Analysis of Becker Value Equity Fund
January 31, 2014
Finding Star Fund Managers
A recent article in Barron’s touts the virtues of Becker Value Equity Fund that just received a five-star rating from Morningstar:
The Becker Value Equity Fund (ticker: BVEFX), which turned 10 late last year, has outperformed in good times and bad, logging much smaller losses than the overall market during the bear turn in 2008 while also outpacing the Standard & Poor’s 500 in the past year, when stocks soared. The fund’s average annual return over the past decade is 8.4%, more than a percentage point better than the S&P 500.
As of January 30, 2014, the fund’s annualized 10-year return was indeed 1.25% higher (8.15% vs. 6.90%) than that of the S&P 500® total return index. However, that index is a secondary prospectus benchmark for the fund; the primary benchmark is the Russell 1000 Value index. Using the iShares Russell 1000 Value ETF (IWD) as a proxy for the latter, the difference in 10-year return was a slightly lower, but still commendable, 1.21%.
Still, according to Morningstar the best-fit index for the fund is the Russell 3000. Applying the iShares Russell 3000 ETF (IWV) as a proxy, the return difference further shrinks to 0.91%. This is a result of the fund’s tilt toward large- and mid-cap stocks compared to the composition of all these benchmarks. It also demonstrates the importance of benchmark selection, especially when a single static index is used.
In contrast, let’s take a look at the fund’s performance from Alpholio™’s perspective, i.e. using a dynamic reference portfolio of ETFs of a comparable risk as a benchmark:
Since early 2005, the cumulative RealAlpha™ for BVEFX has been largely flat. The fund did not add a lot of value on truly risk-adjusted basis until the second half of 2013. As a matter of fact, the annualized RealAlpha™ for the fund was only 0.32% in the entire period.
The following chart shows ETF weights in the reference portfolio for the fund in the same period:
The fund had top-three equivalent positions in the Vanguard Value ETF (VTV; average weight of 21.7%), Guggenheim S&P 500® Equal Weight ETF (RSP; 20.1%) and iShares Morningstar Large-Cap ETF (JKD; 15.3%).
With an average weight of 10.3%, the equivalent short-term investment position in the iShares 1-3 Year Treasury Bond ETF (SHY) was substantial, which indicates that at times the fund may have engaged in market timing typical of value investments. Historically, the weight of this equivalent position was as high as 23.9%. According to the most recent filing, as of the end of October 2013 the fund’s holdings included about 4.5% in the Invesco Short-Term Investment Trust Treasury Portfolio.
The next-highest equivalent position was in SPDR Russell 3000® ETF (THRK; average weight 6.1%). This supports the previously mentioned tilt of the fund toward lower-capitalization stocks. For example, as of the end of 2013 the fund’s top-ten holdings include IAC/InterActive, NCR and Plum Creek Timber Co., each with market cap of less than $8 billion.
At 0.94%, the fund sports a relatively low net expense ratio, which is one of the dominant factors in long-term outperformance. However, it has to be noted that if a contractual fee waiver, currently in effect through February 2014, is not renewed, the expense ratio may revert to the total gross expense ratio of 1.10%. Also, the fund’s annual turnover ratio of 38% is lower than the average 52% in the large-cap value category (including index funds).
In sum, the Becker Value Equity Fund has added a modest amount of value for its investors on a fully risk-adjusted basis, especially if its outperformance in the last six months is factored in. However, there is no guarantee that this recent winning streak will continue.
January 27, 2014
Analysis of Fidelity Contrafund – Revisited
With the new Fund Manager of the Year awards from Morningstar, a question of future performance of star fund managers inevitably arises. Apparently, the awards carry little short-term predictive value:
While our Fund Manager of the Year awards are recognition of past contributions rather than predictions of future results, we’re confident in each one’s long-term prospects because of their deep research resources and willingness to stick with their discipline in good times and bad. We wouldn’t expect repeat performances in 2014, as our winners and their rivals will wrestle with lofty equity valuations, policy-related volatility, a still-recovering economy, and the specter of rising rates.
