Internet Appendix to Picking Winners? Investment Consultants Recommendations of Fund Managers

Size: px
Start display at page:

Download "Internet Appendix to Picking Winners? Investment Consultants Recommendations of Fund Managers"

Transcription

1 Internet Appendix to Picking Winners? Investment Consultants Recommendations of Fund Managers TIM JENKINSON, HOWARD JONES, and JOSE VICENTE MARTINEZ * This Internet Appendix includes the following additional information: I. Details on the Greenwich Associates (GA) survey II. III. Details on the evestment database Additional results Table IA.I Additional information on time variation in fees. In Section II (including Table II) of the main article we discuss the time-series variation in fees. In this table we provide more detail on the stability of fees are over time. In 92% of our sample observations, the product fee is exactly the same as in the previous year. This corresponds to a change in fees, on average, no more than once every 12 years. The average absolute annual change in product fee in the sample is less than 1 bp. Table IA.II Additional information on cross-sectional variation in fees. In Section II (including Table II) of the main article we discuss the intrastyle cross-sectional variation in fees. This table shows that there is little intrastyle cross-sectional variation in fees. * Citation format: Jenkinson, Tim, Howard Jones, and Jose Vicente Martinez, Internet Appendix to Picking winners? Investment consultants recommendations of fund managers, Journal of Finance, DOI: /jofi Please note: information supplied by the authors. Any queries (other than missing material) should be directed to the authors of the article. 1

2 Table IA.III Determinants of consultants recommendations using alternative measures of fees. In Section III.A (including Table III) of the main article we discuss various drivers of consultants recommendations, including fees. In this table we reproduce the main results of Table III, using evestment fees (as in the main paper), time-averaged IIS fees (the approach favored by Busse, Goyal, and Wahal (2010)) and actual year-on-year IIS fees (for which the sample is the smallest). Table IA.IV Determinants of consultants recommendations robustness checks. In Section III.A (including Table III) of the main article we discuss the drivers of consultants recommendations, including assets under management (AUM) at time t-1. In Table IA.IV we first interact past performance and soft investment factors (columns (1) and (2)). We next include additional past performance measures in the Poisson regression, specifically one- and three-year excess return rankings and one- and three-year alpha rankings (columns (3) and (4)), although these measures are highly collinear. We also report results of using the GMM estimator of Mullahy (1997) to address potential endogeneity of AUM(t- 1) using AUM(t-2) as an instrument (columns (5) and (6)), to account for the possibility that current recommendations might have been issued a number of months before they appear in the survey, thus affecting AUM(t-1). Table IA.V Investment products and benchmarks. In many of the tables in the main article we report the performance of portfolios of recommended and nonrecommended products against a benchmark. This table shows the benchmark used for each style-size category included in our analysis. 2

3 Table IA.VI Performance of the most versus least recommended funds. In Section III.C (including Table V) of the main article we analyze the performance of recommended versus nonrecommended funds. In this table we run a similar analysis, but only on the recommended funds, separating these funds into the 50% that received the most and the 50% that received the fewest recommendations. Table IA.VII Performance of recommended and nonrecommended products using alternative measures of fees. In Section III.C (including Table V) of the main article we analyze the performance of recommended and nonrecommended products, showing the results gross and net of fees. The fees used are the endof-period fees provided by evestment. In this table we supplement those results by reporting the gross-of-fees and net-of-fees performance of recommended and nonrecommended products using evestment fees (as in the main paper), time-averaged IIS fees (the alternative followed by Busse, Goyal, and Wahal (2010)), or actual year-on-year IIS fees (for which the sample of products is the smallest). Table IA.VIII Additional information on the performance of products recommended by large versus small consultants. To compare the recommendations of large versus small consultants (see Section III.C) of the main article, we make use of a sample of large versus small consultants recommendations that is available only for 1999, 2000, 2001, 2009, 2010, and In each of these six years, Greenwich Associates classifies the 11 to 13 largest consultants, depending on the year, in the large group and the rest in the small group, and keeps a separate 3

4 record for both groups. As we show in Table IA.VIII (Panel A), there does not seem to be much difference between recommendations issued by large versus small consultants. Average product size, average asset management fees, and past performance rankings of recommended products are similar. Large consultants recommend marginally larger and more expensive products but the difference is negligible. In fact, large and small consultants recommendations appear to be highly correlated: the correlation coefficient between the number of recommendations received by a given product from large and small consultants equals More importantly, in the six years we analyze, we do not find any significant differences in the performance of these two sets of recommendations (Panel B). The net-of-fees performance of the portfolio of U.S. actively managed equity products recommended by large investment consultants is indistinguishable from the net-of-fees performance of the products recommended by the smallest consultants in our sample. 4

5 I. The Greenwich Associates Survey Greenwich Associates (GA) has conducted annual surveys of investment consultants since It carries out three main surveys: Domestic Equity, International Equity, and Fixed Income. These surveys focus on actively managed funds; GA does not conduct a separate survey of investment consultants views on passive fund managers. The data we use come from the GA Domestic (U.S.) Equity survey, in which investment consultants are asked to evaluate fund managers, and provide details of their recommendations on fund products. The structure of the GA survey has varied somewhat over time. For our analysis we obtain three types of data from the survey: 1. Rating of each manager, on a five-point scale, on what we term soft investment factors (from which we select clear decision-making, capable portfolio manager, and consistent investment philosophy, which occur in every survey). 2. Rating of each manager, on a five-point scale, on what we term service factors (from which we select capabilities of relationship professionals, usefulness of reports prepared by the fund manager, and effective presentations to consultants, which occur in every survey). 3. A list of four to six fund managers recommended in the following size-style categories: Large Cap Growth, Large Cap Value, Small Cap Growth, Small Cap Value, Mid Cap Growth, Mid Cap Value, and Domestic Equity Core. The GA surveys also include certain non-u.s. categories, as well as categories that are only available for a few years or are not clearly defined in a way that would allow a clean matching with our return data (e.g., U.S. Equity Active Quantitative products); we do not use these categories in our analysis. 5

6 The sections that we do not use include questions related to problems that consultants have with particular managers, the skills of managers in particular areas (some of which, for example, managing country allocation, are irrelevant to a single-country analysis), and the ability of managers to prepare useful thematic studies. We obtain survey data for the 1999 to 2011 period. Prior to 1999 the GA survey does not contain information on investment consultants recommended products. Each year the survey is carried out over a two- to four-month period starting between late November of one year and early January of the next. The number of products recommended is smaller in the early years of the sample because there is no recommendation data on products in the Mid Cap (Value and Growth) and Equity Core product categories in these years. Approximately 21% of the products receive at least one recommendation each year, a percentage that is relatively stable over the entire sample period (apart from the first year). During the same period, an average of 29 investment consultants answered the survey each year, each of them making, on average, 55 recommendations per year across the seven equity categories in our sample. This means that each recommended product received an average of four recommendations. End-of-year asset size data are available for approximately 68% of the total sample. 6

7 II. The evestment Database The returns we obtain for the products in the evestment database are composite returns. The individual returns earned by each client may deviate from these composite returns, but deviations are typically small. 1 Composite returns are net of trading costs, but gross of investment management fees. The data are self-reported by the fund managers, but constant scrutiny from clients using these data guarantees a high degree of accuracy. The return data are free from survivorship bias: like the GA survey, the evestment database retains data for funds that have been discontinued (e.g., because they have been acquired or closed). For each product, the databases also provide cross-sectional information (as of June 2012) on investment style and capitalization bracket, manager-designated benchmark, and the latest fees. See Jones and Martinez (2014) for further information on the evestment databases. 1 For example, some investors may require that their part of the overall portfolio is purged of, say, the influence of tobacco companies or arms manufacturers. 7

