Do Better Educated Mutual Fund Managers Outperform Their Peers?
|
|
- Lily Carter
- 5 years ago
- Views:
Transcription
1 Do Better Educated Mutual Fund Managers Outperform Their Peers? By P.F. van Laarhoven Tilburg University School of Economics and Management Supervisor: A. Manconi Master s program in Finance Abstract I examine the relationship between managerial characteristics and mutual fund performance. Using a novel dataset of 2,807 US mutual fund managers, I test whether the managerial characteristics of the mutual fund manager in charge with a strong focus on education - are related to the performance and characteristics of the funds that she manages. I find that the quality of the undergraduate institution - measured by SAT scores, and the presence of specific degrees like having an MBA/CFA designation positively and predominantly statistical significantly influences the performance of the concerned mutual fund. I also find that managers that hold an MBA degree take on more idiosyncratic risk to outperform the market. On the other hand, this does not apply to managers that hold a CFA designation, who tend to be less exposed to idiosyncratic risk.
2 Table of Contents I. Introduction... 4 II Hypothesis Development... 7 II.I Literature review... 7 II.II Hypotheses... 9 H1 Mutual fund managers who attended higher and more education tend to earn higher excess returns H2 Better educated mutual fund managers tend to manage bigger firms which have more Investment Inflow H3 Mutual fund managers that hold a degree in finance or beta related studies tend to outperform degrees that are indirect related to the mutual fund industry H4 Education has an influence on the investment style of mutual fund managers H5 Managerial characteristics influence the extent to which mutual fund managers hold on systematic risk II. Data and methodology III.I Exogenous variables III.II CRSP Mutual Fund Information III.III Endogenous variables III.IV Summary statistics and Correlation Matrix III. Empirical results IV.I Simple Excess return OLS IV.III Risk Adjusted Performance Measures IV.IV Sharpe (1964), Fama-French (1992) and Carhart (1997) IV.V Education specific performance measures IV.VI Fama-French Factors OLS VI.VII Systematic and Idiosyncratic risk IV.VIII Endogeneity: Discussion IV. Conclusions V. References Articles Books VI. Appendix Table I Table II
3 Table III Table IV Table V Table VI Table VII Table VIII Table XI
4 I. Introduction Mutual funds or investment companies play an important role in the U.S. stock market. Nearly 25% of household financial assets consist of positions in these funds. There is, particularly in the U.S., a wide range of mutual fund operators. In light of the extant literature, it might come as a surprise that mutual funds are so popular among retail investors. Basically, at least since the work of Malkiel (1979), we have noticed that on average mutual funds do not beat the market, i.e. they do not outperform a diversified market index. He states in his classic finance book A Randow Walk Down Wall Street that asset prices follow a random walk and that investors therefore cannot outperform the market averages. However, (cf. Kacperczyk et al., 2005) find that at least some mutual funds are able to earn abnormal profits. The question if mutual funds can outperform their market averages is therefore an important and popular finance question, since positive risk-adjusted returns has implications for market efficiency. Besides Malkiel (1979) and Kacperczyk et al. (2005), other former studies tried to shed light on this question as well with mixed results. Where other studies in general tried to measure if the risk-adjusted return is positive from an investor prospective only, will this study follow another approach and look especially to the relationship between performance and managerial characteristics. Investors seem to seek for specific investment strategies to realize higher returns than the market will offer. CBS News (July 31, 2012) reported for instance that the endowments at Ivy League universities such as Yale and Harvard are exceptionally successful, causing many investors both individual and institutional to consider replicating their investment strategy. This development could perhaps clarify that managerial characteristics and especially education, has an influence on 4
5 the performance of investment entities. On the other hand, a recent article by Business Insider (April 17, 2014) reveals that having an MBA is a waste of money, since participants faces besides the huge tuition fees also the opportunity costs of not getting a full salary during that time. In this study, I try to look cross-sectionally at how performance of mutual funds is related to the concerning characteristics of the mutual fund manager. Hence, it is irrelevant for this study if the average risk-adjusted returns of the mutual funds within the sample are positive. I want to examine whether there do exist cross-sectional differences in performance by looking at multiple time periods for the same managers and mutual funds. For instance, when having an MBA predicts positively performance, then can this be in place even if all the funds within the sample have negative risk-adjusted performance, since managers who are holding an MBA degree will have on average less negative performance. I use a sample of 2,708 US mutual fund managers and try to look whether managerial characteristics are related to mutual fund performance. In addition to Chevalier and Ellison (1999a), I included several new educational variables to examine the effect on fund performance. I observe that educated managers (proxied by the presence of their degrees) are able to earn significantly higher risk-adjusted returns. This finding is not just statistically significant, but also economically relevant: one standard-deviation higher SAT sore of the manager s undergraduate institution (corresponding to the difference between Yale and Alfred University 1 ) is associated with higher alpha of one basis point per year. Furthermore, I document similar results to that of Gottesman and Morey (2006) regarding the relationship between fund size and having an MBA, since larger firms tend to hire non-mba managers. Besides, I find a strong negative relationship between gender and firm size as well as investment inflow. Female managers are less likely to manage a large 1 SAT score of respectively 2240 and
6 mutual fund and do have less investment inflow. Moreover, I have tried to analyse the investment strategies of mutual fund managers. I observe that managers that attend an undergraduate institution with lower requirements for admission, hence a higher admission rate, tend to load more on Small minus Big strategies. In addition to this, age and tenure seem to have a minor impact on different strategies. Where other studies like Chevalier and Ellison (1999a) report that older managers tend to use more momentum strategies, does it not seem to matter for this study. Finally, I find that managers that hold an MBA degree do take on more idiosyncratic or idiosyncratic risk to outperform the market. On the other hand, this does not count for managers that hold a CFA designation. They tend to hold on more systematic risk and less idiosyncratic risk. The remainder of the thesis proceeds as follows. In Section I is the Hypothesis Development formulated. The Data and Methodology is described in Section II. Section III presents the empirical results, where I have tried to examine the relationship between managerial characteristics and fund performance. In section IV are the conclusions drawn. Section V sums up a reference list and section VI contains the appendix where all the tables and results are presented. 6
7 II Hypothesis Development The rewarding and interest for mutual funds is actually quite odd since there is a lot of competition and the uncertainty about the future values of the investments exists largely. One of the oldest questions in finance (Jensen, 1968) is whether mutual funds do add value and if they can outperform passive benchmarks. II.I Literature review Former studies regarding fund performance have revealed several different outcomes, but in general we might say that mutual funds do not add value according to these papers. Jensen (1968) stated that the 115 mutual funds within their sample where not able to beat the, so called, buy-and-hold-strategy which indicates the index investors. They document very little evidence that any individual fund was able to outperform their passive benchmarks. Furthermore, these conclusions hold even when the funds gross returns of management expenses where measured, which means that they assumed that their management fee was zero and they only faces brokerage commissions. According to Gruber (1999) mutual funds offer on average a negative risk adjusted return and investors are better off by buying index funds, but since future performance are somewhat predictable from lagged performance, sophisticated investors are still interested. Wermers (2000) document that on the one hand mutual funds do outperform a broad market index. However, taken transactions and fees into account, they outperform with 1% per year comparing to the index. They reported their results over the period 1975 to 1994 and 7