Indeed, statistics on award winners presented by an article in The Wall Street Journal are not too encouraging:
||Beating the Benchmark
Generally, the best long-term predictors of fund outperformance remain a low expense ratio (fees), minimal portfolio turnover (a proxy for trading costs), and divergence from benchmark index weightings. The latter measure, known as active share should be high:
Prof. Cremers says the best funds tend to have active-shares percentages that are at least 60%. Large-stock managers should ideally have an active share above 70%. Midcap managers should have active share above 85% and small-cap managers should exceed 90%, he says.
Unfortunately, the proportion of funds with such big active shares has been falling over the years, which gave rise to “closet indexing,” as a chart from a Lazard Research study demonstrates:
The active share in the aggregate portfolio of actively-managed U.S. stock funds has been also declining:
However, active is not always a guarantee of strong performance, as shown in an earlier Alpholio™ post.
As for fund fees, an article in The New York Times points out that
The average total expense ratio, which encompasses management fees and operating expenses but not brokerage commissions and other trading costs, is 1.33 percent of assets a year for domestic stock funds and 0.97 percent for domestic bond funds, according to Morningstar.
Over time, these fees add up. According to a paper by William Sharpe, which estimated an average expense ratio of stock funds at 1.12% compared to 0.06% (now 0.05%) for the Vanguard Total Stock Market Index Fund (VTSAX, Admiral Shares):
Whether one is investing a lump-sum amount or a series of periodic amounts, the arithmetic of investment expenses is compelling… Under plausible conditions, a person saving for retirement who chooses low-cost investments could have a standard of living throughout retirement more than 20% higher than that of a comparable investor in high-cost investments.
However, as a Gerstein Fisher study found, the cheapest funds may not always provide the highest returns:
We found that the best performing quintile of funds was the second most expensive quintile (i.e., the 21-40% highest-cost ones), whether we equally weighted funds or asset-weighted them. The consistent results of the study: the cheapest quintile of funds was not the best performing, but the most expensive funds were the worst performing.
Similarly to a low correlation, a factor that is often quoted to aid stock pickers is a high degree of dispersion (measure of spreading) of stock returns. At first blush, it would seem that, just as with active share, an increased dispersion is beneficial. However, all it does is to enlarge the dispersion of active fund returns, without necessarily moving the average, as another article in The Wall Street Journal indicates:
A bigger spread between the best and worst stocks hasn’t helped active funds as a group, but it does tend to make good funds better—and bad funds worse… To put it another way: Markets that aren’t moving in lock step give active managers more rope with which to climb above the pack or to hang themselves.
While a low cost and small turnover coupled with a significant active share are generally good screening criteria, funds clearly have trouble with performance persistence. As our analyses have repeatedly demonstrated, even the star fund managers stumble, so outperformance is fleeting. This is where the Alpholio™ methodology helps by showing momentum in the smoothed cumulative RealAlpha™ for each analyzed fund, from which buy/sell signals can be derived. To learn more, please visit our FAQ.
January 23, 2014
Timing of IRA Contributions
A recent article in InvestmentNews caused Alpholio™ to revisit its analysis of Fidelity Contrafund originally published in early 2013. The article says
Over the past few years, stock fund managers have struggled mightily to beat their indexes consistently, but you’d never know it by looking at the track record of Fidelity’s William Danoff.
The 23-year veteran and manager of the flagship $111 billion Fidelity Contrafund (FCNTX) is beating the S&P 500 over the trailing one-, three-, five-, 10- and 15-year trailing time periods as of Jan. 17, according to Morningstar Inc.
First, it has to be noted that for the past eleven years Morningstar classified FCNTX in the Large Growth category, while the S&P 500® index is traditionally considered a benchmark for Large Blend funds. Therefore, it may be more appropriate to compare the performance of FCNTX to that of an large-cap growth index fund, such as the Vanguard Growth Index Admiral (VIGAX). It turns out that in terms of returns, FCNTX beat VIGAX in each year from 2003 to 2008 but in no year afterward until 2013. This caused the annualized three- and five-year returns of FCNTX to be lower than VIGAX’s. However, FCNTX outperformed VIGAX in terms of the Sharpe Ratio over the three-, five-, ten- and fifteen-year periods.
