Risks

Systematic and Unsystematic Risk

One way academic researchers measure investment risk is by looking at stock price volatility. Two risks associated with stocks are systematic risk and unsystematic risk. Systematic risk, also known as market risk, cannot be reduced by diversification within the stock market. Sources of systematic risk include: inflation, interest rates, war, recessions, currency changes, market crashes and downturns plus recessions. Because the stock market is unpredictable, systematic risk always exists.

Systematic risk is largely due to changes in macroeconomics. Reducing systematic risk can lower portfolio risk; using asset classes whose returns are not highly correlated (e.g., quality bonds, stocks, fixed-rate annuities, etc.). It is possible to have higher risk-adjusted returns without having to accept additional risk, a process called portfolio optimization.

The website InvestingAnswers.com describes systematic risk as being “comprised of the unknown unknowns occurring as the result of everyday life. It can only be avoided by staying away from all risky investments…because of market efficiency, you will not be compensated for additional risks arising from failure to diversify your portfolio.” Reducing a portfolio’s systematic risk is accomplished by reducing stock exposure or by including other asset categories, such as commodities, quality bonds, CDs, or fixed-rate annuities.

Unsystematic risk, also known as company-specific risk, specific risk, diversifiable risk, idiosyncratic risk, and residual risk, represents risks of a specific corporation, such as management, sales, market share, product recalls, labor disputes, and name recognition. This type of risk is peculiar to an asset, a risk that can be eliminated by diversification.

The portfolio’s risk (systematic + unsystematic) is measured by standard deviation, variation of the mean (average, not annualized) return of a portfolio’s returns. Table xx shows how quickly unsystematic risk is reduced when a modest number of stocks are added to a single-stock portfolio. The table comes from an October 1977 article by E.J. Elton and M. J. Gruber published in the Journal of Business. Most unsystematic risk is eliminated if the portfolio is comprised of 20+ stocks from several different sectors.

Phrased another way, 61% of stock risk can be eliminated by owning 200+ stocks (or a single, broad-based U.S. stock index fund); 56% risk reduction with just 20 stocks from several sectors. The total risk for a well-diversified stock portfolio is basically equivalent to systematic risk. While an investor expects to be rewarded for bearing risk, one is not rewarded for taking on unnecessary risk, such as unsystematic risk.

BusinessDictionary.com notes systematic risk “cannot be circumvented or eliminated by portfolio diversification but may be reduced by hedging. In stock markets systemic risk (market risk) is measured by beta.” Owning different securities or owning stocks in different sectors can reduce systematic risk.

Table 1

Stock Portfolio: Standard Deviations of Annual Returns

[how risk is reduced when stocks from different industries are added]

A classic 1968 study by Evans and Archer, Diversification and the Reduction of Dispersion, concluded an investor owning 15 randomly chosen stocks would have a portfolio no more risky than the overall stock market. This research confirmed earlier advice from Benjamin Graham in his 1949 book, The Intelligent Investor. Graham recommended owning 10-30 stocks for proper diversification.

Risk-Return Characteristics of a 100 Stock Portfolio

A 2004 AAII Journal article by Daniel Burnside, How Many Stocks Do You Need to be Diversified, points out even a 100-stock portfolio will have a high level of return deviation: “a single security selected at random would have an average tracking error in its monthly return of 5.5% from a cap-weighted index…even a portfolio of 100 stocks will deviate from its target index by an average of 0.60% per month for the value-weighted approach...corresponds to an annualized deviation of ~ 2.1%.”

Table 2 shows the period of time analyzed can greatly alter monthly tracking error (standard deviation) of a stock portfolio. For example, a 100-stock portfolio had an average monthly tracking error of 0.4% from 1960-1966 vs. 0.9% from 1995-2001. Table 2 shows diversifiable risk increased over the 42-year period (1960-2001).

Table 2

Monthly Tracking Error for Cap-Weighted Stock Indexa

All data in the table comes from the Burnside July 2004 article.

