Pulling Flower Roots

American Funds: A Deeper Look at the Performance

Pulling Flower Roots

This is an article about statistical significance. If those two words sound like finger nails on a chalkboard to you, you may want to skip this article or find a friend who can assist you in understanding it.

In IFA's opinion, this type of analysis is very important for investors because it is a common academic method to quantify the existence of manager stock picking skill. Stated another way, it addresses the question of whether a manager's past performance was the result of skill or luck. This is very important because investors should expect skill to persist in the future and luck to fade away. Other than academic papers and information from IFA or Dimensional Fund Advisors, we have yet to see any financial services company, financial journalist, or fund rating service such as Morningstar or Lipper, discuss the standard deviation of the alpha, the sample size needed to distinguish luck from skill or the t-Statistic of the Alpha. In statistical analysis, a number without a t-statistic of 2 or more is not a reliable number. In our review of active management investment returns, a t-statistic of 2, which indicates a 95% confidence level, is rare. Please review the formula and input form at this link to better understand this type of analysis. This article titled What's the Significance?, is for the advanced students of financial analysis. Finally, this article titled The Paradox of Skill provides further background information on the question of stock picking skill.

The Mutual Fund Alpha Charts shown below compare 57 mutual funds from American Funds, all A Shares, to their Morningstar analyst-designated benchmark. Please note that the Morningstar Benchmark may differ from the benchmark that the managers of the mutual fund chose.  Morningstar attempts to select benchmarks that, in their opinion, more closely approximates the asset allocation of the fund's holdings. In some cases (such as the Growth Fund of America) the mutual fund data goes back further than the benchmark data, so the alphas for the years prior to the existence of the benchmark are not included in the Alpha Charts. Also note that funds with less than three full calendar years of data are excluded from this article. Average Alpha is defined as the average of the annual return differences between the fund return and the benchmark return. Alpha is commonly thought of as the value added by active managers.

For the funds with positive Average Alpha, the "Minimum Track Record to Indicate Skill" tells us the number of years required of similar average alphas and similar volatilties of alphas (standard deviations) to conclude the manager(s) had skill. When the number of years of fund data, shown in the gold bar subtitle, exceeds the number of Years Needed, we can be about 95% confident the alpha is due to skill rather than luck.

Of these 57 American funds, 58% (or 33 funds) had positive Average Alpha over the period, and only 12.3% (or 7 funds) had a consistently high enough alpha, and a low enough standard deviation of alpha, and a large enough sample size of data that we could be about 95% confident the alpha was due to skill rather than luck. Which still leaves room for a 5% error in certainty, or a 1 in 20 chance of concluding a manager had skill, when in fact it was just luck.

For 26 of the 33 funds with positive alpha, the number of years needed to confirm skill exceeded the number of years of historical returns shown in the subtitle, sometimes by a very wide margin. Of the 7 funds that have a postive alpha that is statistically significant, 4 have 5 years of performance history of less. Their out or underperformance may be to a mismatch in asset allocation versus a positive indication of skill. In other words, we have reason to believe that this outperformance is due to luck versus an indication of actual skill. Further, 2 of the funds are either Target-Date funds or funds used in college 529 plans. These funds are really just fund-of-funds of different American Fund strategies. This is why we believe that their outperformace happens to do with a mismatch between asset allocation of strategy and benchmark.

The three funds that we believe have reason to possibly justify their outperformance are ANWPX, CWGIX, and SMCWX. While having three funds (all funds have Front Loads of 5.75%) with alpha apparently attributable to skill may be considered praiseworthy, it is diluted by the fact that out of 57 different funds, we would expect to see at least three that have statistically significant positive alpha, with about a 95% level of certainty by random chance alone.

As we mentioned above, Morningstar assigned benchmarks are not robust. Because Morningstar cannot completely customize their benchmark to accomodate the thousands of mutual funds that exist, they try to do their best based on key factors such as asset class exposure, market capitalization, and price-to-book ratios. A more robust way of comparing performance is by running multiple regressions on known factors of expected returns (market, size, and relative-price). By controlling for the known drivers behind stock returns, we can create our own customized benchmark to see whether or not a true "alpha" emerges. 

We took all US equity strategies with at least 10 years of data (7 funds) and ran regressions against the market, size, and relative-price factors. Once we controlled for these known dimensions of expected return, not a single strategy from American Funds delivered a postive alpha that was statistically significant at the 95% confidence level (t-stat>2). In fact, most of the funds had an alpha near zero or slightly below, which is what we would expect to see. This analysis reaffirms our suggestion above that most the alpha seems to be a difference in exposure to known dimensions of expected return and asset allocation versus a true indication of skill. In other words, if a particular fund is smaller in size or more value-oriented versus their Morningstar assigned benchmark, then we would expect them to outperform their benchmark over any given time period. 

