Why Do Fund Families Release Underperforming Incubated Mutual Funds?

Size: px
Start display at page:

Download "Why Do Fund Families Release Underperforming Incubated Mutual Funds?"

Transcription

1 Why Do Fund Families Release Underperforming Incubated Mutual Funds? Sara E. Shirley and Jeffrey R. Stark Although the average incubated mutual fund outperforms nonincubated funds by up to 3.41% annually, a large number of released funds underperform during incubation. We find that launching underperforming incubated mutual funds is associated with objectives that attract large inflows and lower relative risk. These findings are consistent with the use of incubation to maximize fee revenue through means other than the flow-to-performance relationship. We also find that underperforming incubated funds are incubated longer suggesting that families release funds opportunistically to take advantage of outperformance when it is observed. The value of a mutual fund to its fund family is its ability to generate revenue. This revenue comes from a fund s capacity to increase its assets under management, which, in turn, increases the fees collected by the fund and results in additional revenue for the fund family. Evans (2010) discusses four methods that are used by fund families to increase revenue, one of which is fund performance. It is well established in the literature that the mechanism by which performance leads to increased revenue is the relationship between past performance and current period inflows (Ippolito, 1992; Chevalier and Ellison, 1997; Sirri and Tufao, 1998). As a fund outperforms, investors chase performance, which increases assets under management and provides additional fee revenues for the family. However, competing on the basis of performance is a difficult task given the documented underperformance of mutual funds (Jensen, 1968; Carhart, 1997; French, 2008; Fama and French, 2010). Nevertheless, outperformance does occur and may be the result of favorable treatment of a specific fund within a family (Guedj and Papastaikoudi, 2004; Gaspar, Massa, and Matos, 2006) or incubation (Evans, 2010). The process of mutual fund incubation begins when fund families internally launch small funds with low levels of total net assets. After a period of evaluation, the family determines which mutual funds to publicly launch and which funds to discontinue. By taking advantage of the incubation process and the established relationship between past performance and current period inflows, mutual fund families are able to selectively launch incubated mutual funds that, on We thank an anonymous referee, Marc Lipson (Editor), Scott Gilbert, Jason Greene, James Musumeci, Edward Nowlin, Mark Peterson, David Rakowski, and Wanli Zhao for helpful comments and discussions. We are also thankful to Frank Hatheway from NASDAQ for providing the data on mutual fund ticker creation dates and to seminar participants at Roger Williams University. The authors are responsible for any remaining errors. Sara E. Shirley is an Assistant Professor of Finance at Roger Williams University in Bristol, RI. Jeffrey R. Stark is an Assistant Professor of Finance at Bridgewater State University in Bridgewater, MA. Financial Management Fall 2016 pages

2 508 Financial Management Fall 2016 average, have generated a positive objective alpha. However, outperformance is difficult to come by. Evans (2010) suggests that incubation is not used to identify skilled managers, but to generate a misleading track record of outperformance as the Securities and Exchange Commission (SEC) allows incubation period performance to be advertised once a fund has been released, but does not require that the performance of discontinued funds be documented. The process of mutual fund incubation raises two unanswered questions: 1) what factors determine how long a mutual fund is incubated? and 2) why do a large portion of incubated funds that are released to the public underperform during the incubation process? These questions are the focus of the present study. We examine a sample of 3,610 US domestic equity mutual funds from 1999 through September 2014 and find that 22.63% (817) of the funds are incubated. We determine that of the 817 incubated funds in our sample, 354 or 43.33% have negative incubation period performance when measured by an equally weighted objective alpha. Our results indicate that the release of underperforming funds is significantly related to an objective that is attracting large inflows. This finding helps explain the launch of underperforming incubated funds and suggests that the need to fill family demands may be a major driving force in how mutual fund families use incubation. We also find that the probability of a quicker release of a fund is positively associated with incubation period performance, objective inflows, and family inflows. These findings support the view that fund families take advantage of outperforming incubated mutual funds as they appear in order to avoid any spuriously outperforming mutual funds from reverting back to average performance. In addition, these results support fund families launching incubated mutual funds faster when there is increased demand for the fund family s mutual funds or the incubated mutual fund s objective, suggesting that fund families seek to take advantage of spillover effects (Nanda, Wang, and Zheng, 2004). This paper is organized as follows. Section I details the data, while Section II examines the distribution of incubation period performance and its relationship with flows. Section III provides the empirical analysis of incubation length. Section IV presents the empirical analysis of the decision to release an underperforming mutual fund, while Section V provides our conclusions. I. Data and Sample Creation Incubated mutual funds are identified based on information from two databases. Mutual fund data (excluding ticker creation dates) are obtained from the Survivor-Bias-Free US Mutual Fund Database hosted by the Center for Research in Security Prices (CRSP). Other variables of interest from the CRSP database include mutual fund and fund family characteristics. 1 Ticker creation dates, or the date when a mutual fund is made available to the public, are obtained from a database hosted by the National Association of Securities Dealers (NASD). The NASD database provides a snapshot of all active mutual funds for each month from January 1999 to September 2014 and includes data for the ticker creation date, the fund s ticker, and the fund s name. Variables from 1 CRSP Style codes were utilized to create our sample of domestic equity mutual funds. Codes of EDSG, EDSH, EDSF, EDSN, EDSR, EDST, EDSU, EDSG, EDSS, EDSI, EDSM, EDSA, EDS, EDCL, EDCM, EDCS, EDCI, EDYG, EDYB, EDYH, EDYS, and EDYI were retained. For a complete description of the objectives used, see the Appendix (Section I and Table A1).

3 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 509 the CRSP database are obtained for each month from 1999 to the third quarter of 2014 to coincide with the NASD data. Before merging the CRSP data with the NASD data to identify incubated mutual funds, the data are filtered as in Evans (2010). 2 The NASD database includes funds that were created prior to 1999 if they survived past that time. Accordingly, any fund created prior to 1999 is omitted from the sample. In addition, fund name observations that contain the word TEST are removed from the NASD data. The merged databases identify incubated mutual funds by ticker. However, since tickers can be recycled over time, matches are checked by comparing fund names for CRSP data and NASD data. Observations with mismatched fund names are removed from the sample. After merging the two databases, we obtain the first date for which each share class has a valid return observation and group together all share classes belonging to the same mutual fund. The start date of the mutual fund is set to the start date of its earliest share class. After obtaining a mutual fund s start date and ticker creation date, we identify incubated funds by calculating the difference in time between the fund s ticker creation date and the date of the fund s first return. A negative difference between these two dates indicates that the mutual fund has been incubated and has generated returns prior to a ticker being assigned to the fund. To account for lags in a fund applying for a ticker from the NASD, observations with negative differences of less than six months are not considered to be incubated and are grouped accordingly. Observations with a positive difference of greater than three months (i.e., more than three months from the ticker creation date to the first returns) are attributed to errors in the data and are removed from the sample. 3 The final data sample consists of 3,610 US domestic equity mutual funds that were launched between 1999 and September Of this sample, 817 funds (22.63%) are incubated. 4 Descriptive statistics for all of the mutual funds in the sample are displayed in Table I. The sample of postincubation and nonincubated mutual funds include up to the first 36 months of a fund s life once it is made available to the public. These data indicate that during the incubation process, mutual funds are relatively small, with an average size of $29.50 million. However, after incubation, the average size rises to $ million. This pattern is consistent with the established function of incubation, which is to allow a mutual fund to operate privately and with a small amount of capital while establishing a track record of performance. In addition, data in Table I indicate that the incubated funds are smaller than their nonincubated counterparts both during and postincubation. The expense ratio, front load, and rear load of incubated mutual funds does not change between the incubation period and the postincubation period, although nonincubated mutual funds charge lower expense ratios than incubated mutual funds (1.27% vs. 1.48%, respectively). 2 Evans (2010) provides detailed instructions for combining the databases in the Supplements & Datasets section of the Journal of Finance website at 3 The nature of incubation data inherently includes a sample bias due to the unobserved incubated mutual funds that do not survive the incubation process and is, therefore, not unique to our analysis (Evans, 2010; Gibson and Finke, 2014). Although this bias does determine the composition of the funds in our sample, the expected impact on our conclusions are minimal due to the similarities between our proxy sample for the unobservable funds and the sample of incubated funds used throughout our analysis. See the Appendix Section II for a detailed discussion of the potential impact of this bias. 4 The 22.63% found between 1999 and September 2014 is similar to the 23.1% reported by Evans (2010) in a sample of funds from 1999 to 2006 (242 of 1,048).