8 stated that mutual funds held stock portfolios that outperform a broad benchmark index by 1.3 percent per year. 60 basis points are due to higher average returns, while 70 basis points are because of talents in picking stocks that beat their benchmark portfolios. On the other hand, when taken net returns into account, they underperformed the benchmark. This difference of 2.3% (-1% and +1.3%) is for 70 basis points duo to underperformance of nonstock holdings while the remaining 160 basis points are due to expenses and transaction costs. In addition, Ding, B., and R. Wermers (2009) find that experience and (advisor-level) stock picking track-record of a fund manager are correlated with following-year performance. Thereby, they document that larger boards are associated with better performance, when the manager has more than 10 year experience. Chevalier and Ellison (1995b) looked more to the characteristics of the fund itself. Contrary to these results, (cf. Kacperczyk et al., 2005) examined the relationship between industry concentration and the performance of actively managed U.S. mutual funds between 1984 and 1999 and they find, on average, that industry concentration performs better. Previous mentioned papers have examined if there is a possibility to outperform and if there is evidence for persistence over time. Regardless of whether it is, an interesting question that arises is where it comes from. Chevallier and Ellison (1999a) looked to the managerial characteristics instead of the fund. They document in their paper Are Some Mutual Funds Managers Better Than Others? Cross-Sectional Patterns in Behavior and Performance that higher education has a positive influence on fund performance. They used a sample of 492 managers who had sole responsibility for a growth or growth and income fund for at least some part of the
9 period. They gathered the majority of their data from Morningstar and used variables as managerial SAT scores, having an MBA or not, age and tenure to explain the variation in the mutual fund returns. First, they examined that higher SAT Scores (in this example 1355 or 1142) and having an MBA leads to higher simple excess returns of respectively 98.6 and 63.1 basis points. Secondly, they regress beta, log of assets, expense ratio% and turnover ratio on the latter variables and find among other that higher educated fund managers tend to manage higher beta funds. Therefore, a risk-adjusted test is also executed. Notably for this measure is that they reported a drop of the coefficient MBA from 0.63 to 0.04, indicating that the higher returns achieved by MBAs are essentially completely attributable to their taking on more systematic risk. Finally, their overall conclusions are that mutual funds managers, who attended more selective undergraduate institutions, seem to earn higher risk-adjusted returns. Golec (1996) shows in his paper The Effect of Mutual Fund Managers Characteristics on Their Portfolio Performance, Risk and Fees that a fund s performance, risk and fees are significantly impacted by a manager s characteristics. They document that investors can expect better risk-adjusted returns from younger managers with an MBA degree that have longer tenure at their funds. Furthermore, they examined that a large management fee signals superior investment skill which leads to better performance. II.II Hypotheses Concluding, this research will shed light on the question if these results are gathered by the manager of the fund or the fund itself. In comparison with, for instance, Chevalier and Ellison (1999a) this research will be an addition to the existence literature because it goes into more depth regarding to the differences in education. Besides higher education (having an MBA 9
10 degree or not), this study will focuses as well on broader education. This allows me to formulate the following hypothesis: H1 Mutual fund managers who attended higher and more education tend to earn higher excess returns. According to Bertrand and Schoar (2003), realizations of all investment, financing and other organizational strategy variables appear to systematically depend on the specific executives in charge. Therefore I want to measure the influence of managerial characteristics on fund characteristics. This enables me to formulate the next hypothesis: H2 Better educated mutual fund managers tend to manage bigger firms which have more Investment Inflow. Gottesman and Morey (2006) argue that following former studies students that attend liberal arts schools might have had more individual attention than students that went to larger, research-oriented institutions. Therefore, they include this independent variable in their study, to examine the influence of this difference. In addition to this, I would like to examine the influence of a having a different degree. This encourages me to formulate the following hypothesis: H3 Mutual fund managers that hold a degree in finance or beta related studies tend to outperform degrees that are indirect related to the mutual fund industry. H4 Education has an influence on the investment style of mutual fund managers. According to Chevalier (1999b), younger managers tend to hold less idiosyncratic risks and have more conventional portfolios. In this study, we would like to examine this further with the additional educational variables. Therefore, I have developed the following hypothesis: 10
11 H5 Managerial characteristics influence the extent to which mutual fund managers hold on systematic risk. II. Data and methodology The majority of the data that is used in this thesis is gathered via intensive online 2 data searching. In collaboration with four others students, we have created from a raw dataset of 27,707 mutual fund managers a unique file of 2,807 mutual fund managers with accompanying mutual funds. From this starting point we have searched for all kind of characteristics of the manager, with a strong focus on education, address details, (ex)-industry and further personal characteristics. From that point on, everyone worked independently on their thesis. As a matter of relevance, this study uses only the characteristics that are related to education with some additional control variables and therefore the following exogenous variables are included: III.I Exogenous variables Age: This variable is denoted in date of birth and is founded in 69% of the cases. In the case that it could not be found, an assumption is made with the tenure variable by subtracting 21 years from this variable. Tenure: This variable indicates the year in which they entered the industry of investing. This variable is founded in 81% of the cases. If it could not be found explicitly on the internet, the year when the degree is granted is denoted. In the case that it could not be 2 Examples of sources that frequently used are: Forbes, LinkedIn, Business Week, Edgar online (SEC filings), ZoomInfo, Morningstar, Intellius, mutual fund websites, The Economist, Yahoo Finance, Reuters, Bloomberg, CRSP Mutual, The Wallstreet Transcript. 11
12 found at all, an assumption is made with the age variable by adding 21 years up to this variable. Gender: A zero is listed when it concerned a man, while a 1 is listed when it concerned a female. This variable is founded in 100% of the cases. Bachelor institution: the name of the institution where the manager has received his bachelor is listed. This variable is founded in 84% of the cases. When the variable could not be found, an assumption is made that the information is not publicity available instead of the manager has no degree. In other words, I assume that all mutual fund managers have at least a bachelor degree. of the cases. Bachelor subject: the subject of the bachelor is listed. This variable is founded in 54% 2 nd bachelor, MSc, MA, MBA, CFA, CPA and PH.D.: A zero is listed when the concerning managers does not have one of these titles, while a 1 is listed when he/she has. These variables are founded respectively in 3%, 8%, 6%, 52%, 48%, 4% and 4% of the cases. For the name of the bachelor institution, I have added two additional proxies, since this variable consist of 632 unique universities: SAT scores: this variable might reflect the manager s ability effort, connection and/or the quality of his degree. The SAT 3 is a standardized test widely used for college admissions in the United States. This test consists of three sections (Mathematics, Writing and Critical Reading) where a score of can be obtained on each of the three sections (total ). Most universities report upper and lower bounds for all of the three sections, while some schools only report these bounds for the writing and mathematical section. 3 Data sources: and 12
13 The bounds are supposed to be constructed so that the middle of 50% of students attending the school lies between the upper and lower bounds. For instance, Harvard University and Princeton University report the following scores: Harvard University Princeton University SAT Math: 710/800 SAT Math: 690/800 SAT Critical reading: 700/800 SAT Critical reading: 680/800 SAT Writing: 710/800 For Harvard, the average of the bounds per section is taken, which results in a SAT score of 2260 for. For Princeton, the average of the bounds is taken, which results in In addition to set things equal, we have multiplied this score by 1.5 to get an estimator of the SAT score when the writing section was not missing, which results in a SAT score of This variable is founded in 92% of the cases. In 7% of the cases, the university is located outside the US and the university therefore didn t report a SAT score. The remaining 1% could not be found. Admission rate%: if publicity available, the admission rate% for all universities is listed. This variable is founded in 92% of the cases. III.II CRSP Mutual Fund Information As stated before, after removing all duplicates and keeping only unique mutual fund managers, 2,807 managers are left. The data file, containing these managers, is merged with a CRSP Mutual Fund Database 4 which contains information about mutual funds descriptive 4 Survivorship bias free. 13
