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by Shane Enete, CFA; Miranda Reiter, CFP®; Wendy Usrey; Andrew Scott; and Martin
Seay, Ph.D., CFP®

Shane Enete, CFA, is an assistant professor of finance and program director of a CFP Board registered program at Biola University and a Ph.D. student in personal financial planning at Kansas State University. Prior to teaching, Enete worked as an investment research professional for 10 years for large institutional asset managers.

Miranda Reiter, CFP®, is Ph.D. candidate at Kansas State University and a financial adviser at USAA. Her research interests include diversity in financial planning and consumer behavior. She is a 2018 FPA Diversity Scholarship recipient and was named to the 2019 InvestmentNews 40 under 40 list.

Wendy Usrey is a faculty member in the Department of Finance and Real Estate at Colorado State University and a Ph.D. student in personal financial planning at Kansas State University.

Andrew Scott is an assistant professor of business at Saint Mary’s University of Minnesota, where he instructs courses in financial planning, finance, and economics. Scott is a Ph.D. student at the Institute of Personal Financial Planning at Kansas State University.

Martin Seay, Ph.D., CFP®, is program chair and associate professor of personal financial planning at Kansas State University, where he oversees and teaches in the CFP Board registered undergraduate, graduate certificate, master’s, and Ph.D. programs. He currently serves as the president-elect for FPA.

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Executive Summary

  • Although exchange-traded funds (ETFs) have grown rapidly over the last 15 years, there is still limited information on who chooses to invest in these funds.
  • Using the 2015 NFCS Investor Survey, the relationship between investor characteristics and ETF ownership was investigated for non-retirement investment accounts.
  • Financial knowledge, among other factors, was tested as a key variable for explaining ETF ownership, using a bounded rationality theoretical framework.
  • Results show that both subjective and objective investor knowledge were associated with a higher likelihood of owning ETFs, as well as being risk tolerant, financially satisfied, and under 45 years old.

Editor’s note: As the 2019 FPA president-elect, co-author Martin Seay was not involved in the peer review process for this research; nor did peer-reviewers know that Seay was a co-author during the double-blind peer review process.

Exchange-traded funds (ETFs) are registered investment vehicles ranging in design from tracking an index, commodity, investment style, or non-U.S. market to providing exposure to particular industries or investment vehicles (Lettau and Madhavan 2018). Investing in an ETF product rather than a mutual fund product offers a number of benefits; the most notable being lower capital gain tax payments, lower fees, and improved liquidity. ETF investors should expect to pay lower capital gain tax payments than mutual funds, given their trading structure (Kostovetsky 2003). In addition, ETF investors should expect to pay lower fees since accounting costs are determined at the shareholder level, rather than fund level. ETFs do not have load fees (which tend to be one of the largest fees associated with mutual funds), and ETFs do not have 12b-1 fees. And ETFs provide investors an additional liquidity benefit, because ETFs share prices allow for intraday values, whereas mutual funds are only priced once-per-day at their net asset value.

According to the FPA Trends in Investing Survey conducted by the Journal of Financial Planning, financial advisers are increasingly favoring ETFs over mutual funds.1 In 2017, ETFs hit a new record in growth with over $460 billion in new assets in comparison to mutual funds, which brought in $91 billion over the same time frame.2 Given that passive funds tend to outperform active funds during strong bull markets (Sorensen, Miller, and Samak 1998; Welch 2008), it is likely that the latest historic bull market, which was the longest running bull market in American history as of August 2018,3 further nudged investors from actively managed mutual funds to passively managed ETFs.

ETFs have steadily increased from 0 percent to 19 percent of total fund assets during 2005 to 2018.4 ETFs have also seen an average organic growth rate (the growth rate after removing the effect of market returns) of 16.5 percent over the last 10 years, compared to a 2 percent rate for mutual funds.5

This analysis sought to understand the relationship between investor characteristics and ETF ownership by exploring the role of investor knowledge, financial advice-seeking, and fee aversion for ETF ownership.