4 510 Financial Management Fall 2016 Table I. Sample Descriptive Statistics This table contains the descriptive statistics of our samples of incubated and nonincubated funds. The sample of incubated mutual funds is separated into two subsamples: 1) an incubation period and 2) a postincubation period. The mean and median of total net assets of a fund and family, the expense ratio of a fund, the average front and rear load of a fund, and the number of funds that were and were not incubated are reported below by subsample. Postincubation and nonincubated performances are calculated over a period of up to the first three years (36 months) a fund is available for public investment. Incubated Funds During Incubation Postincubation Nonincubated Funds Variable Mean Median Mean Median Mean Median Total net assets ($MM) $29.50 $4.50 $ $25.80 $ $28.10 Family size ($MM) $40,701 $5,360 $55,116 $7,475 $96,446 $11,865 Expense ratio 1.48% 1.42% 1.50% 1.45% 1.27% 1.25% Average front load 2.00% 2.80% 1.99% 2.79% 2.28% 2.96% Average rear load 0.73% 0.40% 0.72% 0.38% 0.67% 0.33% Number of funds 817 2,793 II. Incubation Period Performance and Flows A. Methodology Prior literature primarily focuses on the use of incubation to generate a track record of outperformance that creates increased inflows to the incubated fund once it has been released to the public. Consistent with the prior literature, Table II demonstrates that the incubated mutual funds in our sample outperform nonincubated funds when measured by an equally weighted and value-weighted objective alpha and a four-factor alpha during incubation by up to 3.41% risk adjusted per year. 5 This outperformance does not last though with incubated and nonincubated mutual funds performing equally well during postincubation. Further analysis of incubated mutual funds and their incubation period performance reveals that a large portion of incubated funds (354 of 817 or 43.33%) are released to the public with negative objective alphas, as illustrated in Figure 1. To better understand the motivation for incubating and releasing a mutual fund, we create subsamples based on an equally weighted objective alpha measure of fund performance during incubation. As demonstrated in Table III, during incubation, both outperforming and underperforming mutual funds are relatively close in size. However, postincubation, the outperforming funds grow faster than the underperforming funds, increasing in size from $25.46 million to $ million, while the underperforming funds increase in size from $27.16 million to $71.08 million. Table IV reports the difference in performance from incubation to postincubation for outperforming and underperforming funds. During incubation, the annualized difference in average equally weighted objective alpha performance between the subgroups of outperforming and 5 Objective alpha is defined as the raw returns of a mutual fund minus the total equally-weighted average returns of all other funds within the same fund objective. This measure of performance is a proxy for fund performance relative to a benchmark, similar to the performance advertised by many mutual funds ( For robustness, a value-weighted approach is also presented with all of the results.

5 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 511 Table II. Performance of Incubated and Nonincubated Mutual Funds This table examines performance measures for incubated and nonincubated funds. Following the analysis of Evans (2010), Panel A compares the performance of incubated mutual funds during their incubation period to the performance of mutual funds that were not incubated, while Panel B compares the performance of incubated mutual funds during their postincubation period to the performance of nonincubated mutual funds. Asterisks in Columns 1 and 2 indicate the significance levels for a t-test of annualized performance from zero, and the asterisks in Column 3 provide the significance of the difference in annualized performance between the two samples. Performance measures examined are an equal-weighted and a value-weighted objective alpha, a four-factor alpha (Carhart, 1997) and raw returns. Incubation period performance is calculated over the entirety of the incubation period. Postincubation and nonincubated performances are calculated over a period up to the first three years (36 months) a fund is available for public investment. Panel A. Incubation Period Performance Incubated Funds Nonincubated Funds (817 Funds) (2,791 Funds) Annualized Variable t = Incubation Period t = 1 to 36 Months Difference Four-factor alpha 2.89% 0.52% 3.41% EW objective alpha 3.53% 0.47% 3.06% VW objective alpha 2.66% 0.44% 3.10% Raw returns 12.84% 5.75% 7.10% Panel B. Postincubation Period Performance Incubated Funds Nonincubated Funds (817 Funds) (2,791 Funds) Annualized Variable t = 1 to 36 Months t = 1 to 36 Months Difference Four-factor alpha 0.13% 0.52% 0.39% EW objective alpha 0.84% 0.47% 0.37% VW objective alpha 0.24% 0.44% 0.68% Raw returns 4.12% 5.75% 1.64% Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level. underperforming incubated mutual funds is 17.16% per year [10.52% ( 6.64%)]. However, both the positive and negative performance subgroups generate returns close to 1% postincubation. This is consistent with the findings of Table II, confirming that incubation period performance does not predict postincubation performance. Similar to Evans (2010), we employ multivariate regression to examine the impact of incubation on the flows received by a mutual fund after launch. We extend the work of Evans (2010) by creating subsamples based on a positive or negative objective alpha performance during incubation. The relationship is formally examined with the following linear regression equation: Flow i,t = α i + β 1 Incubated i + β 2 Fund TNA i,t + β 3 Family TNA i,t + β 4 Fund Flow i,t 1 + β 5 Objective Flow i,t + β 6 Fees i,t + β 7 Multiple i,t + β 8 Performance i + ε i, (1)

6 512 Financial Management Fall 2016 Figure 1. Distribution of Incubation Period Performance of Individual Mutual Funds This figure displays the distribution of incubation period fund cumulative performance as measured by an equally weighted objective alpha. Table III. Sample Descriptive Statistics by Incubation Period Performance This table contains the descriptive statistics of incubated mutual funds. The sample is separated into a group of mutual funds that have a positive incubation period equally weighted objective alpha and a negative incubation period equally weighted objective alpha. The mean and median of total net assets of a fund and family, the expense ratio of a fund, the average front and rear load of a fund, and the number of funds with positive and negative incubation period performance are reported below. Positive EW Incubation Objective Alpha Negative EW Incubation Objective Alpha During Incubation Postincubation During Incubation Postincubation Variable Mean Median Mean Median Mean Median Mean Median Total net assets ($MM) $25.46 $6.92 $ $40.55 $27.16 $5.68 $71.08 $19.16 Family size ($MM) $54,102 $9,407 $54,988 $8,959 $51,152 $6,729 $54,694 $6,764 Expense ratio 1.47% 1.45% 1.47% 1.44% 1.54% 1.46% 1.52% 1.50% Average front load 1.96% 2.76% 1.97% 2.79% 2.06% 2.83% 2.03% 2.80% Average rear load 0.68% 0.40% 0.70% 0.40% 0.73% 0.33% 0.74% 0.33% Number of funds

7 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 513 Table IV. Performance of Incubated Mutual Funds This table presents the annualized equally weighted objective alpha performance of incubated mutual funds during incubation and for up to 36 months postincubation by incubation period performance. Also presented is the annualized difference in performance between incubation and postincubation period returns. Asterisks in Columns 1 and 2 indicate the significance levels for a t-test of annualized performance from zero, while the asterisks in Column 3 provide the significance of the difference in annualized performance between the incubation and postincubation samples. Incubation Period Postincubation Annualized Obj. Alpha Annualized Obj. Alpha Annualized Difference Positive obj. alpha 10.52% 0.93% 9.59% Negative obj. alpha 6.64% 1.21% 7.85% Significant at the 0.01 level. where Flow i,t is the growth in assets of fund i from time t 1tot after accounting for the growth of assets attributed to the performance of fund i, and is measured as Flow = TNA i,t TNA i,t 1 (1 + R i,t ), (2) where TNA represents the total net assets of fund i at time t (TNA i,t )ort 1(TNA i,t 1 ) and R i,t represents the returns of fund i during period t. Flow is calculated for 12-month periods to create a measure of annual fund flows. For funds that are incubated, flow measurements begin postincubation. As in Evans (2010), monthly cross-sectional ranks are used rather than dollar flow due to the large variation in mutual fund size among startup funds. Incubated is a dummy variable that takes a value of one if a mutual fund has been incubated and zero otherwise. The remaining variables in the regression equation are defined as follows. Fund_TNA i,t is the log of TNA for fund i at time t. Family_TNA i,t is the log of TNA for the management company of fund i at time t, excluding the TNA of the fund of interest (fund i or the dependent variable). All other mutual funds within the family are included in the calculation, not just those that have been incubated. Fund_Flow i,t-1 is a rank from 0.01 to 1.0 of inflows received by fund i over the prior 12-month period. Objective_Flow i,t is a rank from 0.01 to 1.0 of fund flows to the objective for fund i during period t, excluding the flows attributed to the fund of interest (fund i or the dependent variable). Fees i,t represents the expense ratio for fund i at time t. Multiple i,t is a dummy variable indicating whether the incubated fund s family currently has additional funds within an objective class and Performance i is the lifetime performance of fund i as measured by raw returns and includes incubation period performance for incubated mutual funds. B. Results Table V presents the results of regressing flow (the rank of net dollar flows of a fund, as calculated in Equation (2)) on incubation (whether a fund has been incubated or not). Year fixed effects are included to account for any variation from year to year. For incubated mutual funds, the start of the inflow period is the first postincubation month. The dependent variable, Flow, is measured over the second 12-month period (Months 13 to 24) for both incubated and nonincubated mutual funds so that lagged flows can be calculated over the first 12-month period for each fund.