The recent return shortfall can be attributed to a large size of the fund — over $111 billion in assets, trailing only one other actively-managed fund. The article quotes the FCNTX manager admitting that:
“Larger funds have a higher degree of difficulty,” Mr. Danoff said in a rare interview last summer. “For me, it’s the ability to make big bets — it’s harder. My denominator is so big that it’s not that easy to find really great stories at scale.”
Let’s again take a look at the fund’s cumulative RealAlpha™, updated through last December:
In 2013, there was no material change in risk-adjusted performance of the fund until the second half of the year. However, after peaking in October, the cumulative RealAlpha™ declined in the last two months. While for the year the fund managed to return 1.75% more than VIGAX, Alpholio’s longer-term assessment of FCNTX stayed the same. Even prior to 2009, the fund’s cumulative RealAlpha™ was roughly flat, and since then, the fund mostly failed to beat its reference portfolio of exchange-traded funds (ETFs). Since early 2005, the fund’s annualized RealAlpha™ was negative 1.35% with respect to a reference portfolio of comparable volatility.
The fund’s reference portfolio has not changed much since the last analysis, except the average historical weight of iShares MSCI Emerging Markets ETF (EEM) became smaller than that of the Vanguard Consumer Staples ETF (VDC):
In 2013, the reference portfolio continued to be dominated by the iShares Morningstar Large-Cap Growth ETF (JKE; average 12-month weight of 51.3%), iShares Morningstar Mid-Cap Growth ETF (JKH; 14.4%), Vanguard Health Care ETF (VHT; 10.0%), and PowerShares QQQ™ ETF (QQQ; 5.4%).
In sum, from Alpholio™’s perspective there does not appear to be any indication of a permanent change in the fund’s longer-term performance. Since 2005, investors would have achieved better results with a reference portfolio of ETFs and, in the last several years, higher returns with a comparable index fund.
To get more information about Fidelity Contrafund and other mutual funds, please register on our website.
January 21, 2014
Asset Allocation in Retirement Portfolio
With the start of a new calendar year, many investors are considering making 2014 contributions to their individual retirement accounts (IRAs). However, given the recent appreciation of stocks to the perceived point of overvaluation, and poor prospects for bonds in light of an anticipated rise in interest rates, many investors may hesitate to make early contributions. This brings about two questions: What is the historical penalty for such procrastination? What happens if the investor decides to spread the annual contribution over time in the allowable period?
A simplistic answer to the first question is given in an article in The Wall Street Journal:
Contributing $5,500 to an individual retirement account each January, rather than in April of the following year, over 31 years (with an average annual 7% return) could boost the IRA balance by $55,000.
This calculation assumes a constant rate of return on investment in each year, which is unrealistic. In addition, it assumes that the contribution is fixed at a currently allowed maximum amount, even though in recent years the maximum has been revised upwards to approximate inflation (granted, historical maximum contribution was fixed at $2,000 between 1981 and 2001). Also, it does not specify the percentage increase of the terminal balance. Finally, it does not specify the exact nature of the “moderate” portfolio in the IRA.
To provide a more accurate answer to both questions, Alpholio™ conducted a mini study. (Since this post is longer than a usual one, time-pressed or impatient readers may want to skim the charts and navigate right to conclusions at the end of this write-up.)
To make study results tangible, instead of pure indices, two low-cost, no-transaction-fee investment vehicles with sufficiently long life spans were chosen: the Vanguard 500 Index Fund Investor Shares (VFINX) and Vanguard Total Bond Market Index Fund Investor Shares (VBMFX) mutual funds. The younger of the two, VBMFX, determined the longest feasible study period beginning in January 1987. For both funds, total (i.e. with reinvested distributions) rather than just price returns were used.