Given that ETFs are still a relatively new product with benefits still not fully understood by the full investment community, a bounded rationality theoretical framework was used to drive the conclusion of this paper. Specifically, investors may not be fully informed that ETFs are a viable investment option, leading to the main hypothesis that investor knowledge would be a significant explanatory variable when predicting ETF ownership.

This analysis evaluated ETF ownership within non-retirement accounts, which should reflect investor choice preferences more directly than including retirement accounts, since retirement accounts restrict investor choices. Using a binary probit regression model, four specific questions were addressed:

  1. Does subjective and objective investor knowledge influence the likelihood of ETF ownership?
  2. Does the relationship between subjective (how much an investor says they know) and objective investor knowledge (how successful an investor is in answering investor-related knowledge questions) affect the likelihood of ETF ownership?
  3. Do investors who own ETFs seek financial advice?
  4. Are fee-averse investors more likely to own ETF securities?

Literature Review

ETFs were first introduced in 1993 (Poterba and Shoven 2002). Modern-day mutual funds have been around since 1924. The two types of funds share similarities, and they have been found to be substitutes for one another (Agapova 2011). However, far more is known about how mutual funds are used by consumers (Alexander, Jones, and Nigro 1998; Engström 2007; Lenard, Akhter, and Alam 2003; Zheng 2008) than ETFs.

Little has been published in academic journals on ETF investor characteristics, particularly in the U.S., despite U.S. investors representing 72 percent of total net assets. As of December 2017, there were 1,569 index-based ETFs and 194 actively managed ETFs, totaling $3.3 trillion and 4.5 billion in net assets, respectively. Overall, ETFs make up 15 percent of the U.S.-registered investment company total net assets, while mutual funds comprise 83 percent. In 2017, net share issuance of ETFs reached a record high at $471 billion. Issues in global and international ETFs lead this growth with demand for domestic equity ETFs coming in at a close second place.6

Advantages of ETFs. ­ETFs offer some advantages over traditional mutual fund products. ETFs often have lower costs than even index mutual funds because of their improved tax efficiency (the creation and redemption process of buying and selling ETF shares allows for in-kind exchanges to occur that limit the distribution of any capital gains to ETF owners) and lower management fees (lower accounting costs at the shareholder level versus the fund level).

Kostovetsky (2003) analyzed the cost differences of ETFs versus index mutual funds and found that given the cost benefits of ETF securities, ETF investments should be chosen over index mutual funds when there is a high initial investment (i.e., for large investors) and for investors who face a relatively high capital gains tax rate. Zigler (2002) provided a tax efficiency rate measure and found that ETFs scored 97.15 percent in tax efficiency versus the mutual fund counterpart’s score of 81.23 percent. Not all studies have shown a lower tax benefit for ETF securities. Bernstein (2004) found no tax benefit when comparing ETFs with the broad mutual fund industry.

Regarding the proposed liquidity benefit of ETF securities over mutual fund shares, Carty (2001) and Kostovetsky (2003) both provide anecdotal evidence for this liquidity benefit, arguing that being able to trade intraday allows investors: (1) the ability to buy on margin and sell short for hedging purposes; (2) the ability to apply stop-loss and limit orders, and; (3) the ability to limit the loss from a high volatility event (e.g., stock market crash) through trading within minutes instead of having to wait for a once-a-day net asset value pricing.

Characteristics of ETF owners. In a study that examined ETF usage among self-directed German investors, Bhattacharya, Loos, Meyer, and Heckethal (2017) found that ETF owners tended to be younger, wealthier, and have a shorter relationship with their brokerage firm. Their research also found that ETF investors’ portfolios underperformed portfolios without ETF securities. When exploring ETF fund flows from a dataset of over 500 ETFs from 2001 to 2010, Clifford, Fulkerson, and Jordan (2014) found that investors who owned ETFs chased returns in the same way as mutual fund owners. Agapova (2011) investigated the degree of substitution between conventional index funds and ETFs. She found evidence that tax-sensitive investors might prefer ETFs when compared to investors who are either tax exempt or tax insensitive.