8 514 Financial Management Fall 2016 Table V. Relationship between Incubation and Mutual Fund Flows This table provides the coefficient estimates from the regression listed below of fund flows on a dummy variable identifying whether a mutual fund was incubated, as well as fund and family characteristics. Flow i,t = α i + β 1 Incubated i + β 2 Fund TNA i,t + β 3 Family TNA i,t + β 4 Fund Flow i,t 1 + β 5 Objective Flow i,t + β 6 Fees i,t + β 7 Multiple i,t + β 8 Performance i + ε i. The sample used here contains all of the funds identified in the sample (both incubated and nonincubated) sorted into subgroups based on a positive or negative incubation period equally weighted objective alpha. The dependent variable is the rank of dollar flows to the fund and takes on a fractional value between 0.01 and 1.0 based on net dollar flows that year. Observations of flow begin after a mutual fund has been open to the public for 12 months, allowing for lagged flows to be calculated. Independent variables include a dummy variable identifying incubated mutual funds, the log of a fund s total net assets, the log of the family s total net assets, a rank measure of the flows to a fund over the prior 12 months taking a value between 0.01 and 1.0, the rank of flows to the investment objective over the period the dependent variable is calculated and ranked between 0.01 and 1.0, the fees charged by the fund, a dummy variable indicating whether a fund family already had a mutual fund in the incubated fund s objective class, and the total raw returns of a fund. Annual fixed effects are included. One annual observation is retained for each fund that has the necessary 24 months of observations. Asterisks indicate statistical significance of the coefficients and t-statistics are in parentheses. Fund Flow Rank Variable Positive Negative Intercept (17.81) (18.22) Incubated (0.39) (4.31) Fund TNA (3.32) (3.14) Family TNA (1.27) (1.68) Fund Flow t (28.15) (28.84) Objective Flow (3.69) (3.57) Fees ( 4.12) ( 3.98) Multiple ( 0.42) ( 0.49) Performance (7.64) (7.69) Fixed effects Yes Yes Adjusted R % 10.77% Observations 12,004 11,854 Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level. Our sample includes both incubated and nonincubated funds, and the analysis covers the period from the ticker creation date up to 60 months after the fund is made available to the public. Fund performance extends back to the fund s inception. One annual observation is retained for each year that a mutual fund is in our sample. We separate our sample of incubated funds into two

9 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 515 subsamples: 1) funds that generate a positive equally weighted objective alpha during incubation and 2) those that generate a negative equally weighted objective alpha during incubation. Nonincubated mutual fund performance is measured in the same way, beginning at the date of inception. As demonstrated in Table V, for the subsample of funds that generate positive objective alphas during incubation, no significant relationship is found between flow and the incubated variable. These results indicate that the differences in postincubation flow among mutual funds that generate positive objective alphas during incubation is explained by performance, objective flows, expense ratio, fund size, and lagged fund flows. For the subsample of mutual funds that generate negative objective alphas during incubation, the relationship between flow and incubation remains positive and significant with an incubated coefficient of These results indicate that the postincubation flows from these underperforming mutual funds cannot be explained by the fund s performance or other control variables. These findings suggest that underperforming incubated mutual funds serve the fund family in ways that are unrelated to the establishment of a track record of outperformance. III. Incubation Length A. Methodology Evidence in the literature regarding mutual fund manager skill reveals that few mutual funds outperform (Jensen, 1968; Malkiel, 1995; Carhart, 1997; Fama and French, 2010). The findings suggest that, on average, outperformance by a mutual fund, even during incubation, cannot be attributed to manager skill. Accordingly, there is no guarantee that a fund s performance will persist into the future. Given the potentially fleeting nature of mutual fund outperformance and the increased inflows a fund receives for having positive incubation period performance, it follows that fund families will take advantage of outperforming funds by launching them before returns become negative. According to this logic, the duration of incubation for a mutual fund should be inversely related to the mutual fund s performance. Another explanation for the timing of mutual fund launches is voiced by Robert Puff, Chief Investment Officer at Twentieth Century Funds, The industry will keep introducing whatever has been working well lately. 6 In other words, funds are released to the public when an objective s or family s funds are in demand. We use a Cox proportional hazard regression model (Hosmer and Lemeshow, 1999; Fox, 2002) to explore the determinants of a fund s incubation release. The use of this model allows us to examine the impact of our covariates on the decision to release an incubated fund in a given period rather than continuing on with the incubation process. The regression is defined as Incubation Release i = β 1 Incubation Performance i + β 2 Objective Flow i + β 3 Family Flow i + β 4 Family Performance i + β 5 Objective TNA i + β 6 Family TNA i + β 7 Fund TNA i + β 8 Incubation Risk i + β 9 Fees i + β 10 Front i + β 11 Rear i + β 12 Multiple i + β 13 FamilyInc i + ε i, (3) where Incubation_Release i is measured as the month that mutual fund i is released from incubation. Incubation_Performance i measures the objective alpha performance or four-factor alpha of 6 See the article by Jason Zweig in the July 1996 edition of Money.

10 516 Financial Management Fall 2016 an incubated fund over the entirety of its time spent in incubation. Family_Flow i measures the flows of the fund family for fund i over the previous 12 months, excluding the flows attributed to the fund of interest (fund i or the dependent variable) and takes on a rank value of 0.01 to 1.0. Family_Performance i measures performance over the previous 12 months of the incubated fund s family, excluding the performance of the incubated fund of interest (fund i or the dependent variable). Objective_TNA i is the log of total net assets within the objective class for fund i at the time the incubated mutual fund is released to the public, excluding the TNA of the fund of interest (fund i or the dependent variable). Incubation_Risk i is the standard deviation of fund performance during incubation, Front i is the front end load that fund i charges over its incubation period, and Rear i is the rear load that fund i charges over its incubation period. FamilyInc i,t-1 is a dummy variable that takes a value of one if the family of fund i released an incubated mutual fund over the previous 12 months and zero otherwise. The variables of Objective_Flow, Family_TNA, Fund_TNA, Risk, Fees, and Multiple are defined as in Equation (1). B. Results Earlier results that establish the outperformance of mutual funds during incubation as contrived indicates uncertainties surrounding the timing of outperformance (i.e., when will it occur?) and the duration (i.e., how long will it last?). The inability of fund families to control the performance of their incubated mutual funds and the positive inflow response to incubation period performance provide a strong motivation for fund families to launch incubated mutual funds at the first sight of outperformance. In Table VI, we divide the 817 incubated mutual funds in our sample into subgroups based on the length of their incubation: 243 funds are incubated from 7 to 12 months, 320 funds are incubated from 13 to 24 months, and 254 funds are incubated for 25 months or more. Table VI provides a breakdown of performance for each subgroup. The annualized equally weighted objective alpha measure of performance (four-factor alpha) decreases as the incubation period increases, from a high of 6.85% (4.67%) for funds incubated from 7 to 12 months to a low of 0.10% (0.34%) for funds incubated for 25 or more months. In addition, it is the mutual funds that are incubated for the shortest time that attract the most money postincubation. When the 817 incubated mutual funds are further divided into subgroups based on incubation period performance, the results are unchanged. As illustrated in Table VII, there is no pattern to the postincubation performance. However, the funds that outperform during incubation show much greater growth postincubation than the funds that underperform. Taken together, these data indicate that regardless of the length of incubation or the level of incubation period performance, on average, incubated mutual funds tend to revert to an equally weighted objective alpha close to 1% postincubation. Table VIII presents the results of multivariate analysis of the impact of performance and other fund and family characteristics on the likelihood that a mutual fund is released from incubation rather than continuing the incubation process using Equation (3). We examine incubation period performance and the impact of objective and family-level flows. The dependent variable measures the decision to launch an incubated fund to the public in a given month. Consistent with the expectation that fund families take advantage of market conditions to maximize inflows, our results indicate that funds are more likely to be launched when fund performance is high (Incubation Performance), when there is the greatest likelihood of the fund experiencing spillover benefits from a hot family or objective (Objective Flow and Family Flow), and when a fund is charging a higher expense ratio (Fund Expense Ratio). Also of interest is the significant relationship with