8 Table IA.I Product Fees: Time Variation This table shows the fees, in percent per year, for investments of $10 million, $50 million, and $100 million using data provided by Informa Investment Solutions (IIS). We present this information for recommended products, nonrecommended products, and all products in our sample. Fees $10M Fees $50M Fees $100M Rec. Not Rec. All Rec. Not Rec. All Rec. Not Rec. All

9 Table IA.II Product Fees: Cross-Sectional Variation This table shows quintile one (lowest) and quintile five (highest) average fees for an investment of $50 million, and their difference, for the institutional investment products used in our study. These statistics are computed using fees as of 2011 from the evestment database (the last year of our sample), and using fees averaged over the 1999 to 2011 period from Informa Investment Solutions (IIS). Fees are in percent per year. evestment - $50M IIS - $50M Q1 Q5 Diff Q1 Q5 Diff Large Cap Growth Large Cap Value Mid Cap Growth Mid Cap Value Small Cap Growth Small Cap Value Core Average All Cat. Combined

10 Table IA.III What Drives Consultants' Recommendations: Alternative Fee Measures This table reports results of pooled time-series cross-sectional Poisson and negative binomial regressions of the number of investment consultants recommendations received by a product on past gross performance measures, alternative asset management fee measures, and variables capturing soft investment and service characteristics of the asset managers as perceived by the consultants. Soft investment factors and service factors are expressed using the fractional rank of each asset manager in the sample. An asset manager's fractional rank, for a given variable, represents its percentile rank relative to other asset managers in the same period, and ranges from zero to one. Past gross performance measures (excess returns over benchmarks and three-factor alphas) are expressed using the fractional rank of each product in its investment category. Fee measures are also expressed using the fractional rank of each product in its investment category and include evestment fees as of the end of the sample period (or latest available), average IIS fees, and IIS fees as at the end of the year preceding each survey. All regressions also include a lagged measure of return volatility, lagged assets under management (in $ billions), and a full set of time dummies. Each column represents a separate regression. z-scores based on standard errors clustered at the product level are included in parentheses. The second part of the table displays model-implied average marginal effects and the bottom part shows the squared correlation between observed recommendations and modelpredicted ones together with the number of observations in each regression. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. evestment (T) IIS (Av. t) IIS (t-1) (1) (2) (3) (4) (5) (6) Poisson Poisson Poisson Poisson Poisson Poisson Soft Investment Factors (t) (17.18)*** (17.25)*** (14.43)*** (14.54)*** (14.19)*** (14.32)*** Service Factors (t) (3.49)*** (3.43)*** (3.28)*** (3.22)*** (3.23)*** (3.17)*** Past Performance Rank - Return (t) (3.03)*** (3.01)*** (3.18)*** Past Performance Rank - Alpha (t) (2.23)** (2.35)** (2.58)*** Fees (T, Av. t, and t-1) (4.08)*** (4.07)*** (2.87)*** (2.82)*** (2.55)** (2.51)** Assets Under Management (t-1) (9.22)*** (8.83)*** (8.95)*** (8.48)*** (9.11)*** (8.64)*** Return Volatility (t-1) (1.01) (0.73) (0.68) (0.41) (0.74) (0.45) Average Marginal Effects Soft Investment Factors (t) 5.78*** 5.84*** 6.30*** 6.37*** 6.35*** 6.42*** Service Factors (t) 1.04*** 1.03*** 1.28*** 1.27*** 1.27*** 1.26*** Past Performance Rank - Return (t) 0.56*** 0.67*** 0.71** Past Performance Rank - Alpha (t) 0.39** 0.49** 0.55*** Fees (T, Av. t, and t-1) 1.16*** 1.16*** 1.06*** 1.04*** 0.91** 0.90** Assets Under Management (t-1) 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** 0.05*** Return Volatility (t-1) Squared Corr (Y; Ŷ) Number of observations 3,507 3,507 2,675 2,675 2,624 2,624 10

11 Table IA.IV What Drives Consultants Recommendations: Robustness Checks This table reports results of pooled time-series cross-sectional Poisson regressions of the number of investment consultants recommendations received by a product on past gross performance measures, asset management fees, and variables capturing soft investment and service characteristics of the asset managers as perceived by the consultants. Soft investment factors and service factors are expressed using the fractional rank of each asset manager in the sample. An asset manager's fractional rank for a given variable represents its percentile rank relative to other asset managers in the same period, and ranges from zero to one. Past gross performance measures (excess returns over benchmarks and three-factor alphas over several horizons) and fees (as at the end of the sample period) are expressed using the fractional rank of each product in its investment category. All regressions also include a lagged measure of return volatility, lagged assets under management (in U.S. $ billions), and a full set of time dummies. Each column represents a separate regression. Columns (5) and (6) report the results using the GMM estimator of Mullahy (1997) to address potential endogeneity of AUM(t-1) using AUM (t-2) as an instrument. z-scores based on standard errors clustered at the product level are included in parentheses. The second part of the table displays model-implied average marginal effects and the bottom part shows the squared correlation between observed recommendations and model-predicted ones together with the number of observations in each regression. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. (1) (2) (3) (4) (5) (6) Poisson Poisson Poisson Poisson IV Poisson GMM IV Poisson GMM Soft Investment Factors (t) (10.54)*** (11.47)*** (17.18)*** (17.03)*** (19.13)*** (19.54)*** Service Factors (t) (3.52)*** (3.43)*** (3.49)*** (3.66)*** (1.75)* (1.60) 1 Y Excess Return Rank (t) 0.09 (0.91) 2 Y Excess Return Rank (t) (-0.61) (2.08)** (2.27)** 3 Y Excess Return Rank (t) 0.19 (1.37) 1 Y Alpha Rank (t) -0.31*** (-3.30) 2 Y Alpha Rank (t) (-0.17) (-0.08) (0.72) 3 Y Alpha Rank (t) 0.26 (1.92)* 2 Y Exc. Ret. Rank (t) * SIF (t) 0.52 (1.66)* 2 Y Alpha Rank (t) * SIF (t) 0.29 (0.95) Fees (T) (4.08)*** (4.05)*** (4.11)*** (3.89)*** (7.02)*** (7.06)*** Assets Under Management (t-1) (9.44)*** (8.88)*** (9.24)*** (9.25)*** (7.58)*** (7.51)*** Return Volatility (t-1) (1.04) (0.72) (1.00) (1.22) (2.79)*** (2.91)*** 11

12 Table IA.IV (continued) Average Marginal Effects Soft Investment Factors (t) 5.12*** 5.48*** 5.78*** 5.81*** 7.20*** 7.34*** Service Factors (t) 1.05*** 1.03*** 1.04*** 1.10*** 0.64* 0.59*** 1 Y Excess Return Rank (t) Y Excess Return Rank (t) ** 0.57** 3 Y Excess Return Rank (t) Y Alpha Rank (t) -0.76*** 2 Y Alpha Rank (t) Y Alpha Rank (t) 0.63* 2 Y Exc. Ret. Rank (t) * SIF (t) 1.26* 2 Y Alpha Rank (t) * SIF (t) 0.70 Fees (t) 1.16*** 1.16*** 1.17*** 1.11*** 1.65*** 1.65*** Assets Under Management (t-1) 0.05*** 0.05*** 0.05*** 0.05*** 0.14*** 0.14*** Return Volatility (t-1) *** 9.14*** Squared Corr (Y; Ŷ) Number of observations 3,507 3,507 3,507 3,399 3,268 3,268 Large Cap Growth Large Cap Value Mid Cap Growth Mid Cap Value Small Cap Growth Small Cap Value Table IA.V Investment Products and Benchmarks Investment Product Benchmark Russell 1000 Growth Russell 1000 Value Russell Midcap Growth Russell Midcap Value Russell 2000 Growth Russell 2000 Value Domestic Equity Core - All Cap Russell 3000 Domestic Equity Core - Large Cap Russell 1000 Domestic Equity Core - Mid Cap Russell Midcap 12