When trying to understand who might own ETF securities, prior literature has shown that financial behavior and ownership is associated with financial knowledge. Financial knowledge—both objective and subjective—has been shown to impact financial behavior (Allgood and Walstad 2016; Hilgert, Hogarth, and Beverly 2003; Robb and Woodyard 2011).

Financial literacy has been found to be positively associated with saving for emergencies (Chatterjee, Fan, Jacobs, and Haas 2017), total net wealth (Behrman, Mitchell, Soo, and Bravo 2012), improved credit card management behavior (Robb 2011), investor diversification (Abreu and Mendes 2010), and retirement planning abilities and readiness (Lusardi and Mitchell 2007; Young, Hudson, and Davis 2017). On the other hand, financial knowledge has been negatively associated with using alternative financial services (Robb, Babiarz, Woodyard, and Seay 2015; Seay and Robb 2013) and interest-only mortgages (Seay, Preece, and Le 2017).

Investment behavior and financial advice. Financial knowledge has been positively linked with using financial advice (Finke, Huston, and Winchester 2011; Robb, Babiarz, and Woodyard 2012), and the use of a financial adviser has been shown to influence financial behavior. Using a financial adviser has been associated with higher equity ownership (Zhang 2014), enhanced diversification (Bluethgen, Gintschel, Hackethal and Muller 2008), longer investment horizon (Winchester, Huston, and Finke 2011), and increased financial planning activities, awareness, and confidence (Salter, Harness, Chatterjee 2010).

Park and Yao (2016) found that use of a financial planner increased consistency in investors’ financial risk, attitudes, and behavior. Lei and Yao (2016) found that households who hired a financial planner experienced better portfolio performance. Conversely, in a study of Dutch investors, Kramer (2012) found no evidence of risk-adjusted performance between those who sought financial advice and those who were self-directed. However, he concluded that investors who used financial advisers were better diversified with less risky portfolios.

Theoretical Framework

Given a neoclassical economic theory framework, investors would choose to own ETF securities if they helped to maximize their own personal utility. While ETF ownership may, or may not, maximize the utility of many investors, documented advantages (e.g., enhanced liquidity, lower fees, and tax savings benefits) warrant consideration by most investors. Given that ETF securities are still a relatively new investment product that are not fully understood by investors, bounded rationality theory may better explain the current dynamics of ETF ownership.

The theory of bounded rationality proposes that people are not simply utility maximizers, but are a product of a two-system structure—intuition and reason—whose preferences are not always consistent with each other (Kahneman 2003). This leads to decision-making that does not maximize utility (Kahneman 2003). The intuition system seeks an effortless, fast, and accessible way of making decisions that is highly dependent on emotions and perception. The reasoning system is slow, controlled, and is less commonly used by individuals because of the amount of effort required. The intuition system, because of its reliance on perception, is highly “reference dependent,” which leads to the development of rule-of-thumb type of heuristics that people develop to avoid using their reasoning system. Although these heuristics are mostly useful for day-to-day living, they often result in the reliance on only information readily accessible to them (i.e., availability bias) and the use of prototype examples to make judgements (i.e., representative bias) (Thaler 2016). 

When applying bounded rationality theory to this analysis, it contends, “decision makers may be limited in their capacity to process and incorporate all relevant information” (Robb, Babiarz, Woodyard, and Seay 2015, p. 412). Given people’s reliance on heuristics and reference dependence, it is likely that many investors have not considered ETFs as a viable option. In addition, even if investors are familiar with ETF products, investors may still not be fully informed of how they work and their particular benefits.

Given that prior literature has found a strong connection between investor behavior and investor knowledge, ETF ownership was investigated in this analysis as an investor behavior that should be influenced by investor knowledge. Two types of investor knowledge were explored: (1) subjective (how much an investor says they know); and (2) objective (how successful an investor is in answering investor-related knowledge questions).

