Reviewed January 2021

PORTFOLIO DESIGN

Abstract:  This article examines data and decisions that are integral to portfolio design along with returns, volatility and risks in different portfolio allocations.  Equities outperform fixed income by about 3.5% annually over very long time frames but are far more volatile in price and can suffer far greater declines for extended periods.  Globally diversified portfolios which tilt towards small and value and high profitability stocks along with large and growth stocks have outperformed the ever popular US large cap growth stock asset class by over 3% annually long term.  For periods of up to 30 years returns in any given asset class can vary greatly from their long term expected returns.

The text and tables below present a simple two fund index model, DFA's balanced models, and the Evanson Asset Management® (EAM) recommended 10x10% equal weighting or 1/N model.  These models should be considered starting points for allocation decisions and not mandates.  Many factors need to be considered when choosing portfolio allocations.  At EAM each investor's portfolio is custom designed by EAM and takes into account multiple factors.  We consider capital gains consequences in taxable accounts, marginal tax bracket, net worth, eligibility for different types of tax-qualified accounts, age, years to retirement if not retired, worst case acceptable portfolio declines, preferences for certain fund companies or brokerages over others, preferences for weightings on value, size, and international equity dimensions, preferences for various rates of entry into equity allocations, preferences for alternative investments like commodities and gold, investments kept outside the accounts EAM manages, and the frequency and amounts of additional money that may be added to investment accounts in the future.  It's a long list and for many investors an allocation decision falls within a wide range and there is no best answer.

In the broadest sense forward risk and return are determined by the ratio of risky to risk-free assets.  Risky assets would include equities, longer maturity and lower quality bonds, commodities, real estate, gold, hedge funds, venture capital and private equity.  Risk free assets are cash and cash equivalents like CD's or T-bills though it's not impossible that  problems can develop in these securities.  For most investors this means the primary determinant of their forward portfolio risk and return will be the percentage allocated to equity as opposed to fixed income.  For investors requiring income fixed income holdings are indicated.  For investors interested in long-term growth, equities should be emphasized and fixed income included, if necessary, to dampen volatility and risk in equities.  Fixed income investing is the term given to bonds and other interest paying investments.  Possible risks and returns for equities and fixed income are reviewed in detail in "Risk and Return" elsewhere on our website. 

A simple passive index portfolio can be constructed from just two indexes.  In the first table below all equity allocations are represented by the S&P 500 index which accounts for over 90% of the value of all traded US stocks.  Fixed income is represented by Barclays US Government/Credit Bond Index.  The following table shows annual returns and standard deviations for this simple two-fund approach for January 1973 through December 2014, a period of 42 years. It presents annualized (geometric) returns and standard deviations (S.D.) for varying equity/fixed weights.  It is important to note that most active managers underperform the S&P 500 and Barclays bond index every year so even this simple portfolio offers relatively good returns compared with active investment managers.  This table is not adjusted for the 4.2% annual CPI-U inflation rate during 1973 through 2014.

This table clearly illustrates one of the few bedrock principles of asset allocation.  Over the long term equity outperforms fixed income while increasing the yearly variations in returns.  As noted elsewhere on our website Dimson's best estimates based on 1900 through 2017 for 25 countries is that cash and cash equivalents will yield about 0.5% above inflation, short/intermeidate bonds 1.0% to 1.8%, and globally diversified equities about 5%.  Thus, equities yield about 4.5% above the risk free rate of return and 3.5% above bonds.  DFA/Ibbotson data offer very similar probable long term risks and returns.  These are inflation adjusted estimates and future inflation rates are not predictable.  Also, investors should realize that financial market prices do not arrive in nice neat normal distributions and that +/- two standard deviations in normal distributions is considered a normal range that accounts for about 94% of observations with the other 6% being outliers.  Thus, a "normal" return for a 100% equity portfolio in US stocks would be +/- 2 x 15.4% or a volatile 30.8% annually.