Various IRA portfolios, ranging from 100% stocks (all-VFINX), to 60% stocks and 40% bonds (the “standard” portfolio), to 100% bonds (all-VBMFX) were investigated. All portfolios were rebalanced monthly to their nominal asset allocations. Instead of a fixed contribution, a maximum contribution allowed by law in each historical year was assumed. The study did not take into account the higher “catch-up” contributions allowed for older investors, or any withdrawals or mandatory distributions that could trigger taxes or penalties.
The study considered two scenarios. In the lump-sum scenario, the maximum allowable contribution was made in whole at the beginning of a single month ranging from January of the contribution year to the following April (the deadline for making a contribution for the prior calendar year typically falls in mid-April). In the dollar-cost averaging (or “spread”) scenario, the contribution was evenly split and made at the beginning of a number of months starting in January of the contribution year.
The type of scenario determined the terminal year of investment. In the lump-sum scenario, the terminal investment could be made from January 2012 to April 2013 (that is because as of this writing, monthly data through April 2014 are not yet available). To roughly time-align with the lump-sum scenario, the spread investment scenario assumed that the terminal investment would take place in 2012.
For all asset allocations, the penalty was calculated as one minus the ratio of the terminal value of the portfolio with delayed or spread investments to the value of the portfolio when all investments were made as early as possible in January (baseline). For example, if delayed or spread investments resulted in a terminal portfolio value of $93,000 and January lump-sum investments generated $100,000, then the penalty was 1 – 93/100 = 7%.
The Lump-Sum Scenario
As could be expected, due to generally positive returns of stocks and bonds over time, a delayed lump-sum investment carried a penalty. Here is the penalty for a 100% stock and 0% bond (100/0) portfolio:
Generally, the lump-sum penalty had a positive relationship with the investment delay — the longer investor waited, the bigger the shortfall of the terminal value of the portfolio. However, the penalty did not always grow monotonically with the delay, as can be seen by its significant decrease in November and December in the above chart.
This particular case underscores the impact of first years of investing. Here, the almost 22% negative stock market return in October 1987, followed by a negative 8% return in November 1987, caused the penalty to diminish if the investor delayed the contribution toward the end of that year. To further illustrate the importance of early contributions in the IRA life cycle: The $2,000 invested in January 1987 was worth over $27,000, or about 10% of the terminal value portfolio, at the end of 2013.
The trend line in the chart shows that on average a procrastinating investor suffered a penalty of 0.66% of the terminal portfolio value per month of delay, culminating in about 12% of penalty if all investments were made in April of the year following the contribution year.
The more the IRA portfolio tilted towards bonds, the smaller the penalty. Here is a chart for a standard portfolio:
With this asset allocation, the penalty reached just over 10% and accrued at 0.63% per month.
For a 40% stock and 60% bond portfolio, the maximum penalty was just below 10% and grew at an average rate of 0.60% per month:
Finally, for a bond-only portfolio, the penalty peaked at just over 7.5% and increased by 0.52% per month on average:
According to the article:
An analysis of traditional and Roth IRA contributions made by Vanguard Group customers for the 2007 through 2012 tax years showed that, on average, 41% of the dollars contributed to IRAs for any given tax year are invested between January and April of the following year. Half of those dollars are contributed in the first half of April—the final weeks when contributions for the previous year can be made. The study found only 10% of dollars are contributed in January of the corresponding tax year, the earliest month contributions can be made.
This means that the majority of investors pay a significant price for delaying their investments. Granted, many investors may find it hard to come up with a lump sum for the entire contribution each January. Others may want to spread their investment over two or more months to minimize the risk in fluctuating market conditions. Let’s take a look at the effects of the latter scenario next.