14 information, monthly mutual fund returns and Fama-French factors for a chosen period of to III.III Endogenous variables In order to clarify the cross-sectional relationship between the managerial characteristics and mutual fund returns, I have calculated several measures which will be used as endogenous variables in this study. Simple excess return of the mutual fund is an endogenous variable that is calculated by subtracting the risk-free return (One Month Treasury Bill Rate) from the total return at the end of the month. Risk-adjusted return of the mutual fund is calculated by determining the alpha 6 that is generated by the manager in charge. Alpha is Jensen s measure to determine performance adjusted for systematic risk. It measures the portfolio return that is attributable to the manager s skill (or luck). In this study, alpha is calculated in three ways. First, alpha is calculated by using the Capital Asset Pricing Model 7 with the One Month Treasury Bill rate as risk-free rate and a value-weighed market index as the market portfolio. In addition to systematic risk, market capitalization, the book-to-market-ratio and past returns are taken into account since they have significant influence on explaining cross-sectional patterns in stock returns regarding the modern finance literature. The High minus Low (HML) portfolio is a zero-investment portfolio constructed by subtracting the returns of low book-to-market ratio stocks from the returns of high book-to-market ratio stocks. The Small minus Big (SMB) portfolio is a zero-investment portfolio constructed by subtracting the returns of large market capitalization firms from the stock returns of small market capitalization firms. These two 5 Since I capture with this time window all the data that is needed for my sample. 6 See Jensen (1968) 7 Equation to determine Alpha : (1) 14
15 additional portfolio s leave us the alpha according to Fama-French (1992) 8. Finally, the momentum (MOM) is added to calculate the alpha according to Carhart (1997) 9, which consists of a zero-investment portfolio constructed as the spread between the performance of stocks that are in the top 30 percent of returns in the 12 prior months and those that are in the bottom 30%. mutual fund. Investment inflows determines the total investment inflows by investors in (or out) the (4) Systematic risk is measured by beta. Systematic risk is the type of risk that is impossible to completely avoid. It cannot be mitigated through diversification. It is the risk that is inherent to the entire market segment. Idiosyncratic risk is measured by the residual variation in portfolio return after accounting for variation due to systematic risk. It measures the degree of portfolio diversification. Total Net Assets is measured by taking the logarithm of the Total Net Assets. It is included as a control variable for size. 8 (2) 9 (3) 15
16 III.IV Summary statistics and Correlation Matrix Table I lists the summary statistics for all the variables. We observe that the average beta is less than one (0.88) and that all the alphas are on average negative, which implies that the average mutual fund manager underperforms the market. Furthermore, we see that the average mutual fund manager is 57 year old, works for 32 years in the industry, holds an MBA (69%) and CFA designation (52%) and is a man (91%). Table II presents the correlation between the variables. The results indicate a strong negative correlation between SAT scores and Admission rate% of -0.89, which confirms according to ones expectations that higher SAT universities do allow less applicants. Furthermore, we see a correlation coefficient of between CFA and MBA, which means that having an MBA does according to my results not directly encourages to become a CFA. The correlation between having an MBA degree and SAT scores are positive (0.13). This implies that managers from higher educational prestige schools are more likely to become an MBA than managers from lower prestige schools. III. Empirical results My goal in this section is to explain whether mutual fund managers can influence the crosssectional distribution in mutual fund returns. IV.I Simple Excess return OLS Table III shows the first linear regression analysis where the simple excess return on a share is regressed on a set of manager characteristics that are representative for the average mutual fund manager. The dependent variable is the simple excess return of the mutual Fund, 16
17 which is regressed on different managerial characteristics, including the average SAT score of the managers undergraduate institution (divided by 100), a dummy variable that takes the value one if the manager has an MBA or CFA and zero otherwise, the manager s age and the managers tenure in investment years. 10 T-values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. The point estimates suggests that managers who have an MBA and CFA degree and who attended a higher SAT school earn on average higher returns, but none of the coefficients are statistically significant. This also applies to the age and tenure of the mutual fund manager. Furthermore, an increase in the admission rate% will lead on average to a decrease in the simple excess return of the mutual fund, which means that a manager who has attended a undergraduate institution which is easier to apply for, the simple excess return of the mutual fund will decrease. Again, the coefficient is not statistically significant. If we look besides statistical significance, to economic significance, we see quite similar results. has a mean of and, for instance, has a standard deviation of If we look to the estimator β of we see a coefficient of A one standard deviation increase in, i.e. = , will result in a change in the dependent variable of the average of the of = Relative to, this is a 0.082% increase. 10 Regression equation: (5) 17
18 IV.II Mutual Fund Characteristics and Fund Performance Table IV examines whether mutual fund manager characteristics are correlated with different characteristics of the mutual fund itself. In table IV the outcome of these regressions are tabulated and it shows in the first place that manages that attend a higher SAT undergraduate institution tend to manage larger funds which have more investment inflow. According to Chevalier and Ellison (1999a), I do find contrary results. They document that age and firm size are negatively significant related, while tenure and firm size are positively significant related. The impact of the manager s age on firm size is slightly negative and statistically significant at the 1% level, but the economic significance seems to be very low since the coefficient is almost zero. Furthermore, the relationship between tenure and firm size is statistically negatively related to firm size. Managers with more investment experience seem to manage smaller funds. Regarding the relationship between MBA and firm size, I do find similar results to that of Gottesman and Morey (2006), since larger firms tend to hire non- MBA managers. This coefficient is statistically significant at the 1% level. Finally, we see a strong negative relationship between gender and both endogenous variables. Female managers are less likely to manage a large mutual fund and do have less investment inflow. Both coefficients are highly statistically significant. IV.III Risk Adjusted Performance Measures Besides the simple excess return as a dependent variable, I want to look to a risk-adjusted performance measure to determine more accurate the relationship between manager characteristics and mutual fund performance. Table V includes the CAPM alpha 11 as dependent variable. First, in row 1, the same regression equation is presented as in table III for comparison. In row 2, CAPM alpha is regressed on the managerial characteristics. We observe that all the variables except for tenure move from non-significant to highly significant 11 See equation (3). 18
19 at the 1% level. The causal impact is similar to that of row 1. Managers that hold an MBA degree tend to generate a positive alpha, all else equal. Row 3 and 4 show an OLS where all the exogenous variables used in this study are included and log of assets and investment inflow are added as control variables. The added variables do not seem to explain the variation in the dependent variables, since almost all coefficients are quite similar to zero. IV.IV Sharpe (1964), Fama-French (1992) and Carhart (1997) Table VI compares the regression equations for the three different alphas. Besides the alpha according to Sharpe (1964), the other measures of alpha are included 12. The Fama-French factors tend to explain the most variability of the data around its mean, since this OLS regression has the highest R-square (0.06). Furthermore, the coefficients are quite similar to each other. Each row indicates that a manager that holds an MBA seems to outperform a non- MBA manager based on the dependent variable alpha. One possible simple explanation for this could be that managers that hold an MBA are more intelligent than other managers. Another possible explanation is, that these managers do have better connections due to their education and are therefore exposed to more information than other non-mba managers. IV.V Education specific performance measures Table VII examines more education specific performance measures of mutual funds. The bachelor subject of the manager s undergraduate institution is taken into account and the simple excess return and CAPM alpha are regressed on these characteristics. One might expect that mutual fund managers that hold a degree in Finance would be better informed regarding investments than a manager that holds a degree in History. What we see, for instance, is that a manager who holds a bachelor degree in Social Sciences seems to 12 See equation (1), (2) and (3) 19
20 underperform a manager who holds a bachelor degree in Economics/Finance/Business/Accounting/Marketing. The coefficient is significant at the 1% level. Though, the economic significance seems not to be in place on the other hand. Generally speaking, we do not observe a strong relationship between this education variable and fund performance, since most variables are not statistical or economic significant. IV.VI Fama-French Factors OLS Table VIII shows the regression coefficients of the Fama-French factor weights on the managerial characteristics. As mentioned before, recent finance literature has described that besides market risk, three other portfolios might determine the return on investment. Fama- French (1992) explored that the stocks of small firms have consistently outperformed the stocks of large firms. They created a portfolio where stocks of large firms are sold and stock of small firms are bought, which we refer to as the small minus big portfolio. They stated also that the shares of firms with a high book to value of assets divided by market value of assets outperform the market portfolio. They refer to this portfolio as the high minus low portfolio, where shares of high book-to-market stocks are bought and of low book-to-market stocks are sold. Carhart (1997) adds a fourth portfolio, where stocks of last year s outperformers are bought and stocks of last year s underperformers are sold, which we refer to as the momentum. The table tells us that managers that attend an undergraduate institution with lower requirements for admission, hence a higher admission rate, tend to load more on small minus big strategies. This coefficient is statistical significant at the 1% level. The economic significance is also very high, since has a mean of and has a standard deviation of The latter variable reflects a coefficient of A one standard deviation increase in, i.e. 20
21 = , will result in a change in the dependent variable of of = Relative to the average Small minus Bi, this is a 170% increase. Furthermore, age and tenure seem to have a minor impact on different strategies. Where other studies like Chevalier (1999a) report that older managers tend to use more momentum strategies, does it not seem to matter for this study. VI.VII Systematic and Idiosyncratic risk Table XI measures the impact of managerial characteristics on holding on different kind of risks. We would expect that MBA is positively related to systematic risk and negatively related to idiosyncratic risk. MBA s are taught that only beta receives compensation in the market and therefore they will try to outperform the market by only taking one more systematic risk rather than idiosyncratic risk. However, the table shows the opposite of one s expectations. MBA is positively related to beta, but the coefficient is not statistically significant. If we look to the relationship between residual standard deviation (idiosyncratic risk) and MBA we see again a positive (and now significant at the 1% level) relationship. This implies that managers that hold an MBA degree do take on more idiosyncratic or idiosyncratic risk to outperform the market. On the other, this does not count for managers that hold a CFA designation. They tend to hold on more systematic risk (not significant) and less idiosyncratic risk. 21
22 IV.VIII Endogeneity: Discussion I tried to examine whether managerial characteristics are related to mutual fund performance. I used several educational variables to explain the variation in the dependent variables. Even then, my findings may be exposed to endogeneity issues. First of all, it could face reverse causality problems. I tried to examine whether education causes alpha. Hence, I want to measure whether gained knowledge or connections due to education of the mutual fund manager influences the performance of mutual funds. Since it seems to be very unlikely that managers leave the industry to get more education, I do not expect reverse causality problems. Furthermore, my results could be exposed to the omitted variable bias. It is hard to distinguish smarts from education. Smart managers could also have had an easier time acquiring an education. Hence, there could be an omitted variable Smarts - that influences both education and alpha and there might be no relationship between education and alpha, but only smarts is what driving alpha. To address issues like this, I have added several control variables like age, tenure and firm size. However, there could be other omitted variables that explain the variation in alpha, like place of birth, residence and other personal characteristics. 22
23 IV. Conclusions This study examines the relationship between managerial characteristics and mutual fund performance. It shed light on the question whether the quality and difficulty of the obtained degrees of the manager concerned do influences the performance of mutual funds. Similar to Chevalier and Ellison (1999a), I examine if the difficulty of the undergraduate institution that the manager in charge has completed measured by SAT scores - has an impact on the performance of the fund as well as if the manager holds an MBA or not. In addition to this, this study measures the influence of holding a CFA/CPA designation, having an MSc/MA/2 nd bachelor degree, being a Ph.D. as well as the influence of the subject of the bachelor degree that is obtained. Furthermore, it contains besides the control variables age and tenure, the fund size and the total investment inflow within the mutual fund. Besides the relationship with fund performance, it measures whether managerial characteristics are related to fund characteristics, investment style and taking on specific kinds of risk. First, we observe that the SAT scores of the manager s undergraduate institution and the presence of an MBA and CFA designation is positively related to the simple excess return of the mutual fund. Although, none of the coefficients is statistically or economic significant. Second, I document similar results to that of Gottesman and Morey (2006) regarding the relationship between fund size and having an MBA, since larger firms tend to hire non- MBA managers. This coefficient is statistically significant at the 1% level. Furthermore, I find a strong negative relationship between gender and firm size as well investment inflow. Female managers are less likely to manage a large mutual fund and do have less investment inflow. Both coefficients are highly statistically significant. 23
24 Third, if I correct systematic risk and look to the relationship between risk-adjusted performance and managerial characteristics we observe again that SAT scores, holding a CFA designation and having an MBA is positively and this time significant related to alpha. Almost all coefficients are highly statistically significant. Nevertheless, the economic significance seems to be small. Fourth, we observe that managers that attend an undergraduate institution with lower requirements for admission, hence a higher admission rate, tend to load more on small minus big strategies. This coefficient is statistical significant at the 1% level. The economic significance is also very high. Furthermore, age and tenure seem to have a minor impact on different strategies. Where other studies like Chevalier and Ellison (1999a) report that older managers tend to use more momentum strategies, does it not seem to matter for this study. Fifth, we find that managers that hold an MBA degree do take on more idiosyncratic risk to outperform the market. On the other hand, this does not count for managers that hold a CFA designation. They tend to hold on more systematic risk (not significant) and less idiosyncratic risk. 24
25 V. References Articles Bertrand, M., and A. Schoar, 2003, Managing with Style: The Effect of Managers on Firm Policies, Quarterly Journal of Economics 118(4), Chevalier, J., and G. Ellison, 1999a, Are Some Mutual Fund Managers Better Than Others? Cross-Sectional Patterns in Behavior and Performance, Journal of Finance 54(3), Carhart, Mark, On perstistence in mutual fund performance. Journal of Finance 52 (1), Chevalier, J., and G. Ellison, 1999b, Career Concerns of Mutual Fund Managers, Quarterly Journal of Economics 114(2), Cohen, L., A. Frazzini, and C. Malloy, 2010, Sell-Side School Ties, Journal of Finance 65(4), Ding, B., and R. Wermers, 2009, Mutual Fund Performance and Governance Structure: The Role of Portfolio Managers and Boards of Directors, Working paper. Fama, E. F., and K. R. French, 2010, Luck versus Skill in the Cross-Section of Mutual Fund Returns, Journal of Finance 65(5), Golec, Joseph H., The effects of mutual fund managers characteristics on their portfolio performance, risk and fees. Financial Services Review 5, Kacperczyk, M., C. Sialm, and L. Zheng, 2005, On the Industry Concentration of Actively Managed Equity Mutual Funds, Journal of Finance 60(4), Books Malkiel, B. G., 1973, A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing, W. W. Norton and Co. 25
26 VI. Appendix Table I Descriptive Statistics Summary statistics for all of the variables used in the analysis are presented. Simple excess return (%) is calculated by subtracting the risk-free return rate (One Month Treasury Bill Rate) from the total return at the end of the month. Beta is the coefficient of the market portfolio, determined by regressing the fund s monthly returns minus the risk-free rate on the monthly returns of the market portfolio minus the risk-free rate. The HML, SMB, and MOM weights are the coefficient from a regression of the fund s monthly returns on the market returns minus the risk-free rate and the returns of subtracting the returns of low book-to-market ratio stocks from the returns of high book-to-market ratio stocks. The SMB portfolio is a zero-investment portfolio constructed by subtracting the returns of large market capitalization firms from the stock returns of small market capitalization firms. The MOM consists of a zero-investment portfolio constructed as the spread between the performance of stocks that are in the top 30 percent of returns in the 12 prior months and those that are in the bottom 30%. The HML portfolio is a zero-investment portfolio constructed by buying high book-to-market stocks and selling low book-to-market stocks. Alpha4 is the excess return from this four-factor model in percent per year. The log of assets is the logarithm of the monthly asset value. The manager characteristics variables includes the SAT score of undergraduate institutions which are conveniently divided by 100, the admission rate in percent of the undergraduate institution, dummy variables that takes the value of one if the manager has an MBA, Ph.D., CFA, CPA, MSc, MA or 2 nd bachelor and zero otherwise, the managers age and the manager s tenure in investment year. Variable # of Obs. Mean Std. Dev. Min. Max. Excess return Beta Unsys. risk Alpha Alpha Alpha SMB HML MOM Manager SAT (/100) Admission rate% MBA PH.D MA MSc CPA CFA nd bachelor Cash-in-flow Log of Assets Age Tenure Gender
27 Table II Correlation Matrix This table presents the correlation between the different variables. Variable name [1] [2] [3] [4] [5] [6] [7] [8] [9] [10] [11] [12] [13] [14] [15] [16] [17] [18] [19] [20] [21] [22] [23] Excess return [1] Beta [2] Unsys. risk [3] Alpha1 [4] Alpha3 [5] Alpha4 [6] SMB [7] HML [8] MOM [9] Manager SAT (/100) [10] Admission rate% [11] MBA [12] PH.D. [13] MA [14] MSc [15] CPA [16] CFA [17] nd bachelor [18] Investment Inflow [19] Log of Assets [20] Age [21] Tenure [22] Gender [23]
