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Key Points

  • Asset allocation is the basis of the Schwab Intelligent Portfolios™ investment philosophy.
  • For a given level of expected return, diversification lowers portfolio risk and can lead to higher wealth in the long run.
  • Asset allocation plans have been designed to reflect market changes and client preferences for loss aversion and income.

Introduction

Asset allocation—dividing an investment portfolio into different asset classes, such as large-company stocks, small-company stocks, international stocks, bonds, commodities, cash investments, etc.—has been the cornerstone of investment planning for decades. The goal of asset allocation is to reduce risk through diversification by having exposure to a variety of investments that perform differently during various market conditions.

While higher correlations have been seen among asset classes in recent years, it is important to understand that asset allocation still helps investor portfolios even during times of market turmoil. In fact, as long as assets aren't moving in perfect lockstep, the longstanding benefits of diversification still hold true.

Charles Schwab Investment Advisory has evaluated the asset allocation approaches used in the market today. This paper outlines the appropriate asset mix, based on that evaluation, for different types of investors and explains the process of constructing a diversified portfolio.

Asset Allocation

Asset allocation forms the basis of the Schwab Intelligent Portfolios investment philosophy. By providing a framework for deploying capital over a mix of investments, asset allocation allows investors to diversify their holdings and help mitigate downside risk. This built-in benefit is a well-known feature of asset allocation and makes intuitive sense—when one asset class suffers, it pays to not have all your eggs in one basket.

But there's another advantage to asset allocation that is not understood as clearly: the potential to grow wealth.

More than the sum of the parts

Consider the following example with two investments:

  • $100 invested in US large-company stocks (as represented by the S&P 500® Index) at the beginning of 1971 would have grown to $8,642 by the end of 2015.
  • $100 invested in gold (as measured by the London Gold PM Fixing) would have grown to $2,836 over the same time period.

But if that $100 had been invested in a 50-50 split of both investments, the portfolio would have grown to $8,692 over the same span. This return is more than either the stock or gold portfolio alone, while demonstrating lower average risk (see Exhibit 1). Not all time periods will lead to a higher return for the 50-50 portfolio, but most periods have dramatically reduced risk in the combined portfolio relative to the two asset classes individually. While stocks and gold are both deemed relatively risky investments, combining them helps mitigate the risk of the portfolio. This is due to their relatively low correlation to one another.

Exhibit 1: Risk/ return profile of $100 investment: 1971 – 2015

Hypothetical risk/return profile of $100 investment: 1971-2015

Exhibit 1: Risk/return profile of $100 investment: 1971 through 2015 | S&P 500: $8642, 10.42% Average Annual Return, 17.46% Risk* | Gold: $2836, 7.72% Average Annual Return, 28.92% Risk | 50/50 Portfolio Rebalanced Annually: $8692, 10.43% Average Annual Return, 15.05% Risk Exhibit 1: Risk/return profile of $100 investment: 1971 through 2015 | S&P 500: $8642, 10.42% Average Annual Return, 17.46% Risk* | Gold: $2836, 7.72% Average Annual Return, 28.92% Risk | 50/50 Portfolio Rebalanced Annually: $8692, 10.43% Average Annual Return, 15.05% Risk Exhibit 1: Risk/return profile of $100 investment: 1971 through 2015 | S&P 500: $8642, 10.42% Average Annual Return, 17.46% Risk* | Gold: $2836, 7.72% Average Annual Return, 28.92% Risk | 50/50 Portfolio Rebalanced Annually: $8692, 10.43% Average Annual Return, 15.05% Risk

* Risk is measured by the standard deviation of annual returns

Source: Charles Schwab Investment Advisory, Inc. and Morningstar Direct.  The example is hypothetical and provided for illustrative purposes only. It is not intended to represent a specific investment product. Dividends and interest are assumed to have been reinvested, and the example does not reflect the effects of fees or expenses.  If fees and expenses had been included, returns would have been lower. Past performance is no guarantee of future results.

The difference that a diversified portfolio can deliver over the sum of its parts is what Nobel Prize-winning economist Harry Markowitz once called "the only free lunch in finance." In other words, diversification can deliver benefits over time at no additional cost.

This "free lunch" is made possible by the fact that individual assets typically aren't perfectly correlated. If asset values do not move in perfect harmony, then a diversified portfolio will have less risk than the weighted average risk of its constituent parts. In fact, a diversified portfolio can often have less risk than its lowest-risk constituent, as it does in the example.

