Mutual fund selection and performance persistence in 401(k) Plans

North American Journal of Economics and Finance 35 (2016) 78–100

Contents lists available at ScienceDirect

North American Journal of Economics and Finance

Mutual fund selection and performance persistence in 401(k) Plans Hsuan-Chi Chen a, Christine W. Lai b, Sheng-Ching Wu c,∗ a b c

Anderson School of Management, University of New Mexico, Albuquerque, NM 87131, USA Graduate Institute of Management, National Taiwan Normal University, Taipei, Taiwan Department of Finance, Da-Yeh University, Changhua, Taiwan

a r t i c l e

i n f o

Article history: Available online 6 November 2015

JEL classification: G11 G23 J26 Keywords: 401(k) plans Mutual funds Performance persistence

a b s t r a c t We examine how plan sponsors/providers select mutual funds for 401(k) plans and whether performance persistence exists for mutual funds listed in 401(k) plans. Using a hand-collected data set of 401(k) investment options, we find that plan sponsors are likely to choose actively managed growth funds, including aggressive growth funds and long-term growth funds. Furthermore, more than 50% of the mutual funds in our sample of 401(k) plans are selected from the top 10 fund families in terms of total net assets. On average, plan sponsors select funds that outperform the funds with the same investment objective and that have low expense ratios. The performance of mutual funds in 401(k) plans only persists in a short horizon. Our analysis indicates that the menus of 401(k) investment options do not exhibit a signaling effect, indicating that investment options in 401(k) plans do not supply useful information about the future performance of mutual funds for investors in selecting mutual funds. © 2015 Elsevier Inc. All rights reserved.

1. Introduction A 401(k) plan is one of the most popular defined contribution (DC) pension plans and is usually the sole investment channel outside of a bank account for most plan participants1 . Because plan ∗ Corresponding author. Tel.: +886 4 851 1888; fax: +886 4 2364 8372. E-mail address: [email protected] (S.-C. Wu). 1 Holden and VanDerhei (2006) estimate that around 47 million American employees held 401(k) plan accounts with a total of $2.4 trillion in assets in 2005. http://dx.doi.org/10.1016/j.najef.2015.10.004 1062-9408/© 2015 Elsevier Inc. All rights reserved.

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participants can choose only from the subset of mutual funds available in the market for their 401(k) accounts, plan sponsors and plan providers must act prudently to assure that investment options offered to plan participants are carefully selected initially and monitored continuously for inclusion in the 401(k) plan2 . Therefore, understanding how plan providers select mutual funds is not only intriguing for academic research but also important for the retirement wealth of participants in 401(k) plans. The second important question is whether the menus of 401(k) investment options provide valuable information about performance persistence. The investment options offered by 401(k) plans should be in the best interest of plan participants and are usually suggested by financial advisors. We examine whether the mutual funds in 401(k) plans exhibit positive performance persistence. If so, this implies that the fund menus of 401(k) plans supply useful information for investors in selecting mutual funds3 . Despite a wide range of studies examining the behavior of participants in DC plans, only a few have examined the effects of investment offerings on the extent of diversification or investigated fund performance of investment offerings. Elton, Gruber, and Blake (2006) examine the adequacy of the investment choices offered by 401(k) plans. They find that only 53% of the plans offers a reasonable set of investment options for plan participants to construct an efficient frontier equivalent to one constructed from a set of alternative choices and that the loss is substantial because of the inadequate investment options. Angus, Brown, Smith, and Smith (2007) study the investment choices in 403(b) plans and find similar results. Regarding fund performance in 401(k) plans, Elton et al. (2006) find that 401(k) plans offer mutual funds that have better performance than randomly selected funds, but the expense ratios can account for almost all of the difference in performance between the funds offered and randomly selected funds. Elton, Gruber, and Blake (2007) study how well 401(k) plan providers select mutual funds with a certain investment objective based on Investment Company Data, Incorporated (ICDI) categories4 . Their results indicate that on average 401(k) plans offer mutual funds that outperform randomly selected funds in the same ICDI category but underperform index funds with the same risk. Plan providers tend to add mutual funds that have had good performance in the past and drop funds that have had poor performance. However, the performance of the added funds is often no better than the performance of the dropped funds following the change. Elton et al. (2007) also examine whether the good performance of a plan in the prior one year predicts good performance in the subsequent year. They argue that some predictability about future performance of plans exists in past performance and that most of this predictability comes from bad plan performance predicting bad plan performance. The main difference between Elton et al. (2007) and our study is twofold. First, the performance persistence that Elton et al. (2007) investigate is whole plan performance, whereas we focus on the individual fund’s performance persistence. Focusing on the individual fund’s performance persistence

2 In this paper, we refer to the companies that offer retirement accounts to their employees as plan sponsors (plan admin¨ both plan providers and recordkeepers. As istrators). Following Reish and Ashton (2007), we use the term “plan providersfor Reish and Ashton (2007) point out, the entity that offers the core 401(k) services to the market typically performs the function of recordkeeping or outsources that service. Plan providers that restrict the investment options for their 401(k) offerings are called packaged providers since they offer a whole package of investments and services. From the mutual funds offered by packaged providers, the firms or plan sponsors choose a subset of those funds for their 401(k) plans. For some large 401(k) plans, plan sponsors or firms themselves are also the plan providers. In contrast, small plan sponsors tend to find plan providers to provide services for their 401(k) plans. 3 There are various conclusions in the literature. For example, Malkiel (1995) documents that the strong persistence that characterized the 1970s failed to exist during the 1980s and the persistence phenomenon is likely to be influenced by survivorship bias. Grinblatt and Titman (1992), Hendricks, Patel, and Zeckhauser (1993), Goetzmann and Ibbotson (1994), Brown and Goetzmann (1995), Elton et al. (1996), and Carhart (1997) find performance persistence over short-term horizons of one to three years. Jain and Wu (2000) do not find any evidence of performance persistence. 4 The twenty-three ICDI categories of investment objectives include aggressive growth funds (AG), balanced funds (BL), highquality bond funds (BQ), high-yield bond funds (BY), global bond funds (GB), global equity funds (GE), growth and income funds (GI), Ginnie Mae funds (GM), government security funds (GS), international equity funds (IE), income funds (IN), long-term growth funds (LG), money market tax-free funds (MF), money market government securities (MG), high-quality municipal bond funds (MQ), single-state municipal bond funds (MS), money market taxable funds (MT), high-yield municipal bond funds (MY), precious metals funds (PM), sector funds (SF), special funds (SP), total return funds (TR), and utility funds (UT).

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rather than the whole plan performance has an implication for helping plan participants and investors choose mutual funds in 401(k) plans. Second, Elton et al. (2007) indicate that the addition or deletion of funds in 401(k) plans depends, at least in part, on their past performance. In addition to the prior fund performance, our paper proposes more potential determinants that are likely associated with inclusion of mutual funds in 401(k) plans. We manually collect mutual fund lists from 401(k) plans for 1998 and 2004 and compile a database of 113 401(k) plans and 767 mutual funds for 1998 and 192 plans and 2886 mutual funds for 2004. The 401(k) plans are collected from Forms 11-k and the mutual fund data are collected from the Center for Research in Security Prices (CRSP) Survivor-Bias-Free US Mutual Fund Database. Our results indicate that actively managed growth funds, including aggressive growth funds and long-term growth funds, are more likely to be selected by plan providers. In addition, approximately 80% of mutual funds are selected from the top 10 fund families for the sample in 1998 and 63% of funds are from the top 10 fund families for the sample in 2004. We find that on average plan providers select mutual funds that outperform matching funds with the same investment objective. Furthermore, mutual funds selected by plan providers tend to exhibit lower expense ratios than the matching mutual funds. The evidence from our sample of 401(k) plans supports the view that plan providers tend to choose mutual funds with lower expense ratios. On the other hand, if the long-run performance of mutual funds listed in 401(k) plans is good due to the professional services provided by consultants, the fund lists of 401(k) plans supply useful information to investors in a manner similar to a buying recommendation for mutual funds. Our empirical analysis indicates that 401(k) investment menus do not exhibit such a signaling effect, and thus investors cannot benefit largely from following the fund offerings by 401(k) plans in mutual fund selection. Our study makes the following contributions to the literature on 401(k) plans and mutual funds. First, we examine the decision-making of plan providers regarding the inclusion of mutual funds in 401(k) plans. The study enriches our understanding of how the providers of 401(k) plans determine the investment menus for employees. Second, we hypothesize that if the professional services offered by plan providers generate useful information for selecting mutual funds, outside investors are likely to benefit from following the investment menus offered by 401(k) plans. We then investigate whether the mutual funds listed in 401(k) plans can signal their future performance by comparing their performance with the performance of peer funds with the same investment objective. This paper proceeds as follows. Section 2 develops hypotheses to explore how plan providers determine their investment options for 401(k) plan participants. Section 3 describes the data and methodology used to test the hypotheses developed in Section 2. Section 4 presents the empirical results. Section 5 concludes the study. 2. Hypotheses for fund selection in 401(k) plans In this section, we develop four hypotheses to explain how plan providers select the mutual funds offered in 401(k) plans. 2.1. Actively managed funds Brown, Liang, and Weisbenner (2007) find that the vast majority of the mutual funds newly added to 401(k) plans is high-cost actively managed equity funds rather than lower cost index funds. Dvorak and Norbu (2013) find that mutual fund companies are more likely to offer their own mutual funds in the 401(k) plan for their employees and the selected funds usually are actively managed and expensive. In addition, Hutcheson (2007) indicates that actively traded funds, which inherently pay more trading fees, may enable fund managers to charge excess commissions and create a fiduciary breach from “oft dollars.” The 1998 Securities and Exchange Commission (SEC) investigations showed that excess commissions have been used by consultants (plan providers) to make certain services available to mutual funds.5 In addition to paying for the preparation of a research report, mutual funds also pay plan providers a significant amount of money so as to cultivate the loyalty of plan providers or to hold

