In Depth

Introduction to the PIMCO Target-Date Glide Path: 2012 Update and Review

Since most participants will likely depend on their defined contribution plan as a primary source of retirement income, it is critical to structure the glide path – which determines asset allocations over time – to maximize their chance of success.

To better meet the real, or inflation-adjusted, retirement income needs of defined contribution (DC) plan participants, PIMCO uses a real liability-driven and forward-looking methodology in constructing its glide path. Since most participants will likely depend on the DC plan as a primary source of retirement income, it is critical to structure the glide path – which determines asset allocations over time – to maximize the chance of success for participants. With this goal in mind, PIMCO created the methodology for the structure of our glide path, which we review and update on an annual basis.

For target-date strategies, PIMCO defines success as delivering a level of wealth that can provide adequate, real income replacement in retirement. PIMCO believes this goal should be measured not as an average result, but rather across the full distribution of possible outcomes. The ideal glide path should therefore be designed with the goal of achieving:

  • An acceptable median real outcome,
  • A tight distribution of income replacement outcomes, and
  • Fewer very low outcomes.

We engineered the asset allocation approach in our glide path using three frameworks: real return liability-driven investment, total risk management and return optimization through risk factor diversification. The result is a glide path structure designed to offer plan sponsors the potential to increase median expected real income replacement, improve the consistency of outcomes and minimize the chance of participants falling short of an acceptable income replacement level. Importantly, we believe that success should be achievable regardless of the economic environment.

Key points:
Our approach results in an asset allocation that is different than the typical target date approach. Specifically, our glide path:

  • Has a more diversified equity allocation, with a greater focus on emerging markets
  • Has a more meaningful allocation to real assets, including commodities, real estate and TIPS, with an average allocation of about 33% vs. the market average allocation of around 5%
  • Includes meaningful allocations across a broader set of assets including long-term U.S. Treasuries, global bonds, emerging markets fixed income, high yield and emerging markets equity

The impact of these differences includes:

  • A median outcome on par with the market average glide path and above our target threshold of 50% real income replacement
  • A lower level of total risk, with a maximum estimated loss1 at retirement nearly half that of the market average glide path
  • Stronger estimated performance across a variety of market environments, with fewer very low outcomes – Median income replacement rate 10% above the market average in turbulent environments and 7% above the market average in inflationary environments

We now turn to a discussion of the methodology that drives these results.

 

1 Maximum loss defined as 95% Value at Risk

Addressing Inflation Through Real Return Liability-Driven Investment (LDI)
We centered our glide path development first on understanding the nature of people’s future spending needs. While no one can know precisely what any one person will need to spend in retirement, it is clear an individual’s future spending needs generally rise as the prices of goods and services rise: The financial liability is inflation-linked. Thus, the ideal investments to offset people’s spending needs would also be inflation-linked.

Therefore, we believe an LDI framework is critical to making the glide path’s asset allocation approach more efficient in delivering incremental return per unit of risk. We define risk as the probability and magnitude of failing to meet a minimally acceptable real replacement income level, which we define in turn as 50% of final year salary using a real annuity as the basis for this measurement. Our 50% threshold assumes that most plan participants must rely upon their DC plan assets to replace a meaningful percentage of their final pay, with Social Security and defined benefit plans providing supplemental but not necessarily sufficient income for retirement. Therefore, our glide path focuses on helping a median worker in terms of pay, wage increases and savings rates both successfully reach retirement with sufficient savings and maintain his or her lifestyle throughout retirement.

Using an LDI framework, we identified U.S. Treasury Inflation-Protected Securities (TIPS) – not cash – as a DC participant’s hypothetical “risk-free” asset. TIPS are the only U.S. government-backed instruments that offer a rate of return contractually linked to inflation, which can help offset inflation risk, as well as possibly provide incremental yield and thus, may modestly increase purchasing power. 

In theory, if a person had enough money in today’s dollars to pay for all the goods and services he would need in retirement, he could invest the money in a laddered portfolio of zero coupon TIPS. Assuming no government default, this approach would precisely hedge inflation risk and provide a modest gain in future purchasing power, equal to the real yield on the TIPS in the ladder. Unfortunately, ultra-long duration zero coupon TIPS do not exist. Even if they did exist, the high contribution rates required for such a strategy would likely be beyond most participants’ means.