The Spread Scenario
For a stock-only portfolio, uniformly dividing the annual contribution carried an average penalty of 0.53% per each additional spread month. When the contribution was dollar-cost averaged over the entire year, the total penalty was just over 5.5%:
For a standard portfolio, the penalty accrued at 0.41% per additional spread month to reach almost 4.5%:
For a more conservative 40% stock and 60% bond portfolio, the penalty increased on average by 0.34% per month and peaked at almost 4%:
Finally, for a bond-only portfolio, the penalty rose by 0.22% per spread month to reach a maximum of just over 2.5%:
The above findings are consistent with those of a Vanguard study on outcomes of lump-sum and dollar-cost averaging of investments. That study used fixed 10-year intervals, sliding by one month in a longer period of 1926 to 2011. It found out that for a standard portfolio, in 67% of cases a lump-sum investment outperformed dollar-cost averaging over the first 12 months of each 10-year interval. The terminal value of the lump-sum portfolio was on average 2.3% higher than that of the dollar-cost averaging portfolio.
Not surprisingly, delaying or spreading IRA contributions within the allowable 16-month window for each contribution year resulted in a penalty of a lower terminal value of the portfolio. The per-month average accrual rate and the magnitude of the penalty depended on asset allocation in the portfolio: The more tilt toward equities, the higher the rate and magnitude. Contributions in early years had a dominant impact on penalty distribution due to compounding of returns.
Clearly, investors pay a substantial price for procrastination in a lump-sum contribution scenario. Therefore, the investment for a given contribution year should generally be made as soon as possible. However, in many cases a full contribution amount may not be available early in the year, the investor may be averse to taking the risk of a lump-sum investment in given market conditions, or may not have a complete view of his/her income and tax situation until later in the contribution time frame. In that case, dollar-cost averaging with smaller sums can help lower the risk of a one-time investment and penalty for a delayed contribution.
January 16, 2014
REIT Correlations with Stocks
A study by Pfau and Kitces in the Journal of Financial Planning gives a counter-intuitive guidance on asset allocation in a retirement portfolio. Instead of a traditional glide path that decreases the equity portion of the portfolio with the retiree’s age, the authors found that a rising allocation is optimal for retirement success, i.e. not running out of money.
The authors conducted 10,000 Monte Carlo simulations with three different sets of assumptions about stock and bond returns, equity risk premia as well as inflation rates, 121 lifetime asset allocation glide paths, annual withdrawal rates of 4% and 5%, and time horizons of 20, 30 and 40 years. The conclusions were:
Accordingly, for those households looking to maximize their level of sustainable retirement income, and/or to reduce the potential magnitude of any shortfalls in adverse scenarios, portfolios that start off in the vicinity of 20 percent to 40 percent in equities and rise to the level of 60 percent to 80 percent in equities generally perform better than static rebalanced portfolios or declining equity glide paths. The results hold even in situations where the final equity exposure is no higher than what the client’s static portfolio allocation may have been in the first place.
The results also reveal that in particular scenarios where the equity risk premium is depressed, the optimal glide path includes less equity overall. In scenarios where the goal is to withdraw at a level that stresses the portfolio [5%] and its expected growth rate, higher overall levels of equity are necessary (with such high-risk goals, having a relatively high-risk portfolio, even with the danger this approach entails, is still the optimal solution).
The key reason for starting with the initial lower allocation to stocks is that
…in the case of a 30-year time horizon, the outcome of a withdrawal scenario is dictated almost entirely by the real returns of the portfolio for the first 15 years. If the returns are good, the retiree is so far ahead relative to the original goal that a subsequent bear market in the second half of retirement has little impact. Although it is true that final wealth may be highly volatile in the end, the initial spending goal will not be threatened. By contrast, if the returns are bad in the first half of retirement, the portfolio is so stressed that the good returns that follow are absolutely crucial to carry the portfolio through to the end.
This is supported by Vanguard portfolio allocation models that range from 100% bond to 100% stock allocations and are analyzed in the 87 years from 1926 through 2012. As can be expected, the average annual return of a portfolio increases with allocation to equities, but generally so does the number of down years as well as the maximum annual loss. So, is there an optimal allocation that would maximize the average annual return while minimizing the probability of a loss year? To determine that, Alpholio™ compiled the following chart:
The ratio peaks for a portfolio with 20% stocks and 80% bonds, which is consistent with the findings of the study.