11 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 517 Table VI. Descriptive Statistics of Incubation Period Performance and Length of Incubation This table provides the mean and median of incubation period performance and fund characteristics by the length of a fund s incubation. Incubation length is divided into three subgroups of 7 to 12, 13 to 24, and 25+ months. All statistics are presented as during incubation in Panel A and postincubation for a period measuring up to 36 months in Panel B. Performance measures reported include monthly raw returns, an equally weighted objective alpha, a value-weighted objective alpha, and a four-factor alpha (Carhart, 1997). Also reported is the number of funds incubated for each subgroup of length, the average expense ratio, and the total net assets of a fund by incubation length. Postincubation measures are calculated over a period up to the first 36 months a fund is available for public investment. Panel A. Incubation Period Performance by Incubation Length Incubation Length 7 to 12 Months 13 to 24 Months 25+ Months Variable Mean Median Mean Median Mean Median Number of funds Raw returns 15.77% 15.27% 15.06% 15.30% 10.48% 11.82% EW objective alpha 6.85% 2.34% 3.63% 1.64% -0.10% 0.48% VW objective alpha 6.48% 1.64% 2.46% 0.53% 1.17% 0.15% Four-factor alpha 4.67% 0.66% 3.57% 0.68% 0.34% 0.36% Expense ratio 1.52% 1.45% 1.52% 1.50% 1.45% 1.31% Total net assets ($MM) $31.47 $6.48 $23.05 $4.63 $33.49 $3.90 Panel B. Postincubation Period Performance by Incubation Length Number of funds Raw returns 6.19% 11.98% 6.49% 12.05% 6.79% 13.02% EW objective alpha 0.05% 0.15% 0.52% 0.17% 0.14% 0.08% VW objective alpha 0.75% 0.80% 0.23% 0.41% 0.84% 0.50% Four-factor alpha 0.99% 1.04% 0.66% 0.41% 0.30% 1.13% Expense ratio 1.55% 1.44% 1.51% 1.50% 1.43% 1.35% Total net assets ($MM) $ $38.50 $94.86 $24.90 $96.02 $17.65 Family Incubated in Prior Year, which indicates that fund families that are more familiar with the incubation process are willing to launch funds earlier on in their incubation cycle. The results presented in Tables VI, VII, and VIII largely support the view that fund families launch mutual funds quickly once outperformance is achieved. The manufactured nature of incubation period outperformance increases the motivation for fund families to release mutual funds that outperform before their outperformance reverses. The findings relating family and objective flows to incubation length are consistent with the view that mutual funds seek to maximize inflows by continuing to offer investors what they want. Our results indicate that the main determinants of incubation length are revenue driven, specifically the performance of the mutual fund and the demand for the fund s family or objective class at that time. IV. Underperforming Incubated Funds A. Methodology To examine the motivation for releasing an underperforming incubated mutual fund to the public, we examine the determinants for launching a new mutual fund. Based on Chevalier and Ellison (1997), we study the motivations for launching a mutual fund that are based on fulfilling family needs. The decision to launch an incubated fund can be viewed in the same way as the

12 518 Financial Management Fall 2016 Table VII. Descriptive Statistics of Incubation Period Performance and Length of Incubation and Incubation Period Performance This table provides the mean and median of incubation period and postincubation period performance and fund characteristics by the length of a fund s incubation and by incubation period performance. Incubation length is divided into three subgroups of 7 to 12, 13 to 24, and 25+ months. These subgroups are divided further based on a fund s generated incubation period performance. All statistics are presented as during incubation in Panel A and postincubation in Panel B. Performance measures reported include monthly raw returns, an equal and value-weighted objective alpha, and a four-factor alpha (Carhart, 1997). Also reported is the average expense ratio and the total net assets of a fund by incubation length. Postincubation measures are calculated over a period up to thefirst 36 months a fund is available for public investment. Panel A. Incubation Period Performance by Incubation Length Positive Incubation Performance by Length Negative Incubation Performance by Length 7 to to to 36 7 to to Months Months Months Months Months Months Variable Mean Median Mean Median Mean Median Mean Median Mean Median Mean Median Raw returns 54.36% 44.04% 54.48% 41.28% 53.51% 45.08% 54.72% 34.13% 57.42% 28.80% 46.43% 27.60% EW objective alpha 14.88% 8.82% 10.29% 7.50% 6.60% 4.55% 8.18% 5.90% 6.83% 4.56% 5.63% 3.08% VW objective alpha 31.68% 20.53% 27.91% 19.20% 26.87% 17.04% 21.60% 12.42% 23.08% 12.90% 24.24% 15.00% Four-factor alpha 17.28% 10.26% 10.80% 6.66% 6.48% 3.72% 10.30% 6.36% 5.04% 3.48% 4.56% 2.94% Expense ratio 1.49% 1.49% 1.49% 1.49% 1.47% 1.35% 1.79% 1.53% 1.49% 1.50% 1.40% 1.31% TNA ($MM) $28.80 $9.97 $19.22 $6.37 $12.33 $5.55 $34.80 $6.20 $29.06 $6.48 $42.32 $4.49 Panel B. Postincubation Period Performance by Incubation Length Raw returns 10.30% 13.32% 10.21% 13.16% 9.60% 9.83% 6.96% 5.22% 7.00% 14.06% 0.24% 1.00% EW objective alpha 0.72% 0.50% 1.43% 1.03% 0.44% 0.50% 2.16% 1.01% 2.64% 0.96% 1.92% 0.52% VW objective alpha 0.00% 0.00% 0.84% 0.38% 0.16% 0.30% 2.96% 1.84% 2.11% 0.03% 1.61% 0.23% Four-factor alpha 0.22% 0.63% 1.61% 0.00% 0.29% 1.26% 2.61% 2.22% 0.86% 1.44% 0.32% 1.01% Expense ratio 1.49% 1.44% 1.50% 1.49% 1.42% 1.35% 1.59% 1.50% 1.58% 1.50% 1.42% 1.35% TNA ($MM) $ $68.48 $ $37.81 $92.76 $31.43 $79.34 $31.53 $80.60 $19.53 $98.73 $16.15

13 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 519 Table VIII. Determinants of Mutual Fund Incubation Length This table reports the coefficients from the Cox proportional hazard regression model below of incubation length on fund, family, and objective characteristics. Incubation Release i = β 1 Incubation Performance i + β 2 Objective Flow i + β 3 Family Flow i + β 4 Family Performance i + β 5 Objective TNA i + β 6 Family TNA i + β 7 Fund TNA i + β 8 Incubation Risk i + β 9 Fees i + β 10 Front i + β 11 Rear i + β 12 Multiple i + β 13 FamilyInc i + ε i. The dependent variable measures the decision to launch an incubated mutual fund to the public in a given month. Independent variables include incubation period performance measured as an equally weighted objective alpha, a value-weighted objective alpha, or a four-factor alpha (Carhart, 1997), the rank from 0.01 to 1.0 of net dollar flows to the concurrent investment objective over the prior 12 months, the rank from 0.01 to 1.0 of net dollar flows of the family over the prior 12 months, the excess returns of the incubated fund s family over the prior 12 months, the log of the investment objective s total net assets at the time a fund is released from incubation, the log of the incubated fund family s total net assets at the time a fund is released from incubation, the log of the incubated fund s total net assets at the time it is released from incubation, the standard deviation of the incubated mutual fund s monthly returns during incubation, the average expense ratio of the incubated fund over the course of its incubation period, the average front load of the incubated fund over the course of its incubation period, the average rear load of the incubated fund over the course of its incubation period, a dummy variable indicating whether a fund family already had a mutual fund in the incubated fund s objective class, and a dummy variable taking a value of one if the fund family launched an incubated mutual fund over the prior 12 months. Asterisks indicate statistical significance of the coefficients and p-statistics are in parentheses. EW Objective Alpha VW Objective Alpha 4 Factor Alpha Variable Incubation Performance (0.014) (0.000) (0.000) Objective Flow (0.007) (0.013) (0.010) Family Flow (0.000) (0.000) (0.000) Family Performance (0.107) (0.029) (0.286) Objective TNA (0.300) (0.338) (0.321) Family TNA (0.488) (0.556) (0.658) Fund TNA (0.266) (0.218) (0.275) Incubation Risk (0.810) (0.580) (0.451) Fees (0.000) (0.000) (0.000) Front (0.192) (0.178) (0.222) Rear (0.033) (0.063) (0.044) Multiple (0.106) (0.082) (0.135) FamilyInc (0.000) (0.000) (0.135) AIC 9, , , Number of obs Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level.