The reason lower portfolio risk can lead to higher wealth in the long run is that a portfolio with lower risk generally does not decline as much in a market downturn, so its recovery to breakeven need not be as large compared to a portfolio that declined dramatically. For example, a portfolio that falls in value by 25% must grow by 33% to recover from its loss; a portfolio that declines by 10% only needs to grow by 11% to recover.

The Ongoing Evolution of Asset Allocation

Markowitz first introduced the concept of diversification in 1952. Markowitz's work, which served as the foundation for Modern Portfolio Theory (MPT), concluded that an investor could reduce the overall risk of a portfolio by including investments that have low correlations to one another.1 

Since then, others have built upon this core premise.

  • In 1964, Bill Sharpe introduced the Capital Asset Pricing Model (CAPM), which described the relationship between risk and expected return, and introduced "beta" as a measure of sensitivity to market risk.2 Markowitz and Sharpe won the Nobel Prize in Economics in 1990 for their significant contribution to MPT.
  • In 1986, Gary Brinson, Randolph Hood and Gilbert Beebower studied the allocations of 91 pension funds and concluded that asset allocation decisions, on average, explained more than 90% of pension fund risk, as measured by the volatility of returns over time.3 
  • In 2000, Roger Ibbotson and Paul Kaplan showed that a large portion of the variation in time-series returns comes from general stock market movements, not the specific asset allocation decision. More importantly, they correctly point out that many investors mistakenly believe that the Brinson, Hood, and Beebower result applies to the return level. They argue that because, on average, investors do not beat the market (the average return of those who do beat the market is offset by the average return of those who don't), asset allocation policy explains 100% of the typical individual investor's level of return.4 

While some challenged these findings over the years, it wasn't until after the 2008 financial crisis that the merits of MPT were widely questioned. Critics pointed to higher correlations between asset classes during periods of market stress—essentially undermining diversification benefits when investors need them the most.

It's important to understand that even during periods of market stress, diversification still makes sense as long as assets don't move in perfect lockstep.  Nevertheless, an important challenge is to identify asset classes that have desirable risk and return characteristics while providing increased diversification benefits to the portfolios.

New Market Realities

MPT needs to evolve further to reflect new market realities and the ongoing expansion of asset allocation to non-traditional asset and sub-asset classes. Taken together, these realities have significant implications for investors.

Traditional assets are more correlated

Diversification offers substantial benefits. As noted above, the diversification benefits associated with combining assets into a portfolio are driven primarily by how closely the returns on those assets move together. When two assets move in perfectly positively correlated (correlation of +1), there are no benefits from combining them in a portfolio. When two equally risky assets are perfectly negatively correlated (correlation of -1), combining the two assets into a portfolio can eliminate all volatility. A correlation of zero means that the two assets are uncorrelated and don’t move together at all.

In reality, no two assets are perfectly correlated—either positively or negatively. In practice, most correlations are positive, and investors should seek investments with lower correlation to one another. Relatively few assets have low or negative correlations with each other.

As noted before, assets have become more highly correlated in recent years. The correlations for four equity asset classes over three different time periods are shown in Exhibit 2. The correlations have generally been rising since 1995-2000 (as seen below by the increasing amount of red and orange squares). This means diversification benefits have been decreasing over time.

Exhibit 2: Equity correlations have been rising

Correlation Ratios for four equity asset classes from 1995 through 2000
1995–2000
1.00
0.62 1.00
0.69 0.60 1.00
0.66 0.64 0.70 1.00
Correlation Ratios for four equity asset classes from 2001 through 2007
2001–2007
1.00
0.83 1.00
0.85 0.78 1.00
0.77 0.77 0.82 1.00
Correlation Ratios for four equity asset classes from 2008 through 2015
2008–2015
1.00
0.92 1.00
0.91 0.81 1.00
0.82 0.76 0.90 1.00
    • 0.3 – 0.7 Moderate Greatest diversification (Low correlation)
    • 0.7 – 0.9 Moderately high Medium diversification (Medium correlation)
    • 0.9 – 1.00 High Little diversification (High correlation)

Source: Charles Schwab Investment Advisory, Inc. and Morningstar Direct. See disclosures for proxy indices.