According to Burnside (2004): “…investors may view volatility as the typical amount by which a portfolio’s return will deviate from long-term averages. A single-stock investor will experience annual returns averaging a whopping 35% above or below the market—with some years closer to the market and some years further from the market. As a rule of thumb, diversifiable risk will be reduced by the following:

• Holding 25 stocks reduces diversifiable risk by ~ 80%,
• Holding 100 stocks reduces diversifiable risk by ~ 90%, and
• Holding 400 stocks reduces diversifiable risk by ~ 95%.

All of these reductions are compared to the risk of holding one stock. A single stock’s tracking error of ~ 40% would be reduced to ~ 8% if you hold 25 stocks, 4% if you hold 100 stocks and 2% if you hold 400 stocks.”

Burnside does not recommend portfolio diversification using a stock index if each stock has the same weighting, referred to as an equal-weight index: “an equal-weighted portfolio of every U.S. stock will behave primarily like a small-cap fund, since ~ 3% of the holdings would be large cap, ~ 12% would be mid cap and ~ 85% would be small cap (and small cap would be dominated by micro caps).” Moreover, if an equally weighted stock portfolio was used, tracking error would be ~ 50% > the tracking error shown in Table xx. For example, from 1960-1969, monthly tracking error for a 100-stock portfolio was 0.4% using a cap-weighted index but 0.7% for a 100-stock portfolio based on an equally-weighted stock index (not shown in a table); 0.9% for the period 1995-2001 (cap weighted) vs. 1.5% (equal weighted).

Beta

Beta measures market risk, also known as systematic risk. A 1992 Journal of Finance article by Fama and French, The Cross-Section of Expected Stock Returns, shows past and current beta are not a good predictor of future beta—at least when it comes to individual stocks. Fama and French suggest stock betas tend to mean revert; a stock with a past beta of 1.5 or 0.8 should tend to move toward 1.0 in the future.

The stock market, as measured by the S&P 500, always has a 1.0 beta, whether the market is flat, going through a bull market or crashing. For example, if the ABC Growth Fund has a 1.3 beta, its market-related volatility suggests the fund will move 30% > the S&P 500. For a non-diversified stock portfolio, unique characteristics of a company, referred to as unsystematic risk, can result in the company’s stock price to move much more or less than market-related (systematic risk) volatility. Table xx shows the beta of select industries based on January 2015 data (NYU, 2015).

Table 4

Beta of Select Industries 2015

Note. All information for this table is from the NYU Stern School of Business (2015)

aNumber of corporations within the industry is shown in parentheses.

Unsystematic Risk Does Not Equal Higher Returns

Systematic risk principle states expected return depends solely on asset’s systematic risk. Only the systematic portion is important when determining expected return (and risk premium). For example (Table 3), suppose you owned two assets:

Table 3

Systematic Risk and Beta

While Asset #2 has much more total risk than Asset #1 (44% vs. 23%), Asset #1 is expected to have a higher return since its beta is larger (1.4 vs.0.8). According to A Random Walk Down Wall Street: “If investors did get an extra return (a risk premium) for bearing unsystematic risk, it would turn out diversified portfolios made up of stocks with large amounts of unsystematic risk would give larger returns than equally risk portfolios with less unsystematic risk. Investors would snap at the chance to have these higher returns, bidding up the prices of stocks with large unsystematic risk and selling stocks with equivalent betas but lower unsystematic risk. This process would continue until the prospective returns of stocks with the same betas were equalized and no risk premium could be obtained for bearing unsystematic risk. Any other result would be inconsistent with the existence of an efficient market.”

Serial Correlations

For investors, serial correlation, also referred to as autocorrelation, measures predictability of returns from one period to the next. For example, if ABC returned 3% annualized over the past three years and then averaged close to 3% for the subsequent three years it would have a high serial correlation.