28 Table III Mutual fund Performance and Manager Characteristics The dependent variable is the simple excess return of the mutual fund at the end of the month which is regressed on a set of manager characteristics, including the average SAT score of the managers undergraduate institution (divided by 100), a dummy variable that takes the value one if the manager has an MBA and zero otherwise, the manager s age and the managers tenure in investment years. T- values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Independent Variables Coefficients Constant (-1.48) Manager SAT (/100) (-0.96) Admission rate% (-0.34) MBA (-0.36 CFA (-0.09) Age (-1.13) Tenure (-1.35) Gender (-1.91) R No. of observations
29 Table IV Fund Characteristics and Manager Characteristics The dependent variable are the log of total assets and the investment inflow, which are regressed on a set of manager characteristics, including the average SAT score of the managers undergraduate institution (divided by 100), a dummy variable that takes the value one if the manager has an MBA and zero otherwise, the manager s age, the managers gender (M/V), a dummy variable that takes the value one if the manager has an MBA/CFA/CPA/Ph.D./MA/MS/2 nd bachelor and zero otherwise and the managers tenure in investment years. T-values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Independent Variables Log of Assets (1) Dependent Variables Investment inflow (2) Constant (26.35)*** (20.36)*** Manager SAT (/100) (19.65)*** (25.36)*** Admission rate% (-13.97)*** (2.11)** MBA (-7.54)*** (-2.99)*** CFA (8.33)*** (6.71)*** CPA (-0.95) (5.05)*** PH.D (-12.78)*** (-23.06)*** MA (35.24)*** (1703)*** MSc (-10.32)*** (17.91)*** 2nd bachelor (5.34)*** (-2.77)*** Age (-4.07)*** (2.95)*** Tenure (-10.3)*** (-13.92)*** Gender (-15.12)*** (-11.03)*** R No. of observations
30 Table V Risk Adjusted Performance Measures The dependent variables are the simple excess return of the mutual fund at the end of the month and the CAPM alpha which are regressed on a set of manager characteristics, including the average SAT score of the managers undergraduate institution (divided by 100), a dummy variable that takes the value one if the manager has an MBA/CFA/CPA/Ph.D./MA/MS/2 nd bachelor and zero otherwise, the manager s age, the managers tenure in investment years and the log of total assets of the mutual fund at the end of the month. T-values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Independent Variables Simple excess (1) Alpha (2) Dependent Variables Simple excess/full (3) Alpha/full (4) Constant 0,0510-0,0287 0,0216-0,0392 (1.91)* (-11.82)*** (-0.81) (-16.32)*** Manager SAT (/100) 0,0002 0,0001 0,0000 0,0000 (1.48) (-8.21)*** (-0.05) (-4.15)*** Admission rate% -0,0010-0, ,0011-0,0014 (-0.96) (-16)*** (-1.11) (-15.06)*** MBA 0,0001 0,0002 0,0001 0,0003 (0.34) (-8.03)*** (-0.4) (-9.74)*** CFA 0,0001 0,0001 0,0000 0,0001 (0.36) (-4.61)*** (-0.1) (-3.76)*** CPA 0,0000 0,0000 0,0010 (-7.1)*** (-0.01) (-17.53)*** PHD 0,0005-0,0039 (-0.89) (-7.36)*** MA -0,0009 0,0003 (-0.16) (-7.35)*** MSc -0,0005 0,0000 (-0.9) (-0.37) 2nd Bachelor 0,0011 0,0007 (-1.7)* (-12.23)*** Age 0,0000 0,0000 0,0000 0,0000 (0.09) (-7.1)*** (-0.13) (-5.99)*** Tenure 0,0000 0,0000 0,0000 0,0000 (-1.13) (-0.16) (-0.32) (-3.5)*** Gender -0,0064-0,0037-0,0004-0,0003 (-1.35) (-8.68)*** (-0.81) (-6.12)*** Log of Assets 0,0000 0,0002 (-0.41) (-42.17)*** Investment Inflow 0,0002 0,0000 (-19.78)*** (-33.92)*** R 2 0,0002 0,0150 0,0034 0,0516 No. of observations
31 Table VI Alpha and Managerial Characteristics The dependent variables are the alphas from a regression analysis, where the excess return per share is regressed on respectively one (excess return on the market), three (the latter variable, HML and SMB) and four (the latter variables and MOM) portfolio s. These alpha s are regressed on a set of manager characteristics, including the average SAT score of the managers undergraduate institution (divided by 100) and the admission rate, a dummy variable that takes the value one if the manager has an MBA/CFA/CPA/Ph.D./MA/MS/2 nd bachelor and zero otherwise, the manager s age, the managers tenure in investment years, the log of total assets of the mutual fund at the end of the month and the investment inflow. T-values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Independent Variables CAPM (1) Dependent Variables Fama-French (2) Carhart (3) Constant (-16.32)*** (-21.84)*** (-19.37)*** Manager SAT (/100) (4.15)*** (11.25)*** (9.92)*** Admission rate% (-15.06)*** (-6.61)*** (-5.57)*** MBA (9.74)*** (12.36)*** (6.31)*** CFA (3.76)*** (-0.37) (-0.05) CPA (17.53)*** (11.19)*** (10.01)*** PH.D (-7.36)*** (-5.91)*** (-6.26)*** MA (7.35)*** (6.48)*** (8.26)*** MSc (-0.37) (0.36)*** (-3.65)*** 2nd Bachelor (12.23)*** (18.73)*** (16.08)*** Age (5.99)*** (9.95)*** (8.48)*** Tenure (3.5)*** (3.39)*** (2.50)** Gender (-6.12)*** (-8.17)*** (-8.56)*** Log of Assets (42.17)*** (51.62)*** (31.51)*** Investment Inflow (33.92)*** (37.14)* (53.33)*** R No. of observations
32 Table VII Education specific performance measures The dependent variables are the simple excess return of the mutual fund at the end of the month and the CAPM alpha which are regressed on a set of manager characteristics, including the average SAT score of the managers undergraduate institution (divided by 100), a dummy variable that takes the value one if the manager has an MBA/CFA/CPA/Ph.D./MA/MS/2 nd bachelor and zero otherwise, the manager s age, the managers tenure in investment years and the log of total assets of the mutual fund at the end of the month. Furthermore, dummy variables are included which take the value on if the subject of the manager at the undergraduate institution was Languages, Law, Mathematics/Econometrics/Chemistry/Physics, Others or Social Sciences and zero if it is an Economics/Finance/Business/Accounting/Marketing subject. T-values are in parentheses and the symbols *, ** and *** denote statistical significance at the 10%, 5% and 1% levels. Independent Variables Simple excess (1) Dependent Variables Alpha (2) Simple excess/full (3) Alpha/full (4) Constant (-1.09) (-10.21)*** (-0.26) (-15.16)*** Manager SAT (/100) (-0.76) (10.21)*** (-0.25) (7.87)*** Admission rate% (-1.02) (-1.60)*** (-0.37) (0.53)) MBA (-0.29) (4.72)*** (-1.26) (7.77)*** CFA (-0.08) (2.51)** (-0.10) (-4.25)*** CPA (-0.39) (4.10)*** PH.D (-0.75) (-7.05)*** MA (-1.17) (6.88)*** MSc (-0.08) (-3.00)*** 2nd Bachelor (-1.75)* (10.74)*** Age (-0.62) (10.71)*** (-0.82) (9.66)*** Tenure (-0.06) (-3.31)*** (-0.57) (-0.29) Gender (-0.36) (-4.12)*** (-0.59) (-1.17) Log of Assets (-1.05) (45.85)*** Investment Inflow (16.78)*** (21.21)*** Languages
The Role of Work Experience in the Effect of Education. on Mutual Fund Performance
The Role of Work Experience in the Effect of Education on Mutual Fund Performance Author: Raphaël LOUTER Anr. 964687 Supervisor: Dr. Alberto MANCONI Second reader: Dr. Michel VAN BREMEN Master Thesis Tilburg
More informationMUTUAL FUND PERFORMANCE ANALYSIS PRE AND POST FINANCIAL CRISIS OF 2008
MUTUAL FUND PERFORMANCE ANALYSIS PRE AND POST FINANCIAL CRISIS OF 2008 by Asadov, Elvin Bachelor of Science in International Economics, Management and Finance, 2015 and Dinger, Tim Bachelor of Business
More information15 Week 5b Mutual Funds
15 Week 5b Mutual Funds 15.1 Background 1. It would be natural, and completely sensible, (and good marketing for MBA programs) if funds outperform darts! Pros outperform in any other field. 2. Except for...
More informationBehind the Scenes of Mutual Fund Alpha
Behind the Scenes of Mutual Fund Alpha Qiang Bu Penn State University-Harrisburg This study examines whether fund alpha exists and whether it comes from manager skill. We found that the probability and
More informationThe evaluation of the performance of UK American unit trusts
International Review of Economics and Finance 8 (1999) 455 466 The evaluation of the performance of UK American unit trusts Jonathan Fletcher* Department of Finance and Accounting, Glasgow Caledonian University,
More informationDoes fund size erode mutual fund performance?
Erasmus School of Economics, Erasmus University Rotterdam Does fund size erode mutual fund performance? An estimation of the relationship between fund size and fund performance In this paper I try to find
More informationDebt/Equity Ratio and Asset Pricing Analysis
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies Summer 8-1-2017 Debt/Equity Ratio and Asset Pricing Analysis Nicholas Lyle Follow this and additional works
More informationIndustry Concentration and Mutual Fund Performance
Industry Concentration and Mutual Fund Performance MARCIN KACPERCZYK CLEMENS SIALM LU ZHENG May 2006 Forthcoming: Journal of Investment Management ABSTRACT: We study the relation between the industry concentration
More informationCFR Working Paper NO
CFR Working Paper NO. 12-01 Choosing two business degrees versus choosing one: What does it tell about mutual fund managers investment behavior? L. Andreu A. Pütz Choosing two business degrees versus choosing
More informationThe study of enhanced performance measurement of mutual funds in Asia Pacific Market
Lingnan Journal of Banking, Finance and Economics Volume 6 2015/2016 Academic Year Issue Article 1 December 2016 The study of enhanced performance measurement of mutual funds in Asia Pacific Market Juzhen
More informationONLINE APPENDIX. Do Individual Currency Traders Make Money?
ONLINE APPENDIX Do Individual Currency Traders Make Money? 5.7 Robustness Checks with Second Data Set The performance results from the main data set, presented in Panel B of Table 2, show that the top
More informationThe Effect of Kurtosis on the Cross-Section of Stock Returns
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2012 The Effect of Kurtosis on the Cross-Section of Stock Returns Abdullah Al Masud Utah State University
More informationPerformance Attribution: Are Sector Fund Managers Superior Stock Selectors?
Performance Attribution: Are Sector Fund Managers Superior Stock Selectors? Nicholas Scala December 2010 Abstract: Do equity sector fund managers outperform diversified equity fund managers? This paper
More informationDoes portfolio manager ownership affect fund performance? Finnish evidence
Does portfolio manager ownership affect fund performance? Finnish evidence April 21, 2009 Lia Kumlin a Vesa Puttonen b Abstract By using a unique dataset of Finnish mutual funds and fund managers, we investigate
More informationThe Good News in Short Interest: Ekkehart Boehmer, Zsuzsa R. Huszar, Bradford D. Jordan 2009 Revisited
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2014 The Good News in Short Interest: Ekkehart Boehmer, Zsuzsa R. Huszar, Bradford D. Jordan 2009 Revisited
More informationFurther Evidence on the Performance of Funds of Funds: The Case of Real Estate Mutual Funds. Kevin C.H. Chiang*
Further Evidence on the Performance of Funds of Funds: The Case of Real Estate Mutual Funds Kevin C.H. Chiang* School of Management University of Alaska Fairbanks Fairbanks, AK 99775 Kirill Kozhevnikov
More informationFocused Funds How Do They Perform in Comparison with More Diversified Funds? A Study on Swedish Mutual Funds. Master Thesis NEKN
Focused Funds How Do They Perform in Comparison with More Diversified Funds? A Study on Swedish Mutual Funds Master Thesis NEKN01 2014-06-03 Supervisor: Birger Nilsson Author: Zakarias Bergstrand Table
More informationHEDGE FUND PERFORMANCE IN SWEDEN A Comparative Study Between Swedish and European Hedge Funds
HEDGE FUND PERFORMANCE IN SWEDEN A Comparative Study Between Swedish and European Hedge Funds Agnes Malmcrona and Julia Pohjanen Supervisor: Naoaki Minamihashi Bachelor Thesis in Finance Department of
More informationPersistence in Mutual Fund Performance: Analysis of Holdings Returns
Persistence in Mutual Fund Performance: Analysis of Holdings Returns Samuel Kruger * June 2007 Abstract: Do mutual funds that performed well in the past select stocks that perform well in the future? I
More informationInvestment Performance of Common Stock in Relation to their Price-Earnings Ratios: BASU 1977 Extended Analysis
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2015 Investment Performance of Common Stock in Relation to their Price-Earnings Ratios: BASU 1977 Extended
More informationMonthly Holdings Data and the Selection of Superior Mutual Funds + Edwin J. Elton* Martin J. Gruber*
Monthly Holdings Data and the Selection of Superior Mutual Funds + Edwin J. Elton* (eelton@stern.nyu.edu) Martin J. Gruber* (mgruber@stern.nyu.edu) Christopher R. Blake** (cblake@fordham.edu) July 2, 2007
More informationKeywords: Equity firms, capital structure, debt free firms, debt and stocks.
Working Paper 2009-WP-04 May 2009 Performance of Debt Free Firms Tarek Zaher Abstract: This paper compares the performance of portfolios of debt free firms to comparable portfolios of leveraged firms.
More informationOptimal Debt-to-Equity Ratios and Stock Returns
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2014 Optimal Debt-to-Equity Ratios and Stock Returns Courtney D. Winn Utah State University Follow this
More informationDynamic Smart Beta Investing Relative Risk Control and Tactical Bets, Making the Most of Smart Betas
Dynamic Smart Beta Investing Relative Risk Control and Tactical Bets, Making the Most of Smart Betas Koris International June 2014 Emilien Audeguil Research & Development ORIAS n 13000579 (www.orias.fr).
More informationHow to measure mutual fund performance: economic versus statistical relevance
Accounting and Finance 44 (2004) 203 222 How to measure mutual fund performance: economic versus statistical relevance Blackwell Oxford, ACFI Accounting 0810-5391 AFAANZ, 44 2ORIGINAL R. Otten, UK D. Publishing,
More informationEmpirical Study on Market Value Balance Sheet (MVBS)
Empirical Study on Market Value Balance Sheet (MVBS) Yiqiao Yin Simon Business School November 2015 Abstract This paper presents the results of an empirical study on Market Value Balance Sheet (MVBS).
More informationin-depth Invesco Actively Managed Low Volatility Strategies The Case for
Invesco in-depth The Case for Actively Managed Low Volatility Strategies We believe that active LVPs offer the best opportunity to achieve a higher risk-adjusted return over the long term. Donna C. Wilson
More informationEconomics of Behavioral Finance. Lecture 3
Economics of Behavioral Finance Lecture 3 Security Market Line CAPM predicts a linear relationship between a stock s Beta and its excess return. E[r i ] r f = β i E r m r f Practically, testing CAPM empirically
More informationThe Consistency between Analysts Earnings Forecast Errors and Recommendations
The Consistency between Analysts Earnings Forecast Errors and Recommendations by Lei Wang Applied Economics Bachelor, United International College (2013) and Yao Liu Bachelor of Business Administration,
More informationExplaining After-Tax Mutual Fund Performance
Explaining After-Tax Mutual Fund Performance James D. Peterson, Paul A. Pietranico, Mark W. Riepe, and Fran Xu Published research on the topic of mutual fund performance focuses almost exclusively on pretax
More informationReturns on Small Cap Growth Stocks, or the Lack Thereof: What Risk Factor Exposures Can Tell Us
RESEARCH Returns on Small Cap Growth Stocks, or the Lack Thereof: What Risk Factor Exposures Can Tell Us The small cap growth space has been noted for its underperformance relative to other investment
More informationPerformance persistence and management skill in nonconventional bond mutual funds
Financial Services Review 9 (2000) 247 258 Performance persistence and management skill in nonconventional bond mutual funds James Philpot a, Douglas Hearth b, *, James Rimbey b a Frank D. Hickingbotham
More informationThe Disappearance of the Small Firm Premium
The Disappearance of the Small Firm Premium by Lanziying Luo Bachelor of Economics, Southwestern University of Finance and Economics,2015 and Chenguang Zhao Bachelor of Science in Finance, Arizona State
More informationAre You Smarter Than a CFA'er?
Are You Smarter Than a CFA'er? Manager Qualifications and Portfolio Performance Russell B. Gregory-Allen (Corresponding author) Massey University, New Zealand E-mail: r.gregory-allen@massey.ac.nz Hany
More informationManagement Practices and the Performance of Mutual Fund in the Caribbean
Management Practices and the Performance of Mutual Fund in the Caribbean By Winston Moore winston.moore@cavehill.uwi.edu Department of Economics The University of the West Indies, Cave Hill Campus Barbados
More informationThe Predictability of Managerial Heterogeneities in Mutual Funds
The Predictability of Managerial Heterogeneities in Mutual Funds Jun Huang School of Accountancy Shanghai University of Finance and Economics No.777 Guoding Road, Shanghai, China Yan (Albert) Wang 1 Department
More informationSector Fund Performance
Sector Fund Performance Ashish TIWARI and Anand M. VIJH Henry B. Tippie College of Business University of Iowa, Iowa City, IA 52242-1000 ABSTRACT Sector funds have grown into a nearly quarter-trillion
More informationSupplementary Appendix for Outsourcing Mutual Fund Management: Firm Boundaries, Incentives and Performance
Supplementary Appendix for Outsourcing Mutual Fund Management: Firm Boundaries, Incentives and Performance JOSEPH CHEN, HARRISON HONG, WENXI JIANG, and JEFFREY D. KUBIK * This appendix provides details
More informationTopic Nine. Evaluation of Portfolio Performance. Keith Brown
Topic Nine Evaluation of Portfolio Performance Keith Brown Overview of Performance Measurement The portfolio management process can be viewed in three steps: Analysis of Capital Market and Investor-Specific
More informationCompany Stock Price Reactions to the 2016 Election Shock: Trump, Taxes, and Trade INTERNET APPENDIX. August 11, 2017
Company Stock Price Reactions to the 2016 Election Shock: Trump, Taxes, and Trade INTERNET APPENDIX August 11, 2017 A. News coverage and major events Section 5 of the paper examines the speed of pricing
More informationRevisiting Idiosyncratic Volatility and Stock Returns. Fatma Sonmez 1
Revisiting Idiosyncratic Volatility and Stock Returns Fatma Sonmez 1 Abstract This paper s aim is to revisit the relation between idiosyncratic volatility and future stock returns. There are three key
More informationIt is well known that equity returns are
DING LIU is an SVP and senior quantitative analyst at AllianceBernstein in New York, NY. ding.liu@bernstein.com Pure Quintile Portfolios DING LIU It is well known that equity returns are driven to a large
More informationDiversified or Concentrated Factors What are the Investment Beliefs Behind these two Smart Beta Approaches?