Correlations have been rising due to greater inter-connectivity between global markets. Multinational corporations have proliferated to such an extent that what happens in Europe and Asia impacts the US markets and vice versa. Many Fortune 100 companies in the United States depend on emerging markets for growth; and many overseas corporations depend on demand from American consumers. In addition, access to more information via the Internet is fueling the inter-connectivity.

In 2008, correlations increased due to the global credit crisis. Indeed, if you look at the history of financial markets, you will find that correlations tend to rise in times of crisis.

Even as the 2008 financial crisis recedes, Schwab Intelligent Portfolios are built assuming that correlations in equity markets will remain elevated going forward. This does not rob diversification of its merits—it simply means that it will be more nuanced. Instead of looking for uncorrelated investments, slight reductions in correlation will be the focus. For example, investments with a correlation of 0.5 provide greater diversification benefits than those with a correlation of 0.7, and the diversification benefits increase as the correlations decrease.

Increased external shocks

One major repercussion of global interconnectivity is that markets are hit by more external shocks. Major market-moving shocks have increased in number and intensity in recent years. Events like the European debt crisis, the Japanese tsunami of 2011 and government change in Ukraine have unnerved investors and affected the outlook for companies across the globe.

Another factor contributing to this dynamic is how quickly information spreads within and across markets (impacting correlations as well). Individual investors and smaller institutional investors now have access to information once available only to large institutional investors, but they have less time to digest it. Hedge funds and high-frequency traders can respond to news immediately, creating big swings in individual stocks and market segments. This tendency to act quickly on breaking news contributes to market volatility during times of crisis or unease.

Equity risk dominates traditional asset allocation

The traditional approach to asset allocation has been to allocate 60% to stocks and 40% to bonds and cash. However, stocks tend to be much riskier than bonds. Equity risk, as represented by the standard deviation of the S&P 500® Index, is much higher than bond risk, as represented by the Barclays US Aggregate Bond Index. Therefore, it's important to recognize that equity risk dominates the risk of traditional asset allocation. Modern approaches to asset allocation seek to achieve a better balance of risk-taking and reduce the amount of equity risk in the portfolio.

Bond yields are low

Most investors buy bonds for their return of principal, barring default, and for the income they generate. Long-term interest rates, as measured by the yield on the 10-year Treasury bond, have declined dramatically since the mid-1980s (see Exhibit 3).

Exhibit 3: Bond yields are low

Exhibit 3: Bond yields are low | Long-term interest rates, as measured by the yield on the 10-year Treasury bond, have declined dramatically since the mid-1980s. A bond with a starting yield of 11.3% declined to a yield of 2.2% by the end of 2015. Exhibit 3: Bond yields are low | Long-term interest rates, as measured by the yield on the 10-year Treasury bond, have declined dramatically since the mid-1980s. A bond with a starting yield of 11.3% declined to a yield of 2.2% by the end of 2015. Exhibit 3: Bond yields are low | Long-term interest rates, as measured by the yield on the 10-year Treasury bond, have declined dramatically since the mid-1980s. A bond with a starting yield of 11.3% declined to a yield of 2.2% by the end of 2015.

Source: Charles Schwab Investment Advisory, Inc. and Bloomberg.

With interest income at generational low levels, investors have sought other sources of income. A reality of the current low interest rate environment is that many investors in or near retirement will not be able to generate sufficient interest income from investment grade bonds alone, further diminishing their appeal.

Most market prognosticators believe that bond yields are more likely to rise than fall going forward, which means that bond prices are more likely to fall. This is especially true for Treasury and mortgage bonds since the Fed has been purchasing bonds in these sectors to keep long-term rates low. Once this stimulus is removed, it is likely that bond yields will rise.

Therefore, Schwab Intelligent Portfolios features other fixed income investments, including high-yield, international, and emerging-market bonds.

Expected stock returns are lower

A low Treasury yield also generally implies low expected stock returns. This is because the expected return on stocks can be thought of as the expected return on a default risk-free security (like US Treasury bonds) plus an equity risk premium.

Merely extrapolating from stocks and bonds' long-term historical results will not be sufficient for asset allocation models going forward. In sum, it's not just higher correlations that are prompting many to consider their asset allocation strategies going forward. There are plenty of reasons investors should revisit their allocation models to ensure they are realizing the full potential of diversification.