U.S. and foreign securities have close to a zero correlation—past returns are a poor indicator as to future performance, whether the period is a month, quarter, year, or decade. Serial correlation figures are typically based on multi-year or multi-decade returns. As noted by Clements (2000), “Past performance is a rotten guide to future results. But that hasn’t deterred investors.” Nevertheless, serial correlation for short-term debt instruments maturing within 1-2 years can be moderate-to-high.

One appeal of value investing is mean reversion, also known as the reversal effect. A value investor buys an asset at a discount to its expected value with the expectation of future appreciation. Conversely, the momentum effect is based on a belief good-per-forming investment will continue its appreciation short-term.

Asset allocation and risk models assume at least short-term stability return correlations, but “actual covariance and correlation relationships fluctuate dramatically. Correlations tend to increase in volatile periods, which reduces the power of diversification when it might most be desired…an increase in market volatility increases the relative importance of systematic risk compared with unsystematic component of returns…a large portion of the variation in correlation structures can be attributed to variation in market volatility…market volatility contains enough predictability to construct useful forecasts of return correlation…correlation and covariance structures vary dramatically over time—so much so, in fact, and with such high frequency that one must wonder whether asset allocation and risk management models can be of any use whatsoever.” According to Jacquier and Marcus (2001), more than 2/3 of U.S. sector return correlation is due to market volatility.

R2

Barron’s defines R2 as a mutual fund term indicating “on a scale of 0 to 100, the percentage of a fund’s performance…explained by movements of its benchmark index.” For example, if the benchmark was the S&P 500, the typical large cap blend fund would likely have an R2 of > 90%. R2 can be used to gauge relevancy of a fund’s beta; the higher the R2, the greater the importance of beta.

A correlation measures the relationship between two securities or benchmarks, usually a return correlation, often abbreviated as correlation (a scale ranging from -1.0 to +1.0). R2 is similar except it is limited to the return correlation of a benchmark or index; the two most commonly used benchmarks for U.S. investors are the S&P 500 and the Barclays Aggregate Bond Index. The website statisticshowto.com points out R2 is the “square of the correlation coefficient (hence the term R2). For example, when a person gets pregnant has a direct relation to when they give birth.” Any statistical inference from R2, sometimes referred to as Pearson’s correlation coefficient, is sensitive to the sample distribution. The closer return distribution resembles a bell-shaped curve, the greater the R2 predictibility.

An excellent stock portfolio can have a very low R2 since R2 is simply a measure of portfolio return correlation to the benchmark. In the case of U.S. stocks, the most commonly used benchmark is the S&P 500. For example, if the XYZ Large Cap Growth Fund had an R2 of 60, 60% of its movements are expected to be explained by S&P 500 movements. According to Morningstar, the general range for R2 is: 70-100% = good return correlation between the portfolio and benchmark; 40-70% = average correlation; and 1-40% = low correlation. According to Mathbits.com, “a correlation > 0.8 is generally described as strong, whereas a correlation of < 0.5 is generally described as weak.

S&P 500 Sectors: Beta, Correlation, R2 & Weightings

Most of the information from Table 5 comes from State Street’s SPDR ETF website. SPDR ETF symbols are shown in parentheses. R2 figures are from Morningstar and represent fund categories; not shown are precious metals funds (R2 = 12) and natural resource funds (R2 = 77).

Table 5

S&P 500 Sector Stats, November 2015

Note: All data as of November 2015

a3-year return correlation to the S&P 500 (total weighting is > 100% due to SPDR ETF holdings)

bWeighting of sector to the S&P 500

Table 6

Additional S&P 500 Sector Stats, November 2015

aP/E ratios are for iShares ETF sector funds as of October 2015

Currency Risk

In general, a currency futures contract locks in the exchange rate between two currencies. A company in one country selling products in another country can eliminate currency risk by purchasing a sufficient number of such futures contracts. Currency gains and losses represent a “difference in exchange value of the foreign currency and the domestic currency between the time the investment was bought and time it was sold” (Barron’s, 2014). Hedging can offset different types of investment risk, depending on what is being hedged (i.e., currencies, interest rates, cost of raw materials using for production, jet fuel for airlines, etc.).