This is similar to the findings of Barras, Scalliet, and Wermers in "False Discoveries in Mutual Fund Performance: Measuring Luck in Estimating Alphas". When a mutual fund manager has a statistically significant different performance than the fund's benchmark (i.e., positive or negative alpha with a t-stat of 2 or more), there are two possible explanations: skill or luck. The authors define a "false discovery" as a mutual fund that exhibits significant alpha by luck alone. Using a sample of 2,076 actively managed US equity funds between 1975 and 2006, the authors found that total observed alpha is consistent with the following breakdown of the population: 75.4% of the funds have a true alpha of zero after costs and 24.0% have a true alpha that is negative, which leaves only 0.6% with a true positive alpha, a number that the authors consider to be "statistically indistinguishable from zero". IFA's Step 3: Stock Pickers admonishes investors not to pick stocks for themselves or expect an active manager of a mutual fund to add value by picking stocks on their behalf. The chart below summarizes this paper.

Putting aside the question of luck vs. skill, when an actively managed fund exhibits positive alpha, a current or prospective investor should be concerned with the source of that alpha—whether it came from superior security selection, market-timing, or style-picking. For one of the two funds with a t-statistic greater than two, the chart below (generated with Morningstar data) suggests that both market-timing and style drift occurred over the life of the fund. At times, the fund appears to have been up to 20% cash or short-term bonds, and the tilt towards international equities has steadily increased over time to current allocation of just under 50% of the portfolio. Furthermore, there has been a substantial amount of movement within U.S. equities. An investor who is concerned with maintaining the integrity of her asset allocation should think twice about investing in a fund that has a history of taking large cash positions as well as drifting in the allocation among different classes of equities. 

The table below displays the different costs associated with investing in American Funds. Outside of their overall sub-par performance, many investors end up paying quite a premium for that underperformance. It should go without saying that expenses play a major role in determining long term wealth accumulation. Click the fund name to go directly to the alpha chart for that fund.