5

Interested readers can refer to http://www.sec.gov/news/studies/softdolr.htm.

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a meeting that facilitates the sale of mutual funds to 401(k) plan sponsors. Therefore, based on the previous arguments, we develop our first hypothesis as follows: Hypothesis (1). To gain additional benefits from mutual funds, plan providers are more likely to select actively managed mutual funds than other funds. 2.2. Fund family reputation Massa (2003) shows that investors select a fund family first and then choose their investments from among individual funds in the fund family selected. Gerken, Starks, and Yates (2014) also indicate that investors are significantly more likely to purchase funds from families with which they have previous experience, and particularly if the previously experienced return was positive. Since large mutual fund families offer the potential for economies of scale and scope, in terms of asset management, distribution externalities, and better research quality, we expect that large fund families have established a good reputation and can attract business from 401(k) plan providers. Sirri and Tufano (1998) argue that larger fund families reduce the search costs for selecting mutual funds and provide better services (e.g., allow investors to easily switch their investments from fund to fund within a fund family). To lower search costs and enhance employee satisfaction, we expect plan providers to choose mutual funds from large mutual fund families based on their reputation and the benefits associated with economies of scale and scope. An alternative argument for plan providers selecting mutual funds managed by large or well-known fund families is “following the herd” (Scharfstein & Stein, 1990). If plan providers are concerned about their fiduciary role or how plan participants assess their ability to judge the investment options offered in the 401(k) plans, it can be fully rational for plan providers to follow or select the popular mutual funds offered by large fund families. In unfavorable market conditions, plan providers can then share the blame with a large number of investors. Therefore, we develop our second hypothesis as follows: Hypothesis (2). Plan providers are more likely to select mutual funds offered by large fund families than other funds. 2.3. Well-performing funds Performance persistence of mutual funds over short horizons is well documented in the literature. Elton et al. (2006), Elton et al. (2007) argue that 401(k) plans offer more outperforming mutual funds than randomly selected mutual funds with the same investment objective. Based on their findings, it is likely that plan providers will choose top-performing mutual funds and expect performance persistence. Sialm, Starks, and Zhang (2015) find that DC sponsors are sensitive to performance and are more likely to adjust their investment options according to fund performance. Furthermore, if plan providers have some insight into selecting mutual funds, they tend to choose mutual funds that are expected to exhibit good performance for a longer term. If this hypothesis is supported, combined with the performance persistence documented in the mutual fund literature, the menus of mutual funds offered in 401(k) plans can provide investors with valuable information for selecting mutual funds. Therefore, we develop the following hypothesis: Hypothesis (3). It is more likely that plan providers will select mutual funds with good past performance than their peer funds. Implication of Hypothesis (3) If performance persistence also exists among the selected funds, the mutual funds offered by 401(k) plans exhibit better future performance than peer funds. Hence, the fund lists in 401(k) plans can provide useful information to investors in selecting mutual funds. 2.4. Low expense ratios Several studies have documented a negative relationship between the expense ratio of a mutual fund and its performance. Gruber (1996) indicates that expenses are not higher for top-performing

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funds, nor do expenses increase more rapidly in the future for top-performing funds. Similarly, Carhart (1997) shows that expense ratios, transaction costs, and load fees all have a direct, negative impact on fund performance. Furthermore, Livingston and O’Neal (1998) argue that without evidence supporting performance persistence in fund returns, investors should consider expense ratios as a tool for selecting mutual funds since fund expenses adversely affect fund returns. Therefore, expense ratios may account for most of the average 401(k) participant’s costs and erode part of fund performance. Furthermore, plan administrators are more likely to be confronted with a lawsuit if plan participants are dissatisfied with the performance of their retirement accounts. For example, on August 4, 2005 (Page A2), the Wall Street Journal reported that. “They fear workers or class-action lawyers will sue an employer who puts money into any fund that goes down. No expert knows of such a suit – except in cases, like Enron, where employers put a lot of workers’ money into the company’s stock – but that doesn’t matter.” These arguments lead to the expense ratio hypothesis stated below:6 Hypothesis (4). To lower the cost and improve mutual fund performance, plan providers are more likely to choose mutual funds with lower expense ratios than peer funds. 3. Data and methodology 3.1. Sample construction Based on Elton et al. (2007) results and our data, we find that the investment menus of 401(k) plans do not change frequently7 . Therefore, to investigate how plan providers choose mutual funds, it is improper to choose two consecutive years. We select two non-consecutive and distant years and gather information on 401(k) plans from Forms 11-K filed by S&P 500 firms for 1998 and 20048 . The sample from 1998/2004, respectively, reflects the differences before and after the “Internet bubble” in 1999–2000. In addition, Benartzi (2001) uses the 401(k) plans of S&P 500 firms in 1993 and 1995 to explore whether employees overinvest in company stock. To complement his study, we also use 1998 as our sample year. When firms report multiple retirement savings plans, we collect data from the largest plan, as measured by net assets available for plan benefits. The regulatory restriction and selection criteria result in the initial sample containing 144 companies in 1998 and 243 companies in 20049 . Furthermore, we identify the mutual funds in each Form 11-K. We exclude Forms 11-K that only contain data at the aggregate level rather than the individual fund level. On the other hand, if the Forms 11-K contain mutual funds that are not traded publicly and cannot be recognized from the CRSP mutual fund database, we exclude these funds from our sample. These criteria leave us with 113 companies and 767 mutual funds for 1998 and 192 companies and 2886 mutual funds for 2004. The average number of funds listed in a 401(k) plan is 6.8 and 15.0 for 1998 and 2004, respectively. Among these two groups of 401(k) plans, only 56 plans appear in both years. Therefore, these two samples differ to some extent and add credibility to comparisons and robustness checks. Our data for mutual funds are collected from the CRSP Survivor-Bias-Free US Mutual Fund Database. We collect data on the ICDI number (ICDI NO), fund name, fund family, expense ratios (Expense), mutual fund monthly returns (Ret), total net assets under management (TNA), number of years since the mutual fund began trading (Age), ICDI fund objectives (ICDI OBJ), and turnover ratio (Turnover).

6 On the contrary, Dvorak (2015) compares the designs of plans that advisors help create (client plans) to those that the advisors use themselves (advisor plans) and finds that advisors have an impact on the investment menus of their clients. Client plans might choose funds with higher expense ratios to compensate their advisors. 7 Elton et al. (2007) find that over their 289 plan years, only 215 funds were added and 45 were dropped. 8 Because the SEC required public companies to make their filings available in electronic format in 1994, we can manually collect information about Forms 11-K from the Electronic Data Gathering, Analysis, and Retrieval system (EDGAR). Only the companies that provide employees with the choice of investing their own contributions in their employer’s stock and that issue new shares for the 401(k) plans, rather than purchasing shares on the open market, are required to file Form 11-K. Huberman and Sengmueller (2004) discuss the regulatory issues surrounding Form 11-K in more detail. 9 Our sample size is comparable to that in Benartzi (2001). He uses 219 Forms 11-K of S&P 500 firms in 1993 to test whether employees excessively extrapolate the past performance of company stock.

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Table 1 Summary statistics. This table presents the summary statistics for mutual funds listed in 401(k) plans available in 1998 and 2004. The 401(k) plans are collected from Form 11-K and the information on mutual funds is gathered from the CRSP SurvivorBias-Free US Mutual Fund Database. TNA is the total net assets measured in  billions  of dollars. Inflow is the average monthly

inflow of mutual funds, which is defined as Inflowt = asseti,t − asseti,t−1 × 1 + ri,t , where ri,t is the return earned by mutual fund i during month t. Age is the average age of mutual funds measured from fund inception to either 1998 or 2004. Expense is the expense ratio that fund shareholders pay for the fund’s operating expenses. Sharpe Ratio is the average monthly excess return divided by the standard deviation of monthly fund returns over the preceding year. Panel A: Year 1998

TNA (billion) Inflow (million) Age (year) Expense (%) Sharpe ratio

N

Mean

Median

Minimum

Maximum

765 766 767 767 767

8.93 33.13 14.25 0.84 0.30

2.87 14.07 8.00 0.78 0.35

0.01 −315.57 0.00 0.00 −2.06

63.77 404.32 73.00 2.51 1.46

N

Mean

Median

Minimum

Maximum

2879 2863 2886 2886 2886

5.37 33.18 10.34 0.94 0.28

1.14 4.21 7.00 0.92 0.63

0.00 −459.55 0.00 0.00 −803.80

68.00 776.07 75.00 4.58 3.64

Panel B: Year 2004

TNA (billion) Inflow (million) Age (year) Expense (%) Sharpe ratio

We merge the mutual funds in 401(k) plans with the funds in the CRSP mutual fund database by name of mutual fund. If the Form 11-K does not explicitly state which share class the plan providers chose for each fund, we use the information from the share class with the largest total net assets10 . We also use the S&P 500 index as the benchmark for calculating the buy-and-hold abnormal return of each mutual fund. Table 1 contains information about the mutual funds offered in 401(k) plans available in 1998 and 2004, respectively. Because there are more 401(k) plans in 2004 and those plans on average offer more mutual funds for plan participants, the number of mutual funds for 1998 is 767, much smaller than the 2886 funds for 2004. Panel A reports the summary statistics of mutual funds offered in the 401(k) plans for 1998. The mean (median) size of the funds in terms of net assets under management is $8.93 ($2.87) billion with a mean (median) inflow of $33.13 (14.07) million. Fund inflow  is theaverage monthly inflow of mutual funds, which is defined as Inflowt = asseti,t − asseti,t−1 × 1 + ri,t , where ri,t is the return earned by fund i during month t. The mean (median) age of the mutual funds is 14 (8) years. The mean (median) expense ratio is 0.84% (0.78%). The mean (median) Sharpe ratio is 0.30 (0.35), which is defined as the average monthly excess return divided by the standard deviation of monthly fund returns over the preceding year. Panel B reports the summary statistics for 2004. Since a large proportion of young and small mutual funds is selected in the 401(k) plans for 2004, the mean (median) TNA is 5.37 (1.14) billion, which is smaller than the corresponding number in Panel A. Similarly, the average (median) fund age is 10.34 (7) years, which is smaller than that in Panel A. The average (median) expense ratio is 0.94% (0.92%). On average, the expense ratio increased by 10 basis points from 1998 to 2004, which is consistent with Barber, Odean, and Zheng (2005). 3.2. Methodology We begin our empirical investigation by examining whether actively managed funds are more likely to be selected by plan providers. We calculate the frequency of ICDI investment objectives

10 ¨ which can offer a different Frequently, funds are sold through multiple share classes (e.g., “A,¨‘‘B,¨‘‘C,¨‘‘No-Load,¨‘‘Institutional), mix of front-end loads, back-end loads, and 12b-1 fees. See Zhao (2002) for more details.

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for the mutual funds in 401(k) plans and use the turnover rate and expense ratio as the important characteristics of actively managed funds. We then examine whether mutual funds in 401(k) plans are chosen from large fund families. We use the total net assets to proxy for the fund family’s reputation and rank the fund families by total net assets under management in each fund family at the end of 1997 and 2003, respectively. The top 50 fund families and their total net assets are reported in the appendix. We sort these 50 fund families into five categories based on the total net assets managed by each fund family. We then calculate the proportion of mutual funds in our 401(k) sample within each category and test whether plan providers randomly choose mutual funds from the top 10 fund families using the binomial test. We also test whether the mutual funds in 401(k) plans exhibit significantly different performance and cost from the matching funds. We construct three groups of matching funds for comparison with the mutual funds in 401(k) plans. First, we match each mutual fund in each 401(k) plan with all funds both in the same fund family and with the same ICDI fund objective. Second, we only match each mutual fund in each 401(k) plan with all funds that have the same ICDI fund objective. To construct the third sample of matching funds, we randomly select one mutual fund from the same fund family and require the randomly selected fund to have the same ICDI fund objective as each mutual fund in each 401(k) plan. To examine the well-performing fund hypothesis, we compare the average monthly return and the buy-and-hold abnormal return of each mutual fund in 401(k) plans to those of the matching funds. To investigate the low expense ratio hypothesis, we compare the expense ratio of each mutual fund in 401(k) plans to the average expense ratio of matching funds. Combining the factors discussed earlier, we use logit models to examine the determinants of mutual fund selection in the 401(k) plans for 1998 and 2004, respectively. The use of samples from two distant years also facilitates the understanding of whether significant determinants change at different points in time. 4. Empirical results 4.1. Mutual funds selection 4.1.1. Are mutual funds in 401(k) plans mostly actively managed funds? We start by investigating whether plan providers are more likely to choose actively managed funds than other funds. An actively managed fund is defined as a mutual fund with both a high turnover ratio and a high expense ratio. The expense ratio is the percentage of a fund’s assets that fund shareholders pay for the fund’s operating expenses. The turnover ratio is calculated as the minimum of aggregated sales or aggregated purchases of securities divided by the average 12-month total net assets of the fund. Panel A of Table 2 reports the average (median) expense ratio and turnover ratio of the top six investment objectives for 401(k) funds in 1998 and 2004. Overall, the funds with high turnover ratios tend to exhibit higher expense ratios. The coefficient of correlation between the expense ratio and turnover ratio of each fund is 0.14 (p-value < 0.01) and 0.29 (p-value < 0.01) for 1998 and 2004, respectively. In Panel B of Table 2, a fund is defined as an actively managed fund when the fund’s ICDI investment objective is either aggressive growth or long-term growth and as a non-actively managed fund if otherwise. Based on this definition, actively managed funds exhibit both high turnover ratios and high expense ratios. For 401(k) plans in 1998, the actively managed funds have an average (median) expense ratio of 1.02% (0.96%), while the non-actively managed funds exhibit an average (median) expense ratio of 0.87% (0.76%). As for turnover ratio, the actively managed funds have an average (median) turnover ratio of 1.11 (0.79), while the non-actively managed funds exhibit an average (median) turnover ratio of 0.6 (0.39). Both differences in the expense ratio and turnover ratio between these two sub-samples are significant and support the notion that actively managed funds have high expense ratios and high turnover ratios. The pattern for 401(k) plans in 2004 is not qualitatively changed except that the average turnover ratio for non-actively managed funds is affected by a high turnover ratio of the high-quality bond funds.