Findings from a study by Arnott (1996) showed currency hedging among global and foreign mutual funds was less than expected; ~ 1/3 of foreign stock funds hedge on a regular basis while 2/3 either hedge infrequently or never. A different study by Penn (1994) noted currency risk is likely to be more of a concern for foreign and global bond portfolios than their stock counterparts. For example, if interest rates in a foreign country fall, stock prices may go up; such gains could easily surpass any currency loss to a U.S. investor owning stocks from the country. In the case of bonds, gains due to a slight rate decrease may not offset currency loss to the same U.S. investor.

Since the great majority of foreign and global funds do little, if any, currency hedging, it is fair to conclude such a strategy is not worthwhile, particularly for medium- and long-term investors. However, there have been times when currency hedging has benefited U.S. investors owning foreign securities. A paper by Rothschild (1998) shows 23% of 1996 foreign fund returns were due to hedging, but only 13% of returns were due to hedging in 1997. Bernstein (1999) concluded the best strategy for moderate and high risk portfolios was to avoid funds using any kind of currency hedging.

Expense Ratios

Bogle (1999b) concluded 92% of return shortfall for active managers was due to expenses. Expense ratio shows the percentage of fund assets annually spent for overhead (i.e., shareholder services, rent, administrative salaries, etc.) and management. The expense ratio does not include trading costs or reflect any bid-ask spread and does not include any sales commissions or purchase or redemption fees. According to Zweig (1997b), management (advisory) fees represent 60%+ of the total expense ratio. Expense ratios range from < 1/10th of 1% (0.1) to > 3%; the typical yearly charge is ~ 1.0%.

The biggest beneficiary of economies of scale is the fund, not its shareholders (investors). Bogle (1998) noted fund assets increased by 6,650% over a 17-year period studied, yet expenses increased by 8,470% and “in periods of normal returns, a 2.5% expense ratio consumes 50% of investor net ‘real’ returns.”

Zweig (1997) discovered 56% of all bond and stock funds with 10-year records had increased their expense ratio. Another study shows a 38% increase in expense ratios from 1986 to 1999. Moreover, one fund had a net profit of $62 million on $95 million of expenses, a 66% profit margin. Bogle (1994) found fund expenses represented 54% of stock fund income, 12% for bonds, and 18% for money market funds.

Since most funds do not outperform their benchmark index, performance incentive fees are common; Zweig (1999a) found just 2% of U.S. stock funds had incentive-based management fees. Some funds decrease management and other fees based on break points. For example, Vanguard waives a $20 annual charge for accounts with a balance of < $10,000; the fee is also waived if the investor signs up for e-delivery of statements and other information.

A handful of Vanguard funds also charge a fee of 0.25% to 1.00% when shares are bought or sold; the fee discourages trading, which is expected to benefit long-term buy-and-hold investors. Vanguard does not have any marketing or distribution costs, also known as 12-b-1 fees. According to Lipper, the industry average expense ratio is 1.0% vs. 0.2% for the typical Vanguard fund (as of 12/31/2014). The Vanguard 500 Index Fund (VFINX) has a 0.17% expense ratio with a minimum $3,000 initial investment and just 0.05% for accounts valued at $10,000+. As of July 2015, Vanguard, a well-known advocate of indexing, was the third largest active equity fund company in the world (Morningstar, 2015).

Unpopular Funds

Fund popularity can be measured by percentage change in net cash flow over a stated period. Barbee (1999b) discovered unpopular funds had higher returns than popular funds from 1987-1998. Specifically, over 3-year periods, unpopular funds typically outperformed 78% of the time. In a separate paper, Ibbotson concluded picking funds that will outperform their benchmark is easier than trying to determine what investment style will perform best.