14 520 Financial Management Fall 2016 decision to exercise an American call option on a dividend paying stock. In other words, a fund family will retain the option to exercise until the fund and market conditions are conducive to maximizing inflows to the fund or the fund s family. This perspective is supported by evidence in the literature indicating that new mutual funds are launched into hot objectives (Ippolito, 1992; Sirri and Tufano, 1998; Khorana and Servaes, 1999) and by existing mutual funds taking advantage of market conditions to maximize inflows (Cooper, Dimitrov, and Rau, 2001; Cooper, Gulen, and Rau, 2005). Accordingly, we do not expect to find underperforming incubated mutual funds launched unless the fund s objective is particularly strong (i.e., attracting large inflows). The motivation for launching an outperforming fund is clear. Inflows follow outperformance. This motivation prompts managers of incubated mutual funds to compete with each other (both within a family and outside) in an attempt to generate top performing funds (Brown, Harlow, and Starks, 1996; Kempf and Ruenzi, 2008; Massa and Patgiri, 2009). It follows that outperforming incubated mutual funds are those that have taken the greatest amount of risk. The relationship between risk and performance during the incubation period may also indicate that certain funds are incubated in an attempt to generate outperformance, such as those that take on additional risk, while other funds are incubated for the ex ante purpose of fulfilling family needs, resulting in decreased risk taking by removing the need to compete on the basis of performance. We perform a logistic regression analysis to examine the existence of underperforming incubated mutual funds. The regression equation is defined as Incubation Under Perform i,t = α i + β 1 Fund TNA i,t + β 2 Family TNA i,t + β 3 Objective TNA i,t + β 4 Incubation Risk i + β 5 Fees i,t + β 6 Incubation Length i + β 7 Market t 1 + β 8 FamilyInc i,t 1 + β 9 Objective Flow i + β 10 Family Flow i,t +β 11 Multiple i,t +ε i, (4) where Incubation_Under_Perform i,t takes a value of one if the mutual fund s incubation period performance is negative and zero otherwise, as measured by objective alphas and a four-factor alpha. By assigning a value of one to negative performance, the regression coefficients represent their relative impact on the likelihood of releasing an underperforming incubated mutual fund. Market t-1 is equal to the S&P 500 market index returns over the previous 12 months. All other independent variables are measured as in Equations (1) and (3). 7 B. Results The results presented earlier in Figure 1 suggest that incubation must serve a purpose in addition to generating a track record of outperformance as 43.33% of all incubated mutual funds in our sample underperform during their time in incubation when measured by an equally weighted objective alpha. The benefits of outperforming during incubation and the increased inflows that follow are already established, both here and in the existing literature, raising the question as to why underperforming incubated mutual funds are released. To identify the determinants of launching an underperforming mutual fund, we examine the relationship between fund, family, and market characteristics and the likelihood of releasing an 7 Control variables were motivated by Reinganum (1985), Sirri and Tufano (1998), Khorana and Servaes (1999), and Evans (2010).

15 Shirley & Stark Why Do Fund Families Release Underperforming Incubated Mutual Funds? 521 Table IX. Determinants of Releasing an Underperforming Incubated Mutual Fund This table reports the coefficients from the logistic regression below of the decision to release an underperforming mutual fund from incubation. Incubation Under Perform i,t = α i + β 1 Fund TNA i,t + β 2 Family TNA i,t + β 3 Objective TNA i,t + β 4 Incubation Risk i + β 5 Fees i,t + β 6 Incubation Length i + β 7 Market t 1 + β 8 FamilyInc i,t 1 + β 9 Objective Flow i + β 10 Family Flow i,t + β 11 Multiple i,t + ε i. The event examined is the decision to release an underperforming fund and coefficients represent the impact of the dependent variable on the likelihood of this occurring. Column 1 measures incubation period performance with an equally weighted objective alpha, Column 2 measures performance with a value-weighted objective alpha, and Column 3 measures performance with a four-factor alpha (Carhart, 1997). Independent variables include the log of fund total net assets, the log of a fund family s total net assets, the log of a fund s objective total net assets, the standard deviation of the incubated mutual fund s monthly returns during incubation, the average fund expense ratio, the length of a fund s incubation period in months, the cumulative returns of the S&P 500 index over the prior 12 months, a dummy variable taking a value of one if the fund family launched an incubated mutual fund over the prior 12 months, the rank of net flows to the concurrent investment objective over the prior 12 months, the rank of net flows of the family over the prior 12 months, and a dummy variable indicating whether a fund family already had a mutual fund in the incubated fund s objective class. Annual fixed effects are included. Asterisks indicate statistical significance of the coefficients and p-statistics are in parentheses. EW Objective Alpha VW Objective Alpha 4 Factor Alpha Variable Intercept (0.251) (0.926) (0.449) Fund TNA (0.011) (0.090) (0.247) Family TNA (0.828) (0.438) (0.125) Objective TNA (0.170) (0.114) (0.414) Incubation Risk (0.000) (0.000) (0.000) Fees (0.150) (0.599) (0.719) Incubation Length (0.063) (0.057) (0.048) Market (0.938) (0.566) (0.778) FamilyInc (0.643) (0.111) (0.441) Objective Flow (0.017) (0.001) (0.045) Family Flow (0.667) (0.379) (0.668) Multiple (0.886) (0.250) (0.216) Fixed effects Yes Yes Yes Adjusted R % 14.17% 13.32% Number of obs Significant at the 0.01 level. Significant at the 0.05 level. Significant at the 0.10 level.

16 522 Financial Management Fall 2016 underperforming fund using a logistic regression, as in Equation (4). We retain one observation for each incubated mutual fund on the date that it applies for a ticker, as indicated in the NASD database. As demonstrated in Table IX, the regression coefficient for the Objective Flow variable is positive and significant. This finding is consistent with Ippolito (1992) and Khorana and Servaes (1999) and indicates that fund families will launch new funds into an objective if that objective is likely to generate sufficient increased inflows to benefit the family, regardless of fund performance. The negative coefficient for Incubation Period Risk indicates that underperforming incubated mutual funds are associated with less risk taking during the incubation period. This finding is consistent with the literature on mutual fund tournaments. Given that top performing funds have an increased likelihood of being launched, a mutual fund will take on additional risk in an attempt to reach the top levels of performance. Since underperforming incubated mutual funds do not take on the same level of risk as their outperforming counterparts, some underperforming funds may be incubated for the ex ante purpose of filling family needs rather than performance needs and, therefore, take on less risk from their inception. The results presented in Table IX are consistent with the view that underperforming incubated mutual funds are released from incubation due to the additional inflows that the mutual fund can generate for the fund family through market demand for the fund s objective rather than through outperformance. V. Conclusion In this paper, we examine how mutual fund incubation is used to benefit fund families. We begin by reexamining some of the results in Evans (2010) using an updated sample that extends from 1999 through September Our sample consists of 3,610 newly launched US domestic equity mutual funds, of which 817 (22.63%) are incubated. Consistent with Evans (2010), we find that, on average, incubated mutual funds generate increased performance during their incubation period, outperforming nonincubated funds by up to 3.41% risk adjusted annually. However, this performance reverses in the postincubation period, which supports the view that incubation is not used to identify skilled managers, but to establish a track record of artificial outperformance. If fund families are not using incubation to identify skilled managers, the benefit to the family from the incubation period outperformance must come in the form of additional inflows. By building on Evans (2010) analysis of the relationship between incubation and subsequent period inflows, we find that investors respond positively to mutual fund incubation and their response is driven by mutual funds with the highest incubation period performance. The recognition that outperformance of an incubated fund is not necessarily based on skill provides increased motivation for fund families to launch outperforming funds before this performance reverses. This view is supported by results from our investigation indicating that outperforming mutual funds are released sooner. The finding that fund families are more likely to introduce new funds into objectives that are doing well and attracting large inflows in an attempt to capture spillover benefits helps to explain incubation length and supports the use of incubation as a way to maximize revenue for the fund family through means in addition to performance. Finally, we look at the existence of underperforming incubated mutual funds. If the primary benefit to incubation is the establishment of a track record of outperformance (Evans, 2010), then underperforming mutual funds should not survive the process. However, in our sample of 3,610 mutual funds, 43.33% of released funds show negative objective alphas for incubation period performance. Our investigation establishes that underperforming funds are being released for

Mutual Fund Incubation *

Mutual Fund Incubation * Mutual Fund Incubation * Richard Evans Darden Graduate School of Business University of Virginia evansr@darden.virginia.edu First Version: March 3, 2007 This Version: March 17, 2009 JEL Classification:

More information

Foreign focused mutual funds and exchange traded funds: Do they improve portfolio management?

Foreign focused mutual funds and exchange traded funds: Do they improve portfolio management? Foreign focused mutual funds and exchange traded funds: Do they improve portfolio management? D. Eli Sherrill a, Sara E. Shirley b, Jeffrey R. Stark c a College of Business Illinois State University Campus

More information

The Use of ETFs by Actively Managed Mutual Funds *

The Use of ETFs by Actively Managed Mutual Funds * The Use of ETFs by Actively Managed Mutual Funds * D. Eli Sherrill Assistant Professor of Finance College of Business, Illinois State University desherr@ilstu.edu 309.438.3959 Sara E. Shirley Assistant

More information

Does portfolio manager ownership affect fund performance? Finnish evidence

Does 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 information

Spillover Effects in Mutual Fund Companies

Spillover Effects in Mutual Fund Companies Clemens Sialm University of Texas at Austin and NBER Mandy Tham Nanyang Technological University January 2012 Motivation Mutual funds are often managed by diversified financial firms that are also active

More information

Azi Ben-Rephael Indiana University

Azi Ben-Rephael Indiana University Are Some Clients More Equal Than Others? Evidence of Price Allocation by Delegated Portfolio Managers (with Ryan D. Israelsen) Azi Ben-Rephael Indiana University Friday, April 25, 2014 MOTIVATION Management