Diversified or Concentrated Factors What are the Investment Beliefs Behind these two Smart Beta Approaches? Noël Amenc, PhD Professor of Finance, EDHEC Risk Institute CEO, ERI Scientific Beta Eric Shirbini,
More informationState Ownership at the Oslo Stock Exchange. Bernt Arne Ødegaard
State Ownership at the Oslo Stock Exchange Bernt Arne Ødegaard Introduction We ask whether there is a state rebate on companies listed on the Oslo Stock Exchange, i.e. whether companies where the state
More informationThe Effect of Fund Size on Performance:The Evidence from Active Equity Mutual Funds in Thailand
The Effect of Fund Size on Performance:The Evidence from Active Equity Mutual Funds in Thailand NopphonTangjitprom Martin de Tours School of Management and Economics, Assumption University, Hua Mak, Bangkok,
More informationChanges in Analysts' Recommendations and Abnormal Returns. Qiming Sun. Bachelor of Commerce, University of Calgary, 2011.
Changes in Analysts' Recommendations and Abnormal Returns By Qiming Sun Bachelor of Commerce, University of Calgary, 2011 Yuhang Zhang Bachelor of Economics, Capital Unv of Econ and Bus, 2011 RESEARCH
More informationSmart Beta #
Smart Beta This information is provided for registered investment advisors and institutional investors and is not intended for public use. Dimensional Fund Advisors LP is an investment advisor registered
More informationA SEEMINGLY UNRELATED REGRESSION ANALYSIS ON THE TRADING BEHAVIOR OF MUTUAL FUND INVESTORS
70 A SEEMINGLY UNRELATED REGRESSION ANALYSIS ON THE TRADING BEHAVIOR OF MUTUAL FUND INVESTORS A SEEMINGLY UNRELATED REGRESSION ANALYSIS ON THE TRADING BEHAVIOR OF MUTUAL FUND INVESTORS Nan-Yu Wang Associate
More informationFurther Test on Stock Liquidity Risk With a Relative Measure
International Journal of Education and Research Vol. 1 No. 3 March 2013 Further Test on Stock Liquidity Risk With a Relative Measure David Oima* David Sande** Benjamin Ombok*** Abstract Negative relationship
More informationHow Markets React to Different Types of Mergers
How Markets React to Different Types of Mergers By Pranit Chowhan Bachelor of Business Administration, University of Mumbai, 2014 And Vishal Bane Bachelor of Commerce, University of Mumbai, 2006 PROJECT
More informationEmpirical Evidence. r Mt r ft e i. now do second-pass regression (cross-sectional with N 100): r i r f γ 0 γ 1 b i u i
Empirical Evidence (Text reference: Chapter 10) Tests of single factor CAPM/APT Roll s critique Tests of multifactor CAPM/APT The debate over anomalies Time varying volatility The equity premium puzzle
More informationSizing up Your Portfolio Manager:
Stockholm School of Economics Department of Finance Master Thesis in Finance Sizing up Your Portfolio Manager: Mutual Fund Activity & Performance in Sweden Abstract: We examine the characteristics of active
More informationFactors in the returns on stock : inspiration from Fama and French asset pricing model
Lingnan Journal of Banking, Finance and Economics Volume 5 2014/2015 Academic Year Issue Article 1 January 2015 Factors in the returns on stock : inspiration from Fama and French asset pricing model Yuanzhen
More informationMonetary Economics Risk and Return, Part 2. Gerald P. Dwyer Fall 2015
Monetary Economics Risk and Return, Part 2 Gerald P. Dwyer Fall 2015 Reading Malkiel, Part 2, Part 3 Malkiel, Part 3 Outline Returns and risk Overall market risk reduced over longer periods Individual
More informationCommon Macro Factors and Their Effects on U.S Stock Returns
2011 Common Macro Factors and Their Effects on U.S Stock Returns IBRAHIM CAN HALLAC 6/22/2011 Title: Common Macro Factors and Their Effects on U.S Stock Returns Name : Ibrahim Can Hallac ANR: 374842 Date
More informationWhat Drives the Earnings Announcement Premium?
What Drives the Earnings Announcement Premium? Hae mi Choi Loyola University Chicago This study investigates what drives the earnings announcement premium. Prior studies have offered various explanations
More informationLAGGED IDIOSYNCRATIC RISK AND ABNORMAL RETURN. Yanzhang Chen Bachelor of Science in Economics Arizona State University. and
LAGGED IDIOSYNCRATIC RISK AND ABNORMAL RETURN by Yanzhang Chen Bachelor of Science in Economics Arizona State University and Wei Dai Bachelor of Business Administration University of Western Ontario PROJECT
More informationReal Estate Ownership by Non-Real Estate Firms: The Impact on Firm Returns
Real Estate Ownership by Non-Real Estate Firms: The Impact on Firm Returns Yongheng Deng and Joseph Gyourko 1 Zell/Lurie Real Estate Center at Wharton University of Pennsylvania Prepared for the Corporate
More informationMERGERS AND ACQUISITIONS: THE ROLE OF GENDER IN EUROPE AND THE UNITED KINGDOM
) MERGERS AND ACQUISITIONS: THE ROLE OF GENDER IN EUROPE AND THE UNITED KINGDOM Ersin Güner 559370 Master Finance Supervisor: dr. P.C. (Peter) de Goeij December 2013 Abstract Evidence from the US shows
More informationLONGER TENURE, GREATER SENIORITY, OR BOTH? EVIDENCE FROM OPEN-END EQUITY MUTUAL FUND MANAGERS IN TAIWAN
ASIAN ACADEMY of MANAGEMENT JOURNAL of ACCOUNTING and FINANCE AAMJAF, Vol. 4, No. 2, 1 20, 2008 LONGER TENURE, GREATER SENIORITY, OR BOTH? EVIDENCE FROM OPEN-END EQUITY MUTUAL FUND MANAGERS IN TAIWAN Jen-Sin
More informationDecimalization and Illiquidity Premiums: An Extended Analysis
Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 5-2015 Decimalization and Illiquidity Premiums: An Extended Analysis Seth E. Williams Utah State University
More informationModern Fool s Gold: Alpha in Recessions
T H E J O U R N A L O F THEORY & PRACTICE FOR FUND MANAGERS FALL 2012 Volume 21 Number 3 Modern Fool s Gold: Alpha in Recessions SHAUN A. PFEIFFER AND HAROLD R. EVENSKY The Voices of Influence iijournals.com
More informationApplied Macro Finance
Master in Money and Finance Goethe University Frankfurt Week 2: Factor models and the cross-section of stock returns Fall 2012/2013 Please note the disclaimer on the last page Announcements Next week (30
More informationHistorical Performance and characteristic of Mutual Fund
Historical Performance and characteristic of Mutual Fund Wisudanto Sri Maemunah Soeharto Mufida Kisti Department Management Faculties Economy and Business Airlangga University Wisudanto@feb.unair.ac.id
More informationAn analysis of the relative performance of Japanese and foreign money management
An analysis of the relative performance of Japanese and foreign money management Stephen J. Brown, NYU Stern School of Business William N. Goetzmann, Yale School of Management Takato Hiraki, International
More informationThe relationship between share repurchase announcement and share price behaviour
The relationship between share repurchase announcement and share price behaviour Name: P.G.J. van Erp Submission date: 18/12/2014 Supervisor: B. Melenberg Second reader: F. Castiglionesi Master Thesis
More informationFund Manager Educational Networks and Portfolio Performance. Botong Shang. September Abstract
Fund Manager Educational Networks and Portfolio Performance Botong Shang September 2017 Abstract In this study, I investigate the relation between social connections among fund managers and portfolio performance.
More informationAn Assessment of Managerial Skill based on Cross-Sectional Mutual Fund Performance
An Assessment of Managerial Skill based on Cross-Sectional Mutual Fund Performance Ilhan Demiralp Price College of Business, University of Oklahoma 307 West Brooks St., Norman, OK 73019, USA Tel.: (405)
More informationA Snapshot of Active Share
November 2016 WHITE PAPER A Snapshot of Active Share With the rise of index and hedge funds over the past three decades, many investors have been debating about the value of active management. The introduction
More informationIs a Team Different From the Sum of Its Parts? Evidence from Mutual Fund Managers
Is a Team Different From the Sum of Its Parts? Evidence from Mutual Fund Managers Abstract This paper provides the first empirical test of the diversification of opinion theory and the group shift theory
More informationA Comparison of Active and Passive Portfolio Management
University of Tennessee, Knoxville Trace: Tennessee Research and Creative Exchange University of Tennessee Honors Thesis Projects University of Tennessee Honors Program 5-2017 A Comparison of Active and
More informationOn Market Timing, Stock Picking, and Managerial Skills of Mutual Fund Managers with Manipulation-proof Performance Measure
On Market Timing, Stock Picking, and Managerial Skills of Mutual Fund Managers with Manipulation-proof Performance Measure Meifen Qian, Ping-Wen Sun, and Bin Yu International Institute for Financial Studies
More informationMeasuring Performance with Factor Models
Measuring Performance with Factor Models Bernt Arne Ødegaard February 21, 2017 The Jensen alpha Does the return on a portfolio/asset exceed its required return? α p = r p required return = r p ˆr p To
More informationCFA Designation and Mutual Fund Performance: Further Evidence. Key Words: Mutual Fund, Managers Qualification, CFA, MBA, Risk-adjusted Performance
CFA Designation and Mutual Fund Performance: Further Evidence Abstract Extant literature on mutual fund performance and managers human capital (education, training, experience, other qualifications etc.)
More informationRisk adjusted performance measurement of the stock-picking within the GPFG 1
Risk adjusted performance measurement of the stock-picking within the GPFG 1 Risk adjusted performance measurement of the stock-picking-activity in the Norwegian Government Pension Fund Global Halvor Hoddevik
More informationThe effect of portfolio performance using social responsibility screens
The effect of portfolio performance using social responsibility screens Master Thesis Author: Donny Bleekman BSc. (927132) Supervisor: dr. P. C. (Peter) de Goeij Study program: Master Finance December
More informationWhen Equity Mutual Fund Diversification Is Too Much. Svetoslav Covachev *
When Equity Mutual Fund Diversification Is Too Much Svetoslav Covachev * Abstract I study the marginal benefit of adding new stocks to the investment portfolios of active US equity mutual funds. Pollet
More informationMARKET EFFICIENCY & MUTUAL FUNDS
MARKET EFFICIENCY & MUTUAL FUNDS Topics: Market Efficiency Random Walks Different Forms of Market Efficiency Investing in Mutual Funds Introduction to mutual funds Evaluating mutual fund performance Evaluating
More informationSustainable Investing. Is 12b-1 fee still relevant?
Sustainable Investing Is 12b-1 fee still relevant? Sustainability investing or ESG investing is a style of investing encompassing the environmental (E), social (S), and governance (G) factors. The Morningstar
More informationLiquidity skewness premium
Liquidity skewness premium Giho Jeong, Jangkoo Kang, and Kyung Yoon Kwon * Abstract Risk-averse investors may dislike decrease of liquidity rather than increase of liquidity, and thus there can be asymmetric
More informationThe Liquidity Style of Mutual Funds
Thomas M. Idzorek Chief Investment Officer Ibbotson Associates, A Morningstar Company Email: tidzorek@ibbotson.com James X. Xiong Senior Research Consultant Ibbotson Associates, A Morningstar Company Email:
More informationMutual Fund s R 2 as Predictor of Performance
Mutual Fund s R 2 as Predictor of Performance By Yakov Amihud * and Ruslan Goyenko ** Abstract: We propose that fund performance is predicted by its R 2, obtained by regressing its return on the Fama-French-Carhart
More informationIndustry Indices in Event Studies. Joseph M. Marks Bentley University, AAC Forest Street Waltham, MA
Industry Indices in Event Studies Joseph M. Marks Bentley University, AAC 273 175 Forest Street Waltham, MA 02452-4705 jmarks@bentley.edu Jim Musumeci* Bentley University, 107 Morrison 175 Forest Street
More informationFactoring Profitability
Factoring Profitability Authors Lisa Goldberg * Ran Leshem Michael Branch Recent studies in financial economics posit a connection between a gross-profitability strategy and quality investing. We explore
More informationLiquidity and IPO performance in the last decade
Liquidity and IPO performance in the last decade Saurav Roychoudhury Associate Professor School of Management and Leadership Capital University Abstract It is well documented by that if long run IPO underperformance
More informationFinansavisen A case study of secondary dissemination of insider trade notifications
Finansavisen A case study of secondary dissemination of insider trade notifications B Espen Eckbo and Bernt Arne Ødegaard Oct 2015 Abstract We consider a case of secondary dissemination of insider trades.
More informationParameter Estimation Techniques, Optimization Frequency, and Equity Portfolio Return Enhancement*
Parameter Estimation Techniques, Optimization Frequency, and Equity Portfolio Return Enhancement* By Glen A. Larsen, Jr. Kelley School of Business, Indiana University, Indianapolis, IN 46202, USA, Glarsen@iupui.edu
More informationControlling for Fixed Income Exposure in Portfolio Evaluation: Evidence from Hybrid Mutual Funds
Controlling for Fixed Income Exposure in Portfolio Evaluation: Evidence from Hybrid Mutual Funds George Comer Georgetown University Norris Larrymore Quinnipiac University Javier Rodriguez University of
More informationBEYOND SMART BETA: WHAT IS GLOBAL MULTI-FACTOR INVESTING AND HOW DOES IT WORK?
INVESTING INSIGHTS BEYOND SMART BETA: WHAT IS GLOBAL MULTI-FACTOR INVESTING AND HOW DOES IT WORK? Multi-Factor investing works by identifying characteristics, or factors, of stocks or other securities
More informationStatistical Understanding. of the Fama-French Factor model. Chua Yan Ru
i Statistical Understanding of the Fama-French Factor model Chua Yan Ru NATIONAL UNIVERSITY OF SINGAPORE 2012 ii Statistical Understanding of the Fama-French Factor model Chua Yan Ru (B.Sc National University
More informationNew Zealand Mutual Fund Performance
New Zealand Mutual Fund Performance Rob Bauer ABP Investments and Maastricht University Limburg Institute of Financial Economics Maastricht University P.O. Box 616 6200 MD Maastricht The Netherlands Phone:
More informationBetter Equity Portfolios through Active Share. September 2013
Better Equity Portfolios through Active Share September 2013 EXECUTIVE SUMMARY Active Share is an important innovation that gives our industry a common method and language to define how active an active
More informationPortfolio performance and environmental risk
Portfolio performance and environmental risk Rickard Olsson 1 Umeå School of Business Umeå University SE-90187, Sweden Email: rickard.olsson@usbe.umu.se Sustainable Investment Research Platform Working
More informationManagement Practices and the. Caribbean. Winston Moore (PhD) Department of Economics University of the West Indies Cave Hill Campus
Management Practices and the Performance of Mutual Funds in the Caribbean Winston Moore (PhD) Department of Economics University of the West Indies Cave Hill Campus Overview The mutual fund industry in
More informationAssessment on Credit Risk of Real Estate Based on Logistic Regression Model
Assessment on Credit Risk of Real Estate Based on Logistic Regression Model Li Hongli 1, a, Song Liwei 2,b 1 Chongqing Engineering Polytechnic College, Chongqing400037, China 2 Division of Planning and
More informationPension fund investment: Impact of the liability structure on equity allocation
Pension fund investment: Impact of the liability structure on equity allocation Author: Tim Bücker University of Twente P.O. Box 217, 7500AE Enschede The Netherlands t.bucker@student.utwente.nl In this
More informationDeviations from Optimal Corporate Cash Holdings and the Valuation from a Shareholder s Perspective
Deviations from Optimal Corporate Cash Holdings and the Valuation from a Shareholder s Perspective Zhenxu Tong * University of Exeter Abstract The tradeoff theory of corporate cash holdings predicts that
More informationPerformance Measurement and Attribution in Asset Management
Performance Measurement and Attribution in Asset Management Prof. Massimo Guidolin Portfolio Management Second Term 2019 Outline and objectives The problem of isolating skill from luck Simple risk-adjusted
More informationFactor Investing: Smart Beta Pursuing Alpha TM
In the spectrum of investing from passive (index based) to active management there are no shortage of considerations. Passive tends to be cheaper and should deliver returns very close to the index it tracks,
More informationEssays on Open-Ended Equity Mutual Funds in Thailand Presented at SEC Policy Dialogue 2018: Regulation by Market Forces
Essays on Open-Ended Equity Mutual Funds in Thailand Presented at SEC Policy Dialogue 2018: Regulation by Market Forces Roongkiat Ranatabanchuen, Ph.D. & Asst. Prof. Kanis Saengchote, Ph.D. Department
More information