Duration

A fund’s duration can sometimes be a misleading measurement of interest rate risk if the bond fund has a meaningful weighting in convertibles, foreign stocks and bonds or derivatives. Haslem (2003) believes duration is a more accurate measurement when there are small interest rate changes. Duration tends to better reflect interest rate risk of portfolios of high quality bonds.

Bond Investing

The SEC requires bond funds to invest at least 80% of their assets according to what is implied by the fund name. Since bond returns are usually lower than stock returns, a bond fund’s expenses and fees can greatly impact results. For example, if a 10-year Treasury bond portfolio has an average yield of 2% and expenses totaling 1.2%, return will be just 0.8% plus or minus any gain or loss due to the appreciation or depreciation of bond principal. Purcell (1993) found intermediate-term bonds offered ~ 90% of the total returns of long-term bonds with just ½ the volatility.

Rekenthaler (1995) found 82-93% of actively-managed U.S. government bonds underperformed their benchmark for periods ranging from 1-10 years.

Indexing

Wells Fargo Investment Advisors were the first to use indexed portfolios for some of their institutional pension plans from 1969-1971. The Vanguard 500 Index Fund was the first U.S. index fund offered to individual investors. Beginning in 1976, the fund did not reach $10 billion in assets for almost 20 years.

The S&P 500 represents ~ 75% of U.S. stock market valuation. By the late 1970s, the majority of the academic community viewed U.S. stock market as being reasonably efficient, recommending indexing over active management. Such thoughts likely first began with Malkiel (1973) who believed monkeys throwing darts at the Wall Street Journal’s stock listings would likely have the same results as professional money managers.

John Bogle, Vanguard’s former chairperson, came up with the idea of setting up the first retail U.S. index fund. Because the fund attracted only modest amounts of money during its earlier years, some believe the fund would have closed had it not been a pet project of the boss. According to MarketWatch.com, the Vanguard 500 Index Fund’s admiral shares (VFIAX) represent the largest mutual fund (SPDR S&P 500 is the largest ETF); Vanguard has six of the eight largest funds in the U.S.

There are a number of reasons advisors and clients do not index: [1] they think they can beat the market by using actively-managed funds, [2] there is a pattern to the market and it just needs to be discovered, [3] newsletters and other advisory services proclaiming a superior strategy can be convincing, and [4] using active management means advisor or client can take credit for good returns and blame others, such as a fund manager or newsletter, for negative returns.

Each year, Morningstar selects a Portfolio Manager of the Year. According to Bryant (2000), subsequent returns of passed winners was quite mixed: [1] just over 50% continued to outperform their peers, [2] past winners who attempted to time the market had the most unpredictable returns, and [3] managers who were contrarian with a moderate-sized portfolio had the most reliable results.

Efficient Markets

A cornerstone of indexing advocates is based on securities markets being efficient. Barron’s defines the efficient markets theory: “…market prices reflect the knowledge and expectations of all investors. Those who adhere to this theory consider it futile to seek undervalued stocks or to forecast market movements. Any new development is reflected in a firm’s stock price, making it impossible to beat the market.” This vociferously disputed hypothesis also holds an investor who throws darts at a newspaper’s stock listings has as good a chance to outperform the market as any professional investor. The theory, also known as the random walk theory, was first set forth in 1900 by the French mathematician Louis Bachelier, and received modern treatment in Burton Malkiel’s book, A Random Walk Down Wall Street. Most years, the majority of active fund managers underperform market indexes, adding support to the efficient markets hypothesis.

An article by DiTeresa (1999) contains an interview with George Sauter, a Vanguard fund manager who oversaw its flagship S&P 500 Index Fund as well as an actively-managed Vanguard mid-cap fund: “Indexing’s key advantage is long-term performance. Look at the Morningstar style-box categories and you’ll find that in every one, indices beat the majority of funds over the long haul….investing is a zero-sum game.” Haslem (2003) believes indexed funds should comprise 80-90% of a securities portfolio.