More information

Optimal Debt-to-Equity Ratios and Stock Returns

Optimal 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 information

Sources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As

Sources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As Sources of Financing in Different Forms of Corporate Liquidity and the Performance of M&As Zhenxu Tong * University of Exeter Jian Liu ** University of Exeter This draft: August 2016 Abstract We examine

More information

How to measure mutual fund performance: economic versus statistical relevance

How 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 information

Spillover Effects in Mutual Fund Companies

Spillover Effects in Mutual Fund Companies Clemens Sialm University of Texas at Austin and NBER Mandy Tham Nanyang Technological University March 2012 Finance Down Under Conference Lehman Brothers Example The investment management unit of Lehman

More information

Risk Taking and Performance of Bond Mutual Funds

Risk Taking and Performance of Bond Mutual Funds Risk Taking and Performance of Bond Mutual Funds Lilian Ng, Crystal X. Wang, and Qinghai Wang This Version: March 2015 Ng is from the Schulich School of Business, York University, Canada; Wang and Wang

More information

The ABCs of Mutual Funds: A Natural Experiment on Fund Flows and Performance

The ABCs of Mutual Funds: A Natural Experiment on Fund Flows and Performance The ABCs of Mutual Funds: A Natural Experiment on Fund Flows and Performance Vikram Nanda University of Michigan Business School Z. Jay Wang University of Michigan Business School Lu Zheng University of

More information

New Zealand Mutual Fund Performance

New 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 information

Inexperienced Investors and Bubbles

Inexperienced Investors and Bubbles Inexperienced Investors and Bubbles Robin Greenwood Harvard Business School Stefan Nagel Stanford Graduate School of Business Q-Group October 2009 Motivation Are inexperienced investors more likely than

More information

The evaluation of the performance of UK American unit trusts

The 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 information

Online Appendix to. The Value of Crowdsourced Earnings Forecasts

Online Appendix to. The Value of Crowdsourced Earnings Forecasts Online Appendix to The Value of Crowdsourced Earnings Forecasts This online appendix tabulates and discusses the results of robustness checks and supplementary analyses mentioned in the paper. A1. Estimating

More information

MUTUAL FUND PERFORMANCE ANALYSIS PRE AND POST FINANCIAL CRISIS OF 2008

MUTUAL 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 information

A Portrait of Hedge Fund Investors: Flows, Performance and Smart Money

A Portrait of Hedge Fund Investors: Flows, Performance and Smart Money A Portrait of Hedge Fund Investors: Flows, Performance and Smart Money Guillermo Baquero and Marno Verbeek RSM Erasmus University Rotterdam, The Netherlands mverbeek@rsm.nl www.surf.to/marno.verbeek FRB

More information

Supplementary Appendix for Outsourcing Mutual Fund Management: Firm Boundaries, Incentives and Performance

Supplementary 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 information

Controlling 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 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 information

Determinants of flows into retail international equity funds

Determinants of flows into retail international equity funds (008) 39, 1169 1177 & 008 Academy of International Business All rights reserved 0047-506 www.jibs.net Determinants of flows into retail international equity funds China Europe International Business School,

More information

Active Management in Real Estate Mutual Funds

Active Management in Real Estate Mutual Funds Active Management in Real Estate Mutual Funds Viktoriya Lantushenko and Edward Nelling 1 September 4, 2017 1 Edward Nelling, Professor of Finance, Department of Finance, Drexel University, email: nelling@drexel.edu,

More information

Persistence in Mutual Fund Performance: Analysis of Holdings Returns

Persistence 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 information

Regression Discontinuity and. the Price Effects of Stock Market Indexing

Regression Discontinuity and. the Price Effects of Stock Market Indexing Regression Discontinuity and the Price Effects of Stock Market Indexing Internet Appendix Yen-Cheng Chang Harrison Hong Inessa Liskovich In this Appendix we show results which were left out of the paper

More information

Keywords: Equity firms, capital structure, debt free firms, debt and stocks.

Keywords: 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 information

Investors seeking access to the bond

Investors seeking access to the bond Bond ETF Arbitrage Strategies and Daily Cash Flow The Journal of Fixed Income 2017.27.1:49-65. Downloaded from www.iijournals.com by NEW YORK UNIVERSITY on 06/26/17. Jon A. Fulkerson is an assistant professor

More information

Investor Attrition and Mergers in Mutual Funds

Investor Attrition and Mergers in Mutual Funds Investor Attrition and Mergers in Mutual Funds Susan E. K. Christoffersen University of Toronto and CBS Haoyu Xu* University of Toronto First Draft: March 15, 2013 ABSTRACT: We explore the properties of

More information

Private Equity Performance: Returns, Persistence, and Capital Flows

Private Equity Performance: Returns, Persistence, and Capital Flows THE JOURNAL OF FINANCE VOL. LX, NO. 4 AUGUST 2005 Private Equity Performance: Returns, Persistence, and Capital Flows STEVEN N. KAPLAN and ANTOINETTE SCHOAR ABSTRACT This paper investigates the performance

More information

NBER WORKING PAPER SERIES HOW MUCH DOES SIZE ERODE MUTUAL FUND PERFORMANCE? A REGRESSION DISCONTINUITY APPROACH. Jonathan Reuter Eric Zitzewitz

NBER WORKING PAPER SERIES HOW MUCH DOES SIZE ERODE MUTUAL FUND PERFORMANCE? A REGRESSION DISCONTINUITY APPROACH. Jonathan Reuter Eric Zitzewitz NBER WORKING PAPER SERIES HOW MUCH DOES SIZE ERODE MUTUAL FUND PERFORMANCE? A REGRESSION DISCONTINUITY APPROACH Jonathan Reuter Eric Zitzewitz Working Paper 16329 http://www.nber.org/papers/w16329 NATIONAL

More information

The Consistency between Analysts Earnings Forecast Errors and Recommendations

The 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 information

Decimalization and Illiquidity Premiums: An Extended Analysis

Decimalization 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 information

Mutual fund flows and investor returns: An empirical examination of fund investor timing ability

Mutual fund flows and investor returns: An empirical examination of fund investor timing ability University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln CBA Faculty Publications Business, College of September 2007 Mutual fund flows and investor returns: An empirical examination

More information

Real 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 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 information

Journal of Banking & Finance

Journal of Banking & Finance Journal of Banking & Finance 36 (2012) 1759 1780 Contents lists available at SciVerse ScienceDirect Journal of Banking & Finance journal homepage: www.elsevier.com/locate/jbf The flow-performance relationship

More information

Common Holdings in Mutual Fund Family

Common Holdings in Mutual Fund Family Common Holdings in Mutual Fund Family Jean Chen, Li Xie, and Si Zhou This version: August 30, 2016 ABSTRACT This paper investigates common holding behavior across fund members as a consequence of information

More information

Investor Reaction to the Stock Gifts of Controlling Shareholders

Investor Reaction to the Stock Gifts of Controlling Shareholders Investor Reaction to the Stock Gifts of Controlling Shareholders Su Jeong Lee College of Business Administration, Inha University #100 Inha-ro, Nam-gu, Incheon 212212, Korea Tel: 82-32-860-7738 E-mail:

More information

Explaining After-Tax Mutual Fund Performance

Explaining 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 information

Industry Concentration and Mutual Fund Performance

Industry 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 information

The Role of Credit Ratings in the. Dynamic Tradeoff Model. Viktoriya Staneva*

The Role of Credit Ratings in the. Dynamic Tradeoff Model. Viktoriya Staneva* The Role of Credit Ratings in the Dynamic Tradeoff Model Viktoriya Staneva* This study examines what costs and benefits of debt are most important to the determination of the optimal capital structure.

More information

Sharpening Mutual Fund Alpha

Sharpening Mutual Fund Alpha Sharpening Mutual Fund Alpha Bing Han 1 Chloe Chunliu Yang 2 Abstract We study whether mutual fund managers intentionally adopt negatively skewed strategies to generate superior performance. Using the

More information

Mutual Fund Size versus Fees: When big boys become bad boys

Mutual Fund Size versus Fees: When big boys become bad boys Mutual Fund Size versus Fees: When big boys become bad boys Aneel Keswani * Cass Business School - London Antonio F. Miguel ISCTE Lisbon University Institute Sofia B. Ramos ESSEC Business School Preliminary

More information

Diseconomies of Scope and Mutual Fund Manager Performance. Richard Evans, Javier Gil-Bazo and Marc Lipson*

Diseconomies of Scope and Mutual Fund Manager Performance. Richard Evans, Javier Gil-Bazo and Marc Lipson* Diseconomies of Scope and Mutual Fund Manager Performance by Richard Evans, Javier Gil-Bazo and Marc Lipson* We examine the changes in performance of mutual fund managers that result from changes in the

More information

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 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 information

Are There Disadvantaged Clienteles in Mutual Funds? Evidence from German Mutual Fund Investors

Are There Disadvantaged Clienteles in Mutual Funds? Evidence from German Mutual Fund Investors Are There Disadvantaged Clienteles in Mutual Funds? Evidence from German Mutual Fund Investors Stephan Jank This Draft: January 4, 2010 Abstract This paper studies the flow-performance relationship of

More information

Defined Contribution Pension Plans: Sticky or Discerning Money?

Defined Contribution Pension Plans: Sticky or Discerning Money? Defined Contribution Pension Plans: Sticky or Discerning Money? Clemens Sialm University of Texas at Austin, Stanford University, and NBER Laura Starks University of Texas at Austin Hanjiang Zhang Nanyang

More information

DIVIDEND POLICY AND THE LIFE CYCLE HYPOTHESIS: EVIDENCE FROM TAIWAN

DIVIDEND POLICY AND THE LIFE CYCLE HYPOTHESIS: EVIDENCE FROM TAIWAN The International Journal of Business and Finance Research Volume 5 Number 1 2011 DIVIDEND POLICY AND THE LIFE CYCLE HYPOTHESIS: EVIDENCE FROM TAIWAN Ming-Hui Wang, Taiwan University of Science and Technology

More information

Diseconomies of Scope and Mutual Fund Manager Performance. Richard Evans, Javier Gil-Bazo and Marc Lipson*

Diseconomies of Scope and Mutual Fund Manager Performance. Richard Evans, Javier Gil-Bazo and Marc Lipson* Diseconomies of Scope and Mutual Fund Manager Performance by Richard Evans, Javier Gil-Bazo and Marc Lipson* We examine the changes in performance of mutual fund managers that result from changes in the

More information

Return Reversals, Idiosyncratic Risk and Expected Returns

Return Reversals, Idiosyncratic Risk and Expected Returns Return Reversals, Idiosyncratic Risk and Expected Returns Wei Huang, Qianqiu Liu, S.Ghon Rhee and Liang Zhang Shidler College of Business University of Hawaii at Manoa 2404 Maile Way Honolulu, Hawaii,

More information

Smart Beta #

Smart 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 information

Governance in the U.S. Mutual Fund Industry

Governance in the U.S. Mutual Fund Industry Governance in the U.S. Mutual Fund Industry A Dissertation Presented to The Academic Faculty by Lei Xuan In Partial Fulfillment of the Requirements for the Degree Doctoral of Philosophy in the School of

More information

Sector Fund Performance

Sector 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 information

Do Investors Care about Risk? Evidence from Mutual Fund Flows

Do Investors Care about Risk? Evidence from Mutual Fund Flows Do Investors Care about Risk? Evidence from Mutual Fund Flows Christopher P. Clifford* Gatton College of Business and Economics University of Kentucky Jon A. Fulkerson Sellinger School of Business and

More information

THE DETERMINANTS OF FLOWS INTO RETAIL INTERNATIONAL EQUITY FUNDS *

THE DETERMINANTS OF FLOWS INTO RETAIL INTERNATIONAL EQUITY FUNDS * THE DETERMINANTS OF FLOWS INTO RETAIL INTERNATIONAL EQUITY FUNDS * Xinge Zhao Associate Professor of Finance China Europe International Business School (CEIBS) 699 Hongfeng Road, Pudong Shanghai, China,

More information

Does Investor Care about SEC Comment Letter? Evidence from Mutual Fund Industry

Does Investor Care about SEC Comment Letter? Evidence from Mutual Fund Industry Does Investor Care about SEC Comment Letter? Evidence from Mutual Fund Industry Stig Xenomorph This Draft: July 29, 2018 (Preliminary work; please do not cite or circulate) ABSTRACT The SEC comment letter

More information

How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach *

How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach * How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach * Jonathan Reuter Boston College and NBER Eric Zitzewitz Dartmouth College and NBER First draft: August 2010 Current

More information

Mutual Fund Performance and Flows: The Effects of Liquidity Service Provision and Active Management

Mutual Fund Performance and Flows: The Effects of Liquidity Service Provision and Active Management Mutual Fund Performance and Flows: The Effects of Liquidity Service Provision and Active Management George J. Jiang, Tong Yao and Gulnara Zaynutdinova November 18, 2014 George J. Jiang is from the Department

More information

FUND FLOWS AND PERFORMANCE A Study of Canadian Equity Funds 1

FUND FLOWS AND PERFORMANCE A Study of Canadian Equity Funds 1 FUND FLOWS AND PERFORMANCE A Study of Canadian Equity Funds 1 Rajeeva Sinha Edmond and Louis Odette School of Business University of Windsor Vijay Jog Eric Sprott School of Business Carleton University

More information

Appendix Tables for: A Flow-Based Explanation for Return Predictability. Dong Lou London School of Economics

Appendix Tables for: A Flow-Based Explanation for Return Predictability. Dong Lou London School of Economics Appendix Tables for: A Flow-Based Explanation for Return Predictability Dong Lou London School of Economics Table A1: A Horse Race between Two Definitions of This table reports Fama-MacBeth stocks regressions.

More information

Does MAX Matter for Mutual Funds? *

Does MAX Matter for Mutual Funds? * Does MAX Matter for Mutual Funds? * Bradley A. Goldie Miami University Tyler R. Henry Miami University Haim Kassa Miami University, and U.S. Securities and Exchange Commission This Draft: March 19, 2018

More information

Flow-Performance Relationship and Tournament Behavior in the Mutual Fund Industry

Flow-Performance Relationship and Tournament Behavior in the Mutual Fund Industry Singapore Management University Institutional Knowledge at Singapore Management University Dissertations and Theses Collection (Open Access) Dissertations and Theses 2008 Flow-Performance Relationship

More information

Is Pay for Performance Effective? Evidence from the Hedge Fund Industry. Bing Liang and Christopher Schwarz * This Version: March 2011

Is Pay for Performance Effective? Evidence from the Hedge Fund Industry. Bing Liang and Christopher Schwarz * This Version: March 2011 Is Pay for Performance Effective? Evidence from the Hedge Fund Industry Bing Liang and Christopher Schwarz * This Version: March 2011 First Version: October 2007 Abstract Using voluntary decisions to limit

More information

Stock Liquidity and Default Risk *

Stock Liquidity and Default Risk * Stock Liquidity and Default Risk * Jonathan Brogaard Dan Li Ying Xia Internet Appendix A1. Cox Proportional Hazard Model As a robustness test, we examine actual bankruptcies instead of the risk of default.

More information

How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach *

How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach * How Much Does Size Erode Mutual Fund Performance? A Regression Discontinuity Approach * Jonathan Reuter Boston College and NBER Eric Zitzewitz Dartmouth College and NBER First draft: August 2010 Current

More information

The Free Cash Flow and Corporate Returns

The Free Cash Flow and Corporate Returns Utah State University DigitalCommons@USU All Graduate Plan B and other Reports Graduate Studies 12-2018 The Free Cash Flow and Corporate Returns Sen Na Utah State University Follow this and additional

More information

CFR Working Paper NO Knowledge Spillovers in the Mutual Fund Industry through Labor Mobility. G. Cici A. Kempf C.

CFR Working Paper NO Knowledge Spillovers in the Mutual Fund Industry through Labor Mobility. G. Cici A. Kempf C. CFR Working Paper NO. 18-04 Knowledge Spillovers in the Mutual Fund Industry through Labor Mobility G. Cici A. Kempf C. Peitzmeier Knowledge Spillovers in the Mutual Fund Industry through Labor Mobility

More information

DERIVATIVES, SHORT SELLING AND U.S. EQUITY AND BOND MUTUAL FUNDS. Current Version September 2014

DERIVATIVES, SHORT SELLING AND U.S. EQUITY AND BOND MUTUAL FUNDS. Current Version September 2014 DERIVATIVES, SHORT SELLING AND U.S. EQUITY AND BOND MUTUAL FUNDS by Kaveh Moradi Dezfouli a and Lawrence Kryzanowski b Current Version September 2014 a Dezfouli is a Ph.D. Candidate, John Molson School

More information

This Draft: November 20, 2006

This Draft: November 20, 2006 Managerial Career Concern and Mutual Fund Short-termism Li Jin Harvard Business School Boston, MA 02163 ljin@hbs.edu and Leonid Kogan Sloan School of Management Massachusetts Institute of Technology lkogan@mit.edu.