13 Table IA.VI Performance of Most Recommended and Least This table shows the performance of portfolios of U.S. actively managed equity products recommended by the investment consultants in our sample during the 1999 to 2011 period. Portfolios analyzed are the portfolio of the 50% most frequently recommended products, the portfolio of the 50% least frequently recommended products, and their difference. Performance is measured using raw returns, returns in excess of a benchmark chosen to match the product style and market capitalization, and one-, three-, and four-factor alphas (corresponding to the CAPM, the Fama-French three-factor model, and the Fama-French-Carhart model). Excess returns and alphas are expressed in percent per year. These statistics are computed on monthly returns and annualized by multiplying returns and alphas by 12. All reported figures are net of management fees. The first part of the table shows the results for equally weighted portfolios of products and the second part of the table shows the same statistics for portfolios of products weighted using total net assets at the end of the previous year. t-statistics based on standard errors, robust to conditional heteroskedasticity and serial correlation of up to two lags as in Newey and West (1987), are reported in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. Equally Most Frequently Least Frequently Avg. Returns Avg. Excess Ret. over Benchmark One-Factor Alpha Three-Factor Alpha Four-Factor Alpha 5.98% 0.41% 1.29% 0.15% 0.16% (1.18) (0.74) (1.43) (0.18) (0.19) 7.89% 1.01% 3.16% 1.59% 1.53% (1.51) (1.81)* (2.71)*** (1.60) (1.50) Difference -1.91% -0.61% -1.87% -1.44% -1.37% (-2.59)** (-1.96)* (-2.59)** (-2.22)** (-2.23)** Value Most Frequently Least Frequently 4.28% 0.38% -0.44% -0.17% -0.18% (0.85) (0.46) (-0.52) (-0.20) (-0.21) 4.95% 0.58% 0.30% -0.18% -0.13% (0.99) (0.77) (0.36) (-0.20) (-0.14) Difference -0.67% -0.21% -0.74% 0.01% -0.05% (-0.77) (-0.33) (-0.84) (0.01) (-0.06) 13

14 Table IA.VII Net Performance of Recommended and Nonrecommended Products This table shows the net-of-fees performance of the portfolio of all U.S. actively managed equity products recommended by the investment consultants in our sample during the 1999 to 2011 period, as well as the net-of-fees performance of institutional products not recommended by any of the consultants. The table also shows the difference in performance between the two. Performance is measured using raw returns, returns in excess of a benchmark chosen to match the product style and market capitalization, and one-, three-, and four-factor alphas (corresponding to the CAPM, the Fama-French (1993) three-factor model, and the Fama- French-Carhart (1997) model). Excess returns and alphas are expressed in percent per year. These statistics are computed on monthly returns and annualized by multiplying returns and alphas by 12. Results reported in Panel A are based on end-of-sample evestment fees, results in Panel B are based on Informa Investment Solutions (IIS) time-averaged product fees, and results in Panel C are based on IIS product fees (not averaged). The table shows the results for equally weighted portfolios of products and for portfolios of products weighted using total net assets at the end of the previous year. t-statistics based on standard errors, robust to conditional heteroskedasticity and serial correlation of up to two lags as in Newey and West (1987), are reported in parentheses. ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. Equally Value Nonrecommended Products Recommended Non recommended Products Nonrecommended Products Recommended Nonrecommended Products Avg. Returns Avg. Excess Ret. over Benchmark One-Factor Alpha Three-Factor Alpha Four-Factor Alpha Panel A: evestment Fees 6.31% 0.51% 1.62% 0.39% 0.39% (1.24) (0.95) (1.77)* (0.48) (0.46) 7.43% 1.67% 2.82% 1.36% 1.30% (1.51) (2.58)** (2.87)*** (1.70)* (1.58) -1.12% -1.17% -1.21% -0.97% -0.92% (-2.29)** (-3.16)*** (-2.70)*** (-2.41)** (-2.38)** 4.29% 0.36% -0.43% -0.18% -0.18% (0.85) (0.46) (-0.52) (-0.21) (-0.22) 4.51% -0.11% -0.10% -0.97% -0.88% (0.93) (-0.16) (-0.11) (-1.23) (-1.16) -0.22% 0.48% -0.33% 0.79% 0.70% (-0.18) (0.58) (-0.27) (0.82) (0.76) 14

15 Table IA.VII (continued) Equally Value Panel B: IIS Average Fees 6.78% 0.84% 2.09% 0.75% 0.76% (1.33) (1.50) (2.13)** (0.89) (0.88) Nonrecommended Products 8.01% 1.99% 3.42% 1.80% 1.75% (1.64) (3.05)*** (3.17)*** (2.14)** (2.02)** Recommended Nonrecommended Products -1.23% -1.15% -1.33% -1.05% -0.99% (-2.78)*** (-3.10)*** (-3.51)*** (-3.07)*** (-3.00)*** 4.35% 0.47% -0.37% -0.16% -0.16% (0.86) (0.58) (-0.45) (-0.20) (-0.20) Nonrecommended Products 4.99% 0.13% 0.39% -0.56% -0.43% (1.03) (0.18) (0.38) (-0.63) (-0.50) Recommended Nonrecommended Products -0.64% 0.34% -0.76% 0.40% 0.27% (-0.48) (0.40) (-0.58) (0.39) (0.27) Equally Value Panel C: IIS Fees 6.78% 0.84% 2.09% 0.75% 0.76% (1.33) (1.51) (2.13)** (0.89) (0.88) Nonrecommended Products 8.02% 2.00% 3.42% 1.80% 1.76% (1.64) (3.08)*** (3.15)*** (2.14)** (2.03)** Recommended Nonrecommended Products -1.23% -1.16% -1.33% -1.05% -0.99% (-2.83)*** (-3.12)*** (-3.57)*** (-3.13)*** (-3.04)*** 4.36% 0.47% -0.36% -0.16% -0.15% (0.86) (0.58) (-0.44) (-0.19) (-0.19) Nonrecommended Products 4.90% 0.02% 0.32% -0.63% -0.48% (1.01) (0.02) (0.28) (-0.67) (-0.54) Recommended Nonrecommended Products -0.55% 0.45% -0.68% 0.47% 0.32% (-0.39) (0.52) (-0.50) (0.45) (0.32) 15