Adapting Asset Allocation to Changing Times

In response to these changing economic conditions, asset allocation has evolved a great deal from the typical stocks, bonds and cash blend popular during the 1990s (as shown in Exhibit 4). Modern asset allocation now encompasses non-traditional asset classes, like gold or other commodities.

In addition, it is now common to divide stocks and bonds into a variety of sub-asset classes. Stocks can be broken up into large and small, domestic and international, and developed and emerging markets. Bond allocations can include Treasuries, agencies, investment grade corporate bonds and high-yield bonds.

Exhibit 4: Sample of a modern approach to asset allocation

For illustrative purposes only

To meet their long-term needs and objectives, institutional investors have adopted different approaches to incorporating a wider range of asset and sub-asset classes. These include:

  • The Endowment Model, based on the extraordinary results delivered by endowments managed by Yale University and others in the late 1990s and early 2000s. Yale, Harvard and other large endowments allocated about 70–80% of their portfolios to alternative investments, including private equity, real estate, timber and absolute return strategies.
  • The Liability-Driven Investment (LDI), a holistic investment strategy based on cash flows needed to fund an institution's unique future liabilities, which tends to rely on bonds.
  • The Risk Parity approach, in which each asset class is assigned a weight such that it contributes equally to the overall risk of the portfolio. This approach lends itself to large allocations to fixed income.

While these asset allocation approaches have proven successful for institutions, they are not necessarily appropriate for use with individual investors because they are not scalable (LDI) or involve the use of highly illiquid securities (Endowment Model) or high amounts of leverage (Risk Parity).

A modernized asset allocation model for individual investors

After evaluating the asset allocation approaches used in the market today, the perspective used for Schwab Intelligent Portfolios is influenced by the fact that the clients enrolled in Schwab Intelligent Portfolios are primarily individual investors and embraces aspects of three different asset allocation philosophies:

  • Traditional diversification: Asset class weights are chosen so as to maximize the expected return for a given level of risk.
  • Risk budgeting: Weights are assigned to asset classes with the goal of diversifying the sources of risk across multiple asset classes.
  • Goal driven: Asset allocation is designed to achieve a specific goal, such as absolute return, inflation hedge or income. Success is measured by the achievement of a specific target, such as income.

An additional built-in factor is that investors often feel more strongly about avoiding losses than acquiring gains. As a result, a preference for loss aversion is factored into the portfolio construction process. In addition, many retired investors prefer to live off the income from their portfolio and not dip into the principal. Therefore, both total return and income strategies have been developed.

Asset Classes in Schwab Intelligent Portfolios

The first step in the process is to identify which asset classes to include in the portfolios. Three factors are considered:

  • Asset classes must be accessible through at least two liquid ETFs that do not issue K-1s and create tax complications for investors. (A primary and Alternate ETF are required for SIP)
  • Ideally, asset classes should be minimally correlated to achieve greater diversification benefits, and asset classes that provide unique risk or return characteristics tend to have low correlations.
  • In addition, the level of expected income is an important consideration for the income models.

Each of the following asset classes meets one or more of the above criteria:

  • Core equity: US large-company stocks, US small-company stocks, international developed country large-company stocks. For each of these, there is also a variation that focuses on stocks using "fundamental" weightings.
  • Equity income: US large-company stocks (high dividend), international developed country large-company stocks (high dividend), master limited partnerships (MLPs)
  • Non-traditional equity: international developed country small-company stocks, international emerging markets stocks, US Real Estate Investment Trusts (REITs), international REITs. For small company and emerging markets there is a fundamental variation.
  • US investment grade bonds: Treasury bonds, corporate bonds, securitized bonds, national municipal bonds, and California municipal bonds.
  • Non-traditional bonds: US inflation protected bonds, US corporate high-yield bonds, international developed bonds, international emerging market bonds, preferred stocks, bank loans and other floating-rate notes
  • Commodities: gold and other precious metals
  • FDIC-insured Cash 

Asset Class Roles with the Portfolio

To understand the rationale behind each asset class, it's helpful to group them according to their role in the portfolio (see Exhibit 5).