Research question No. 1: Does subjective and objective investor knowledge influence the likelihood of ETF ownership?

Hypothesis 1: There is a positive association between subjective investor knowledge and ETF ownership.

Hypothesis 2: There is a positive association between objective investor knowledge and ETF ownership.

When testing both subjective and objective investor knowledge, it is important to also test whether interaction effects exist (Allgood and Walstad 2013; Robb, Babiarz, Woodyard, and Seay 2015). When present, an interaction effect would signify that the relationship between objective financial knowledge and ETF ownership is dependent on an individual’s level of subjective knowledge, and vice versa.

Research question No. 2: Is there an interaction effect between subjective and objective investor knowledge when assessing the likelihood of ETF ownership?

Hypothesis 3: When assessing the likelihood of ETF ownership, there is a statistically significant interaction effect between subjective and objective investor knowledge.

In addition to financial knowledge, previous literature has also found a strong connection between investor behavior and seeking financial advice. Given that financial advisers tend to disseminate financial knowledge to investors (Winchester, Huston, and Finke 2011; Robb, Babiarz, and Woodyard 2012), a positive association is hypothesized between investors seeking financial advice and ETF ownership.

Research question No. 3: Does seeking financial advice influence the likelihood of ETF ownership?

Hypothesis 4: There is a positive association between seeking financial advice and ETF ownership.

Finally, given that one of the key benefits of ETFs over mutual funds is lower fees, ETF owners are hypothesized to be more sensitive to fees than non-ETF owners.

Research question No. 4: Are investors who are fee averse (i.e., view fees as a very important consideration when evaluating investments) more likely to own ETF securities?

Hypothesis 5: There is a positive association between fee aversion and ETF ownership.

Methods

Data and sample. Data from two surveys within the 2015 National Financial Capability Study (NFCS) were used in this study: the state-by-state survey and the investor survey. The 2015 state-by-state survey included responses from 27,564 adults over age 18. This survey was designed to be generalizable for the average adult living in the U.S. It measured perceptions, attitudes, experiences, knowledge, and behaviors on a wide variety of financial topics. The second survey used was the 2015 NFCS investor survey. This survey was conducted as a follow-up survey of the state-by-state survey and was limited to 2,000 respondents who indicated owning investments outside of retirement accounts. Data from these surveys can be merged, allowing respondents’ information to be connected. Both surveys were self-administered by respondents on a website, and respondents were not told that the investor survey and state-by-state survey were connected.

Dependent variable. The dependent variable for this analysis was a question from the 2015 NFCS investor survey that reads: “Which of the following types of investments do you currently own in non-retirement accounts?” Those participants who included ETF securities as a type of investment were coded as 1 (22 percent, n = 442), whereas, all other investors who had non-retirement investment accounts without listing ETF securities were coded as 0 (88 percent, n = 1,558). ETF ownership was evaluated within non-retirement accounts, which should reflect investor choice preferences more directly since retirement accounts restrict investor choices.

Independent variables. Independent variables for this analysis, as informed by theory and previous literature, included subjective and objective investor knowledge, whether an investor used an investment professional for investment advice, sensitivity to investment fees, overall financial satisfaction, and risk tolerance. Given limited missing data, listwise deletion was employed, resulting in a sample size of 1,920 from the original 2,000 observations.

Subjective and objective investor knowledge. Subjective investor knowledge was measured using a question from the 2015 NFCS investor survey that read: “On a scale from 1 to 7, where 1 means very low and 7 means very high, how would you assess your overall knowledge about investing?” Objective investor knowledge was measured using a series of multiple-choice questions that were included in the investor survey. Seven of these questions were used to create an objective investor knowledge scale (Cronbach alpha = 0.67). Three available questions were not used in the objective investor knowledge scale after identifying high correlation with the other seven questions.

Two alternative measurement strategies were employed to investigate a potential interaction effect as proposed by hypothesis 3. The first approach created a direct interaction term variable (subjective * objective). Consistent with previous literature, the second approach (i.e., bucket approach) tested for a potential interaction effect by allocating all investors into four distinct objective/subjective interaction buckets (Robb, Babiarz, Woodyard, and Seay 2015).

Investors were split into one of four buckets: (1) high objective/high subjective investor knowledge; (2) high objective/low subjective investor knowledge; (3) low objective/high subjective investor knowledge; and (4) low objective/low subjective investor knowledge. High objective investor knowledge was coded as 1 if the participant’s objective investor knowledge scale was 6, 5, or 4 (out of 6). Low objective investor knowledge was coded as 1 if the participant’s objective investor knowledge scale was 0, 1, 2, or 3 (out of 6). High subjective investor knowledge was coded as 1 if the participant’s subjective investor knowledge scale was 6, 5, or 4 (out of 6). And low subjective investor knowledge was coded as 1 if the participant’s objective investor knowledge scale was 0, 1, 2, or 3 (out of 6). This measurement strategy is consistent with Robb, Babiarz, Woodyard, and Seay 2015.

Seeking financial advice. To investigate hypothesis 4, the use of a financial adviser was measured through the investor survey question: “Which of the following best describes your current investment style?” Those who answered: “I make some decisions on my own and some with the help of a broker or professional adviser,” or “I let my broker or professional adviser make all my decisions for me,” were coded as 1. Those who answered: “I make all my investment decisions on my own without the help of a broker or professional adviser,” were coded as 0.

Fee aversion. For hypothesis 5, the level of fee aversion was measured using the 2015 NFCS investor survey question: “How important to you were the fees and pricing structure when opening your non-retirement investment account(s)?” A scale of 1 to 10 was used.

Other financial characteristics. Other financial variables included in the analysis were the participants’ level of financial satisfaction and risk tolerance. Financial satisfaction was measured using the state-by-state question: “Overall, thinking of your assets, debts, and savings, how satisfied are you with your current personal financial condition? (scale of 1 to 10). Level of risk tolerance was measured using the state-by-state question: “When thinking of your financial investments, how willing are you to take risks? A scale of 1 (“not at all willing”) to 10 (very willing”) was used.

Control variables. The control variables used in this study included sex, age, race, education, and total income. These socioeconomic variables have been used in previous literature as significant contributors to financial product choice (Robb, Babiarz, Woodyard, and Seay 2015; Alexander, Jones, and Nigro 1998).

Empirical Model

Let Y be whether a participant has an ETF security in their non-retirement investment account, whic​h is a function of financial variables (F), socioeconomic control variables (K), and an error term (ε). Three separate tests wer​e run in order to test the five hypotheses. For all three tests, a binary probit model was used given the binary nature of the dependent variable, Y (participant owns ETF security: yes or no). Every model tested for statistically significant coefficients, π> 0 with a null hypothesis expressed as H0 : π’ = 0, and alternative hypotheses as Ha : π 0.

Y = α + Fπ + Kβ + ε

To test for initial correlations between aspects of investor knowledge and ETF investment, model 1 includes the separate measures of objective and subjective financial knowledge. Given results from model 1, which indicate a relationship between each aspect of investor knowledge and ETF ownership, models 2 and 3 use alternative approaches to test for the presence of an interaction effect. All models include the full complement of financial characteristics and socioeconomic control variables.

Results

Sample characteristics. Table 1 provides an overview of sample characteristics for investors who own and do not own ETFs. Twenty-two percent of 2015 NFCS investor survey participants owned an ETF security. One-quarter of the full sample scored high subjective and high objective investor knowledge, while slightly more participants (28 percent) scored low in both subjective and objective investor knowledge. The full sample appeared to be highly sensitive to fees, with an average score of 8.2 out of 10.0. Looking at socioeconomic characteristics, the full sample tended to be over the age of 45 years (69 percent), white (80 percent), married (70 percent), and college-educated (70 percent).


Between ETF owners and non-ETF owners, ETF owners appeared to have higher subjective (4.6 versus 3.7) and objective (3.8 versus 3.5) investor knowledge, higher risk tolerance (7.5 versus 6.0), be younger (25 percent versus 14 percent under 35), and have a higher level of education (32 percent versus 25 percent have graduate degrees).

Model 1: The results for model 1 are shown in Table 2. Results provide evidence that support hypotheses 1 and 2, as subjective and objective investor knowledge were found to have a positive association with ETF ownership. When looking at average marginal effects, a one-unit increase in objective and subjective investor knowledge was associated with a 4 percent and 1 percent higher probability of owning an ETF security in a participants’ non-retirement portfolio, respectively.


Results failed to find support for hypotheses 4 and 5. No relationship was found between either seeking financial advice or fee aversion and ETF ownership. Other variables significantly associated with ETF ownership include the degree of financial satisfaction (2 percent higher probability of owning ETFs for every one-unit increase in financial satisfaction), level of risk tolerance (+3 percent), and age (being 25 to 34 years old meant having an 11 percent higher probability of having an ETF security, relative to those who were over age 65).

Model 2: The results for model 2 are also shown in Table 2. No evidence was found to support hypothesis 3, as the coefficient for interaction effect between objective and subjective investor knowledge was insignificant. In other words, no compelling evidence was found in support of objective knowledge on ETF ownership depending on the level of subjective investor knowledge, or vice versa. This would suggest that the effects of the two domains of knowledge are independent of each other when it comes to assessing ETF ownership.

Model 3: The results for model 3 are also shown in Table 2. These results are consistent with model 2 and fail to support the presence of an interaction effect. Specifically, investors in all buckets were found to have an increased probability of owning ETFs than those in the low objective/low subjective environment. Alternative models were also tested, and no difference was found between investors in the low objective/high subjective and high objective/low subjective bucket. This reinforced the results from model 2, indicating the effects of the two domains of knowledge are independent of each other.

Limitations

The primary limitation of this study is the relatively small sample size of ETF owners (436 of 2,000 original sample). In addition, the sample included a higher proportion of individuals who are high-income (35 percent >$100K), highly educated (73 percent completed college), and white (80 percent), which reduces the generalizability of the results to the American population. Another limitation is that this study only looked at ETF ownership among individuals who have investments outside of retirement accounts. Although evaluating non-retirement versus retirement accounts does help us understand direct investor choice more accurately, evaluating ETF ownership across all types of accounts should provide a more complete picture of the characteristics of ETF owners.

Discussion and Implications

ETFs are a relatively new investment product. The theory of bounded rationality provides a basis for understanding the nature of investor adoption given their limited ability to access, process, and incorporate all relevant information. Limited evidence was found to support the theory of bounded rationality, as objective and subjective financial knowledge were found to be positively associated with ETF investment (hypotheses 1 and 2). However, no evidence was found to support hypothesis 3, which might have suggested the presence of an interaction effect and potentially overconfidence bias. Similarly, no evidence was found to support a relationship between receiving investment advice and fee aversion and ETF ownership (hypotheses 4 and 5). This may be surprising if one considers using a financial professional as a proxy for increased access to information. Given that a primary benefit of ETFs is low fees, it may also be surprising that an aversion to investment fees did not appear to drive investors toward ETFs.

The results of this analysis show that ETF owners tend to have more investment knowledge. This has significant implications for both ETF companies and financial advisers. For ETF companies that are seeking a greater adoption of their ETF products, these results provide evidence that marketing and education efforts directed toward investors who have non-retirement investment accounts might improve ETF adoption by those investors. This study provided evidence that subjective and objective investor knowledge moved independently of each other, signifying that efforts meant to improve subjective and objective investor knowledge of ETF securities may both have a positive effect on ETF ownership. In other words, supporting investors’ confidence in their financial knowledge may be as important as educating those investors.

Other characteristics of ETF owners include higher financial satisfaction, risk tolerance, and being younger than 45 years old. Considering this result, financial advisers should understand that older investors are likely uninformed and could be a market that has high growth opportunities.