However, given the relatively low real return of TIPS, it is important to view TIPS not as the sole asset, but rather as a core asset – one that should be complemented with potentially higher return assets that have links to inflation in an effort to increase the long-term real return potential of the glide path. Equities should be among these higher return assets because they are an important driver of long-term portfolio returns. However, they also add volatility, especially in light of their inflation-adjusted returns. So it is important to consider other liquid, high risk, potentially higher return asset classes with an implicit link to inflation, namely, commodities and real estate investment trusts (REITs). These assets may not only improve the inflation fighting power of the portfolio, but also further improve the diversification of the asset allocation mix in the glide path.

Assessing Risk Across the Glide Path
Building on our real return LDI framework, we next established a risk management framework to determine the risk budget, or what we believe to be the appropriate level of risk, across the glide path.

We first defined the maximum potential drawdown, or investment loss, that a participant could withstand based on estimates of age-appropriate capacity for loss. While there is no rule book for estimating an individual investor’s capacity for loss, we applied a common-sense approach. First, we surveyed investment consultants to understand what they view to be the maximum loss that a participant can sustain at each age and still meet his or her income goal.

In PIMCO’s 2012 Defined Contribution Consulting Support and Trends Survey, we asked 39 consulting firms what they believe is the loss capacity for DC plan participants at various ages. The majority responses for each age are presented below. 

Second, by analyzing the relationship between single year shocks along the glide path and the resulting change in final year asset balances, we estimated the maximum drawdown that a participant can sustain across each vintage of the glide path and still be on pace to meet their target income replacement threshold. While there is no industry standard for computing maximum potential loss on a portfolio, we applied a host of risk metrics, as well as our proprietary risk analytics, to “stress test” potential portfolios; for example, we looked at value-at-risk, conditional value-at-risk, volatility, portfolio equity beta, and the probability of outcomes below 0%, -10% and -20%. The results of this iterative process, combining the external market perspective from the consultants with our internal quantitative analysis, were total risk budgets, or the capacity for loss, along the entire glide path.

Working to Maximize Returns through Risk Factor Diversification
Our final step was to maximize return potential along the glide path with our risk budget. In general, we favor portfolio construction based on risk factor diversification rather than asset class diversification. PIMCO has found that during periods of market stress, seemingly different assets tend to be highly correlated. Simply diversifying across asset classes therefore often results in portfolios that appear diversified, but have concentrated risks. We have developed what we believe is a more efficient allocation approach that looks beyond asset class labels and focuses instead on the common underlying risks that many assets share, such as equity, bond, currency, momentum, etc. Once we identify the risk factors that are likely to produce future returns, we then assess which combination of asset classes we believe provides the most efficient exposure to those risk factors.

Our risk factor optimization is designed to produce well-diversified portfolios. Starting with a core allocation to TIPS, we build portfolios along the glide path that represent a diversified set of risk factors, tailored to a participant’s risk capacity. For example, when a participant has the greatest amount of time prior to retirement, say 25 to 40 years, the optimal asset allocation includes a heavy allocation to higher return potential assets like equities, commodities and REITs. We believe when participants are younger, they have the ability to tolerate a higher risk level; moreover, account balances in the early years are usually smaller, so there is not as much at stake. On the other hand, for those participants closer to retirement, say within 20 years, risk is dialed down with more weight to TIPS, nominal bonds and cash. This is consistent with our view that older participants no longer have the ability to tolerate a high level of market risk because they are likely to have more at stake and not enough time to recover from a severe market shock.

It is worth noting that our approach is not driven by a traditional mean-variance optimization. While we do use a constrained mean-variance analysis as an input to guide our allocation, the optimization uses a block bootstrap1 simulation rather than a normal distribution and allocates the portfolio based on risk factors rather than solely by asset classes. Despite these expansions beyond traditional mean-variance analysis, there are several reasons why this type of optimization analysis is not the primary driver of our glide path allocations. First, it may be deficient over long-term horizons; we believe claiming any certainty regarding risk and return estimates over 40 years would have required a high degree of hubris on our part. In addition, a key input to the mean-variance approach is the covariance matrix of asset classes, which, we have observed, is inherently unstable over time. Finally, when we did run mean-variance optimization on the glide path, it resulted in “corner solutions,” or portfolios with high concentrations in a single asset, and this did not align with our objective of risk diversification.

1Bootstrapping is a procedure by which new samples are generated from an original data set by randomly selecting observations from the original data set. “Block” bootstrapping in particular uses contiguous blocks of data.

The table shows some important risk measures (as of 31 December 2012) for a set of hypothetical portfolios using our glide path (see the appendix for asset allocation tables).

The PIMCO Glide Path: Results
The PIMCO Glide Path embraces a broad set of asset classes, aggressively dials down risk as it approaches the target date and utilizes a full toolkit of real assets, including TIPS, commodities and REITs. Figure 1 shows our glide path based on the asset allocation market value percentages. Furthermore, in the Appendix we have provided this same data in pie chart form along with the breakdown of risk allocations. (Note that we rounded the optimized allocations to the nearest 5% so that we did not convey false precision of the allocations in our glide path.)

How does PIMCO’s Glide Path compare with others? Based on an analysis of the risk and return characteristics of the PIMCO Glide Path and the market average glide path (based on 25 to 30 glide paths currently in the market as reported by MarketGlide), we believe our approach is a differentiated solution for the DC market.

In our analysis, we investigated the distribution of outcomes for three different economic scenarios:

  • “Normal”- a period characterized by risk and returns that are proportionally aligned (e.g., higher risk means higher return); the 1980s and 1990s are good examples.
  • Turbulent - a period when volatility, as measured by the VIX, exceeds 20%. The last decade is a good example.
  • Inflationary - a period in which the annualized monthly change in the Consumer Price Index (CPI NSA-U) exceeds 3%; similar to the experience in the 1970s.

Our analysis spanned the full 40-year periods over each glide path. Conditions during the first 30 years of each analysis were consistent, while the final 10 years were subjected to the three economic scenarios. The outcomes are illustrated below. In each case, the PIMCO Glide Path provides a comparable, or in some cases improved median income replacement outcome, a tighter distribution of income replacement outcomes and fewer extremely low income replacement outcomes.

Summary and Conclusions
PIMCO set out to reengineer target-date strategies by constructing a new glide path for the DC market. Starting with a “blank sheet,” we first embraced a real return LDI framework. Then we defined what we believe to be the appropriate level of total risk, or maximum potential for loss, along the entire glide path. Finally, using this risk budget, we endeavored to construct efficient return-maximizing portfolios based on risk factor diversification.

The result of our efforts, the PIMCO Glide Path, seeks to provide several advantages over other glide paths:

  • Comparable, or in some cases improved, median real income replacement outcome;
  • Tighter distribution of real income replacement outcomes; and
  • Fewer extremely low income replacement outcomes.

PIMCO has launched a suite of target-date strategies based on this glide path methodology. The PIMCO RealRetirement Strategies provide DC plans with a next generation solution for target-date strategies.

Please contact your PIMCO representative for further information.

2012 Glide Path Review
PIMCO reviews its glide path allocations on an annual basis in light of the firm’s secular outlook. The 2012 review analyzed the potential inclusion of additional asset classes, including absolute return strategies, global inflation-linked bonds, emerging market (EM) corporate bonds, and gold. Our analysis revealed that these additions would not provide benefits significant enough to justify modifications to the glide path in 2013. Instead, in all cases, we concluded that the proposed asset classes could be incorporated into the strategy on a tactical basis as needed. We continue to believe the glide path, with its current allocations, offers a strong focus on real assets, risk factor diversification and total risk management in light of long-term market trends and the firm’s outlook. As a reference, the 2011 glide path review resulted in adding global, high yield and emerging market bonds in an effort to provide increased risk factor diversification. Additionally, the EM currency exposure stemming from EM local bonds may incorporate indirect inflation hedging into the glide path, which is consistent with our secular outlook for inflationary pressures building in the global economy.