Exhibit 5: Each asset class has a specific role in the portfolio

  • Growth
  • US large-company stocks
  • US small-company stocks
  • International developed large-company stocks
  • International developed small-company stocks
  • International emerging markets stocks
  • Growth and income
  • US large-company stocks (high dividend)
  • International developed large-company stocks (high dividend)
  • Master limited partnerships (MLPs)
  • Income
  • US investment grade corporate bonds
  • US corporate high-yield bonds
  • US securitized bonds
  • International emerging markets bonds
  • Preferred stocks
  • Bank loans & other floating-rate notes
  • Inflation
  • US inflation protected bonds
  • US REITs
  • International REITs
  • Defensive assets
  • Cash
  • Treasuries
  • Gold & other precious metals
  • International developed country bonds

Source: Charles Schwab Investment Advisory, Inc.

Growth potential will come primarily from the equity allocations (US large-company, US small-company, international developed country large-company, international developed country small-company and international emerging markets). These asset classes have historically delivered the highest returns, with a correspondingly higher risk. Investors should have at least some long-term exposure to all of the major equity markets.

Growth potential and income will come from dividend-paying stocks (US and international), as well as yield-oriented securities such as master limited partnerships (MLPs). These securities offer the potential for both high returns and high yield.

Income will come from a broad array of fixed income investments, including US investment grade corporate bonds, US corporate high yield bonds, US securitized bonds, international emerging market bonds, preferred stocks, bank loans and other floating-rate notes. Income generally accounts for the majority of a bond's total return; as such, bonds do not typically offer significant opportunities for growth. While bonds historically have provided higher levels of income, they carry varying degrees of risk.

Inflation protection comes from allocations to US inflation protected bonds, FDIC-insured cash and REITs. With US inflation protected bonds, the principal value adjusts upward with inflation. As US inflation protected bonds have a constant coupon rate, this implies that the coupon, or interest received, grows with inflation.

REITs are considered by many to be an effective hedge against inflation. When looking for inflation protection, it's beneficial to find an asset that moves with inflation (the higher correlation, the better). Lease rates and real estate prices do not immediately adjust to inflation so the benefits of REITs as an inflation hedge may not be apparent when correlations are calculated over short horizons. During the period from 1972 to 2015, the average five-year correlation was 0.37 (shown in Exhibit 6). This suggests that REITs have historically provided better inflation protection than traditional asset classes such as stocks.

Exhibit 6: Correlation of inflation with stocks and REITs (1972 - 2015)

Stocks: 0.02
US REITs: 0.37
Exhibit 6: Correlation of inflation with stocks and REITs (1972 through 2015) | Stocks: 0.02, Poorer Inflation Hedge | US REITs: 0.37, Better Inflation Hedge Exhibit 6: Correlation of inflation with stocks and REITs (1972 through 2015) | Stocks: 0.04, Poorer Inflation Hedge | US REITs: 0.389 Better Inflation Hedge Exhibit 6: Correlation of inflation with stocks and REITs (1972 through 2015) | Stocks: 0.04, Poorer Inflation Hedge | US REITs: 0.39, Better Inflation Hedge Exhibit 6: Correlation of inflation with stocks and REITs (1972 through 2015) | Stocks: 0.04, Poorer Inflation Hedge | US REITs: 0.39, Better Inflation Hedge

Source: Morningstar Direct. Correlations based on overlapping five-year return data from January 1, 1972 to December 31, 2015. Stocks are represented by the S&P 500 Index, REITS are represented by the FTSE NAREIT All Equity REIT index, and inflation is represented by the Ibbotson Associates SBBI US Inflation.

Defensive assets are generally assets that have low or negative correlations with equity securities. These asset classes tend to perform well when there is downward pressure on equities. Examples of defensive assets include Treasury securities, gold, international developed country bonds, and FDIC-insured cash.

Correlation Matrix of Chosen Asset Classes

As noted earlier, a goal of asset allocation is to include asset classes that provide diversification to the portfolio. Below is a correlation matrix of the chosen asset classes that points to the diversification benefits of including non-traditional asset classes.