Name Ticker Turnover Ratio % Prospectus Net Expense Ratio 12b-1 Fee Max Front Load Global Category
American Funds 2010 Trgt Date Retire A AAATX 19.00 0.69 0.24 5.75 Target Date 2000-2020
American Funds 2015 Trgt Date Retire A AABTX 15.00 0.71 0.25 5.75 Target Date 2000-2020
American Funds 2020 Trgt Date Retire A AACTX 8.00 0.71 0.25 5.75 Target Date 2000-2020
American Funds 2025 Trgt Date Retire A AADTX 9.00 0.73 0.24 5.75 Target Date 2021-2045
American Funds 2030 Trgt Date Retire A AAETX 6.00 0.73 0.23 5.75 Target Date 2021-2045
American Funds 2035 Trgt Date Retire A AAFTX 5.00 0.74 0.22 5.75 Target Date 2021-2045
American Funds 2040 Trgt Date Retire A AAGTX 5.00 0.74 0.22 5.75 Target Date 2021-2045
American Funds 2045 Trgt Date Retire A AAHTX 5.00 0.75 0.22 5.75 Target Date 2021-2045
American Funds 2050 Trgt Date Retire A AALTX 6.00 0.76 0.22 5.75 Target Date 2046
American Funds 2055 Trgt Date Retire A AAMTX 6.00 0.78 0.20 5.75 Target Date 2046
American Funds AMCAP A AMCPX 33.00 0.68 0.23 5.75 US Equity Large Cap Growth
American Funds American Balanced A ABALX 68.00 0.59 0.24 5.75 Moderate Allocation
American Funds American High-Inc A AHITX 49.00 0.67 0.24 3.75 High Yield Fixed Income
American Funds American Mutual A AMRMX 27.00 0.58 0.24 5.75 US Equity Large Cap Value
American Funds Balanced Portfolio 529A CBAAX 13.00 0.80 0.22 5.75 Moderate Allocation
American Funds Bond Fund of Amer A ABNDX 348.00 0.62 0.25 3.75 US Fixed Income
American Funds Capital Income Bldr A CAIBX 63.00 0.59 0.24 5.75 Allocation
American Funds Capital World Bond A CWBFX 185.00 0.93 0.24 3.75 Global Fixed Income
American Funds Capital World Gr&Inc A CWGIX 35.00 0.77 0.24 5.75 Global Equity
American Funds College 2018 529A CNEAX 13.00 0.74 0.22 4.25 Cautious Allocation
American Funds College 2021 529A CTOAX 25.00 0.71 0.20 4.25 Cautious Allocation
American Funds College 2024 529A CFTAX 20.00 0.76 0.20 4.25 Moderate Allocation
American Funds College 2027 529A CSTAX 10.00 0.78 0.19 4.25 Moderate Allocation
American Funds College 2030 529A CTHAX -- 0.79 0.16 4.25 Aggressive Allocation
American Funds College Enrollment 529A CENAX 15.00 0.78 0.23 2.50 US Fixed Income
American Funds Europacific Growth A AEPGX 28.00 0.83 0.24 5.75 Global Equity Large Cap
American Funds Fundamental Invs A ANCFX 29.00 0.61 0.24 5.75 US Equity Large Cap Blend
American Funds Global Balanced 529A CBFAX 85.00 0.93 0.20 5.75 Allocation
American Funds Global Growth Port 529A CPGAX 2.00 0.90 0.19 5.75 Global Equity
American Funds Growth and Inc Port 529A CGNAX 7.00 0.78 0.20 5.75 Aggressive Allocation
American Funds Growth Fund of Amer A AGTHX 29.00 0.65 0.24 5.75 US Equity Large Cap Growth
American Funds Growth Portfolio 529A CGPAX 24.00 0.82 0.18 5.75 US Equity Large Cap Growth
American Funds Income Fund of Amer A AMECX 45.00 0.55 0.24 5.75 Moderate Allocation
American Funds Income Portfolio A INPAX 7.00 0.64 0.23 5.75 Cautious Allocation
American Funds Inflation Linked Bd A BFIAX 801.00 0.80 0.30 2.50 Inflation Linked
American Funds Interm Bd Fd of Amer A AIBAX 192.00 0.61 0.25 2.50 US Fixed Income
American Funds Intl Gr and Inc 529A CGIAX 25.00 0.97 0.20 5.75 Global Equity Large Cap
American Funds Invmt Co of Amer A AIVSX 29.00 0.59 0.23 5.75 US Equity Large Cap Blend
American Funds Ltd-Term Tx-Ex Bd A LTEBX 19.00 0.57 0.28 2.50 US Municipal Fixed Income
American Funds Mortgage 529A CMFAX 1,205.00 0.79 0.22 3.75 US Fixed Income
American Funds New Economy A ANEFX 34.00 0.78 0.23 5.75 US Equity Large Cap Growth
American Funds New Perspective A ANWPX 27.00 0.75 0.23 5.75 Global Equity
American Funds New World A NEWFX 41.00 1.04 0.23 5.75 Emerging Markets Equity
American Funds Preservation Port A PPVAX 2.00 0.71 0.27 2.50 US Fixed Income
American Funds Shrt-Term Tx-Exmpt Bd A ASTEX 38.00 0.58 0.15 2.50 US Municipal Fixed Income
American Funds SMALLCAP World A SMCWX 33.00 1.07 0.24 5.75 Global Equity
American Funds ST Bd Fd of Amer A ASBAX 452.00 0.60 0.18 2.50 US Fixed Income
American Funds Tax-Exempt Bond A AFTEX 14.00 0.54 0.25 3.75 US Municipal Fixed Income
American Funds Tax-Exempt CA A TAFTX 17.00 0.62 0.25 3.75 US Municipal Fixed Income
American Funds Tax-Exempt Fund of NY A NYAAX 42.00 0.67 0.20 3.75 US Municipal Fixed Income
American Funds Tax-Exempt MD A TMMDX 27.00 0.69 0.25 3.75 US Municipal Fixed Income
American Funds Tax-Exempt Presv Port A TEPAX 8.00 0.76 0.30 2.50 US Municipal Fixed Income
American Funds Tax-Exempt VA A TFVAX 14.00 0.66 0.25 3.75 US Municipal Fixed Income
American Funds Tx-Advtg Inc A TAIAX 1.00 0.79 0.30 3.75 Cautious Allocation
American Funds US Government Sec A AMUSX 771.00 0.65 0.25 3.75 US Fixed Income
American Funds Washington Mutual A AWSHX 24.00 0.58 0.24 5.75 US Equity Large Cap Value
American High-Income Municipal Bond A AMHIX 23.00 0.68 0.28 3.75 US Municipal Fixed Income

 

 

Below are the Alpha Charts for the American Funds (A shares) compared to their Morningstar analyst-designated benchmark. The mutual fund trading symbol is shown just above each chart.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Here is a calculator to determine the t-stat. Don't trust an alpha or average return without one.

The Figure below shows the formula to calculate the number of years needed for a t-stat of 2. We first determine the excess return over a benchmark (the alpha) then determine the regularity of the excess returns by calculating the standard deviation of those returns. Based on these two numbers, we can then calculate how many years we need (sample size) to support the manager's claim of skill.

 

We have taken a deeper look at the performance of several other mutual fund companies and have come to one universal conclusion: they have failed to deliver on the value proposition they profess, which is to reliably outperform a risk comparable benchmark. You can review by clicking any of the links below: