Investor returns show the costs of bad timing around the world.
Morningstar expanded its Mind the Gap study from the United States and Europe to its first ever global look at investor returns across markets and asset classes. Although the five-year annualized investor returns gap ranged widely from region to region, from negative 1.4% to 0.53% for the year ended 2016, some common themes emerged. Investment vehicles that required systematic investment produced better investor returns, as did lower-cost funds.
Investor returns are a way to understand when investors use funds well and when they don’t. Although much has been written about active mutual fund managers lagging their benchmark, there is less attention to investors lagging their funds’ performance. Investor returns are money-weighted returns, as opposed to time-weighted returns, which are the standard way of displaying an investment’s total returns. We calculate investor returns for a single fund by adjusting returns to reflect monthly asset flows and their compounding effect over time to better illustrate the returns captured by the typical investor. Generally, investor returns fall short of a fund’s time-weighted returns because, in the aggregate, investors tend to buy after a fund has gained value and sell after it has lost value. Thus, they miss out on a key part of the return stream.
Gaps Around the Globe
The main challenge we face in calculating investor returns globally is that they require monthly flows at the share-class level. That data has become readily available in most markets in recent years. We are now able to calculate aggregate investor return data for the trailing five years in many but not all markets. There is insufficient share-class-level data to run 10-year investor returns in most markets outside the United States. The lack of 10-year data is important because investor return trends become more apparent during longer periods that include both up and down markets. We calculated the returns for share classes where the data is available to start the discussion while we await more-definitive data.
To aggregate fund investor returns data, we asset-weight investor returns using average assets under management during the period being measured. Then, we compare the asset-weighted return to the average fund’s total return. Essentially, we are comparing the average fund’s return in each peer group to the average investor experience. The gap between the two figures tells us how well investors timed their investments in the aggregate. Exchange-traded funds were not included because it is difficult to estimate investor intent.
This global study also considers asset-weighted total returns based on funds’ asset sizes at the beginning of the time period, while our previous U.S.-based studies considered fund sizes at the end of the period. Comparing this with asset-weighted investor returns tells us whether investors made wise changes in the ensuing time period or whether they should have stood pat. We also sorted investor returns based on a few factors to see which appear to have a link with investor returns. For this report, we tested fees, Morningstar Risk, standard deviation, and manager tenure. These tests may be the most important part of the study because they suggest which kinds of funds investors use well.
This study also uses global fund groupings. Some of the groupings used in previous U.S. studies, such as foreign and municipal bond, were rolled into equity and fixed income. We use Luxembourg as a proxy for Europe except for the U.K.
Strong Results for Automatic Plans
In the United States and Europe, we found declining gaps between investor returns and total returns (EXHIBIT 1). In other markets where we calculated investor returns for the first time, we found generally modest gaps of less than 100 basis points. Again, we caution that data in some of these markets is limited and, therefore, not sufficient to draw strong conclusions.
In South Korea, investors had particularly good timing in fixed-income funds. In Australia, superannuation funds enjoyed positive gaps. In the U.S., allocation funds had positive gaps. The link across these markets were automatic investment plans. In the U.S., target-date funds have consistently had positive gaps because investors contribute to their 401(k) savings with every paycheck. In South Korea, general savings plans feature automatic monthly investments, though they are not the only means of investing in funds. These relatively simple plans work wonders at keeping investors on track and preventing them from unwise market-timing moves. Seeing this work in three different investment cultures is a strong endorsement for the practice worldwide.
Automatic investment plans are a structure that regulators around the world are considering as a way to encourage retirement savings. The most recent example is the launch of the Default Investment Strategy in Hong Kong. The evidence suggests the idea has merit for its ability to help investors realize the potential of retirement plans. In a sense, it combines some of the strengths of defined-benefit plans and defined-contribution plans by making low-cost diversified investments the default option.
The overall 10-year gap in the U.S. has shrunk from 55 basis points at the end of 2015 to 37 basis points at the end of 2016. Adding another year of solid market returns likely helps. A second factor that is driving the aggregate gap lower over the long haul is that yearly flows have not kept pace with the growth in assets under management. Thus, in the aggregate mutual fund investors are making fewer market-timing calls that can harm results. However, that doesn’t mean the challenge for individual investors has diminished, as they can still do as much harm to their portfolios as before.
The Do-Nothing Portfolio
To determine how investors would fare had they left their portfolios untouched, we created the Do-Nothing Portfolio, which uses fund total returns that are asset-weighted at the beginning of the time period. This allows us to isolate the changes investors made during the time period in question by comparing the typical investor return (as measured by investor returns that are asset-weighted using an average for the entire time period in question) with the Do-Nothing Portfolio.
We created Do-Nothing Portfolios in five regions around the globe (shown in EXHIBIT 1 ). Performance for this measurement was mixed, but in the United States, it performed surprisingly well. In the U.S., the portfolio weighted with beginning-of-the-period assets produced better results than either investor returns or a straight average of returns in each asset class. The typical diversified-equity-fund investor would have had a return of 5.31%, topping the 5.15% average fund return and the 4.36% average investor return. For U.S. bond funds, the Do-Nothing return was 4.3% compared with 2.99% for the average investor return and 3.72% for the average fund return. For allocation funds, the Do-Nothing return was 4.98%, decisively beating the average investor return (4.31%) and the average fund return (4.26%). The reason, as stated above, is that target-date funds are a fast-growing segment of the allocation group.
Factor Sort Results
For our factor tests, we grouped funds into quintiles based on the data at the beginning of the time period, and we ranked within the mapping group. For example, we ranked fees within concentrated equity from five years ago and then tracked investor returns for each quintile’s subsequent results. Funds of funds were excluded, so the data set for the factor tests was slightly different from the broad asset-class gap figures. The number of funds to survive the time period declines sharply as we move to higher-cost groups. As a result, the negative impact of higher costs is understated because many high-cost failures are eliminated by fund companies.
We sorted the results in two ways. First, we sorted relative to Morningstar Category, and then we sorted relative to the broad mapping group. For example, the category sort ranked all U.S. large-blend funds against each other and placed them into quintiles. For the broad mapping groups, we compared U.S. large-blend funds against all other diversified equity funds. This is a useful exercise particularly for markets where the relative-to-category rankings were less helpful because there was a limited data set of funds with sufficient data in a category. In last year’s U.S. Mind the Gap paper, we did something similar, but only for standard deviation, as it appeared that volatility relative to the broad group was more meaningful than within a more narrow peer group. Sorts such as fees and Morningstar Risk make the most sense on a category level, while standard deviation and manager tenure fit better with our broad mapping groups.
The data was fairly clear for fees and manager tenure. When we tested fees, we generally saw investor returns decline as we moved from low-cost to pricey expense quintiles. In addition, the gap usually grew as we moved up in price. In markets with strong survivorship bias, these results were likely understated because high-cost funds that fail are often eliminated. In addition, five-year figures tend to show less of an effect because there is less time for the fee to compound and drag down returns.
Still, the trend is clear. In Luxembourg’s diversified equity group, the five-year investor return in the category rank steadily eroded as fees rose. In the U.S., investor returns shrunk and the gap grew with each step to higher fee levels (E X H I B I T 2).
The impact appears to exceed the stated expense ratio. There are likely two additional factors at work. First, higher-cost funds frequently take on greater risks to overcome their lofty fees. Thus, they may be more prone to inspiring fear and greed in investors, leading to poor timing decisions in both directions. Second, we likely have a meeting of savvy investors and responsible fund companies in cheap funds and a meeting of less-responsible investors and fund companies in the high-cost zone.
Manager tenure results were quite similar across markets. They showed no trend whatsoever when we grouped funds by manager tenure. This isn’t a surprise, as manager tenure hasn’t shown much of a link with returns or risk. Manager tenure does not equate to experience, and more importantly, it does not account for quality of experience.
We saw mixed results for standard deviation and Morningstar Risk, which is similar to standard deviation except that it penalizes downside volatility more ( EXHIBIT 2 ). In the past, we’ve found a fairly strong suggestion that more-volatile equity funds lead to worse investor returns because they are harder to time and trigger emotional responses. Some markets showed this relationship, but others did not. It could be that a relatively smooth market environment in the past five years has rewarded volatility and, therefore, understates the effect, but that’s just a guess. In any case, the least-volatile quintile generally fared better than the most-volatile quintile, but the quintiles in between did not follow a neat stair-step pattern down the way fees did. Thus, the link between volatility and investor returns remains but appears to be weaker than in past studies.
Follow the Gap
More important than the size of the gap are the characteristics of funds that deliver strong investor returns. They suggest where the fund industry needs to go. Clearly, low costs are vital, and advisors would do well to steer investors away from the highest-risk funds, as such funds tend to have poor investor returns. Also, it appears that simple tactics to prevent performance chasing, such as dollar-cost averaging and automatic rebalancing, help investors stick to their plan.
This article originally appeared in the August/September 2017 issue of Morningstar magazine.