We extend our sincere appreciation to the following PIMCO experts who kindly contributed to the content of this paper:

John Cavalieri
Asset Allocation Product Manager 

Bob Greer
Real Return Product Manager

John Miller, CFA
Head, U.S. Retirement

Stacy Schaus, CFP®
DC Practice Leader

APPENDIX
Index Descriptions
Barclays Long-Term Treasury consists of U.S. Treasury issues with maturities of 10 or more years. Prior to November 1, 2008, this index was published by Lehman Brothers.

The Barclays U.S. Aggregate Index represents securities that are SEC-registered, taxable, and dollar denominated. The index covers the U.S. investment grade fixed rate bond market, with index components for government and corporate securities, mortgage pass-through securities, and asset-backed securities. These major sectors are subdivided into more specific indices that are calculated and reported on a regular basis.

The Barclays U.S. TIPS Index is an unmanaged market index comprised of all U.S. Treasury Inflation Protected Securities rated investment grade (Baa3 or better), have at least one year to final maturity, and at least $250 million par amount outstanding. Performance zdata for this index prior to 10/97 represents returns of the Lehman Inflation Notes Index.

Barclays U.S. Treasury Inflation Notes: 10+ Year is an unmanaged index market comprised of U.S. Treasury Inflation Protected securities with maturities of over 10 years.

The BofA Merrill Lynch U.S. 3-Month Treasury Bill Index is comprised of a single issue purchased at the beginning of the month and held for a full month. At the end of the month that issue issold and rolled into a newly selected issue. The issue selected at each month-end rebalancing is the outstanding Treasury Bill that matures closest to, but not beyond, three months from the rebalancing date. To qualify for selection, an issue must have settled on or before the month-end rebalancing date. While the index will often hold the Treasury Bill issued at the most recent 3-month auction, it is also possible for a seasoned 6-month Bill to be selected.

BofA Merrill Lynch U.S. High Yield, BB-B Rated, Constrained Index tracks the performance of BB-B Rated U.S. dollar-denominated corporate bonds publicly issued in the U.S. domestic market. Qualifying bonds are capitalization-weighted provided the total allocation to an individual issuer (defined by Bloomberg tickers) does not exceed 2%. Issuers that exceed the limit are reduced to 2% and the face value of each of their bonds is adjusted on a pro-rata basis. Similarly, the face value of bonds of all other issuers that fall below the 2% cap are increased on a pro-rata basis.

The Consumer Price Index (CPI) is an unmanaged index representing the rate of inflation of the U.S. consumer prices as determined by the U.S. Department of Labor Statistics.  There can be no guarantee that the CPI or other indexes will reflect the exact level of inflation at any given time.

The Dow Jones UBS Commodity Total Return Index is an unmanaged index composed of futures contracts on 19 physical commodities. The index is designed to be a highly liquid and diversified benchmark for commodities as an asset class. Prior to May 7, 2009, this index was known as the Dow Jones AIG Commodity Total Return Index.

The Dow Jones U.S. Select Real Estate Investment Trust (REIT) Total Return Index, a subset of the Dow Jones U.S. Select Real Estate Securities Total Return Index, is an unmanaged index comprised of U.S. publicly traded Real Estate Investment Trusts. This index was formerly known as the Dow Jones Wilshire REIT Index.

JPMorgan GBI Global Hedged in USD is an unmanaged index market representative of the total return performance in U.S. dollars on a hedged basis of major world bond markets.

JPMorgan Government Bond Index-Emerging Markets Global Diversified Index (Unhedged) is a comprehensive global local emerging markets index, and consists of regularly traded, liquid fixed-rate, domestic currency government bonds to which international investors can gain exposure.

The Morgan Stanley Capital International (MSCI) Emerging Markets Index is an unmanaged index that measures equity market performance in the global emerging markets. As of May 2005, the Emerging Markets Index (float-adjusted market capitalization index) consisted of indices in 26 emerging countries: Argentina, Brazil, Chile, China, Colombia, Czech Republic, Egypt, Hungary, India, Indonesia, Israel, Jordan, Korea, Malaysia, Mexico, Morocco, Pakistan, Peru, Philippines, Poland, Russia, South Africa, Taiwan, Thailand, Turkey, and Venezuela.