Legendary Legg Mason fund manager Bill Miller has a refreshing perspective on active vs. passive investing by pointing out no one buys an average-performing fund and that there are a number of funds whose returns have beaten the S&P 500 over time. For 10 consecutive years, Miller outperformed the S&P 500. While he believes the stock market is efficient over time, he also believes there are times when it is not efficient. Miller is particularly attracted to mispriced securities. He describes the S&P 500 as “a very successful actively managed portfolio.”

Dziubinski (1998) and DiTeresa (1999)

Studies by Dziubinski and DiTeresa state there is a role for both active and passively managed funds. DiTeresa (1999) favors indexing for large caps; the author appears to have no preference for selected active management or indexing when it comes to other U.S. and developed stock markets. DiTeresa does lean toward active management for regional and emerging markets. Conversely, Dziubinski favors active stock management when the fund has: [1] < 50% annual turnover, [2] 50-60% of assets in two sectors, [3] 30%+ of its assets invested in its 10 largest holdings, and [4] a small expense ratio.

Superior Active Fund Management

Arnott (1993) and Odelbo (1995)

Arnott (1993) reviewed characteristics of equity funds with superior returns, finding 17 actively-managed large cap funds outperforming their benchmark in 37 out of 49 rolling 5-year periods ending 1993. A paper by Odelbo (1995) found great stock fund managers did not exclusively follow one investment style while looking for undervalued stocks. The author also found there was no statistical evidence of their superior performance.

Chevalier and Ellison (1999)

Chevalier and Ellison (1999) considered the background of active stock managers and found: [1] those with an MBA added 63 basis points a year to returns but also more risk than their peers, [2] increased portfolio tenure turned in slightly better results, [3] older managers did not perform as well as those younger (maybe because older managers had more job security and possibly less formal education), and [4] those from high-SAT colleges did better.

Bryant (2000)

Bryant (2000) in a study based solely on 23 Morningstar Managers of the Year, discovered what he believed were the traits of fund managers who turned in superior performance, shown in Table 7.

Table 7

Traits of Superior Mutual Fund Active Managers

Table 8

Traits of Superior Mutual Funds

Warren Buffet said, “Diversification is a protection against ignorance…You concentrate to create wealth; you diversify to preserve it…Inactivity (buy and hold) strikes us as intelligent behavior.”

Performance Consistency

Bernstein (1999c) reviewed return consistency of the 30 best-performing mutual funds for five different 5-year periods compared to their returns for the subsequent five years ending 1998. In each of the following 5-year period, the S&P 500 had higher returns than all 30 of the previous best fund performers.

Largest Mutual Funds

Table 9 lists the largest mutual funds in the U.S. as of December 2015, according to MarketWatch.com.

Table 9

20 Largest Mutual Funds as of December 2015

Appendix A

The following is an edited copy of an October 2015 Vanguard Research paper, Keys to improving the odds of active management success.

Challenge of Outperforming

Over the past 20 years, 27% of actively managed U.S. equity mutual funds outpaced their prospectus benchmarks (which have no expenses or costs, unlike any fund). Research has shown underperformance of actively managed funds is relatively consistent across countries, market segments, and time periods.

The poor results of active managers can be understood as a product of the zero-sum game theory as it applies to financial markets; holdings of all participants aggregate to form that market (Sharpe, 1991). Every dollar of outperformance achieved by one investor in the market is offset by a dollar of underperformance from the others. This suggests an outperformance probability of 50%. However, the concept assumes no transaction-related costs (or taxes). In reality, these costs can be significant, reducing returns over time (Philips et al., 2015). For example, active large-cap equity funds charge an average of 0.8%; comparable index funds charge 0.1% (Philips et al., 2015).