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Table 2 Expense ratio and turnover of mutual funds by investment objective. This table reports the average expense ratio and turnover for mutual funds listed in 1998 and 2004 401(k) plans on the basis of investment objectives. Expense (%) is the expense ratio that fund shareholders pay for the fund’s operating expenses. Turnover is the fund turnover ratio, which is calculated as the minimum of aggregated sales and aggregated purchases of securities divided by the average 12-month total net assets of the fund. Panel A reports the statistics for mutual funds by the top six ICDI investment objectives. In Panel B, we designate both the aggressive growth funds and long-term growth funds as actively managed funds and the other funds as non-actively managed funds. The median values of the variables are reported in brackets. The symbol *** denotes significance at the 1% level. Year 1998 N

2004 Expense (%)

Turnover

N

Expense (%)

Turnover

1.05 [1.03] 0.99 [0.95] 0.56 [0.39] 1.33 [1.24] 0.70 [0.68] 0.64 [0.72]

1.15 [0.79] 1.10 [0.96] 0.34 [0.32] 0.42 [0.22] 0.95 [0.87] 0.83 [0.49]

506

1.15 [1.13] 1.06 [0.99] 0.46 [0.20] 1.27 [1.19] 1.02 [0.82] 0.68 [0.64]

0.76 [0.49] 0.84 [0.58] 0.32 [0.10] 0.65 [0.55] 2.94 [3.14] 0.66 [0.50]

N

Expense (%)

Turnover

N

Expense (%)

Turnover

Actively managed funds

241 526

1.11 [0.79] 0.60 [0.39]

991

Non-actively managed funds

1.02 [0.96] 0.87 [0.76] 5.52*** [8.19]***

1.11 [1.05] 0.86 [0.80] 10.75*** [12.25]***

0.80 [0.55] 0.96 [0.52] −3.31*** [1.70]***

Panel A: The top six ICDI investment objectives 94 Aggressive Growth Funds Long-Term Growth Funds

147

Growth and Income Funds

95

International Equity Funds

120

High-Quality Bond Funds

58

Balanced Funds

80

485 459 313 220 179

Panel B: Actively vs. non-actively managed funds Year 2004

1998

t-test Wilcoxon rank-sum test

***

3.66 [5.29]

1895

Fig. 1 displays the distribution of investment objectives for the top six styles of mutual funds listed in 401(k) plans in 1998 and 2004. The top six fund styles make up 78% of mutual funds for 1998 and 76% for 2004. The aggressive growth funds and long-term growth funds account for 12% and 20% of the sample for 1998, respectively; they account for 18% and 17% of the sample for 2004. Therefore, actively managed funds account for roughly one-third of 401(k) funds. 4.1.2. Do mutual funds in 401(k) plans largely come from top fund families? We then investigate whether plan providers choose investment options for their 401(k) plans from the top fund families. The rankings of the fund families for 1998 and 2004 are based on the sum of total net assets of funds belonging to the same fund family in 1997 and 2003. The appendix reports the top 50 fund families for both years. Table 3 presents the results of univariate tests comparing the distribution of mutual funds in 401(k) plans belonging to the top 50 fund families in 1998 and 2004, respectively. In 1998, among 803 mutual funds in 401(k) plans, 638 funds (slightly less than 80%) are from the top 10 families. The binomial test also rejects the hypothesis that plan providers select mutual funds randomly. Similarly, 1918 (about 63%) of 3066 mutual funds in the sample 401(k) plans of 2004 were selected from the largest 10 fund families. The binomial test also suggests that plan providers consciously select mutual funds from the top 10 fund families. Furthermore, around 90% and 81% of mutual funds in 401(k) plans were selected

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Percentage

86

Aggressive Long Term Growth and International Growth Funds Growth Funds Income Funds Equity Funds

Balanced Funds

High Quality Bond Funds

Fig. 1. Sample distribution of mutual funds by the top six investment objectives. This figure presents the sample distribution of mutual funds by the top six fund styles for 1998 and 2004 401(k) plans filed by S&P 500 firms. The classification of fund styles is based on the ICDI fund objective from the CRSP mutual fund database.

from the top 50 fund families in 1998 and 2004, respectively. Overall, the result indicates that the mutual funds in 401(k) plans largely come from top fund families. 4.1.3. The effect of well-performing funds To test whether plan providers select mutual fund with good prior performance, we use three matching methods to control for other effects. First, we match each mutual fund in each 401(k) plan with all funds in the same fund family and with the same fund style. Next, we only match each mutual fund in each 401(k) plan with all funds with the same investment objective. Finally, we randomly select one fund from the same fund family and with the same fund style counterparts for each mutual fund in each 401(k) plan. In Table 4, we compare the average monthly return of each fund in year t (Ret(t)) and the annual buy-and-hold abnormal return of each fund in year t (BHAR(t)) to that of matching funds. Panel A of Table 4 reports the result for controlling for fund family and fund style defined by ICDI OBJ. We compare the Ret(t) and BHAR(t) of each fund in each plan with the average of counterparts of the matched group in 1998 and 2004, respectively. For 401(k) plans in 1998, the mutual funds in 401(k) plans have an average monthly return of 1.45% for 1997, while the matching funds only have an average return of 1.35%. As for the annual buy-and-hold abnormal return, the mutual funds in 401(k) plans have an average abnormal return of −15.13% for 1997, while the matching funds have an average abnormal return of −16.28%. Furthermore, since a retirement saving plan is a long-term investment, accumulating slight differences can make an enormous difference for the participating employees after several years. However, the mutual funds of 401(k) plans in 2004 do not perform significantly better than the matching funds in 2003 in any measure of abnormal return. In other words, plan providers seemed to choose the investment options of 401(k) plans for 1998 based on prior performance, but not for 2004. Furthermore, plan providers with particular insight into the funds’ performance may choose funds that are likely to perform well in the future without regard for past performance. Hence, we posit that mutual funds in 401(k) plans exhibit top performance after they are selected into the plans. However, the subsequent performance (in year t + 1) of the funds in 401(k) plans is worse than the average performance of the matched group in 1998 and 2004. This result does not support the above hypothesis. In Panel B of Table 4, we control for mutual fund style only. The results for the 401(k) plans of 1998 are similar to those reported in Panel A of Table 4 and show that these funds exhibit better prior performance and worse subsequent performance than the matched group. Furthermore, the funds in the 401(k) plans of 2004 exhibit better performance in 2003 (the prior year) than the matched group based on comparing the average monthly return. As for subsequent performance, these funds on average outperform those in the matched group in both performance measures.

Panel A: 1998

1st ∼ 10th largest fund families 11th ∼ 20th largest fund families 21st ∼ 30th largest fund families 31st ∼ 40th largest fund families 41st ∼ 50th largest fund families

Number of funds

Number of funds in the sample of 401(k) plans

Proportion

Cumulative distribution

Binomial test (p-Value)

638 56 19 6 7

803 803 803 803 803

0.795 0.070 0.024 0.007 0.009

0.795 0.864 0.888 0.895 0.904

<0.0001 NA NA NA NA

Number of funds

Number of funds in the sample of 401(k) plans

Proportion

Cumulative distribution

Binomial test (p-Value)

1918 271 133 85 69

3066 3066 3066 3066 3066

0.626 0.088 0.043 0.028 0.023

0.626 0.714 0.757 0.785 0.808

<0.0001 NA NA NA NA

Panel B: 2004

1st ∼ 10th largest fund families 11th ∼ 20th largest fund families 21st ∼ 30th largest fund families 31st ∼ 40th largest fund families 41st ∼ 50th largest fund families

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 3 Distribution of mutual funds in 401(k) plans by fund family. This table shows the distribution of mutual funds in 401(k) plans in the top 50 fund families for 1998 and 2004. We rank the fund families by the sum of total net assets of funds belonging to the same fund family in 1997 and 2003, respectively. The binomial test is used to test whether plan sponsors select funds randomly from the top 10 fund families (H0 : p = 0.5).