16 Table IA.VIII Large Versus Small Consultants Panel A of this table presents descriptive statistics on the sample of institutional investment products recommended by large and small investment consultants. Average asset size is in millions of U.S. dollars. Fees, for the management of U.S. $50 million, are in percent per year (source: evestment). All averages are weighted by the number of recommendations. Panel B shows the net-of-fees performance of the portfolio of U.S. actively managed equity products recommended by large and small investment consultants in our sample. Performance is measured using returns in excess of a benchmark chosen to match the product style and market capitalization, and one-, three-, and four-factor alphas (corresponding to the CAPM, the Fama-French three-factor model, and the Fama-French-Carhart model). Excess returns and alphas are expressed in percent per year. The table shows the results for equally weighted portfolios of products and for portfolios of products weighted using total net assets at the end of the previous year. t-statistics based on standard errors, robust to conditional heteroskedasticity and serial correlation of up to two lags as in Newey and West (1987), are reported in parentheses. Sample period: 1999 to 2001 and 2009 to ***, **, and * denote statistical significance at the 1%, 5%, and 10% levels, respectively. Equally Value Average Product Asset Size Panel A - Descriptive Statistics Average Product Fee ($50M) Average Past Gross Performance - Excess Return Percentile Average Past Gross Performance - Alpha Percentile Large Consultants 5, Small Consultants 5, Large Consultants Small Consultants Difference Large Consultants Small Consultants Difference Avg. Excess Ret. over Benchmark Panel B - Recommendations' Performance: Net Returns One Factor Alpha Three Factor Alpha Four Factor Alpha 1.07% 2.97% 0.99% 1.00% (1.26) (1.83)* (0.89) (0.88) 1.62% 3.38% 1.36% 1.40% (1.86)* (2.05)** (1.36) (1.39) -0.55% -0.42% -0.38% -0.41% (-1.70)* (-1.12) (-1.13) (-1.25) 1.33% -0.14% 0.40% 0.41% (0.83) (-0.06) (0.18) (0.46) 1.36% -0.63% -0.08% 0.01% (0.94) (-0.37) (-0.05) (0.01) -0.03% 0.48% 0.47% 0.40% (0.10) (0.58) (0.72) (0.64) 16

17 REFERENCES Busse, Jeffrey, Amit Goyal, and Sunil Wahal, 2010, Performance and persistence in institutional investment management, Journal of Finance 65, Carhart, Mark, 1997, On persistence in mutual fund performance, Journal of Finance 52, Fama, Eugene, and Kenneth French, 1993, Common risk factors in the returns on stocks and bonds, Journal of Financial Economics 33, Jones, Howard, and Jose Martinez, 2014, Institutional investor expectations, manager performance, and fund flows, Working paper, University of Oxford. Mullahy, John, 1997, Instrumental-variable estimation of count data models: Applications to models of cigarette smoking behavior, Review of Economics and Statistics 79, Newey, Whitney K., and Kenneth D. West, 1987, A simple, positive semi-definite, heteroskedasticity and autocorrelation consistent covariance matrix, Econometrica 55,

Picking winners? Investment consultants' recommendations of fund managers

Picking winners? Investment consultants' recommendations of fund managers Picking winners? Investment consultants' recommendations of fund managers Tim Jenkinson, Howard Jones, and Jose Vicente Martinez 1 Abstract U.S. plan sponsors managing over $13 trillion rely on investment

More information

Pension funds and their investment consultants

Pension funds and their investment consultants Pension funds and their investment consultants Tim Jenkinson Professor of Finance Director, Private Equity Institute May 2014 A mystery Academic evidence, and industry analysis,over several decades has

More information

Picking winners? Investment consultants' recommendations of fund managers

Picking winners? Investment consultants' recommendations of fund managers Picking winners? Investment consultants' recommendations of fund managers Tim Jenkinson, Howard Jones, and Jose Vicente Martinez* Abstract Investment consultants advise plan sponsors how to invest $25

More information

Internet Appendix. Individual Investors and Local Bias *

Internet Appendix. Individual Investors and Local Bias * Internet Appendix for Individual Investors and Local Bias * This internet appendix presents supplemental analyses and results to the main tables in Individual Investors and Local Bias. The additional results

More information

Internet Appendix for When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks * Tim Loughran and Bill McDonald

Internet Appendix for When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks * Tim Loughran and Bill McDonald Internet Appendix for When is a Liability not a Liability? Textual Analysis, Dictionaries, and 10-Ks * Tim Loughran and Bill McDonald In the Internet Appendix we provide a detailed description of the parsing

More information

Internet Appendix for Institutional Trade Persistence and Long-term Equity Returns

Internet Appendix for Institutional Trade Persistence and Long-term Equity Returns Internet Appendix for Institutional Trade Persistence and Long-term Equity Returns AMIL DASGUPTA, ANDREA PRAT, and MICHELA VERARDO Abstract In this document we provide supplementary material and robustness

More information

Internet Appendix to Payout Taxes and the Allocation of Investment 1

Internet Appendix to Payout Taxes and the Allocation of Investment 1 Internet Appendix to Payout Taxes and the Allocation of Investment 1 Table IA.I Average Investment and Cash Flow around 2000/2001 German Tax Reform This table shows the average investment for bottom and

More information

DOES IT PAY TO HAVE FAT TAILS? EXAMINING KURTOSIS AND THE CROSS-SECTION OF STOCK RETURNS

DOES IT PAY TO HAVE FAT TAILS? EXAMINING KURTOSIS AND THE CROSS-SECTION OF STOCK RETURNS DOES IT PAY TO HAVE FAT TAILS? EXAMINING KURTOSIS AND THE CROSS-SECTION OF STOCK RETURNS By Benjamin M. Blau 1, Abdullah Masud 2, and Ryan J. Whitby 3 Abstract: Xiong and Idzorek (2011) show that extremely

More information

Internet Appendix to Stock Market Liquidity and the Business Cycle

Internet Appendix to Stock Market Liquidity and the Business Cycle Internet Appendix to Stock Market Liquidity and the Business Cycle Randi Næs, Johannes A. Skjeltorp and Bernt Arne Ødegaard This Internet appendix contains additional material to the paper Stock Market

More information

Performance and Persistence in Institutional Investment Management

Performance and Persistence in Institutional Investment Management THE JOURNAL OF FINANCE VOL. LXV, NO. 2 APRIL 2010 Performance and Persistence in Institutional Investment Management JEFFREY A. BUSSE, AMIT GOYAL, and SUNIL WAHAL ABSTRACT Using new, survivorship bias-free

More information

Online appendix to paper Downside Market Risk of Carry Trades

Online appendix to paper Downside Market Risk of Carry Trades Online appendix to paper Downside Market Risk of Carry Trades A1. SUB-SAMPLE OF DEVELOPED COUNTRIES I study a sub-sample of developed countries separately for two reasons. First, some of the emerging countries

More information

Active vs. Passive Asset Management Investigation Of The Asset Class And Manager Selection Decisions

Active vs. Passive Asset Management Investigation Of The Asset Class And Manager Selection Decisions Active vs. Passive Asset Management Investigation Of The Asset Class And Manager Selection Decisions Jianan Du, Quantitative Research Analyst, Quantitative Research Group, Envestnet PMC Janis Zvingelis,

More information

Internet Appendix to The Effect of SOX Section 404: Costs, Earnings Quality and Stock Prices *

Internet Appendix to The Effect of SOX Section 404: Costs, Earnings Quality and Stock Prices * Internet Appendix to The Effect of SOX Section 404: Costs, Earnings Quality and Stock Prices * Contents A Section 404 of the Sarbanes Oxley Act of 2002 2 B SEC Regulation 2 C Discretionary Accruals Measures

More information

What Level of Incentive Fees Are Hedge Fund Investors Actually Paying?