The main problem with this and similar studies is that they assume a mechanical annual adjustment of withdrawals based on the prior year’s inflation rate. This is done to maintain the purchasing power of withdrawals. However, in reality expenses fall with age during retirement, as an article in The Wall Street Journal indicates:
“Pretty much every paper you read about retirement assumes that spending increases every year by [the rate of] inflation,” Mr. Blanchett says. But when he analyzed government retiree-spending data, he found otherwise: Between the ages of 65 and 90, spending decreased in inflation-adjusted terms.
Most models would assume that someone spending $50,000 the first year of retirement would need $51,500 the second year (if the inflation rate were 3%). But Mr. Blanchett found that the increase is closer to 1%, which has big implications over decades, “because these changes become cumulative over time,” he says.
In the above example, the terminal annual withdrawal after 25 years would be $104,689 with a 3% annual increase vs. only $64,122 with a 1% increase. This significant difference would certainly change the outcome of simulations with the rising equity glide paths. Most likely, either a flatter (less risky) path would suffice for a given success rate, or a success rate would increase for a given glide path.
To determine the optimal asset allocation in retirement, it is also useful to see the spending distribution among major expense categories:
Not surprisingly, in a typical retirement period healthcare and charity expenditures grow, while insurance/pensions, transportation and clothing expenditures shrink as a percentage of the overall budget. A recent slowdown in medical-price inflation, which historically outpaced the overall inflation, is likely a result of passing on more costs to consumers (as well as a temporary effect of the Great Recession). Therefore, it seems reasonable to keep a sizable exposure to equities even late into retirement, while minimizing the risk in early years. This is what a U-shaped glide path strives to accomplish.
For most of current retirees, Social Security is a major source of income:
However, with the ongoing shift from the defined-benefit to defined-contribution plans, careful (and individualized) planning of retirement asset allocation in employer-sponsored plans and IRAs as well as other personal investments is evermore important.
January 14, 2014
Entering an Exclusive Dimension
Traditionally, real-estate investment trusts (REITs) provided a good diversification to other stocks in a portfolio. However, in the last several years, REIT returns have become highly correlated with returns of other equities. One theory, outlined in a Morningstar article, is that over the years REITs evolved from a small, illiquid and neglected to a mainstream and easility accessible asset class.
As an article in The Wall Street Journal indicates
From 1980 through 2006, stock performance of REITs moved in tandem with the broader market only 47% of the time, according to an analysis for The Wall Street Journal by Citi Private Bank in New York… Since then, as the bank’s research shows, REIT correlations have jumped to nearly 80%, erasing more than a quarter of a century in decoupling.
To illustrate that, Alpholio™ compiled the following chart of correlation between returns of the SPDR® S&P 500® ETF (SPY) and iShares U.S. Real Estate ETF (IYR):
The chart shows rolling correlations in trailing three- and four-year periods using total monthly returns of both ETFs since mid-2000. (As expected, thanks to a larger number of data points the latter curve is a bit smoother but lags the former one.) Either curve is characterized by four distinct phases:
- Through 2006, the correlation was indeed in the mid-40%
- From 2007 through 2008, the correlation gradually increased to about 70% and abruptly jumped to over 80% at the onset of the financial crisis
- From 2009 through mid-2013, the correlation stayed at about 85%
- Afterwards, the correlation decreased started to decrease.
The last two phases were caused, at least in part, by the Federal Reserve’s interest rate policy: a strong coupling of rising returns stimulated by low rates, followed by an indication of decoupling when rates rose. A better economic outlook is also a factor:
Improving conditions in the broader economy usually lead to lower real-estate correlations… In fact, correlations between the S&P 500 and REITs have dropped by about 10% since late last year.