If we examine inflation adjusted returns for January 1999 through December 2010 for this hypothetical portfolio we find a very different result.  Another bedrock principle of asset class returns reveals itself.  For this twelve year period returns from equities were quite a bit lower than for 1973 through 2014 and fixed income outperformed equities, an unusual result for a 12-year period.  For a decade or longer asset class returns can deviate greatly from longer-term trends shown in historical data.  Investors should not rely completelyl upon very long returns data to predict the returns they will receive over ten or even twenty-year investment time frames.  We do not recommend investing in equities unless they can be held for a minimum of ten years and preferably longer.  The data is this table have been adjusted by the CPI-U annual inflation rate for 1999 through 2010 of 2.5%.  Returns in equities were the opposite of the 1973-2014 period.

The first decade of the 2000's was obviously not kind to U.S. equity investors and the normal relationship between equities and fixed reversed.  For January 2000 through end 2015, a 16 year period, the Vanguard total bond market index, VBMFX, gave a compounded return of 120.6% to the S&P 500's 89.1% with dividends reinvested.  Time of market entry and the time frame sampled obviously make a huge difference when comparing asset class returns.  Standard deviation is simply a measure of the variation of yearly returns around long-term mean returns.  A "normal" variation in a normally distributed time series is considered plus or minus two standard deviations.  Returns outside this range are considered outliers bit they do occur from time to time.  The 2008 financial crisis was one such time.  Standard deviation does not define risk in the way most investors experience it.  Most investors are primarily concerned about how much their portfolio might decline in a worst case drawdown, how long it could stay down, and what effects those declines might have on their longer term lifestyle.  Standard deviation does not tell us this.  Standard deviation only measures volatility in normal statistical distributions.

Extensive academic research, championed particularly by DFA and Fama-French and confirmed by Dimson et al and Siegel, J., has exhaustively examined the sources of portfolio returns and found that additional portfolio returns are likely if value stocks and small stocks are overweighted relative to the total equity market and if REIT's and international stocks are included.  In 2015 Fama and French expanded their three factor model, equity/fixed, value/growth and large/small, with two additional factors, company profitability and reinvestment.  The table below shows that a better risk/return ratio is achieved when short-term and intermediate bonds are used for fixed income allocations.  The next table shows annual returns and standard deviations for a highly diversified DFA "balanced" passive portfolio with various equity/fixed ratios for 1973 through 2017, a 45-year period.  Data are from DFA.  Portfolio holdings include U.S. and international and emerging markets, large and small cap stocks, growth and value equity asset classes, US Reits, and U.S. and International short-term bonds.  Weightings are roughly 60/40 Large/Small caps, 1:1 Value/Growth equities, and 70/30 U.S. and international equities.  Bonds, referred to as fixed income, run from 1-6 years in maturity and are U.S. and Iinternational with the latter fully hedged for currency fluctuations.  These returns do not adjust for an annual CPI inflation rate of 4.1%.

A comparison of the table above with the first two tables, a simple two index portfolio, clearly illustrates the benefits of DFA's globally diversified asset class strategy.  A DFA style globally diversified 100% equity portfolio with a tilt towards value and small caps gave a return, not inflation adjusted, of 13.5% annually to the S&P 500's 6.2% annually.  Of course, if one is paying 1% in management fees or maintaining a lower equity percentage then 100.0% there is less outperformance for DFA strategies.  Another bedrock principle we can see is that standard deviations were lower for portfolios with lower equity allocations and higher for those with high equity allocations.  For each allocation mix the advantage in return clearly goes to the more highly diversified investor who has overweighted value, small, and international stocks relative to the S&P 500.  Lower volatility goes to the investor who increases short and intermediate fixed income allocations.

DFA's highly diversified equity asset classes protected assets nicely in the bear market which began in April 2000 and ended around March 2003.  For nine quarters following March 2000 the S & P 500 declined 15.8% annually while DFA's equity strategy was up 0.6% annually, a remarkable achievement.  From April 2000 through March 2003, the bear market which ended in March 2003, the S & P declined 40.9% while a portfolio 100% in DFA's globally diversified equity offerings declined a far smaller 14.3%.  However, nothing is ever 100% certain based on historical financial data.  A 100% DFA balanced equity portfolio declined 52% from March 2008 through February 2009 while the S&P 500 declined 41%.  Asset class allocations for DFA balanced equity portfolios are given below.  Research noted elsewhere on this site clearly indicates that a passive and index investor will outperform the majority of active investors after expenses, security selection errors, and taxes of at least 1% per year are taken into account.  Thus, an investor in a globally diversified DFA passive equity asset class portfolio in a taxable account would have been likely to outperform a typical active portfolio manager in the S&P 500 by 1%+2.95% or 3.95% annually from January 1973 through December 2014 after taxes.