One potential counterargument to this powerful concept is active fund managers do not represent the totality of active investors. Other investors include hedge funds, pensions, separately managed account managers, and holders of individual securities. If active fund managers were able to systematically outperform their benchmarks before costs, this might compensate for or outstrip effects of higher costs. However, Philips et al. (2015) suggests such an outcome is unlikely and provides evidence the average active manager is unable to compensate for higher costs.

Also impeding success is lack of persistence among top-performing managers (Philips et al., 2015; Carhart, 1997; Brown and Goetzmann, 1995). Philips et al. (2015) confirms past performance is unreliable when trying to identify active managers who will outperform. According to significant research, most quantitative measures of fund attributes (such as fund size, active share, past alpha, etc.) or performance are equally undependable (Wallick, Wimmer, & Balsamo, 2015; Financial Research Corporation, 2002; Philips & Kinniry, 2010; Schlanger, Philips, & LaBarge, 2012). Although such studies reveal many challenges of successful active management, investors’ odds can be improved by using low-cost funds.

Low costs: Increasing the Chance of Success

Many investors search for the quantitative silver bullet enabling them to identify talented managers in advance. A fund’s current expense ratio—a simple and readily available figure—has historically proven to be an effective predictor of relative future fund performance. Intuitively, this approach makes senses; an investor’s return is decreased by every dollar spent on investment-related costs. Some argue higher costs are indicative of a more skilled manager. Our research suggests otherwise.

Table 10 and Table 11 shows the percentage of actively managed funds outperforming a cost-free benchmark. If we lower benchmark returns by 20 basis points to compensate for the cost of investing in a low-cost index fund, probability of lowest-cost-quartile funds’ success rises from 36% to 40% [averaging percentages over 10, 15 (not shown), 20, and 25 years].

Table 10

Percentage of Actively-Managed Funds Outperforming Their Benchmarka

aAs of 12/31/2014; data from Morningstar

Table 11

2000-2014: Outperforming Their Benchmark Using Hypothetical Expense Ratiosa

aPercentage of actively-managed mutual funds as of 12/31/2014; data from Morningstar

bExpense ratios shown are hypothetical

Identifying Superior Performing Funds

Academic studies have suggested shortcuts for identifying a skilled active manager. Much of the industry has settled on using a variation of the “4 Ps” cited by Vanguard founder Jack Bogle in 1984—people, philosophy, portfolio, and performance.

Vanguard’s Structure

Vanguard is the only mutually owned fund company in the asset management business. This distinction is critical. It is owned collectively by the funds it operates. These funds are owned by its shareholders. A company issuing public stock or owned by a group of private investors is obligated to provide a return on investors’ capital. This layer of fees can pose a hurdle to providing low-cost funds.

All Vanguard sub-advisors are paid a base fee equaling a percentage of managed assets. The vast majority of these sub-advisors also have contracts structured with an incentive fee rewarding them for outperforming the fund’s benchmark. This is rare in the industry; only 3% of all mutual funds offer performance fees. The SEC mandates if a manager performance fee is used in a fund, it must be structured symmetrically, with rewards for outperformance and penalties for underperformance. The SEC requires such fees apply to a minimum of one year of performance; Vanguard’s fees typically cover periods of 3-5 years. This long-term structure aligns managers’ interests more closely with those of investors. Vanguard is the largest user of sub-advisors in the world: 30 of them manage > $420 billion in active equity mutual fund assets; its average management tenure is > 14 years.

Morningstar Ratings

Table 12 shows median excess returns of funds vs. style benchmarks for 36 months following the Morningstar rating. Based on this table, it appears investing in a 1-star fund is a better strategy than buying into a fund just receiving five stars.

Table 12

Median Excess Fund Return 3 Years After Morningstar Rating, 12/31/2013

The Survivors

Of the 2,085 active equity funds in existence at the start of 2000, 952 (46%) were still operating 15 years later (as of 12/31/2014). The rest had been either merged or liquidated, often because of poor performance; 552 of the 952 (26% of 2,085) outperformed their prospectus benchmark during the period (see Table xx). These findings confirm previous research—achieving outperformance is tough.

Table 13

Successful Funds Underperforming Their Benchmarka

aDistribution of the 552 mutual funds (from an original sample of 2,085 actively managed stock funds)

Table 13 shows distribution of outperforming funds according to number of years of underperformance; 96% (541 of 552 funds) lagged their prospectus benchmarks in at least four calendar years and 59% had 7+ years of underperformance.

Investors may be able to withstand individual periods of poor results scattered over a 15-year time frame. But for many, three consecutive bad years is the breakpoint after which they will divest the fund. This can occur for an explicit reason (for example, an investment policy statement requirement) or because it violates some mental rule of thumb (such as an assumption results indicate an unskilled manager). Only 185—or 9%—of the initial 2,085 funds: (1) survived 15 years, (2) outperformed their benchmark for the cumulative 15 years, and (3) avoided three (or more) consecutive years of underperformance.

Appendix B

Best Practices for Portfolio Rebalancing

Vanguard Research

Nov. 2015 by Yan Zilbering and Colleen M. Jaconetti, and Francis M. Kinniry Jr.

Retrieved from https://personal.vanguard.com/pdf/ISGPORE.pdf

Executive summary

The primary goal of a rebalancing strategy is to minimize risk relative to a target asset allocation. Over time, asset classes produce different returns that can change the portfolio’s asset allocation. Research has found there is no optimal frequency or threshold for rebalancing; risk-adjusted returns do not differ meaningfully from one rebalancing strategy to another.

For most broadly diversified stock and bond fund portfolios, annual or semiannual monitoring, with rebalancing at 5% thresholds, is likely to produce a reasonable balance between risk control and cost minimization for most investors. Annual rebalancing is likely to be preferred when taxes or substantial time/costs are involved.

Table 14

Distribution of calendar-year returns: 1926 through 2014a

aAll data from FactSet

Time Only Rebalancing

When using the time-only strategy, rebalancing is done at a predetermined time interval—daily, monthly, quarterly, annually, and so on. As the strategy’s name implies, the only variable taken into consideration is time, regardless of how much or how little the portfolio’s asset allocation has drifted from its target.

Table 15

Portfolio rebalancing based solely on time

Distribution of calendar-year returns: 1926 through 2014a

aAll data from FactSet; portfolio is 50% global stocks and 50% global bonds

bWhenever a security is sold in a taxable account a capital gain or loss is likely

Threshold Only Rebalancing

With the threshold-only strategy, the portfolio is rebalanced only when its asset allocation has drifted from the target allocation by a predetermined minimum rebalancing threshold such as 5% or 10%, regardless of frequency. Rebalancing could be daily or every five years, depending on portfolio’s performance relative to its target allocation.

Table 16

Portfolio rebalancing based solely on threshold

Distribution of calendar-year returns: 1926 through 2014a

aAll data from FactSet; portfolio is 50% global stocks and 50% global bonds

bWhenever a security is sold in a taxable account a capital gain or loss is likely

Time and Threshold Rebalancing

Time and threshold strategy rebalances on a scheduled basis (quarterly or annually), but only if the portfolio’s asset allocation has drifted from its target asset allocation by a predetermined minimum rebalancing threshold such as 5% or 10%. If, as of the scheduled rebalancing date, portfolio’s deviation from target allocation is less than the predetermined threshold, portfolio will not be rebalanced. Likewise, if portfolio’s asset allocation drifts by the minimum threshold or more at any time interval, the portfolio will not be rebalanced at that time.

Table 17

Portfolio rebalancing based on time and threshold

Distribution of calendar-year returns: 1926 through 2014a

aAll data from FactSet; portfolio is 50% global stocks and 50% global bonds

bWhenever a security is sold in a taxable account a capital gain or loss is likely

Table 18

Summary of Time, Threshold, and Time and Threshold Rebalancing