Let’s take a look at the last phase in more detail, this time using trailing 18- and 24-month returns:
Here, thanks to shorter time windows the degree of decoupling in the last phase is more evident: the correlation reverted to about 50%. This would suggest that REITs might once again help with portfolio diversification. However, as the next chart shows, REIT returns are currently negatively correlated with the interest rate on a 10-year Treasury note:
With the prospect of rising interest rates this year, REIT returns are likely to continue to be depressed. At the same time, many analysts forecast 5-10% returns of the overall equity market (for example, S&P just increased its 12-month target for the S&P 500® index from 1895 to 1940, which implies an approx. 7% total return). Therefore, until interest rates stabilize, it may be too early to declare a structural decrease in correlation of REIT returns to those of other stocks. A permanent return to pre-2007 correlation levels would certainly help with portfolio construction.
January 7, 2014
Following Leaders and Laggards
A cover story in Barron’s provides lots of interesting details about the history and operations of Dimensional Fund Advisors (DFA). Founded in 1981, DFA has recently reached $332 billion in assets under management (AUM).
About 78% of these AUM are in stocks, and about 85% in low-cost mutual funds with an average expense ratio of 0.39%. The funds have a small-cap and value tilt, based on the Fama-French three-factor model. Lately, the firm started to augment its funds with a profitability factor.
The article states that
More than 75% of its funds have beaten their category benchmarks over the past 15 years, and 80% over five years, according to Morningstar — remarkable for what some investors wrongly dismiss as index investing.
To substantiate this, the article compares two similar funds from DFA and Vanguard:
For example, take the Vanguard Small Cap Value index fund (VISVX), which is based on the S&P 600 Small Cap Value index and is the counterpart to Dimensional’s DFA US Small Cap Value (DFSVX). The DFA fund has a much smaller tilt — its average market value is $1.1 billion, versus Vanguard’s $2.7 billion — and on all measures is much more value-oriented. So the Dimensional fund better captures the market-beating advantage of small and value stocks. In fact, a lot better: The DFA fund returned 42% in 2013, beating 88% of its peers in Morningstar’s small-cap value category, versus the Vanguard fund’s 36% return, which beat just 53%. Over 15 years, which includes periods that were less favorable to small and/or value stocks, DFA’s fund returned an average of 12% a year, beating 80% of peers. The Vanguard fund returned 10% on average, beating just 37% of peers. The Dimensional fund costs twice as much as Vanguard’s — 0.52% versus 0.24% — but the significant outperformance more than makes up for that difference.
That only tells a part of the story. According to Morningstar data, DFSVX had a lower Sharpe Ratio than VISVX in the 3-year (0.96 vs. 1.01) and 10-year (0.47 vs. 0.48) periods through 2013. This is also reflected in the generally higher volatility and upside and downside capture ratios for the DFA fund. As a result, the DFA fund produced lower returns than the Vanguard fund did in the down years of 2007, 2008 and 2011.
The article says that a deliberately paced trading as well as market making in the 14,000 stocks DFA owns both add to its outperformance. However, DFA faces an ongoing criticism: since its funds are sold exclusively through 1,900 rigorously screened and trained financial advisors, they are not easily accessible to individual investors, especially those with a small amount of investable assets, not willing to pay advisory fees or already having an unaffiliated advisor. This is what creates an “exclusive dimension” of DFA, which Alpholio™ can help investors enter. Following up on one of the previous posts, let’s analyze DFSVX in more detail.
The following chart shows the relative performance of the fund vs. its reference portfolio of ETFs:
An investor who committed to the fund in early 2005 would have gained only a modest amount of cumulative RealAlpha™ by late 2013. This was mostly caused by the fund’s underperformance in the three years mentioned above. In addition, at about 22.7% the annualized volatility of the fund was 2% higher than that of its reference portfolio in the overall analysis period.
The next chart illustrates ETF weights in the reference portfolio in the same period:
The fund could effectively be emulated by a collection of just four related ETFs: iShares Russell 2000 Value (IWN; average weight of 34.9%), iShares S&P Small-Cap 600 Value (IJS; 30.1%), iShares Morningstar Small-Cap (JKJ; 18.5%), and iShares Morningstar Small-Cap Value (JKL; 13.7%). (The remaining two ETFs accounted for only 2.8% of the reference portfolio on average.)