In May 2017 DFA's research team reported an additional significant factor in its multi-factoral model of equity premiums, high profitability, and introduced two new funds.  One fund covers US large caps, DURPX, and the other international large caps, DIHRX, and both are based on DFA's high profitability indexes.  Both funds specifically target the profitability premium along with additional modifications.  Stocks with higher profitability have higher expected future returns.  DFA starts with the large cap universe and sorts equities by profitability/book value and isolates the top 35% by market cap.  It continuously adjusts targeted stock weights as prices change and rebalances portfolios frequently.  DFA defines profitability by removing some non-recurring costs, excludes Reits and utilities, and measures it as operating income before depreciation and amortization minus interest expense scaled to book value.  In the US, between 1964 and 2016, the high profitability index gave returns 4.32% greater than the low profitability index with slightly higher percentages in overseas markets.  Since the funds just began trading in May 2017 only historical index data is available at this time though some comparisons with Russell and MSCI indices indicate the porfitability premium adds 0.8% to 1.2% to long term returns.

Everyone would like to receive an annual return in equities 3% or more above the S&P 500 but future returns may be different and no one is guaranteeing future returns based on past returns.  That's the risk in equities.  And, as the article "Stocks for the Long Run?" elsewhere on this website indicates, equity returns could be far lower than those shown in this table depending upon the time of market entry.  Beginning in 1982 and running through March 2000, the US experienced the strongest equity bull market in its history and returns in bonds were also far above normal as interest rates declined from the mid-teens in 1981 to near zero in 2009.  DFA data show that the longest post-WWII period where investors received no additional return for holding equities was 17 years, and on two occasions the value premium and the small cap premium did not occur for 16 and 27 years respectively.  The possibility of long periods with no returns in equities should be carefully considered by all investors.

What mix of equities and fixed income should an investor choose?  EAM recommends approaching the equity/fixed income allocation issue from a "worst case" scenario discussed in detail on our website in "Risk and Return". We know that under adverse circumstances equities can produce a rough ride and breakeven may take up to 20 years.  Historical MSCI global index data indicates a globally diversified equity portfolio can decline up to to 65% from peak to trough.  EAM provides an estimate to clients quarterly on how much their portfolios might decline in a worst case.  We use the 2008 crisis as a recent worst case example of what might be a worst case decline in a given asset class.  As of late 2016 we estimate a worst case decline for a fully diversified global equity portfolio with value and small cap stocks included between 50% and 60%.  Of course, worst case decline estimates are only estimates, can't be precise and declines could be greater.

Dimson et al and DFA/Ibbotson have carefully constructed the longest time samples of financial and economic data.  They are in agreement that the real inflation adjusted return for equities above inflation is 5%, about 1.5% for bonds, and 0.5% for cash and cash equivalents.  Thus, each increment of 10% in equities adds about 50 basis points above inflation in annual returns and about 40 basis points above risk free returns to the portfolio.  A basis point is one one-hundredth of a percent.  If we use the 2008-2009 liquidity crisis as an example of possible worst case market declines then we estimate that a globally diversified DFA style portfolio could decline 3% to 5% in short bonds, 8-12% in intermediate bonds, and 55% in equities.  The risk/return payoff in equities offers about 0.5% additional return annually for each 10% increment in equities added to a portfolio.  That increment also adds roughly 5% to 6% in additional potential total portfolio decline during a severe market sell-off in stocks and bonds.  We strongly recommend carefully considering this risk/return trade off when deciding on an equity/fixed target for your portfolio and that its potential decline be expressed not only in a percentage but also in a dollar amount.  The equity to fixed ratio is the single most important determinant of forward probable returns, volatility of prices about those returns, and worst case probable declines.