87

88

Panel A: Control for fund family and fund objective Year 1998

Ret (t − 1) (%)

N

401(k) funds

Matching funds

Difference test

718

1.45 [1.66] 1.29 [1.32] 1.74 [1.64] −15.13 [−12.27] −13.72 [−13.71] 2.95 [−0.44] 0.92 [0.91]

1.35 [1.61] 1.19 [1.29] 1.90 [1.43] −16.28 [−13.44] −15.15 [−14.59] 5.74 [−3.03] 1.07 [1.09]

4.32 [2.43] 3.61*** [2.54] −3.67 [−3.04] 3.98 [2.26] 3.79 [2.14] −3.90 [−3.56] −9.48 [−6.72]

401(k) funds

Matching funds

Difference test

Ret (t) (%)

718

Ret (t + 1) (%)

718

BHAR (t − 1) (%) BHAR (t) (%) BHAR (t + 1) (%) Expense (t − 1) (%)

2004

718 718 718 718

***

N

401(k) funds

Matching funds

Difference test

2762

2.12 [2.23] 0.97 [0.89] 0.68 [0.57] −0.22 [0.44] 1.14 [−0.05] 3.36 [1.93] 0.94 [0.92]

2.18 [2.34] 0.96 [0.92] 0.72 [0.62] 0.69 [2.63] 0.98 [0.40] 3.82 [2.34] 1.19 [1.20]

−5.53 [−2.96] 1.33 [−0.35] −3.90 [−4.40] −5.90 [−3.59] 1.68 [−0.22] −4.61 [−4.62] −26.43 [−17.95]

N

401(k) funds

Matching funds

Difference test

2886

2.13 [2.24] 0.97 [0.89] 0.68 [0.57]

2.10 [2.26] 0.92 [0.88] 0.62 [0.55]

2.46** [0.66] 7.10*** [1.19] 8.33*** [2.64]***

** ***

2761

** ***

2735

*** ***

2762

** ***

2761

** ***

2735

*** ***

2762

***

Panel B: Control for fund objective Year 1998 N Ret (t − 1) (%) Ret (t) (%) Ret (t + 1) (%)

767 767 767

2004

1.45 [1.65] 1.27 [1.29] 1.73 [1.49]

1.37 [1.51] 1.06 [0.98] 1.78 [2.14]

4.16 [3.19] 7.17 [5.39] −1.20 [−3.78]

*** *** ***

2885

***

2857 ***

*** ***

*** *** *** *** *

*** *** *** ***

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 4 Univariate analysis—fund performance and expense ratio. This table reports the average performance and expense ratio of the mutual funds in the 401(k) plan for 1998 and 2004. Ret (t) is the average monthly return of each fund in year t. BHAR(t) is the annual buy-and-hold abnormal return of each fund in year t with the corresponding S&P 500 index return as the benchmark. Expense is the expense ratio that fund shareholders pay for the fund’s operating expenses. In Panel A, each fund in 401(k) plans is compared with all funds both in the same fund family and with the same ICDI investment objective. In Panel B, each fund in 401(k) plans is compared with all funds with the same ICDI investment objective. In Panel C, each fund in 401(k) plans is compared with one fund selected randomly from funds both in the same fund family and with the same ICDI investment objective. The median values of the variables are reported in brackets. The symbols *** , ** , and * denote significance at the 1%, 5%, and 10% levels, respectively.

Table 4 (Continued ) Panel A: Control for fund family and fund objective Year

BHAR (t − 1) (%) BHAR (t) (%) BHAR (t + 1) (%) Expense (t − 1) (%)

2004

N

401(k) funds

Matching funds

Difference test

767

−15.08 [−12.34] −13.95 [−13.85] 2.70 [−2.35] 0.92 [0.91]

−16.12 [−14.20] −16.75 [−16.99] 3.88 [8.20] 1.38 [1.43]

3.93 [3.06] 7.02 [5.55] −1.67 [−5.09] −28.12 [−19.72]

767 767 767

***

N

401(k) funds

Matching funds

Difference test

2886

−0.13 [0.50] 1.15 [0.03] 3.35 [1.93] 0.95 [0.93]

−0.35 [1.49] 0.42 [−0.01] 2.63 [1.86] 1.46 [1.50]

1.36 [−0.67] 7.15*** [0.94] 6.84*** [1.58] −49.07*** [−39.02]***

*** ***

2885

*** *

2857

*** ***

2886

***

Panel C: Randomly select one fund from the sample controlling fund family and fund objective Year 1998

2004

N

401(k) funds

Matching funds

Difference test

Ret (t−1) (%)

716

Ret (t) (%)

716

1.45 [1.66] 1.29 [1.32] 1.74 [1.64] −15.13 [−12.27] −13.72 [−13.71] 2.95 [−0.44] 0.92 [0.91]

1.35 [1.60] 1.20 [1.22] 1.95 [1.49] −16.28 [−13.25] −15.04 [−15.60] 6.78 [−2.74] 1.07 [0.99]

2.65 [−0.13] 1.99 [−1.93] −3.40 [1.13] 2.50 [−0.33] 2.09 [−2.11] −3.54 [1.19] −7.05 [−4.51]

Ret (t + 1) (%)

716

BHAR (t−1) (%)

716

BHAR (t) (%)

716

BHAR (t + 1) (%)

716

Expense (t−1) (%)

718

N

401(k) funds

Matching funds

Difference test

***

2761

**

2722

2.12 [2.23] 0.97 [0.89] 0.68 [0.57] −0.22 [0.44] 1.14 [−0.05] 3.36 [1.93] 0.94 [0.92]

2.18 [2.20] 0.97 [0.90] 0.71 [0.59] 0.73 [0.06] 1.02 [0.17] 3.94 [2.05] 1.19 [1.13]

−4.27 [0.56] 0.54 [−0.53] −1.48 [0.87] −4.32 [0.44] 0.78 [−0.86] −3.84 [0.76] −19.10 [−13.45]

* ***

2662

**

2761

**

2722

** ***

2662

***

2762

***

***

***

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

1998

***

*** ***

89

90

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

We then control for fund family and fund style and randomly select one fund from this group for comparison. Panel C of Table 4 reports these results. For the fund sample of 1998, the average prior performance is still better than the matched group. However, the average subsequent performance of the funds in 401(k) plans is worse than the matched group. Similar to the results reported in Panel A of Table 4, the fund sample of 2004 exhibits worse prior performance and subsequent performance than the matching funds do. Overall, the empirical results suggest that plan providers selected funds with good prior fund performance for the sample of 1998. However, these selected funds underperformed after they were included in 401(k) plans. For the sample of 2004, the results are mixed. If we control for fund family and fund style, the results do not support the well-performing hypothesis. On the contrary, the results show that the plan providers choose well-performing funds in their 401(k) plans if we only control for fund style or objective. 4.1.4. The effect of the expense ratio We now turn to discuss the results for examining expense ratios. Since expense ratios account for most of the average 401(k) participant’s costs and erode fund performance, we posit that plan providers select funds with low expense ratios to reduce costs and achieve performance, other things being equal. Panel A of Table 4 reports that the average (median) expense ratio of 401(k) funds is 92 (91) basis points for 1998 and 107 (109) basis points for the matching funds in the same category. Similarly, the average (median) expense ratio for the funds in the 401(k) plans of 2004 is 94 (92) basis points and 119 (120) basis points for the matching funds. All the mean (median) expense ratios of the funds in 401(k) plans are significantly lower than those of the matching funds. Furthermore, Panel B and Panel C of Table 4 report similar results. Overall, the univariate analysis suggests that most of the funds in 401(k) plans come from the top fund families. However, there is no strong evidence that plan providers choose mutual funds for their 401(k) plans based on prior performance. Compared to their matching funds, the mutual funds in 401(k) plans of 1998 and 2004 have a lower average expense ratio but underperform their counterparts in the subsequent year. 4.1.5. The determinants of mutual fund selection in 401(k) plans Table 5 presents logit models to examine the determinants of mutual fund selection in the 401(k) plans while controlling for other factors simultaneously. The dependent variable is a binary variable that takes the value of one when a fund is included in a sample 401(k) plan in a given year and zero when the fund is not included in any sample 401(k) plan in a given year. Active fund is a dummy variable equal to one when the fund’s ICDI investment objective is either aggressive growth or longterm growth and zero otherwise. Top-10-family is a dummy variable that takes the value of one when the fund belongs to top 10 fund families and zero otherwise. Expense is the expense ratio, which is the percentage of total investment that fund shareholders pay for the fund’s operating expenses. Retirement plans typically are long-term investments. Hence, the fund size, liquidity, and fund age may be the focus for plan providers. In addition to fund performance and cost, plan providers or participants may also be explicitly concerned about the risk of mutual funds. Therefore, we also consider the Sharpe ratio and fund objective, which are related to fund risk. Sharpe Ratio is the average monthly excess return divided by the standard deviation of monthly fund returns over the preceding year. We also control the fund style, which is classified by the fund’s ICDI fund objective code in our regressions. The codes include GI (Growth and Income Funds), IE (International Equity Funds), BQ (High Quality Bond Funds), and BL (Balanced Funds). Ret (t) is the average monthly return of each fund in year t. We use the S&P 500 index as the benchmark for calculating the buy-and-hold abnormal return BHAR(t) for each mutual fund in year t. The first two columns of Table 5 report the results for the sample from the 401(k) plans in 1998 and the remaining two columns for the sample from the 401(k) plans in 2004. In both Models (1) and (2) of Table 5, the coefficient estimate on the variable Active Fund is significantly positive, indicating that actively managed funds are more likely to be included in 401(k) plans. This result supports the actively managed fund hypothesis. Furthermore, the significantly positive coefficient estimate on

Inflowt = asseti,t − asseti,t−1 × 1 + ri,t , where ri,t is the return earned by fund i during month t. Age is the average age of mutual funds measured from fund inception to either 1998 or 2004. Sharpe Ratio is the average monthly excess return divided by the standard deviation of monthly fund returns over the preceding year. Ret(t − 1) is the average monthly return of each fund in year t − 1. BHAR(t − 1) is the annual buy-and-hold abnormal return of each fund in year t − 1 with the corresponding S&P 500 index return as the benchmark. Fund Style indicates that we control the ICDI fund objective in a logit regression model. The symbols *** and ** denote significance at the 1% and 5% levels, respectively. Year 1998

2004

Model 1

Intercept Active fund Top-10-family Expense (%) TNA Inflow Age Sharpe ratio Ret(t−1) BHAR(t−1) Fund style N Pseudo R2

Model 2

Coefficient

z-Statistic

−4.272 1.202 1.702 −0.551 0.015 0.006 0.006 0.347 12.415

−20.35 5.88 12.49 −4.25 5.43 2.87 0.95 2.46 1.22

yes 7110 0.279

*** *** *** *** *** ***

**

7110 0.208

Model 3

Coefficient

z-Statistic

−3.968 1.213 1.704 −0.548 0.015 0.006 0.006 0.350

−14.25 5.98 12.50 −4.24 5.43 2.87 0.95 2.46

0.889 yes 16072 0.105

*** *** *** *** *** ***

**

z-Statistic

−3.544 0.530 1.059 −0.625 0.009 0.003 0.003 −0.002 46.937

−31.43 5.72 13.63 −10.09 6.67 2.67 0.73 −1.16 12.74

1.15 yes 16072 0.102

Model 4

Coefficient

*** *** *** *** *** ***

Coefficient

z-Statistic

−2.611 0.600 1.067 −0.606 0.009 0.003 0.003 −0.002

−23.93 6.53 13.76 −9.83 6.66 2.79 0.60 −0.95

***

12.13

***

*** *** *** *** ***

***

2.901 yes

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 5 Logit models for fund selection in 401(k) plans. The dependent variable is a binary variable that takes the value of one when a fund is selected by a 401(k) plan and zero when the fund is not selected by any 401(k) plan in a given year. Active Fund is a dummy equal to one when the fund’s ICDI investment objective is either aggressive growth fund or long-term growth fund and zero otherwise. Top-10-family is a dummy equal to one when the fund belongs to the top 10 fund families and zero otherwise. Expense is the expense ratio that fund shareholders pay for the fund’soperating  expenses. TNA is the total net assets measured in billions of dollars. Inflow is the average monthly inflow of mutual funds, which is defined as

91

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Top-10-family indicates that plan providers are more likely to select mutual funds from large fund families. The result is consistent with the fund family reputation hypothesis. The coefficient estimate on Expense is significantly negative, suggesting that plan providers likely choose funds with lower expense ratios. This result supports the low expense ratio hypothesis. The findings that plan providers tend to select active funds and to choose funds with lower expenses are not necessarily inconsistent. One reason may be that large active mutual funds, with economies of scale, are more likely to be selected, as suggested by the significantly positive coefficient estimate on TNA. Furthermore, for the potential trade-off between the financial incentive and the fiduciary duty, plan providers may select large active mutual funds with lower expense ratios. The significantly positive coefficient estimates on Inflow are consistent with the concept that plan providers tend to select funds with more inflows in the prior year11 . A significantly positive association between fund inclusion and the Sharpe Ratio is consistent with the well-performing fund hypothesis. However, the coefficient estimate on Ret(t − 1) is not significant in Model (1) when we control for the other variables. The result is robust since the coefficient estimate on BHAR(t − 1) in Model (2) is not significant, either. These results are consistent with the interpretation that plan providers tend to choose funds keeping risk in mind rather than just focusing on prior fund performance. Model (3) and Model (4) of Table 5 report similar results and suggest that our conclusions do not change qualitatively when using the 401(k) plans of 2004. That is, plan providers tend to choose actively managed funds, funds from top fund families, and/or funds with low expense ratios. In contrast, the results for fund inclusion in 401(k) plans of 2004 suggest that plan providers focus on prior fund performance. 4.2. Can prior performance of mutual funds in 401(k) plans help participants in selecting mutual funds? The empirical results suggest that plan providers tend to choose mutual funds with good prior performance for their 401(k) plans in terms of different performance measures. We now examine whether the good performance of mutual funds in 401(k) plans persists or not. If performance persistence holds, the participants of 401(k) plans can benefit by investing in funds with positive performance and staying away from funds with negative performance. Therefore, we investigate the performance persistence of mutual funds in 401(k) plans. In contrast, Elton et al. (2007) examine performance persistence of whole 401(k) plans and find evidence of performance persistence among plans with prior poor performance. The main difference between Elton et al. (2007) and our study is that they examine the whole plan performance persistence, whereas we investigate the performance persistence of individual mutual funds in 401(k) plans. To measure performance persistence of individual funds, we use the naïve regression suggested by Jagannathan, Malakhov, and Novikov (2010), ˛1i = a + b˛0i + εi

(1)

where ˛0i and ˛1i are the intercept of Carhart’s (1997) four-factor model in the evaluation and prediction period, respectively12 . If the coefficient estimate b is significantly positive, the fund’s performance is persistent. However, since the slope coefficient b of Eq. (1) may have downward bias in persistence caused by measurement errors in alphas, we also use a weighted least squares approach to potentially correct such bias13 . The model is t˛∗ 1i = a + bt˛0i + εi

(2)

˛0i /˛0 , t˛∗ 1i

where t˛0i = = ˛1i /˛0 , and ˛0 is the standard deviation of alpha during the evaluation period. For robustness, we also eliminate outliers by truncating the top and bottom 1% of the data

11 To mitigate the concern about multicollinearity between Inflow and TNA, we also delete TNA in the regression, but the results do not change qualitatively. 12 We wish to thank Ken French for making available the data on four factors (RMRF, SMB, HML, and UMD). 13 Refer to Jagannathan et al. (2010) for details.

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

93

Table 6 Performance persistence for funds in 401(k) plans and their matched funds. This table reports that performance persistence for funds in 1998 and 2004 401(k) plans. Following Jagannathan et al. (2010), we use naïve regression: ˛1i = a + b˛0i + εi , where ˛0i and ˛1i are the intercept of the 4-factor model in the evaluation and prediction period, respectively. To minimize downward bias in persistence caused by measurement errors in alphas, we also use weighted least squares (WLS) regression: t˛∗ = a + bt˛0i + εi , 1i where t˛0i = ˛0i /˛0 , t˛∗ = ˛1i /˛0 , and ˛0 is the standard deviation of alpha during the evaluation period. We also eliminate 1i outliers in the prediction period by truncating the top and bottom 1% of the data for these two models. Panel A reports the 3year evaluation period and the 1-year prediction period. Panel B reports the 1-year evaluation period and the 1-year prediction period. Panel A: 3-year evaluation period and 1-year prediction period Naïve regression without outliers in ˛1

Naïve regression 1998 401(k)

a b

2004 401(k)

1998 401(k)

Estimate

t-stat.

Estimate

t-stat.

−0.028 0.736

−0.87 14.63

−0.005 −0.018

−0.40 −0.65

t-stat.

Estimate

t-stat.

−0.084 0.493

−3.08 10.72

−0.007 −0.049

−0.67 −1.85

WLS regression without outliers in ˛1

WLS regression 1998 401(k)

a b

a b

2004 401(k)

Estimate

2004 401(k)

1998 401(k)

Estimate

t-stat.

Estimate

t-stat.

−0.101 0.431

−1.02 6.30

−0.392 0.399

−6.58 13.31

a b

2004 401(k)

Estimate

t-stat.

Estimate

t-stat.

−0.030 0.455

−0.32 7.02

−0.370 0.064

−7.08 1.88

Panel B: 1-year evaluation period and 1-year prediction period Naïve regression without outliers in ˛1

Naïve regression 1998 401(k)

a b

2004 401(k)

1998 401(k)

Estimate

t-stat.

Estimate

t-stat.

0.049 0.374

1.52 17.14

−0.004 0.014

−0.33 0.81

t-stat.

Estimate

t-stat.

0.004 0.299

0.16 15.91

−0.003 −0.020

−0.30 −1.20

WLS Regression without Outliers in ˛1

WLS regression 1998 401(k)

a b

a b

2004 401(k)

Estimate

2004 401(k)

1998 401(k)

Estimate

t-stat.

Estimate

t-stat.

0.221 0.432

3.52 10.63

−0.394 0.448

−7.79 19.74

a b

2004 401(k)

Estimate

t-stat.

Estimate

t-stat.

0.164 0.379

2.77 9.91

−0.371 0.154

−9.12 6.63

with respect to ˛1 and t˛∗ 1 for naïve and weighted least squares regression, respectively. In this study, we use two evaluation periods (3-year and 1-year) and a 1-year prediction period to investigate the performance persistence of individual funds in the 401(k) plans of 1998 and 2004. Panel A of Table 6 reports the results for the 3-year evaluation period and 1-year prediction period. In the naïve regression models of 1998, the slope coefficient estimates are significantly positive, suggesting that the funds in 401(k) plans of 1998 exhibit performance persistence. In contrast, for the sample of funds in the retirement plans of 2004, the slope coefficient estimates of naïve regression models are not significantly positive. However, if we use the weighted least squares regressions to minimize the downward bias in persistence caused by measurement errors in alphas, all slope coefficient estimates for both 1998 and 2004 are significantly positive. Panel B of Table 6 shows similar significant results for the 1-year evaluation period when we use weighted least squares regressions. Overall, the mutual funds in 401(k) plans exhibit persistent performance for both 1-year and 3-year evaluation periods. Furthermore, various studies find that persistence in fund performance exists among poorly performing funds (Hendricks, Patel, & Zeckhauser, 1993; Carhart, 1997; Elton et al., 2007). A natural

94

Panel A: 3-year evaluation period and 1-year prediction period WLS regression without Outliers in ˛1

WLS regression

1998 2004

b t−stat. b t-stat.

Top10%

Top33%

Bottom33%

Bottom10%

1.623 4.00 0.059 0.32

0.839 4.00 0.445 5.15

0.206 0.97 0.928 17.12

−0.088 −0.30 0.967 14.61

1998 2004

b t-stat. b t-stat.

Top10%

Top33%

Bottom33%

Bottom10%

1.823 4.69 0.027 0.14

0.818 4.38 0.458 5.21

0.107 0.51 0.742 5.42

−0.159 −0.58 1.496 5.67

Panel B: 1-year evaluation period and 1-year prediction period WLS regression without outliers in ˛1

WLS regression

1998 2004

b t-stat. b t-stat.

Top10%

Top33%

Bottom33%

Bottom10%

−0.382 −0.84 0.679 6.71

−0.058 −0.43 0.098 2.06

−0.041 −0.30 0.878 24.69

0.279 1.16 1.181 24.30

1998 2004

b t-stat. b t-stat.

Top10%

Top33%

Bottom33%

Bottom10%

0.224 0.68 0.675 6.52

−0.212 −1.70 0.098 2.06

−0.037 −0.30 0.543 9.62

0.403 2.40 1.143 10.63

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 7 Positive performance persistence vs. negative performance persistence. This table investigates whether performance persistence is caused by positive or negative performance for the mutual funds in 1998 and 2004 401(k) plans. We rerun the weighted least squares (WLS) regression: t˛∗ = a + bt˛0i + εi , separately for funds in the upper 10% and 33% and the bottom 33% and 1i 10% sample according to their alpha t-statistic (t˛0 ) ranking during the evaluation period. We also perform this analysis after eliminating outliers in the prediction period by truncating the top and bottom 1% of the data. Panel A reports the 3-year evaluation period and the 1-year prediction period. Panel B reports the 1-year evaluation period and the 1-year prediction period.

Panel A: Control for fund family and fund objective Year 1998

2004

N

401(k) funds

Matched funds

Difference test

Post 1-Year BHAR (%)

718

2.95 [−0.44]

5.74 [−3.03]

−3.90 [−3.56]

1 (low)

239

6.69 [0.02] 5.41 [−2.74] −3.27 [−0.37]

6.36 [−1.70] 6.09 [−4.16] 4.77 [−0.44]

0.23 [−0.54] −0.54 [−1.09] −8.65 [−4.57]

2

240

3 (high)

239

***

N

401(k) funds

Matched funds

Difference test

2762

3.36 [1.93]

3.82 [2.34]

−4.61 [−4.62]

−0.74 [−1.39] 3.15 [2.63] 7.52 [5.58]

0.28 [0.32] 2.99 [1.13] 8.08 [5.38]

−7.68 [−8.06] 1.07 [−0.17] −2.57 [−0.67]

***

910 925 ***

927

***

*** *** *** ***

**

Panel B: Control for fund objective Year 1998

2004

N

401(k) funds

Matched funds

Difference test

Post 1-Year BHAR (%)

767

2.70 [−2.35]

3.88 [8.20]

−1.67 [−5.09]

1 (low)

255

2

256

7.73 [0.19] 4.66 [−3.33] −4.28 [−1.03]

6.02 [8.23] 3.40 [−6.60] 2.24 [8.23]

1.17 [−0.99] 1.04 [−2.44] −7.39 [−6.43]

3 (high)

256

*

N

401(k) funds

Matched funds

Difference test

2886

3.35 [1.93]

2.63 [1.86]

6.84 [1.58]

***

948

−0.76 [−1.39] 3.21 [2.86] 7.43 [5.58]

−0.27 [−0.74] 2.38 [0.73] 5.72 [2.34]

−4.00 [−8.55] 4.97 [4.96] 8.01 [6.17]

***

***

969 ** *** ***

969

***

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 8 The subsequent one-year fund performance. This table reports the subsequent one-year performance of the mutual funds in the 401(k) plans for 1998 and 2004, respectively. Post 1-Year BHAR is the subsequent one-year buy-and-hold abnormal return of each fund following the 401(k) plan year with the corresponding S&P 500 index return as the benchmark. We also divide the sample into three groups according to the average monthly return of mutual funds in 401(k) plans for 1997 and 2003, respectively. In Panel A, each fund in 401(k) plans is compared with all funds both in the same fund family and with the same ICDI investment objective. In Panel B, each fund in 401(k) plans is compared with all funds with the same ICDI investment objective. In Panel C, each fund in 401(k) plans is compared with one fund selected randomly from funds both in the same fund family and with the same ICDI investment objective. The median values of the variables are reported in brackets. The symbols *** , ** , and * denote significance at the 1%, 5%, and 10% levels, respectively.