More information

Bayesian Alphas and Mutual Fund Persistence. Jeffrey A. Busse. Paul J. Irvine * February Abstract

Bayesian Alphas and Mutual Fund Persistence. Jeffrey A. Busse. Paul J. Irvine * February Abstract Bayesian Alphas and Mutual Fund Persistence Jeffrey A. Busse Paul J. Irvine * February 00 Abstract Using daily returns, we find that Bayesian alphas predict future mutual fund Sharpe ratios significantly

More information

Investor Flows and Fragility in Corporate Bond Funds. Itay Goldstein, Wharton Hao Jiang, Michigan State David Ng, Cornell

Investor Flows and Fragility in Corporate Bond Funds. Itay Goldstein, Wharton Hao Jiang, Michigan State David Ng, Cornell Investor Flows and Fragility in Corporate Bond Funds Itay Goldstein, Wharton Hao Jiang, Michigan State David Ng, Cornell Total Net Assets and Dollar Flows of Active Corporate Bond Funds $Billion 2,000

More information

Seasonality in Mutual Fund Flows Hyung-Suk Choi, Ewha Womans University, Korea

Seasonality in Mutual Fund Flows Hyung-Suk Choi, Ewha Womans University, Korea Seasonality in Mutual Fund Flows Hyung-Suk Choi, Ewha Womans University, Korea ABSTRACT In this paper the author established the presence of seasonality in cash flows to U.S. domestic mutual funds. January

More information

Liquidity Risk and Bank Stock Returns. June 16, 2017

Liquidity Risk and Bank Stock Returns. June 16, 2017 Liquidity Risk and Bank Stock Returns Yasser Boualam (UNC) Anna Cororaton (UPenn) June 16, 2017 1 / 20 Motivation Recent financial crisis has highlighted liquidity mismatch on bank balance sheets Run on

More information

Equity ETF Arbitrage and Daily Cash Flow. Jon A. Fulkerson School of Business Administration University of Dayton

Equity ETF Arbitrage and Daily Cash Flow. Jon A. Fulkerson School of Business Administration University of Dayton Equity ETF Arbitrage and Daily Cash Flow Jon A. Fulkerson School of Business Administration University of Dayton 937-229-2404 jfulkerson1@udayton.edu Susan D. Jordan Gatton College of Business and Economics

More information

15 Week 5b Mutual Funds

15 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 information

Incentives behind Side-by-Side Management. of Mutual Funds and Hedge Funds *

Incentives behind Side-by-Side Management. of Mutual Funds and Hedge Funds * Incentives behind Side-by-Side Management of Mutual Funds and Hedge Funds * John Bae, Chengdong Yin, and Xiaoyan Zhang July 2017 Abstract We examine the incentives that motivate management firms to simultaneously

More information

Institutional Money Manager Mutual Funds *

Institutional Money Manager Mutual Funds * Institutional Money Manager Mutual Funds * William Beggs September 1, 2017 Abstract Using Form ADV data, I document the extent to which investment advisers to mutual funds manage accounts and assets for

More information

Liquidity skewness premium

Liquidity 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 information

University of California Berkeley

University of California Berkeley University of California Berkeley A Comment on The Cross-Section of Volatility and Expected Returns : The Statistical Significance of FVIX is Driven by a Single Outlier Robert M. Anderson Stephen W. Bianchi

More information

How Markets React to Different Types of Mergers

How 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 information

Internet Appendix for: Does Going Public Affect Innovation?

Internet Appendix for: Does Going Public Affect Innovation? Internet Appendix for: Does Going Public Affect Innovation? July 3, 2014 I Variable Definitions Innovation Measures 1. Citations - Number of citations a patent receives in its grant year and the following

More information

An Online Appendix of Technical Trading: A Trend Factor

An Online Appendix of Technical Trading: A Trend Factor An Online Appendix of Technical Trading: A Trend Factor In this online appendix, we provide a comparative static analysis of the theoretical model as well as further robustness checks on the trend factor.

More information

ONLINE APPENDIX (NOT FOR PUBLICATION) Appendix A: Appendix Figures and Tables

ONLINE APPENDIX (NOT FOR PUBLICATION) Appendix A: Appendix Figures and Tables ONLINE APPENDIX (NOT FOR PUBLICATION) Appendix A: Appendix Figures and Tables 34 Figure A.1: First Page of the Standard Layout 35 Figure A.2: Second Page of the Credit Card Statement 36 Figure A.3: First

More information

Portfolio Manager Ownership and Fund Performance

Portfolio Manager Ownership and Fund Performance Forthcoming, Journal of Financial Economics Portfolio Manager Ownership and Fund Performance Ajay Khorana Georgia Institute of Technology Henri Servaes * London Business School, CEPR and ECGI Lei Wedge

More information

Fund flows, manager change and performance persistence

Fund flows, manager change and performance persistence Forthcoming Review of Finance Fund flows, manager change and performance persistence Wolfgang Bessler, David Blake, Peter Lückoff, and Ian Tonks Abstract Most empirical studies suggest that mutual funds

More information

GDP, Share Prices, and Share Returns: Australian and New Zealand Evidence

GDP, Share Prices, and Share Returns: Australian and New Zealand Evidence Journal of Money, Investment and Banking ISSN 1450-288X Issue 5 (2008) EuroJournals Publishing, Inc. 2008 http://www.eurojournals.com/finance.htm GDP, Share Prices, and Share Returns: Australian and New

More information

Asubstantial portion of the academic

Asubstantial portion of the academic The Decline of Informed Trading in the Equity and Options Markets Charles Cao, David Gempesaw, and Timothy Simin Charles Cao is the Smeal Chair Professor of Finance in the Smeal College of Business at

More information

in-depth Invesco Actively Managed Low Volatility Strategies The Case for

in-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 information

Excess Cash and Mutual Fund Performance

Excess Cash and Mutual Fund Performance Excess Cash and Mutual Fund Performance Mikhail Simutin The University of British Columbia November 22, 2009 Abstract I document a positive relationship between excess cash holdings of actively managed

More information

Essays 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 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

Premium Timing with Valuation Ratios

Premium Timing with Valuation Ratios RESEARCH Premium Timing with Valuation Ratios March 2016 Wei Dai, PhD Research The predictability of expected stock returns is an old topic and an important one. While investors may increase expected returns

More information

Outsourcing of Mutual Funds Non-core Competencies

Outsourcing of Mutual Funds Non-core Competencies Outsourcing of Mutual Funds Non-core Competencies Christoph Sorhage This Draft: September 2014 ABSTRACT I investigate the consequences for mutual funds operational outcomes when fund families focus their

More information

VALCON Morningstar v. Duff & Phelps

VALCON Morningstar v. Duff & Phelps VALCON 2010 Size Premia: Morningstar v. Duff & Phelps Roger J. Grabowski, ASA Duff & Phelps, LLC Co-author with Shannon Pratt of Cost of Capital: Applications and Examples, 3 rd ed. (Wiley 2008) and 4th

More information

Further 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* 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 information

Predation versus Cooperation in Mutual Fund Families

Predation versus Cooperation in Mutual Fund Families Predation versus Cooperation in Mutual Fund Families Alexander Eisele, Tamara Nefedova, Gianpaolo Parise Abstract In this paper we investigate how mutual funds react to the distress of another fund in

More information

An Assessment of Managerial Skill based on Cross-Sectional Mutual Fund Performance

An 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 information

Do Better Educated Mutual Fund Managers Outperform Their Peers?

Do Better Educated Mutual Fund Managers Outperform Their Peers? 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 22-08-2014

More information

Essays on Open-Ended on Equity Mutual Funds in Thailand

Essays on Open-Ended on Equity Mutual Funds in Thailand Essays on Open-Ended on Equity Mutual Funds in Thailand Roongkiat Ratanabanchuen and Kanis Saengchote* Chulalongkorn Business School ABSTRACT Mutual funds provide a convenient and well-diversified option

More information

Performance-Chasing Behavior in Mutual Funds: New Evidence from Multi-Fund Managers

Performance-Chasing Behavior in Mutual Funds: New Evidence from Multi-Fund Managers Performance-Chasing Behavior in Mutual Funds: New Evidence from Multi-Fund Managers Darwin Choi, HKUST C. Bige Kahraman, SIFR and Stockholm School of Economics Abhiroop Mukherjee, HKUST* August 2012 Abstract

More information

NBER WORKING PAPER SERIES SPILLOVER EFFECTS IN MUTUAL FUND COMPANIES. Clemens Sialm T. Mandy Tham

NBER WORKING PAPER SERIES SPILLOVER EFFECTS IN MUTUAL FUND COMPANIES. Clemens Sialm T. Mandy Tham NBER WORKING PAPER SERIES SPILLOVER EFFECTS IN MUTUAL FUND COMPANIES Clemens Sialm T. Mandy Tham Working Paper 17292 http://www.nber.org/papers/w17292 NATIONAL BUREAU OF ECONOMIC RESEARCH 1050 Massachusetts

More information

Financial Constraints and the Risk-Return Relation. Abstract

Financial Constraints and the Risk-Return Relation. Abstract Financial Constraints and the Risk-Return Relation Tao Wang Queens College and the Graduate Center of the City University of New York Abstract Stock return volatilities are related to firms' financial

More information

The Impact of the Morningstar Sustainability Rating on Mutual Fund Flows

The Impact of the Morningstar Sustainability Rating on Mutual Fund Flows The Impact of the Morningstar Sustainability Rating on Mutual Fund Flows Manuel Ammann a, Christopher Bauer b, Sebastian Fischer c, Philipp Müller d University of St.Gallen First Version: May 5, 2017 This

More information