Equities and fixed income are completely different categories of investment.  Equities are ownership and fixed income is money lent.  Equities offer the benefits of ownership along with income from dividends if dividends are offered.  Fixed income offers interest on money loaned and full return of principal in high quality bonds.  DFA ran some data for EAM on equity/fixed correlations in October 2015.  From 1926 through 2014 the correlation of the S&P 500 to one month T-bills was -0.02, to long term Treasuries, 0.09, and to long term corporate bonds, 0.19, essentially showing no statistical relationship whatsoever between equities and fixed income.  In some decades during that period correlations went negative to as much as -0.56 (2010 through 9/2015) and positive to as much as 0.53 (1970-1979 in corporate bonds).  Since the 2008-2009 financial crisis the correlation between equities and fixed income has been increasing despite long term data showing little correlation between the two.

Of course, portfolio declines could be more than 55% in a 100% equity allocation but asset class diversification will hopefully prevent a global equity asset class melt-down like that which occurred when the Dow Jones Industrials declined 89% from 1929 through 1932.  Investors should consider four factors in determining how much decline they can tolerate.  First, could they endure a worst possible case decline emotionally?  Second, at what percentage does the decline become too uncomfortable?  Third, at what point would they sell?  This is a subjective decision based upon several factors including current personal circumstances, mood, and market conditions and narratives.  We know that investors have a high risk tolerance during bull markets and low risk tolerance during bear markets.  Fourth, can they still reach their investment and retirement income goals in a worst case?  The answers to these questions help investors determine an appropriate equity/fixed ratio.

It is also important for investors to realize that past asset class risk and return numbers are dependent variables and not independent variables.  Past numbers are the result of events in the real world.  These events include competitive advantages or disadvantages between nations, fluctuations in currency exchange rates and trade, new technologies and industries which arise, new investment instruments that are created like derivatives and CDS's, high frequency computer trading technology (HFT), changing societal values regarding consumption and debt, stimulative policies by central banks, and countless other factors.  These events are wholly unpredictable yet influence economic variables, securities prices and investment risks and returns.  No one can guarantee or know future returns with certainty.  Elsewhere on our website "Financial Superstructures" discusses other factors that influence securities prices but can't be quantified.

Standard deviations, often presented to investors as a measure of portfolio risk, indicate the probability of variations about a mean return in a "normal" or Gaussian return distribution.  But, distributions for investment returns are not all that normal and tend to exhibit kurtosis, clustering towards the mean and outliers, a few extreme scores that lie far to the sides of the distributions.  Since 2011 the S&P 500 has produced returns as much as 7 standard deviations from the mean, gold has produced returns 9 standard deviations below the mean, and numerous asset classes, as was the case in 2008 and 2009, have intermittently traded 7 standard deviations from the mean.  The probability that a number in a standard distribution will lie seven standard deviations from the mean is about one in a trillion, in other words never.  Yet, these extreme events have occurred fairly regularly since the financial crisis.  This clearly suggests that employing standard deviations in evaluating portfolio risk may cause an investor to believe they know more than they do.  Standard deviations may not be an appropriate measure of portfolio risk as investors will experience it.  We recommend conceptualizing portfolio risk in terms of a simple worst case percentage decline from today's prices for a given asset allocation mix and estimating what that would be.  It can only be a rough estimate since asset class returns can always decline further than they have in previous worst cases but at least it offers a substantive number describing the possible real-time experience of watching one's portfolio decline and the dollar amount that could be lost.

Occasionally we are asked to recommend portfolios which are at the efficient frontier.  The meaning of this concept is often debated and the historical data is very clear.  What constituted an efficient portfolio in each decade of the last five decades, 1960 through 2010, was very different and not knowable in advance and thus nothing can be optimized.  Means, standard deviations, and asset class intercorrelations are variables, not constants, and change constantly over time.  There is no optimal allocation for all asset classes all the time.  We can only know what was optimal retrospectively.

In a DFA working paper for advisors in 2004 Truman Clark titled his piece, "Stop Playing with Your Optimizer", noting that outputs from optimizers are based on historical returns which produce results which are largely the result of random sampling errors.  Monte Carlo statistical sampling and "bootstrapping" may look appealing but they are still only based on the last 50 to 100 years of data and that data is noisy and varies greatly depending upon the time sampled.  An additional article on optimizers which expanded on the first article was published by DFA in November 2012.  DFA noted that "the accuracy of optimizers is extremely sensitive to the accuracy of the inputs" and "Although there is tremendous cachet from associating one's asset allocation approach with 'Nobel Prize-winning research' so-called optimizers merely create the illusion of scientific accuracy.  The illusory effects are magnified when precise weights in various asset classes are specified to two decimal places."