*** *** *** ***

95

96

Panel C: Randomly select one fund from the sample controlling fund family and fund objective Year 1998

2004

N

401(k) funds

Matched funds

Difference test

Post 1-Year BHAR (%)

718

2.95 [−0.44]

5.83 [−2.00]

−2.92 [1.34]

1 (low)

239

2

240

3 (high)

239

6.69 [0.02] 5.41 [−2.74] −3.27 [−0.37]

6.51 [−5.37] 6.44 [−6.91] 4.55 [−0.39]

0.17 [−0.01] −0.74 [−0.52] −5.53 [3.32]

***

N

401(k) funds

Matched funds

Difference test

2762

3.36 [1.93]

3.86 [1.67]

−3.25 [0.48]

***

910

−0.74 [−1.39] 3.15 [2.63] 7.52 [5.58]

0.19 [−0.67] 2.97 [1.58] 8.44 [5.48]

−5.28 [5.02] 0.95 [−3.59] −2.15 [−0.92]

***

925 *** ***

927

***

*** **

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

Table 8 (Continued )

H.-C. Chen et al. / North American Journal of Economics and Finance 35 (2016) 78–100

97

question is whether the performance persistence reported in Table 6 results from the group of funds with poor performance. This question also has an important implication since plan participants can benefit from observing the fund menus in their 401(k) plans. We address the above issue by separately investigating whether negative performance persists and whether positive performance persists. We run regression model (2) independently for the plan funds in the top 10%, top 33%, bottom 33%, and bottom 10% based on their alpha t-statistic (t˛0 ) ranking over the evaluation period. For robustness, we also perform this analysis after truncating outliers in the prediction period. Panel A of Table 7 reports the results for the 3-year evaluation period and 1-year prediction period. For the fund sample of 1998, the top 10% and top 33% of 401(k) plan funds exhibit significant performance persistence. In contrast, the bottom 33% and bottom 10% of plan funds have no evidence of performance persistence. These results suggest that the 401(k) plan funds of 1998 exhibit positive performance persistence. Furthermore, consistent with the previous literature, we find that performance persistence exists among poorly performing funds in 2004. Panel B of Table 7 reports the results for the 1-year evaluation period and 1-year prediction period. For the sample of 1998, we do not find consistent results. In contrast, for the sample of 2004, we find both negative performance persistence and positive performance persistence. Overall, the fund menus of 401(k) plans do not provide consistent recommendations for plan participants to select mutual funds. 4.3. Can investors benefit from observing the fund menus in 401(k) plans? As mentioned previously, Forms 11-k are publicly available from EDGAR, the SEC filings database. Therefore, if plan providers and advisors select well-performing mutual funds, the fund menus in 401(k) plans provide useful information to outside investors much like a buying recommendation for choosing mutual funds. We call this the signaling hypothesis. If the signaling hypothesis gains empirical support, then investors without excellent fund selection skills can just choose the funds that are listed in Forms 11-k to greatly reduce their search costs and likely improve their investment performance. To address this issue, we use three matching methods as in Table 4 when comparing the subsequent performance of mutual funds in 401(k) plans with the matching funds. Table 8 reports the average subsequent one-year buy-and-hold abnormal return for mutual funds in our 401(k) plan samples and their matching funds. Panel A of Table 8 shows that the average (median) post one-year buy-and-hold abnormal return for funds in 401(k) plans of 1998 is 2.95% (−0.44%) and 5.74% (−3.03%) for the matching funds. Although the mutual funds in 401(k) plans outperform the S&P 500 index, they do not exhibit better performance than the matching funds. Furthermore, the mutual funds in 401(k) plans of 2004 still underperform the matching funds. Similarly, the mutual funds in 401(k) plans do not outperform the matching funds in either Panel B or Panel C of Table 8, except in Panel B for 2004. Therefore, the fund menus of 401(k) plans do not provide good recommendations for investors to select mutual funds. We further divide our sample into three sub-groups based on the average monthly return in the prior year to examine subsequent performance. Panel A of Table 8 shows that, for the mutual funds in 401(k) plans of 1998, the groups of prior worst and middle performance do not outperform the matching funds significantly. In contrast, the group with prior best performance exhibits the worst performance and underperforms the matching funds. Both Panel B and Panel C of Table 8 show similar results when we use different criteria. If we examine the sample of 2004, the groups of prior worst and best performing funds still underperform the matching funds except in Panel B of Table 8. Overall, the fund menus of 401(k) plans do not provide recommendations for investors to select mutual funds because on average 401(k) funds underperform the matching funds. 5. Conclusion Since 401(k) plan assets are the sole financial assets outside of a bank account for most plan participants, the performance of plan investments is vitally important to plan participants. Furthermore,

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a 401(k) plan is a long-term investment, and plan participants are required to invest their salaries in investment options that are determined by plan providers. In this paper, we examine how plan providers select their plan investment options as well as the performance persistence of individual funds in the plan lists. We find that actively managed funds are more likely to be selected and around 80% and 63% of funds came from the top 10 fund families in 1998 and 2004, respectively. Overall, plan providers tend to choose actively managed funds, funds from top fund families, and/or funds with low expense ratios. Furthermore, although some evidence suggests that the performance of 401(k) funds is persistent, 410(k) investment options do not provide a good investing recommendation for plan participants because of the lack of consistent results across sample years. Similarly, since the performance of the selected funds does not outperform the matching funds, the 401(k) investment lists do not convey valuable information for outside investors to select mutual funds.

Acknowledgements We thank Kunchi Tsai and the conference participants at the National Taiwan Normal University for their helpful comments. Hsuan-Chi Chen gratefully acknowledges support from the Anderson School of Management at the University of New Mexico. Christine W. Lai wishes to thank the Ministry of Science and Technology in Taiwan for awarding the Grant 103-2410-H-003 -031-. The authors also gratefully acknowledge the editing assistance of Jacqueline Ramey.

Appendix A. The top 50 fund families This table reports the top 50 mutual fund families for 1997 and 2003, respectively. We rank the fund families based on the sum of total net assets (TNA) of mutual funds in the same fund family. TNA is reported in millions of dollars. Panel A: 1997 Rank

Family name

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Fidelity Funds Vanguard Funds American Funds Putnam Funds Franklin Funds Morgan Stanley Funds Dreyfus Funds Merrill Lynch Funds T Rowe Price Funds Smith Barney Funds Scudder Funds Federated Funds AIM Funds AXP Funds CMA Funds American Century Funds Oppenheimer Funds Schwab Funds Janus Funds MFS Funds Alliance Funds Prudential Funds Wells Fargo Funds Evergreen Funds BlackRock Funds

TNA 509,901 331,583 224,420 151,875 135,100 90,266 87,782 87,318 85,586 82,101 78,070 76,565 75,169 71,260 65,676 57,925 56,048 55,888 54,513 44,504 38,733 38,099 36,126 36,073 32,058

Rank

Family name

TNA

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

PIMCO Funds JPMorgan Funds UBS Funds Van Kampen Funds Mutual Series Funds Liberty Funds One Group Mutual Funds Strong Funds Financial Square Funds USAA Funds Nations Funds John Hancock Funds First American Funds Pioneer Funds SEI Funds Neuberger Berman Funds Waddell & Reed Advisor Funds Lord Abbett Funds Goldman Sachs Funds Centennial Funds INVESCO Funds Northern Funds Delaware Funds Seligman Funds ING Funds

31,704 30,757 30,245 28,915 28,171 27,951 25,265 22,584 22,219 21,798 21,678 21,212 20,979 19,094 18,250 17,980 17,810 17,448 16,890 16,393 16,248 15,883 13,987 13,910 13,246

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Panel B: 2003 Rank

Family name

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Fidelity Funds Vanguard Funds American Funds Franklin Funds PIMCO Funds Schwab Funds Putnam Funds Dreyfus Funds T Rowe Price Funds Nations Funds Janus Funds JPMorgan Funds Federated Funds AIM Funds Evergreen Funds One Group Mutual Funds Smith Barney Funds Oppenheimer Funds Merrill Lynch Funds Morgan Stanley Funds Scudder Funds ING Funds MFS Funds American Century Funds Wells Fargo Funds

TNA 800,789 711,379 494,530 168,061 143,464 138,892 136,231 134,969 124,094 120,820 111,520 105,688 104,016 103,340 102,594 101,092 94,842 94,665 94,441 93,276 87,125 81,683 79,922 78,315 77,063

Rank

Family name

TNA

26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50

Alliance Funds AXP Funds Hartford Funds Financial Square Funds BlackRock Funds Van Kampen Funds UBS Funds First American Funds Prime Funds Dodge & Cox Funds Northern Funds Liberty Funds Lord Abbett Funds SEI Funds Prudential Funds Goldman Sachs Funds Citigroup Family of Funds SSgA Funds CMA Funds USAA Funds DFA Funds Strong Funds Legg Mason Funds Pioneer Funds Eaton Vance Funds

69,350 68,764 65,232 64,008 62,223 54,553 52,182 50,744 50,051 48,985 44,603 40,886 40,571 38,948 34,692 32,859 31,537 31,193 30,415 28,276 28,051 27,364 26,503 26,079 26,057

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