What Level of Incentive Fees Are Hedge Fund Investors Actually Paying? What Level of Incentive Fees Are Hedge Fund Investors Actually Paying? Abstract Long-only investors remove the effects of beta when analyzing performance. Why shouldn t long/short equity hedge fund investors

More information

The term structure of equity option implied volatility

The term structure of equity option implied volatility The term structure of equity option implied volatility Christopher S. Jones Tong Wang Marshall School of Business Marshall School of Business University of Southern California University of Southern California

More information

B.3. Robustness: alternative betas estimation

B.3. Robustness: alternative betas estimation Appendix B. Additional empirical results and robustness tests This Appendix contains additional empirical results and robustness tests. B.1. Sharpe ratios of beta-sorted portfolios Fig. B1 plots the Sharpe

More information

Cash Holdings and Mutual Fund Performance. Online Appendix

Cash Holdings and Mutual Fund Performance. Online Appendix Cash Holdings and Mutual Fund Performance Online Appendix Mikhail Simutin Abstract This online appendix shows robustness to alternative definitions of abnormal cash holdings, studies the relation between

More information

Luck versus Skill in the Cross-Section of Mutual Fund Returns

Luck versus Skill in the Cross-Section of Mutual Fund Returns THE JOURNAL OF FINANCE VOL. LXV, NO. 5 OCTOBER 2010 Luck versus Skill in the Cross-Section of Mutual Fund Returns EUGENE F. FAMA and KENNETH R. FRENCH ABSTRACT The aggregate portfolio of actively managed

More information

The cross section of expected stock returns

The cross section of expected stock returns The cross section of expected stock returns Jonathan Lewellen Dartmouth College and NBER This version: August 2014 Forthcoming in Critical Finance Review Tel: 603-646-8650; email: jon.lewellen@dartmouth.edu.

More information

Value versus Growth in the UK Stock Market, 1955 to 2000

Value versus Growth in the UK Stock Market, 1955 to 2000 Value versus Growth in the UK Stock Market, 1955 to 2000 Elroy Dimson London Business School Stefan Nagel London Business School Garrett Quigley Dimensional Fund Advisors May 2001 Work in progress Preliminary

More information

What Drives the Performance of US Convertible Bond Funds?

What Drives the Performance of US Convertible Bond Funds? What Drives the Performance of US Convertible Bond Funds? Manuel Ammann, Axel Kind, and Ralf Seiz May 2006 Abstract This paper examines the return characteristics of US mutual funds investing primarily

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 Laura Starks University of Texas at Austin Hanjiang Zhang Nanyang Technological University, Singapore

More information

Appendices with Supplementary Materials for CAPM for Estimating Cost of Equity Capital: Interpreting the Empirical Evidence

Appendices with Supplementary Materials for CAPM for Estimating Cost of Equity Capital: Interpreting the Empirical Evidence Appendices with Supplementary Materials for CAPM for Estimating Cost of Equity Capital: Interpreting the Empirical Evidence This document contains supplementary material to the paper titled CAPM for estimating

More information

The Case For Passive Investing!

The Case For Passive Investing! The Case For Passive Investing! Aswath Damodaran Aswath Damodaran! 1! The Mechanics of Indexing! Fully indexed fund: An index fund attempts to replicate a market index. It is relatively simple to create,

More information

Internet Appendix to Who Gambles In The Stock Market?

Internet Appendix to Who Gambles In The Stock Market? Internet Appendix to Who Gambles In The Stock Market? In this appendix, I present background material and results from additional tests to further support the main results reported in the paper. A. Profile

More information

Stock Return Momentum and Investor Fund Choice

Stock Return Momentum and Investor Fund Choice Stock Return Momentum and Investor Fund Choice TRAVIS SAPP and ASHISH TIWARI* Journal of Investment Management, forthcoming Keywords: Mutual fund selection; stock return momentum; investor behavior; determinants

More information

New Zealand mutual funds: measuring performance and persistence in performance

New Zealand mutual funds: measuring performance and persistence in performance Accounting and Finance 46 (2006) 347 363 New Zealand mutual funds: measuring performance and persistence in performance Rob Bauer a,rogér Otten b, Alireza Tourani Rad c a ABP Investments and Limburg Institute

More information

The Performance of Thai Mutual Funds: A 5-Star Morningstar Mutual Fund Rating

The Performance of Thai Mutual Funds: A 5-Star Morningstar Mutual Fund Rating The Performance of Thai Mutual Funds: A 5-Star Morningstar Mutual Fund Rating Chollaya Chotivetthamrong Abstract Due to Tax-benefit from Thai government s regulation, most of investors are interested in

More information

General Information about Factor Models. February 2014

General Information about Factor Models. February 2014 February 2014 Factor Analysis: What Drives Performance? Financial factor models were developed in an attempt to answer the question: What really drives performance? Based on the Arbitrage Pricing Theory,

More information

Luck versus Skill in the Cross Section of Mutual Fund Returns. Eugene F. Fama and Kenneth R. French * Forthcoming in the Journal of Finance.

Luck versus Skill in the Cross Section of Mutual Fund Returns. Eugene F. Fama and Kenneth R. French * Forthcoming in the Journal of Finance. First draft: October 2007 This draft: December 2009 Not for quotation: Comments welcome Luck versus Skill in the Cross Section of Mutual Fund Returns Eugene F. Fama and Kenneth R. French * Forthcoming

More information

Investment Policy Statement

Investment Policy Statement Investment Policy Statement Prepared on: February 04, 2013 Prepared for: Sample Individual Client 432 Elm St Chicago IL 60630 Executive Summary Client Name: Sample Individual Client Client Type: Individual

More information

Manager Structure Presentation

Manager Structure Presentation Presentation to the Tobacco Settlement Investment Board May 18, 2009 Millie Viqueira Senior Vice President Jay Kloepfer Executive Vice President Callan Associates Inc. 200 Park Avenue, Suite 230 Florham

More information

Glossary of Investment Terms

Glossary of Investment Terms online report consulting group Glossary of Investment Terms glossary of terms actively managed investment Relies on the expertise of a portfolio manager to choose the investment s holdings in an attempt

More information

Volume autocorrelation, information, and investor trading

Volume autocorrelation, information, and investor trading Journal of Banking & Finance 28 (2004) 2155 2174 www.elsevier.com/locate/econbase Volume autocorrelation, information, and investor trading Vicentiu Covrig a, Lilian Ng b, * a Department of Finance, RE

More information

Portfolio Manager Compensation in the U.S. Mutual Fund Industry

Portfolio Manager Compensation in the U.S. Mutual Fund Industry Discussion of Portfolio Manager Compensation in the U.S. Mutual Fund Industry Linlin Ma Yuehua Tang Juan-Pedro Gómez WFA 2015 Jonathan Reuter Boston College & NBER What Does the Paper Do? Uses hand-collected

More information

No More Weekend Effect

No More Weekend Effect No More Weekend Effect Russell P. Robins 1 and Geoffrey Peter Smith 2 1 AB Freeman School of Business, Tulane University 2 WP Carey School of Business, Arizona State University Abstract Before 1975, the

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 Administration, College of 9-1-2007 Mutual fund flows and investor returns: An empirical

More information

Mutual fund attributes and their relationship to riskadjusted return: A study on the performance and characteristics on the Swedish fund market

Mutual fund attributes and their relationship to riskadjusted return: A study on the performance and characteristics on the Swedish fund market STOCKHOLM SCHOOL OF ECONOMICS Master Thesis in Finance Mutual fund attributes and their relationship to riskadjusted return: A study on the performance and characteristics on the Swedish fund market Johan