Often investors are offered risk assessment questionnaires purporting to measure their risk tolerance.  These are then used to recommend allocations.  Sometimes investors are asked to sign an investment policy statement summarizing their investment plan and risk levels.  While assessing risk and developing a detailed plan are important there are serious methodological shortcomings with paper and pencil assessments of risk tolerance.  In order to measure risk tolerance with a questionnaire it must be demonstrated that the instrument has both reliability, offering consistent results for an individual, and validity, actually measuring what it purports to measure.  The only way to determine the latter is to show a strong correlation between questionnaire responses and actual investor behavior during times of high risk.  To the best of my knowledge no investor risk tolerance questionnaire has ever addressed these methodological issues nor is there any evidence that signed investment policy statements make investors less reactive to major economic and market shifts.

A large and well-replicated body of psychological research suggests that people, even highly intelligent people, are strongly influenced by the perceptions and actions of others. Self-reports predicting future behavior are often untrustworthy and influenced by whatever is deemed socially desirable or appropriate in a given situation at a given time.  Risk tolerance is not a physical constant or stable entity.  It is a variable.  Investment decisions are often influenced by media pundits, finanancial analysts and brokerage recommendations.  Then there is the recency effect.  Research by academics in behavioral finance as well as numerous surveys has shown that most investors have a mental time horizon on investment markets that reaches back 6 to 24 months.  What happened recently is what investors expect to happen in the future.  In the world of investing this often turns out to be wrong.  In addition, psychological research has shown a loose connection at best between stated intentions and actual behaviors when it comes to several aspects of human behavior.

Here are a few more general rules for determining an overall equity/fixed allocation.  Study the tables above carefully and assume these are optimistic numbers.  Avoid extreme allocations unless your circumstances allow it.   Handle lump sum monies more conservatively.  Younger investors with many years to average into the markets will be hurt far less by a long bear market than older investors close to or in retirement.  Younger investors can be more aggressive in their equity allocation.  One way to examine your risk tolerance is to imagine how it would feel to watch your equity holdings decline "X"% and stay down for "Y" years while you have "lost" Z dollars.  No table or questionnaire can tell you what your risk tolerance should be. It is a highly individual and subjective matter.

Once an overall equity/fixed allocation has been decided upon individual asset class allocations need to be determined.  In a hypothetical group of family accounts these might include U.S. and international stocks and bonds, large and small cap and growth and value asset classes, REIT's, emerging market equities, and tax-free municipal bonds in a taxable account.  These would then apportioned to appropriate accounts, perhaps taxable bonds, REIT's and international small and small value equities might be placed in tax-qualified accounts due to their relatively high tax pass-throughs and tax-free municipals and tax-managed equity index funds might be placed in taxable accounts.

Debate often occurs in the passive and index investment community over how to weight different equity asset classes.  The most fundamental principle is to include all asset classes.  We've run countless hypothetical portfolios using DFA's historial data and substantial differences in equity asset class weightings produce relatively small differences in risk and return.  Let's compare two portfolios with different equity asset class weightings for the 25-year period from 1976 through 2000.  The first portfolio allocates 20% each to U.S. large growth and value, 15% each to U.S. small growth and value, 10% to Reit's, and 10% each to international large growth and value.  The second significantly increases weightings for value and international stocks, allocating 25% to U.S. large value, 15% to U.S. large growth, 15% to U.S. small value, 5% to U.S. small growth, 10% to Reits, and 15% each to international large growth and value.  The first, roughly equal-weighted portfolio produced an annualized return of 17.09% with a standard deviation of 12.53%.  The second portfolio, overweighted in value and international stocks, produced an annualized return of 17.03% with a standard deviation of 12.29%.  There is no statistical or practical significance to these differences whatsoever.