Exhibit 7: Nontraditional asset classes provide diversification opportunities (2004-2015)

Exhibit 7: Nontraditional asset classes provide diversification opportunities (2004-2014)

2004–2015

US large-company stocks
US small-company stocks
International large-company stocks
US large-company stocks (high dividend)
International large-company stocks (high dividend)
International developed small-company stocks
International emerging markets stocks
US REITs
International REITs
Master limited partnerships (MLPs)
Treasuries
Core bonds
US investment grade corporate bonds
US securitized bonds
US inflation protected bonds
US corporate high yield
International developed country bonds
International emerging markets bonds
Bank loans and other floating-rate notes
Preferred stocks
Gold and other precious metals
Cash
US large-company stocks US small-company stocks International large-company stocks US large-company stocks (high dividend) International large-company stocks (high dividend) International developed small-company stocks International emerging markets stocks US REITs International REITs Master limited partnerships (MLPs) Treasuries Core bonds US investment grade corporate bonds US securitized bonds US inflation protected bonds US corporate high yield International developed country bonds International emerging markets bonds Bank loans and other floating-rate notes Preferred stocks Gold and other precious metals Cash

Source: Charles Schwab Investment Advisory, Inc., Morningstar Direct and Bloomberg. Matrix depicts correlations of monthly data from January 1, 2004 to December 31, 2015. See disclosures for proxy indices.

As indicated by the increased number of green, blue, and yellow data points, these non-traditional asset classes provide a level of diversification beyond that of traditional stocks, bonds, and cash.

Determining the Optimal Mix

A Modern Approach

When looking at a traditional 60/40 portfolio for the period of 2002-2013, the core equity portion of the portfolio accounts for 99% of the total risk. This property caught investors by surprise in the 2008 financial crisis and its aftermath. The agony over the large drawdowns in this 60/40 allocation highlighted investors' asymmetric risk preference and aversion to large losses.

The fixed income portion of a traditional portfolio consists of US investment grade bonds and cash. Investment grade bonds have little or no credit risk so their total risk is driven almost entirely by maturity, or duration, risk. These bonds are likely to be hurt the worst in a rising rate environment as they have little credit exposure to help offset the risk of rising rates.

Schwab Intelligent Portfolios address both of these issues and additional asset classes are introduced to better diversify the plans.

Optimization Methodology

Two optimization methodologies were used to create the Schwab Intelligent Portfolios investment strategy allocations. In addition to the traditional mean variance optimization, full scale optimization is also used.

Mean Variance Optimization

Mean variance optimization seeks out the highest level of expected return for a given level of risk. The optimization requires two data inputs: expected returns for all asset classes included and the variance-covariance matrix.

Full Scale Optimization

A shortcoming of MPT—that it disregards key findings from the field of behavioral economics—is also addressed. The financial services industry tends to define risk in mathematical terms and use risk statistics to compare results. MPT defines risk as the standard deviation of returns, or how much they vary from the average. This assumes risks are symmetrical, meaning all risks are treated equally.

But investors often have a more emotional definition of risk. For example, investors tend to strongly prefer avoiding losses to acquiring gains, a phenomenon known as loss aversion. Studies suggest that the psychological pain investors feel from a loss is twice as strong as the joy they receive from a similar size gain.

Full scale optimization can incorporate investor's preference of loss aversion. There is a threshold in the value function where the pain of losses becomes greater than the joy of an equal sized gain. This technique optimizes based on returns rather than wealth. Rather than just using mean and variance summary statistics, this optimization requires the historical returns of all the asset classes to search for the optimal portfolio. The monthly historical returns of each asset class are adjusted by a constant so that the annualized historical return is equal to the expected return. This ensures that the full scale optimization uses the same expected returns as the mean variance optimization while simultaneously preserving the historical volatility of each asset class.

In the optimization, the return threshold is set to 0. This is the point where the pain of losses exceeds the joy of a similar sized gain. Consistent with the findings by Kahneman and Tversky5, the slope below the threshold is set to two which means that the pain of losses is two times more painful than the joy an investor would experience from a similar sized gain.

Optimized Portfolio

The optimized portfolio is equal to the average weights of the results from the mean variance optimization and full scale optimization. By averaging the two optimization methods the optimized portfolio has a balance between seeking the highest risk/reward portfolio and a portfolio that has preferences for loss aversion.

Risk Allocation

After creating the optimized portfolio, certain asset class weights are determined through risk allocation. Risk allocation allocates more weight to asset classes that contribute less risk and less weight to asset classes that contribute more risk.

Strategy Adjustments

After the optimizer generates the results they are rounded to whole percentages. This can cause the results to not add up to 100%; therefore some small adjustments are necessary to ensure the optimized investment strategy meets the constraints.

Finally, some qualitative judgment is applied to ensure that the investment strategies meet investors' preference and intuition. This can result in small changes being made to the optimized model.

