio. Slope coefficients estimated by using both White (1980) heterokedasticity-robust standard errors and clustering by time yield statistically significant results.

Slope coefficient in Panel B is twice as negative as in the Panel B of the Table 4, this is another evidence of the a bigger explanatory power of the four-factor model, since it entails an additional factor which accounts for passive investment strategies followed by fund managers. Moreover, the momentum factor also erodes the significance of the slope coefficient estimated with the standard errors clustered by time.

Risk-adjusted

Performance Standard Errors Coefficient Constant Adj. R-sq

Fama-French White 0.937*** 0.001*** 0.350

0.0033 0.0001

Fama-French Clustered by time 0.937*** 0.001*** 0.350

0.0195 0.0003

Fama-French White -0.063*** 0.001*** 0.107

0.0033 0.0001

Fama-French Clustered by time -0.063*** 0.001*** 0.107

0.0195 0.0003

Panel A. Before-fee risk-adjusted return

Panel B. After-fee risk-adjusted return TABLE 6. Before-Fee and After-Fee Performance and Expense Ratios

The table shows estimated slope coefficients and constants for the OLS regressions of funds' yearly before-fee and after-fee risk-adjusted risk-adjusted return on yearly expense ratios from January 1999 and December 2012. Risk-adjusted performance is estimated using 3 factor model. Standard errors are reported below the coefficients and adjusted R-squared statistics in decimal form. *,**,*** indicate statistical significance at 10%, 5% and 1% levels respectively. The number of observations is 396038.

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Table 7 presents some facts about my sample with the division to the funds that were already non-existent or closed during my observation period and the funds still operating in the industry. As we can see from the table, one of the main striking facts is that dead funds had significantly higher expense ratio which could have been a driving force towards the closure of these funds. Moreover, these funds also had significantly lower risk-adjusted return, another important distinction. Funds that ceased to exist also had higher turnover, and what is more interesting they charged lower management fees which are used exclusively for the portfolio management. Overall, I think this table provides extensive summary of the funds and presents possible reasons for their closure.

Obs. Dead Expense Ratio

(%) 12b-1 (%) Management fee (%) TNA ($ mln) Turnover (%) Alpha

156392 Yes 1.84% 0.67% 0.31% 131.20 99.49% -0.14%

239646 No 1.70% 0.64% 0.61% 551.47 82.85% -0.04%

0.14%*** 0.03%*** -0.30%*** -420.27*** 16.64%*** -0.09%***

84.68 23.95 -16.64 -55.66 59.64 -37.13

TABLE 7. Differences between surviving and non-surviving funds

Difference t-test

The tables demonstrates a summary statistics that distinguishes between the funds which were still in existence and those that ceased to exist in the sampling period. It presents a number of observations in each category, dead variable represents if the fund was operating or not. Expense ratio, 12b-1 fee, management fee are mean percentages of total assets under management. TNA stands for the size of the funds (in millions of dollars), alpha is a risk-adjusted return from a four-factor model, turnover is the percentage of the fund assets turned over. T-statistics is presented below the difference line. *,**,*** indicate statistical significance at 10%, 5% and 1% levels respectively. Number of observations is 396038.

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Table 8 is a summary statistics of the funds charging their clients with distribution fees represented with the presence of 12b-1 fee. We can see that these funds had much higher expense ratio and the difference between these 2 categories of the funds is statistically significant at 1% level, this fact alone contradicts the arguments of the proponents of this fee. Another fact which is in stark contrast with the supporters of this fee is that the size of the funds charging this fee is smaller. Funds with 12b-1 also produce both lower raw and risk-adjusted return, which of course should be taken into account. However, the problem with these results is that the fraction of the funds not charging this fee is much smaller and this can affect the results presented.

Obs. 12b-1 Expense Ratio _(%) Management _{fee (%)} TNA ($ mln) Turnover (%) mret (%) Alpha

392706 Yes 1.76% 0.49% 377.04 89.37% 0.40% -0.08%

3332 No 1.13% 0.70% 1383.99 94.72% 1.89% 0.09%

0.63%*** -0.21%** -1006.94*** -5.35%*** -1.49%*** -0.17%***

69.07 -2.22 -24.84 -3.56 -16.14 -12.72

alpha is a risk-adjusted return from a four-factor model, turnover is the percentage of the fund assets turned over, mret is an average monthly return. T-statistics is presented below the difference line. *,**,*** indicate statistical significance at 10%, 5% and 1% levels respectively. Number of observations is 396038.

Difference

t-test

percentages of total assets under management. TNA stands for the size of the funds (in millions of dollars),

TABLE 8. Differences between funds based on the presence of 12b-1 plan

The tables demonstrates a summary statistics that distinguishes between the funds which charge 12b-1 fee and those who do not in the sampling period. It presents a number of observations in each category 12b-1 variable represents if the fund had this charge or not. Expense ratio, management fee are mean