A November 2007 paper privately circulated by an MIT research institute statistician calculated trailing optimized or super-efficient portfolios (SEP) for 1927 through 1966 and for 1967 through 2006 for U.S. equity asset classes.  He used six Fama-French benchmark portfolios and found that SEP for the earlier period was 75% large growth, 15% large blend, and 10% small value while SEP for the second period was 5% large growth, 15% large blend, 30% large value, and 50% small value.  Contrasting the two portfolios showed an almost total reversal in returns for growth and value stocks with growth stocks much stronger in the first 40 years and value stocks much stronger in the second 40 years.  Anyone for predicting which asset classes will outperform and which allocations will give the best risk-adjusted returns for the next 40 years?  Any argument that equity asset class weighting A is superior to equity asset class weighting B overlooks substantial limits in the data including insufficient independent sampling periods, non-normal distributions with significant outliers, high variance relative to mean returns, varying equity asset class intercorrelations, and continuing change in the larger financial structures involved in the public securities markets like banks or regulators.  The future is quite unpredictable.

DFA offers sample "balanced" portfolios which are the basis of the risk and return data presented in the third table above.  DFA states that these portfolios are not intended to be recommendations but illustrations, just one way of allocating across individual asset classes.  Their 100% equity balanced portfolio allocates 20% each to U.S. large and large value stocks, 10% each to U.S. small and small value, Reit, and international large value stocks, 5% each to international small and small value stocks, 3% each to emerging market large and value stocks, and 4% to emerging markets small stocks.  Balanced portfolios with fixed allocations included typically contain equal weights of DFA's one year U.S. fixed income portfolio, two-year global fixed income portfolio, five year U.S. government portfolio, and five-year global fixed income portfolio.  A 60% equity/40% fixed "balanced" portfolio would contain 10% each of the preceding four fixed income funds, and proportionally reduce the equity allocations.

We recommend the use of an equal asset class weighting strategy for equities.  This is sometimes called a 1/N weighting strategy where N equals the number of asset classes one wishes to include.  EAM's strategy equally weights ten different equity asset classes, adding international large growth to DFA's balanced portfolios, and divides the 10% allocated to emerging markets into 5% emerging value and 5% emerging small, a 10x10% model.  This approach fits with Dimson's data and seeks to minimize the reductions in return created by individual asset class underperformance that may occur for twenty years or more.  We've been using it as a starting point for planning asset allocations since early 2003 and it can be fairly closely simulated with DFA's core/vector funds.  For January 2000 through December 2015, 16 years, an equally weighted 1/N DFA portfolio did a little better than DFA's balanced portfolios and far better than the S&P 500 with dividends included.  The following returns for 2000 through 2015 are not adjusted for a CPI-U inflation rate of 2.1%.

DFA "Balanced" 100% equity model: 244.0% total geometric return.

Evanson 10x10% 1/N equity model:  247.5% total geometric return.

S&P 500:  89.1% total geometric return.

DFA's balanced portfolios weight US equities and large cap equities heavier than an equal weighting strategy and since the 2008 credit crisis and particularly since 2011 US large cap growth equities have put in a stronger performance than other equity asset classes.  Global diversification hasn't worked quite as well as it has at other times though longer term it can be expected to produce returns about 3% above those in US large cap growth equities.  Asset classes go in and out of favor and when they will do so cannot be predicted.

Science News (June 2011) published a paper reviewing 1/N weighting strategies in equity portfolios and business management and also examined real-world heuristic decision making strategies (rules of thumb) in business.  In one study researchers compared 1/N strategies with 14 complex models for investing in the same stocks and found 1/N models superior to all other models.  Predictions made by complex risk/return models usually generated lower returns.  In real-world business decisions participants favored simple heuristics and not complex risk/return models.  Simplicity works.

We want to emphasize that we don't believe that there is one absolutely correct weighting for equity allocations for each investor.  Advisors hold many different opinions as do clients.  We are not dogmatic about how our clients weight asset classes within their portfolios but are always candid about the effects of unusual weightings.  Some investors wish to tilt more towards value or more overseas or omit Reits since they hold private residential or commercial real estate.  Some investors wish to modify or counterbalance an equity/fixed mix with alternative investments like commodities, gold, or hedge funds.  The most important equity allocation issue as we see it is that equity portfolios are global and contain an exposure to the value and small cap premiums and that fixed portfolios are highly diversified across different types of investment grade debt and short or intermediate maturities.

After individual asset class allocations have been determined investors should choose the most cost efficient and accurate investment vehicle for capturing equity and fixed returns for each asset class.  As research elsewhere on this site explains the odds are very much on an investor's side if low-cost passive and index investment vehicles are chosen.  If an advisor is desired advisor fees should be kept as low as possible.  EAM has promoted very low fixed advisory fees since 1995, typically averaging around 0.1%.  For equity allocations there are three choices for investment vehicles available to passive and index investors; passive asset class funds like those offered by DFA, indexed open-ended mutual funds like those offered by Vanguard, and exchange traded index funds (ETF's).  These are discussed in more detail in "Is DFA Superior?" elsewhere on this website.  The details involved in making specific choices are beyond the scope of this article and many choices are available in each category.  DFA offers a precise and comprehensive selection of equity asset classes  and many tax-managed funds while Vanguard offers slightly lower fees but less diversification globally.  Vanguard indexes are committee based and not asset class based like DFA and not as sophisticated as DFA's portfolios.  ETF's, offered by Vanguard but not DFA, offer very low fees but are primarily based on committee based indexes and pledged securities from authorized participants.  Any and all attempts to improve on returns above what these options offer will involve trading models that attempt to predict the future, leverage, and timing.  Research clearly shows that these active management approaches are likely to underperform passive and index strategies over time due to increased costs and increased risks.

Investors sometimes focus on the lower expense ratios and tax pass-throughs ETF's offer or the very low expense ratios Vanguard indexes offer.  At a November 2007 conference DFA presented data comparing their passive asset class offerings to indexes for the prior five years.  Due to index tracking error in traded indexes and ETF's DFA estimates its portfolios added 30% bps. (0.30%) or more annually to returns versus ETF's.  DFA employs Fama-French factor models which empirically define asset classes rather than base portfolios on committe decisions.  DFA also picks up about 35 bps. per year from lending securities.  ETF's are, in a sense, borrowers of securities from authorized participants.  And, DFA adds about 35 bps. per year from being patient buyers and sellers of securities within their portfolios rather than having to reconstitute their portfolios the same day the composition of an index is changed, usually every six months.  DFA portfolios also incorporate short term momentum effects, profitability screens and other accounting variables which add a few basis points in return over an index strategy.  DFA's value-added strategies are reflected in the outperformance of their portfolios compared to indexes in comparable asset classes.

DFA's value added strategies sum to an additional 1% or more annual return.  DFA's US microcap fund has outperformed the Russell 2000 by about 165 bps. annually.  DFA's US small value fund has outperformed the Russell 2000 by 351 bps. annually.  We've had several clients compare Vanguard's offerings with DFA and we typically see an advantage for DFA of about 0.5% to 2.0% per year versus matched comparable indexes. These comparisons are based on short-term samples and are not statistically significant though they do suggest that the Fama-French models and DFA's trading strategies put DFA's funds ahead of committee designed indexes.

For fixed income allocations, we typically recommend a mix of cash and cash-equivalents, fixed income index funds, available from both DFA and Vanguard, fixed income ETF's, and A or better rated maturity laddered individual bonds.  EAM's portfolios often include investment grade tax-free municipal bonds, corporate, and government bond issues, and international government and corporate bonds.  Other options are available like mortgage and asset backed securities, preferred stocks, MLP's, and lower rated and unrated hi-yield or "junk" bonds.  Investors should be aware that fixed income markets are ruthlessly efficient and higher returns mean higher risks and more potential complications or defaults.

The pricing efficiency and risk in fixed income marketplaces is overt and obvious in comparison with pricing and risk in equity markets.  For example, as of mid-2016 10 year US Treasuries were around 1.8%, preferred stocks were around 6%, and better quality hi-yield non-collateralized junk bonds were around 7%.  Of course, any investor would prefer a 7% return to a 1.8% return.  The problem is that unlike risk in equities where long-term investors who can tolerate risk in the form of volatility may receive higher returns investors in high yielding lower quality fixed income investments have some chance of never being rewarded for their higher risk.  Lower quality bonds can fail to repay principal or interest or both.