Fundamental Strategies

Based on prior research, adding fundamental strategies in combination with market cap strategies can be beneficial to a portfolio over the long term. Therefore in the US large company stocks, US small company stocks, international large company stocks, international small stocks, and international emerging markets asset classes, the portfolios use a combination of market cap and fundamental strategies. In these five asset classes, the split between market cap and fundamental is approximately 40% market cap and 60% fundamental.

Muni Strategies

The Muni strategies are similar to the taxable strategies, except that investment grade munis are substituted for Treasuries, corporate bonds, agency bonds and securitized bonds.

Income Strategies

The income strategies follow the same optimization methodology as the total return strategies as outlined above. But, because these are income oriented strategies, low income generating asset classes are removed from the optimization process and replaced with higher income generating asset classes. The low income generating asset classes that were removed are the growth oriented US and International Stocks, and Gold & other precious metals. The high income generating asset classes that were added are the US and International High Dividend paying stocks, MLPs, Preferred Stocks, and Bank Loans & other floating rate notes.

Conclusion

Asset allocation has evolved beyond stocks, bonds, and cash to include a broader array of asset classes. This evolution is largely the result of several new market realities, which include low expected returns and higher correlations. In addition, individual investors generally have a preference for loss aversion and sometimes exhibit a preference for income. The Schwab Intelligent Portfolios asset allocation plans were designed to reflect these new market realities and client preferences for loss aversion and income.

1. Markowitz, Harry, "Portfolio Selection," Journal of Finance, March 1952.

2. Sharpe, William, "Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk," Journal of Finance, September 1964.

3. Brinson, Gary, Randolph Hood, and Gilbert Beebower, "Determinants of Portfolio Performance," Financial Analysts Journal, July–August 1986, 39–44.

4. Ibbotson, Roger and Paul D. Kaplan, "Does Asset Allocation Policy Explain 40%, 90% or 100% of Performance?" Financial Analysts Journal, January-February 2000, 26–32.

5. Kahneman, D. and Tversky, A. (1984). "Choices, Values, and Frames". American Psychologist 39 (4): 341–350. doi:10.1037/0003-066x.39.4.341.

Deposit Balances held in the Sweep Program at Schwab Bank are eligible for FDIC insurance up to allowable limits.

Diversification and rebalancing strategies do not ensure a profit and do not protect against losses in declining markets. Investing involves risk including loss of principal.

The information here is for general informational purposes only and should not be considered an individualized recommendation or personalized investment advice. The type of securities and investment strategies mentioned may not be suitable for everyone. Each investor needs to review an investment strategy for his or her own particular situation. Data here is obtained from what are considered reliable sources; however, its accuracy, completeness or reliability cannot be guaranteed.

Indexes are unmanaged, do not incur management fees, costs and expenses, and cannot be invested in directly.

Exhibit 2 proxy indices: S&P 500 (US large-company stocks), Russell 2000 (US small-company stocks), MSCI EAFE (international large-company stocks) and MSCI Emerging Markets (emerging market stocks).

Exhibit 7 proxy indices: S&P 500 (US large-company stocks), Russell 2000 (US small-company stocks), MSCI EAFE (international large-company stocks), DJ US Select Dividend (US large-company stocks – high dividend), MSCI EAFE High Dividend Yield (international large-company stocks – high dividend), MSCI EAFE Small Cap (international developed small-company stocks), MSCI Emerging Markets (international emerging market stocks), S&P United States REIT (US REITs), S&P Global Ex US REIT (international REITs), Morningstar MLP Composite (master limited partnerships), Barclays US Treasury 3-7 Yr (treasuries), Barclays US Aggregate Bond (core bonds), Barclays US Corporate Investment Grade (US investment grade corporate bonds), Barclays US Securitized (US securitized bonds), Barclays US Treasury US TIPS (US inflation-protected bonds), Barclays VLI High Yield (US corporate high yield), Barclays Gbl Agg Ex (international developed country bonds), Barclays EM USD Aggregate (international emerging markets bonds), Barclays USFRN (bank loans and other floating-rate notes), BofAML Preferred Stock Fixed Rate (preferred stocks), S&P GSCI Precious Metal (gold and other precious metals) and Barclays US Treasury Bill 1-3 Month (cash).

(0117-SJC8)


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