The MSCI EAFE (Morgan Stanley Capital International Europe, Australasia, Far East Index) is an unmanaged index of over 900 companies, and is a generally accepted benchmark for major overseas markets.  Index weightings represent the relative capitalizations of the major overseas markets included in the index on a U.S. dollar adjusted basis.

The Russell 2000 Index is an unmanaged index generally representative of the 2,000 smallest companies in the Russell 3000 Index, which represents approximately 10% of the total market capitalization of the Russell 3000 Index. 

The S&P 500 Index is an unmanaged market index generally considered representative of the stock market as a whole. The index focuses on the Large-Cap segment of the U.S. equities market.

VIX, the ticker symbol for the Chicago Board Options Exchange (CBOE) Volatility Index, shows the market’s expectation of 30-day volatility. It is constructed using the implied volatilities of a wide range of S&P 500 index options. This volatility is meant to be forward looking and is calculated from both calls and puts. The VIX is a widely used measure of market risk and is often referred to as the “investor fear gauge.”

It is not possible to invest directly in an unmanaged index.

The Authors

Bransby Whitton

Product Manager, Real Return

Ying Gao

Account Manager, Defined Contribution

Justin Blesy

Product Manager, Asset Allocation

Disclosures

Past performance is not a guarantee or a reliable indicator of future results. All investments contain risk and may lose value.  Investing in the bond market is subject to certain risks including market, interest-rate, issuer, credit, and inflation risk; investments may be worth more or less than the original cost when redeemed. Investing in foreign denominated and/or domiciled securities may involve heightened risk due to currency fluctuations, and economic and political risks, which may be enhanced in emerging markets. Inflation-linked bonds (ILBs) issued by a government are fixed-income securities whose principal value is periodically adjusted according to the rate of inflation; ILBs decline in value when real interest rates rise. Treasury Inflation-Protected Securities (TIPS) are ILBs issued by the U.S. Government. Commodities contain heightened risk including market, political, regulatory, and natural conditions, and may not be suitable for all investors. Equities may decline in value due to both real and perceived general market, economic, and industry conditions. High-yield, lower-rated, securities involve greater risk than higher-rated securities; portfolios that invest in them may be subject to greater levels of credit and liquidity risk than portfolios that do not. Commodities contain heightened risk including market, political, regulatory and natural conditions, and may not be suitable for all investors. REITs are subject to risk, such as poor performance by the manager, adverse changes to tax laws or failure to qualify for tax-free pass-through of income. Derivatives and commodity-linked derivatives may involve certain costs and risks such as liquidity, interest rate, market, credit, management and the risk that a position could not be closed when most advantageous. Commodity-linked derivative instruments may involve additional costs and risks such as changes in commodity index volatility or factors affecting a particular industry or commodity, such as drought, floods, weather, livestock disease, embargoes, tariffs and international economic, political and regulatory developments. Investing in derivatives could lose more than the amount invested. 

No representation is being made that any account, product, or strategy will or is likely to achieve profits, losses, or results similar to those shown.  Hypothetical or simulated performance results have several inherent limitations.  Unlike an actual performance record, simulated results do not represent actual performance and are generally prepared with the benefit of hindsight. There are frequently sharp differences between simulated performance results and the actual results subsequently achieved by any particular account, product, or strategy.  In addition, since trades have not actually been executed, simulated results cannot account for the impact of certain market risks such as lack of liquidity. There are numerous other factors related to the markets in general or the implementation of any specific investment strategy, which cannot be fully accounted for in the preparation of simulated results and all of which can adversely affect actual results. There is no guarantee that these investment strategies will work under all market conditions or are suitable for all investors and each investor should evaluate their ability to invest long-term, especially during periods of downturn in the market. No representation is being made that any account, product, or strategy will or is likely to achieve profits, losses, or results similar to those shown. The correlation of various indices or securities against one another or against inflation is based upon data over a certain time period.  These correlations may vary substantially in the future or over different time periods that can result in greater volatility.