DFA continually evaluates all its fixed income portfolios using a variety of parameters.  For example, DFA will assign credit ratings to bonds which may differ from credit agency ratings if DFA finds that a given bond issue trades at substantially higher yields than its peers.  DFA has found that such bonds perform more like bonds with lower credit ratings and experience a downgrades more frequently.  It will therefore assign them a lower credit rating and may not include them in its portfolios.  If the risk were the same in preferred stocks or junk bonds as in Treasuries their price would soon be bid up until their returns were as low as Treasuries.  For example, the default rate in hi-yield bond portfolios for 2001 reached about 10% for the year due to the collapse of the internet/tech bubble that began in March 2000 and many of the defaulted issues never paid since there was no collateral behind them.  Our yield-grabbing  investor might have received a yield of 7% on his bonds but experienced a 10% decline in his high yield bond portfolio and ended up receiving -3.0% for that year.  In fact, DFA's research shows that after defaults and other complications higher yielding and more risky fixed income investments give a return about the same as top quality short-term Treasury bonds and bond indexes which have long track records and involve far less anxiety.

Finally, an investor needs to decide whether they wish to enter the equity and fixed income markets in one lump sum or gradually over time.  Maturity laddered fixed income bond indexes and individual bonds in the 1 to 6 year range pose little risk because the portfolios are continuously renewing themselves as issues mature and will do well in inflationary or deflationary environments if they are held long-term.  If interest rates rise for an extended period of time than income from the portfolio will rise.  Research has shown that economists and experts can't predict future interest rates at a rate greater than chance guessing for more than 3 to 6 months in advance so timing bond purchases doesn't make a lot of sense.

Equities, however, are another matter, particularly for older investors or lump-sum investors who will not benefit as much should a long-term bear market bring lower future equity prices for an extended period.  We know we can value equity markets based on fundamentals or other valuation metrics but it's unlikely we'll see additional returns from timing and trading asset classes or guessing when equities should be owned or not.  We discuss this issue elsewhere on our website in "Tactical Asset Allocation."  So, what's an investor to do?  Recent research by Vanguard suggests that lump sum investing produces a little more return for rolling ten year periods with somewhat more frequent and substantially greater declines.  Logically, this should be the case since equity markets go sideways or up about two-thirds of the time and decline about one-third of the time.  Averaging into equity positions is a form of insurance and there is a minor cost for doing so due to less total return from low yielding cash vehicles where money is kept in cash for some period of time.

In the last five years or so "smart beta" strategies have grown in popularity across the investment industry.  Smart beta is a general term encompassing fundamental-weighted strategies, low volatility strategies, and factor based indixes.  DFA defines smart beta as rules-based index strategies that deviate from market capitalization weights.  In a discussion with a DFA statistician in 2015 it was mentioned that DFA had looked at over 100 factors that might add to equity returns.  In a DFA article by Singh and Lee (January 2015) DFA deconstructed fundamental weighting strategies and found they were highly correlated (0.98) with large cap value equities.  DFA also deconstructed low volatility exposure, popular in 2016, and found an inconsistent relationship between low volatility and returns with low volatility producing lower market returns in the 1970 through 2013 period while from 1929 through 1969 higher returns and lower volatility were positively correlated.  There are no constants in financial market data.  In 2015 Fama and French expanded their three factor model, described above, to include two additional factors, company profitability and corporate investment strategy.  All equities within DFA's equity portfolios include these additional factors.

Not mentioned in this review of passive and index portfolio design are several alternative investments to equities, REIT's, and bonds.  These include hedge funds, commodity index funds and individual commodities like gold or oil, venture capital investments, private equity investments, and private real estate.  We discuss these elsewhere on this website in "Alternative Asset Classes".  Investors should always remember that promises of high potential returns often involve greater risks, high price volatility, long periods of flat returns, illiquidity, and even the potential for a total loss of principal.

This summary is intended to be general in nature and does not constitute specific investment advice.  The numbers provided are from sources believed to be reliable but cannot be guaranteed.  A compact and useful portfolio planning guide for investors is Steven R. Davis's "Retire Early and Sleep Well", Grote Publishing, 2002.  Another useful book which combines lifestyle planning and "early semi-retirement" with passive investment strategy is Bob Clyatt's "Work Less, Live More", Nolo, 2005.