Recall that hypothesis 5 (there is a positive association between fee aversion and ETF ownership) was not supported. There are two possible explanations for this. First, lack of investor knowledge may be driving this result, which would mean investors are not fully informed consumers who would know that there are possible fee savings available to them by switching to ETFs. The second reason that ETF owners may not be more fee averse than non-ETF owners is that the fee difference between mutual funds and their ETF counterparts may not be enough to warrant a switch for the average investor. Kostovetsky (2003) suggested that the cost difference between index mutual funds and ETFs was only beneficial for relatively large investors.
Financial advisers who would like to increase ETF adoption among their clients should engage in education efforts to pave the way for greater acceptance of ETF securities among their clients. Possible education tools available for both advisers and clients include: etfdb.com, etf.com, etftrends.com, and merrilledge.com/investor-education/understanding-etfs.

A financial adviser may desire to increase ETF adoption among their clients for many possible reasons, including the desire to get access to a specific sector or niche market, gain access to a particular ETF product that is appropriate for a client and is only available as an ETF security (e.g., socially responsible product offerings), no or low minimum investment requirement, lower capital gain tax payments, smart beta strategies that can provide a blend of active and passive approaches, and the use of stop-loss orders to help mitigate downside market risk.

ETFs are not for all investors and carry some drawbacks. While a key benefit of ETFs are low expense ratios, some index mutual funds are cheaper, especially as large mutual fund institutions take measures to cut costs for investors while increasing their market competitiveness. And although some index mutual funds have no upfront costs or minimums for initial and subsequent purchases, ETFs trade much like stocks, so consumers must often pay a commission to purchase ETFs. This may pose a barrier to entry for consumers who are interested in contributing to a fund on an automatic periodic schedule. Therefore, it can be argued that those who are more cost sensitive may seek out low-cost index mutual funds rather than ETFs.

Two other disadvantages include thin trading among smaller ETFs as well as premiums to net asset value. Some of these disadvantages may shed light on why fee aversion was not associated with ETF owners in this study. Even with considering some of the disadvantages of owning ETFs, it does not undermine the key implications of this study: that ETF owners are more financially knowledgeable, have higher financial satisfaction, are younger, and have higher risk tolerance levels when compared to non-ETF owners.

Endnotes

  1. ​See “ETFs Still Reign; Planners Show Caution When Investing,” in the June 2018 Journal of Financial Planning. Available at OneFPA.org/Journal/Documents/June2018_SpecialReport.pdf​.
  2. See “ETFs Shattered Their Growth Records in 2017,” by Ryan Vlastelica, posted Jan. 3, 2019 at MarketWatch.com. Available at marketwatch.com/story/etfs-shattered-their-growth-records-in-2017-2017-12-11. Also see “ETF Growth ‘Is In Danger of Devouring Capitalism’,” by Robin Wigglesworth, posted Feb. 4, 2018 by Financial Times. Available at ft.com/content/09cb4a5e-e4dc-11e7-a685-5634466a6915.
  3. See “Reflections On The 9½-Year-Long Bull Market,” by John A. Prestbo, posted Sept. 9, 2018 by the Wall Street Journal. Available at wsj.com/articles/reflections-on-the-9-year-long-bull-market-1536545460.
  4. See “5 Charts on U.S. Fund Flows That Show the Shift to Passive Investing,” by Timothy Strauts, posted March 12, 2018 on the Morningstar Blog. Available at morningstar.com/blog/2018/03/12/fund-flows-charts.html.
  5. See endnote No. 4.
  6. See “U.S. Exchange Traded Funds,” in the 2019 Investment Company Factbook at icifactbook.org/ch4/18_fb_ch4​. See also “About ICI” from the Investment Company Institute at ici.org/about_ici.

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Citation

Enete, Shane, Miranda Reiter, Wendy Usrey, Andrew Scott, and Martin C. Seay. 2019. “Who Is Investing in ETFs? Exploring the Role of Investor Knowledge.” Journal of Financial Planning 32 (7): 44–53. 

 

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