More information

Uncertainty in Second Moments: Implications for Portfolio Allocation

Uncertainty in Second Moments: Implications for Portfolio Allocation Uncertainty in Second Moments: Implications for Portfolio Allocation David Daewhan Cho SUNY at Buffalo, School of Management September 2003 Abstract This paper investigates the uncertainty in variance

More information

Uninformative Feedback and Risk Taking: Evidence from Retail Forex Trading

Uninformative Feedback and Risk Taking: Evidence from Retail Forex Trading Uninformative Feedback and Risk Taking: Evidence from Retail Forex Trading Itzhak Ben-David Fisher College of Business, The Ohio State University, and NBER Justin Birru Fisher College of Business, The

More information

Stock Prices and Institutional Holdings. Adri De Ridder Gotland University, SE-621 67 Visby, Sweden

Stock Prices and Institutional Holdings. Adri De Ridder Gotland University, SE-621 67 Visby, Sweden Stock Prices and Institutional Holdings Adri De Ridder Gotland University, SE-621 67 Visby, Sweden This version: May 2008 JEL Classification: G14, G32 Keywords: Stock Price Levels, Ownership structure,

More information

Internet Appendix to Collateral Spread and Financial Development *

Internet Appendix to Collateral Spread and Financial Development * Internet Appendix to Collateral Spread and Financial Development * This online appendix serves as a companion to our paper Collateral Spread and Financial Development. It reports results not reported in

More information

Internet Appendix to False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas

Internet Appendix to False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas Internet Appendix to False Discoveries in Mutual Fund Performance: Measuring Luck in Estimated Alphas A. Estimation Procedure A.1. Determining the Value for from the Data We use the bootstrap procedure

More information

Do Direct Stock Market Investments Outperform Mutual Funds? A Study of Finnish Retail Investors and Mutual Funds 1

Do Direct Stock Market Investments Outperform Mutual Funds? A Study of Finnish Retail Investors and Mutual Funds 1 LTA 2/03 P. 197 212 P. JOAKIM WESTERHOLM and MIKAEL KUUSKOSKI Do Direct Stock Market Investments Outperform Mutual Funds? A Study of Finnish Retail Investors and Mutual Funds 1 ABSTRACT Earlier studies

More information

Active U.S. Equity Management THE T. ROWE PRICE APPROACH

Active U.S. Equity Management THE T. ROWE PRICE APPROACH PRICE PERSPECTIVE October 2015 Active U.S. Equity Management THE T. ROWE PRICE APPROACH In-depth analysis and insights to inform your decision-making. EXECUTIVE SUMMARY T. Rowe Price believes that skilled

More information

Table 4. + γ 2 BEAR i

Table 4. + γ 2 BEAR i Table 4 Stock Volatility Following Hedge Funds Reported Holdings This table reports the output from cross-sectional regressions of future excess volatility against aggregate hedge fund demand for holding

More information

Pursuing a Better Investment Experience

Pursuing a Better Investment Experience Pursuing a Better Investment Experience Last updated: March 2015 1. Embrace Market Pricing World Equity Trading in 2014 Daily Average Number of Trades 60 million Dollar Volume $302 billion The market is

More information

Hedge Fund Returns: Auditing and Accuracy

Hedge Fund Returns: Auditing and Accuracy Hedge Fund Returns: Auditing and Accuracy Bing Liang Weatherhead School of Management Case Western Reserve University Cleveland, OH 44106-7235 Phone: (216) 368-5003 Fax: (216) 368-6249 E-mail: BXL4@po.cwru.edu

More information

Trading Probability and Turnover as measures of Liquidity Risk: Evidence from the U.K. Stock Market. Ian McManus. Peter Smith.

Trading Probability and Turnover as measures of Liquidity Risk: Evidence from the U.K. Stock Market. Ian McManus. Peter Smith. Trading Probability and Turnover as measures of Liquidity Risk: Evidence from the U.K. Stock Market. Ian McManus (Corresponding author). School of Management, University of Southampton, Highfield, Southampton,

More information

Jonathan A. Milian. Florida International University School of Accounting 11200 S.W. 8 th St. Miami, FL 33199. jonathan.milian@fiu.

Jonathan A. Milian. Florida International University School of Accounting 11200 S.W. 8 th St. Miami, FL 33199. jonathan.milian@fiu. Online Appendix Unsophisticated Arbitrageurs and Market Efficiency: Overreacting to a History of Underreaction? Jonathan A. Milian Florida International University School of Accounting 11200 S.W. 8 th

More information

THE NUMBER OF TRADES AND STOCK RETURNS

THE NUMBER OF TRADES AND STOCK RETURNS THE NUMBER OF TRADES AND STOCK RETURNS Yi Tang * and An Yan Current version: March 2013 Abstract In the paper, we study the predictive power of number of weekly trades on ex-post stock returns. A higher

More information

INVESTING LIKE THE HARVARD AND YALE ENDOWMENT FUNDS JULY 2015. Frontiergottex.com

INVESTING LIKE THE HARVARD AND YALE ENDOWMENT FUNDS JULY 2015. Frontiergottex.com INVESTING LIKE THE HARVARD AND YALE ENDOWMENT FUNDS JULY 2015 Frontiergottex.com Introduction The US University Endowment Funds ( US Endowment Funds ), such as Harvard and Yale, have been leaders in diversified

More information

Informed trading in options market and stock return predictability

Informed trading in options market and stock return predictability Informed trading in options market and stock return predictability Abstract Prior research has highlighted the importance of two distinct types of informed trading in options market: trading on price direction

More information

Should a mutual fund investor pay for active

Should a mutual fund investor pay for active Volume 69 Number 4 2013 CFA Institute Active Share and Mutual Fund Performance Antti Petajisto Using Active Share and tracking error, the author sorted all-equity mutual funds into various categories of

More information

Does the Number of Stocks in a Portfolio Influence Performance?

Does the Number of Stocks in a Portfolio Influence Performance? Investment Insights January 2015 Does the Number of Stocks in a Portfolio Influence Performance? Executive summary Many investors believe actively managed equity portfolios that hold a low number of stocks

More information

Edwin J. Elton* Martin J. Gruber** Christopher R. Blake***

Edwin J. Elton* Martin J. Gruber** Christopher R. Blake*** The Performance of Separate Accounts and Collective Investment Trusts by Edwin J. Elton* Martin J. Gruber** Christopher R. Blake*** October 1, 2012 * Professor Emeritus and Scholar in Residence, Stern

More information

FOREIGN SMALL CAP EQUITIES

FOREIGN SMALL CAP EQUITIES MEKETA INVESTMENT GROUP FOREIGN SMALL CAP EQUITIES ABSTRACT International equity investing is widely accepted by institutional investors as a way to diversify their portfolios. In addition, expanding the

More information

Bank Profitability: The Impact of Foreign Currency Fluctuations

Bank Profitability: The Impact of Foreign Currency Fluctuations Bank Profitability: The Impact of Foreign Currency Fluctuations Ling T. He University of Central Arkansas Alex Fayman University of Central Arkansas K. Michael Casey University of Central Arkansas Given

More information

Evaluating Managers on an After-Tax Basis

Evaluating Managers on an After-Tax Basis Evaluating Managers on an After-Tax Basis Brian La Bore Senior Manager Research Analyst Head of Traditional Research Greycourt & Co., Inc. March 25 th, 2009 Is Your Alpha Big Enough to Cover Its Taxes?

More information

2 11,455. Century Small Cap Select Instl SMALL-CAP as of 09/30/2015. Investment Objective. Fund Overview. Performance Overview

2 11,455. Century Small Cap Select Instl SMALL-CAP as of 09/30/2015. Investment Objective. Fund Overview. Performance Overview SMALL-CAP as of 09/30/2015 Investment Objective Century Small Cap Select Fund (CSCS) seeks long-term capital growth. Performance Overview Cumulative % Annualized % Quarter Year Since to Date to Date 1

More information

Report to Board of Administration

Report to Board of Administration Report to Board of Administration Agenda of: JUNE 10, 2014 From: Thomas Moutes, General Manager ITEM: IV-C SUBJECT: CONTRACT RENEWAL WITH LOOMIS, SAYLES & COMPANY, L.P. AND POSSIBLE BOARD ACTION Recommendation:

More information

Do Implied Volatilities Predict Stock Returns?

Do Implied Volatilities Predict Stock Returns? Do Implied Volatilities Predict Stock Returns? Manuel Ammann, Michael Verhofen and Stephan Süss University of St. Gallen Abstract Using a complete sample of US equity options, we find a positive, highly

More information

We are motivated to test

We are motivated to test James X. Xiong is head of quantitative research at Morningstar Investment Management in Chicago, IL. james.xiong@morningstar.com Thomas M. Idzorek is the president of Morningstar Investment Management

More information

Cross-Autocorrelation in Asian Stock Markets. First Draft: March1998. Abstract

Cross-Autocorrelation in Asian Stock Markets. First Draft: March1998. Abstract Cross-Autocorrelation in Asian Stock Markets Eric C. Chang a, Grant R. McQueen b, and J. Michael Pinegar b First Draft: March1998 Abstract Five Asian stock markets (Hong Kong, Japan, South Korea, Taiwan,

More information

Practical. I conometrics. data collection, analysis, and application. Christiana E. Hilmer. Michael J. Hilmer San Diego State University

Practical. I conometrics. data collection, analysis, and application. Christiana E. Hilmer. Michael J. Hilmer San Diego State University Practical I conometrics data collection, analysis, and application Christiana E. Hilmer Michael J. Hilmer San Diego State University Mi Table of Contents PART ONE THE BASICS 1 Chapter 1 An Introduction

More information

Vanguard Research April 2015. Christopher B. Philips, CFA, Francis M. Kinniry Jr., CFA, Todd Schlanger, CFA, David J. Walker, CFA

Vanguard Research April 2015. Christopher B. Philips, CFA, Francis M. Kinniry Jr., CFA, Todd Schlanger, CFA, David J. Walker, CFA The buck case stops for index-fund here: Vanguard investing money for Canadian market funds investors Vanguard Research April 2015 Christopher B. Philips, CFA, Francis M. Kinniry Jr., CFA, Todd Schlanger,

More information

Should a mutual fund investor pay for active

Should a mutual fund investor pay for active Volume 69 Number 4 2013 CFA Institute Active Share and Mutual Fund Performance Antti Petajisto Using Active Share and tracking error, the author sorted all-equity mutual funds into various categories of

More information

INTERNET APPENDIX TIME FOR A CHANGE : LOAN CONDITIONS AND BANK BEHAVIOR WHEN FIRMS SWITCH BANKS. This appendix contains additional material:

INTERNET APPENDIX TIME FOR A CHANGE : LOAN CONDITIONS AND BANK BEHAVIOR WHEN FIRMS SWITCH BANKS. This appendix contains additional material: INTERNET APPENDIX TO TIME FOR A CHANGE : LOAN CONDITIONS AND BANK BEHAVIOR WHEN FIRMS SWITCH BANKS This appendix contains additional material: I. Assumptions II. Simulations III. Static Results IV. Dynamic

More information

Internet Appendix to The Pre-FOMC Announcement Drift

Internet Appendix to The Pre-FOMC Announcement Drift Internet Appendix to The Pre-FOMC Announcement Drift DAVID O. LUCCA and EMANUEL MOENCH This appendix provides supplementary results. Section A details the bootstrap analyses discussed in Section III.D.

More information

Internet Appendix for. Liquidity Provision and the Cross-Section of Hedge Fund Returns. Russell Jame

Internet Appendix for. Liquidity Provision and the Cross-Section of Hedge Fund Returns. Russell Jame Internet Appendix for Liquidity Provision and the Cross-Section of Hedge Fund Returns Russell Jame This document contains supplementary material for the paper titled: Liquidity Provision and the Cross-Section

More information

Bond Fund Risk Taking and Performance

Bond Fund Risk Taking and Performance Bond Fund Risk Taking and Performance Abstract This paper investigates the risk exposures of bond mutual funds and how the risk-taking behavior of these funds affects their performance. Bond mutual funds

More information

Public vs. Private: Characteristics of the Companies Backed by Listed Private Equity

Public vs. Private: Characteristics of the Companies Backed by Listed Private Equity Public vs. Private: Characteristics of the Companies Backed by Listed Private Equity M. Sinan Goktan California State University, East Bay Erdem Ucar University of South Florida Listed Private Equity (LPE)

More information

FTS Real Time System Project: Portfolio Diversification Note: this project requires use of Excel s Solver

FTS Real Time System Project: Portfolio Diversification Note: this project requires use of Excel s Solver FTS Real Time System Project: Portfolio Diversification Note: this project requires use of Excel s Solver Question: How do you create a diversified stock portfolio? Advice given by most financial advisors

More information

The buck case for stops here:

The buck case for stops here: The buck case for stops here: Vanguard index-fund money investing market funds Vanguard research April 214 Christopher B. Philips, CFA; Francis M. Kinniry Jr., CFA; Todd Schlanger, CFA; Joshua M. Hirt

More information

Competition of socially responsible and conventional mutual funds and its. impact on fund performance

Competition of socially responsible and conventional mutual funds and its. impact on fund performance Competition of socially responsible and conventional mutual funds and its impact on fund performance Martin Kim Department of Accounting and Finance Monash University Clayton, Victoria, 3168 Australia

More information

Liquidity and Flows of U.S. Mutual Funds

Liquidity and Flows of U.S. Mutual Funds Liquidity and Flows of U.S. Mutual Funds Paul Hanouna, Jon Novak, Tim Riley, Christof Stahel 1 September 2015 1. Summary We examine the U.S. mutual fund industry with particular attention paid to fund

More information

To have the ability to pay all benefits obligations when requested.

To have the ability to pay all benefits obligations when requested. INVESTMENT POLICY STATEMENT FOR: Alliance Benefit Group Health Savings Account Program I. GENERAL Purpose and Overview The Alliance Benefit Group Health Savings Account Program ( Program ) was established

More information

Internet Appendix to. Why does the Option to Stock Volume Ratio Predict Stock Returns? Li Ge, Tse-Chun Lin, and Neil D. Pearson.

Internet Appendix to. Why does the Option to Stock Volume Ratio Predict Stock Returns? Li Ge, Tse-Chun Lin, and Neil D. Pearson. Internet Appendix to Why does the Option to Stock Volume Ratio Predict Stock Returns? Li Ge, Tse-Chun Lin, and Neil D. Pearson August 9, 2015 This Internet Appendix provides additional empirical results

More information

How to assess the risk of a large portfolio? How to estimate a large covariance matrix?