Glide Path is the asset allocation within a Target Date Strategy (also known as a Lifecycle or Target Maturity strategy) that adjusts over time as the participant’s age increases and their time horizon to retirement shortens. The basis of the Glide Path is to reduce the portfolio risk as the participant’s time horizon decreases. Typically, younger participants with a longer time horizon to retirement have sufficient time to recover from market losses, their investment risk level is higher, and they are able to make larger contributions (depending on various factors such as salary, savings, account balance, etc). Generally, older participants and eligible retirees have shorter time horizon to retirement and their investment risk level declines as preserving income wealth becomes more important.

Forecasts, estimates, and certain information contained herein are based upon proprietary research and should not be interpreted as investment advice, as an offer or solicitation, nor as the purchase or sale of any financial instrument. Forecasts and estimates have certain inherent limitations, and unlike an actual performance record, do not reflect actual trading, liquidity constraints, fees, and/or other costs. In addition, references to future results should not be construed as an estimate or promise of results that a client portfolio may achieve.

The portfolio analysis is based on model portfolios consisting of index blends. No representation is being made that the structure of the average portfolio or any account will remain the same or that similar returns will be achieved. Results shown may not be attained and should not be construed as the only possibilities that exist. Different weightings in the asset allocation illustration will produce different results. Actual results will vary and are subject to change with market conditions. There is no guarantee that results will be achieved. No fees or expenses were included in the estimated results and distribution. The scenarios assume a set of assumptions that may, individually or collectively, not develop over time. The analysis reflected in this information is based upon data at time of analysis. Forecasts, estimates, and certain information contained herein are based upon proprietary research and should not be considered as investment advice or a recommendation of any particular security, strategy or investment product.

PIMCO routinely reviews, modifies, and adds risk factors to its proprietary models. Due to the dynamic nature of factors affecting markets, there is no guarantee that simulations will capture all relevant risk factors or that the implementation of any resulting solutions will protect against loss. All investments contain risk and may lose value. Simulated risk analysis contains inherent limitations and is generally prepared with the benefit of hindsight. Realized losses may be larger than predicted by a given model due to additional factors that cannot be accurately forecasted or incorporated into a model based on historical or assumed data.

We employed a block bootstrap methodology to calculate volatilities. We start by computing historical factor returns that underlie each asset class proxy from January 1997 through the present date. We then draw a set of 12 monthly returns within the dataset to come up with an annual return number. This process is repeated 15,000 times to have a return series with 15,000 annualized returns. The standard deviation of these annual returns is used to model the volatility for each factor. We then use the same return series for each factor to compute covariance between factors. Finally, volatility of each asset class proxy is calculated as the sum of variances and covariance of factors that underlie that particular proxy.

Value at Risk (VAR) estimates the risk of loss of an investment or portfolio over a given time period under normal market conditions in terms of a specific percentile threshold of loss (i.e., for a given threshold of X%, under the specific modeling assumptions used, the portfolio will incur a loss in excess of the VAR X percent of the time.  Different VAR calculation methodologies may be used.  VAR models can help understand what future return or loss profiles might be.  However, the effectiveness of a VAR calculation is in fact constrained by its limited assumptions (for example, assumptions may involve, among other things, probability distributions, historical return modeling, factor selection, risk factor correlation, simulation methodologies).  It is important that investors understand the nature of these limitations when relying upon VAR analyses. Stress testing involves asset or portfolio modeling techniques that attempt to simulate possible performance outcomes using historical data and/or hypothetical performance modeling events.  These methodologies can include among other things, use of historical data modeling, various factor or market change assumptions, different valuation models and subjective judgments.

This material contains the opinions of the authors but not necessarily those of PIMCO and such opinions are subject to change without notice. This material has been distributed for informational purposes only and should not be considered as investment advice or a recommendation of any particular security, strategy or investment product. Information contained herein has been obtained from sources believed to be reliable, but not guaranteed. No part of this material may be reproduced in any form, or referred to in any other publication, without express written permission. PIMCO and YOUR GLOBAL INVESTMENT AUTHORITY are trademarks or registered trademarks of Allianz Asset Management of America L.P. and Pacific Investment Management Company LLC, respectively, in the United States and throughout the world. ©2013, PIMCO.