The weighted expense ratio of these four ETFs is currently only 0.33% compared to the fund’s 0.52%. In addition, while an investor trading these ETFs might incur some commission, spread and premium/discount costs, he/she would not have to pay a recurring advisory fee of about 1% (or be forced to switch advisors) to gain benefits similar to those offered by DFA funds. Over time, dedicated factor ETFs will likely make such fund substitution even easier. Thus, entering an exclusive dimension of factor investing is no longer as hard as it has been.
To get a unique perspective on the DFA and other funds, please register on our website.
January 4, 2014
An article in The Wall Street Journal provides evidence that following both the recent leaders and laggards results in inferior investment performance:
According to these figures, after 20 years investors following the portfolio of the previous year’s top-performing newsletter would end up with only 2.4% of their original investment. Those following the portfolio of the previous year’s worst-performing newsletter would finish with virtually nothing. In contrast, investors in a broad market index would realize a return of over 460% in the same period.
These findings are similar to those of the recurring SPIVA reports, discussed in a previous Alpholio™ post. Mutual funds in the top half of quartile of the population are more likely to revert to the mean than could be expected by chance. On the other hand, funds in the bottom quartile are more likely to continue to underperform, and eventually end up being liquidated or merged with other funds.
The article indicates that merely focusing on lower-risk investment strategies is insufficient. Instead, the investor should extend the observation period:
You would do much better to focus on performance over far longer periods than the past 12 months. That is because, when picking an adviser based on his track record, you implicitly are betting that the future will be just like the period over which that record was produced.
While there is no magical track-record length on which you should always focus, 15 years is a good rule of thumb. The past 15 years—from the beginning of 1999 through the end of last year—encompass two powerful bull markets as well as two punishing bear markets.
As an example of a suitable mutual fund, the article offers the Turner Emerging Growth Fund (TMCGX, investor shares) with the highest annualized return among diversified U.S. equity funds in that long time span. Let’s take a closer look at that fund’s performance.
First, data from Morningstar show that the fund’s 15-year annualized return of about 17.6% was significantly higher than the 10-year return of about 10.6%. This indicates that the fund may have outperformed early on since its inception in late February 1998. Indeed, in the first couple of years the fund generated a return of over 355%, no doubt riding the wave of appreciation of small-cap stocks caused by the Internet boom. While this performance could in theory be repeated, it seems unlikely.
In the next three years through February 2003, the fund generated a cumulative loss of only 21% compared to about 52% of an average small-growth peer. This was another contribution to the high annualized 15-year return. However, the fund failed to beat the iShares Russell 2000 Growth ETF (IWO), a practical implementation of its prospectus benchmark, in four out of six most recent years. This is further illustrated by the fund’s performance relative to its reference portfolio of ETFs since early 2005:
The chart shows that all of the cumulative RealAlpha™ the fund generated through mid-2008 was subsequently lost. The fund strongly rebounded only in the second half of 2013. Moreover, the reference portfolio had a lower volatility than that of the fund.
The next chart depicts ETF membership and weight changes in the reference portfolio over the same analysis period:
The fund could have effectively been emulated by a collection of four ETFs: iShares Russell 2000 Growth (IWO; average weight 63.8%), iShares Morningstar Mid-Cap Growth (JKH; 25.4%), Vanguard Energy (VDE; 7.7%), and iShares 20+ Year Treasury Bond (TLT; 3.1%). Over time, the equivalent position in IWO became even more dominant, which implies that the fund’s characteristics were getting closer to those of its benchmark.
Only time will tell if the fund is able to outperform its reference portfolio on a consistent basis. There is no guarantee that the spectacular performance of early years will be repeated or even that the fund will be in existence in the next 15 years. In addition, as the above charts demonstrated, investor’s returns depend heavily on the timing on the initial investment. Therefore, while following the laggards is certainly not a fruitful endeavor, blindly following the leaders, even those with a long-term record, is not advisable either.