How to assess the risk of a large portfolio? How to estimate a large covariance matrix? Chapter 3 Sparse Portfolio Allocation This chapter touches some practical aspects of portfolio allocation and risk assessment from a large pool of financial assets (e.g. stocks) How to assess the risk

More information

fi360 Asset Allocation Optimizer: Risk-Return Estimates*

fi360 Asset Allocation Optimizer: Risk-Return Estimates* fi360 Asset Allocation Optimizer: Risk-Return Estimates* Prepared for fi360 by: Richard Michaud, Robert Michaud, Daniel Balter New Frontier Advisors LLC Boston, MA 02110 February 2015 * 2015 New Frontier

More information

How To Explain Momentum Anomaly In International Equity Market

How To Explain Momentum Anomaly In International Equity Market Does the alternative three-factor model explain momentum anomaly better in G12 countries? Steve Fan University of Wisconsin Whitewater Linda Yu University of Wisconsin Whitewater ABSTRACT This study constructs

More information

Do the asset pricing factors predict future economy growth? An Australian study. Bin Liu Amalia Di Iorio

Do the asset pricing factors predict future economy growth? An Australian study. Bin Liu Amalia Di Iorio Do the asset pricing factors predict future economy growth? An Australian study. Bin Liu Amalia Di Iorio Abstract In this paper we examine whether past returns of the market portfolio (MKT), the size portfolio

More information

INVESTMENT POLICY STATEMENT. Creighton University 403(b) Retirement Plan

INVESTMENT POLICY STATEMENT. Creighton University 403(b) Retirement Plan INVESTMENT POLICY STATEMENT For Creighton University 403(b) Retirement Plan November 2008 Cornerstone Advisors Asset Management, Inc. 74 West Broad Street, Suite 340 Bethlehem, PA 18018 TABLE OF CONTENTS

More information

Liquidity Commonality and Pricing in UK Equities

Liquidity Commonality and Pricing in UK Equities Liquidity Commonality and Pricing in UK Equities Jason Foran*, Mark C. Hutchinson** and Niall O Sullivan*** January 2015 Forthcoming in Research in International Business and Finance Abstract We investigate

More information

Xiaoding Liu and Jay R. Ritter December 20, 2010

Xiaoding Liu and Jay R. Ritter December 20, 2010 Xiaoding Liu and Jay R. Ritter December 20, 2010 Local Underwriter Oligopolies and IPO Underpricing Internet Appendix Figure IA-1 Gross Spread Distribution for Moderate Size IPOs The sample consists of

More information

Chapter 5: Analysis of The National Education Longitudinal Study (NELS:88)

Chapter 5: Analysis of The National Education Longitudinal Study (NELS:88) Chapter 5: Analysis of The National Education Longitudinal Study (NELS:88) Introduction The National Educational Longitudinal Survey (NELS:88) followed students from 8 th grade in 1988 to 10 th grade in

More information

Stock market booms and real economic activity: Is this time different?

Stock market booms and real economic activity: Is this time different? International Review of Economics and Finance 9 (2000) 387 415 Stock market booms and real economic activity: Is this time different? Mathias Binswanger* Institute for Economics and the Environment, University

More information

Real Estate Returns in Public and Private Markets

Real Estate Returns in Public and Private Markets Real Estate Returns in Public and Private Markets The NCREIF Property Index understates the return volatility of commercial properties. JOSEPH GYOURKO PRIOR TO THE 1990S, commercial real estate was undoubtedly

More information

Target-Date Funds: The Search for Transparency

Target-Date Funds: The Search for Transparency Target-Date Funds: The Search for Transparency Presented by: Joachim Wettermark, Treasurer Salesforce.com, inc. Linda Ruiz-Zaiko, President Financial, Inc. Qualified Default Investment Alternative (QDIA)

More information

Portfolio Implications of Triple Net Returns. Journal of Wealth Management Forthcoming. Abstract

Portfolio Implications of Triple Net Returns. Journal of Wealth Management Forthcoming. Abstract Portfolio Implications of Triple Net Returns Journal of Wealth Management Forthcoming Peter Mladina Director of Research Waterline Partners 6701 Center Drive West, Suite 955 Los Angeles, CA 90045 310.256.2576

More information

Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance?

Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance? Does Asset Allocation Policy Explain 40, 90, or 100 Percent of Performance? Roger G. Ibbotson and Paul D. Kaplan Disagreement over the importance of asset allocation policy stems from asking different

More information

Defensive equity: Is the market mispricing risk?

Defensive equity: Is the market mispricing risk? By: Bob Collie, FIA, Chief Research Strategist, Americas Institutional JUNE 2011 John Osborn, CFA, Director, Consulting, Americas Institutional Defensive equity: Is the market mispricing risk? Intuitively,

More information

Performance of UK Pension Funds. - Luck or Skill?

Performance of UK Pension Funds. - Luck or Skill? Performance of UK Pension Funds - Luck or Skill? Emelie Jomer Master Thesis, Department of Economics, Uppsala University June 7, 2013 Supervisor: Mikael Bask, Associate Professor of Economics, Uppsala

More information

In recent years, Federal Reserve (Fed) policymakers have come to rely

In recent years, Federal Reserve (Fed) policymakers have come to rely Long-Term Interest Rates and Inflation: A Fisherian Approach Peter N. Ireland In recent years, Federal Reserve (Fed) policymakers have come to rely on long-term bond yields to measure the public s long-term

More information

Credit Ratings and The Cross-Section of Stock Returns

Credit Ratings and The Cross-Section of Stock Returns Credit Ratings and The Cross-Section of Stock Returns Doron Avramov Department of Finance Robert H. Smith School of Business University of Maryland davramov@rhsmith.umd.edu Tarun Chordia Department of

More information

Private Equity Performance: Returns, Persistence and Capital Flows

Private Equity Performance: Returns, Persistence and Capital Flows Private Equity Performance: Returns, Persistence and Capital Flows Steve Kaplan and Antoinette Schoar Abstract This paper investigates the performance and capital inflows of private equity partnerships.

More information

Robust reverse engineering of crosssectional returns and improved portfolio allocation performance using the CAPM

Robust reverse engineering of crosssectional returns and improved portfolio allocation performance using the CAPM Robust reverse engineering of crosssectional returns and improved portfolio allocation performance using the CAPM XIAOHUI NI, YANNICK MALEVERGNE, DIDIER SORNETTE, AND PETER WOEHRMANN XIAOHUI NI is a Ph.

More information

Strategy Distinctiveness and Hedge Fund Performance

Strategy Distinctiveness and Hedge Fund Performance Strategy Distinctiveness and Hedge Fund Performance Ashley Wang Lu Zheng March 2008 Wang is at the Paul Merage School of Business, University of California Irvine, Irvine, CA 92697-3125; Phone: (949) 824-9149;

More information

Draft - Proof INVESTING IN WHAT YOU KNOW: THE CASE OF INDIVIDUAL INVESTORS AND LOCAL STOCKS. Mark S. Seasholes a and Ning Zhu b

Draft - Proof INVESTING IN WHAT YOU KNOW: THE CASE OF INDIVIDUAL INVESTORS AND LOCAL STOCKS. Mark S. Seasholes a and Ning Zhu b JOIM Journal Of Investment Management, Vol. 11, No. 1, (2013), pp. 20 30 JOIM 2013 www.joim.com INVESTING IN WHAT YOU KNOW: THE CASE OF INDIVIDUAL INVESTORS AND LOCAL STOCKS Mark S. Seasholes a and Ning

More information

Active vs. Passive Money Management

Active vs. Passive Money Management Active vs. Passive Money Management Exploring the costs and benefits of two alternative investment approaches By Baird s Advisory Services Research Synopsis Proponents of active and passive investment

More information