THE JOURNAL OF INDEX INVESTING Influencing … · SUMMER 2016 THE JOURNAL OF INDEX INVESTING Transparency Transparency is a defining attribute of smart beta strategies, which follow

THE JOURNAL OF

ETFs, ETPs & IndexingSUMMER 2016 VOLUME 7 NUMBER 1 | www.IIJII.com

THE JOURNAL OF INDEX INVESTING ETFS | ETPS | INDEXINGS

UM

ME

R 2

016

VO

LU

ME

7 N

UM

BE

R 1

Thought Leading Sponsor

The Voices of Influence | iijournals.com

Influencing Retirement Saving: Smart Beta in Defined Contribution Default OptionsMANUELA SPERANDEO, MARCO CORSI, AND SARA SHORES

THE JOURNAL OF INDEX INVESTING SUMMER 2016

MANUELA SPERANDEO

is a director at BlackRock in London, [email protected]

MARCO CORSI

is a director at BlackRock in London, [email protected]

SARA SHORES

is a managing director at BlackRock in San Francisco, [email protected]

Influencing Retirement Saving: Smart Beta in Defined Contribution Default OptionsMANUELA SPERANDEO, MARCO CORSI, AND SARA SHORES

Concerns over the adequacy of lifetime retirement income are, more than ever before, a global phenomenon. Issues around par-

ticipants’ engagement and retirement secu-rity seem to be present across countries with different macroeconomic and cultural back-grounds as well as savings and social security setups. The traditional focus on f iduciary responsibilities, such as selecting managers and monitoring fees, has been expanded to cover such areas as participant usage and successful outcome, which are now some of the main areas of interest for industry practitioners. Prevailing academic research on the topic is grounded in the concept of the experiential learning cycle, namely that people learn from experience (see Goby and Lewis [2000]). The question then becomes how to improve participants’ experience within existing defined contribution (DC) plans to encourage them to save more and save regularly. In this article, we take a look at some of the features of smart beta strate-gies (i.e., passively managed portfolios that move away from market-capitalization-weighted indexes) that make these strategies an interesting potential tool for DC plans. We then test this idea by using existing smart beta indexes in the context of a traditional lifestyle fund, where market-cap indexes are replaced with smart beta indexes on pre-defined allocations.

THE POTENTIAL BENEFITS OF SMART BETA INVESTING

By the term “smart beta,” we refer to the benchmark version of factor strategies that aim to capture broad persistent drivers of return, generally long only and usually implemented within an asset class. One of the fastest growing segments in the finan-cial industry globally, smart beta has been embraced by institutional and retail investors in recent years and has been at the center of product development in index investing. If we look at exchange-traded products (ETPs), for example, f lows in the category were in the region of USD 29.6 billion for 2015 alone, totaling 12% of total equity ETP f lows and bringing assets under management (AUM) in smart beta strategies to USD 246 billion as of December 2015 (see Exhibit 1).1 We estimate that the number of providers active in the space also rose, from 54 at the end of 2012 to 59 in 2013, 80 in 2014, and 92 as of the end of 2015.2 As such, looking more closely at the popularity of different strategies delivered via ETPs, while dividend-weighted exchange-traded funds (ETFs) continue to represent the largest portion of the AUM, minimum volatility and multifactor strategies have been growing at the fastest rate in terms of new assets. Far smaller in terms of adop-tion has been smart beta in f ixed income, an area where many think new approaches

JII-Sperandeo.indd 25 17/05/16 2:38 pm

INFLUENCING RETIREMENT SAVING: SMART BETA IN DEFINED CONTRIBUTION DEFAULT OPTIONS SUMMER 2016

to passive investing could help to address several of the shortcomings of traditional benchmark indexes (see Staal et al. [2015]).

The investment community’s increasing interest in smart beta is due to many of the benefits that it can potentially deliver, among which we would highlight improved portfolio outcomes, transparency and fee reduction. In the following, we explore the details of each of these features and the reasons we think they are particularly relevant in the context of DC plans.

Improved Portfolio Outcomes

With their aim to capture broad, persistent drivers of return, smart beta strategies have the potential to reward investors with returns in excess of traditional index-based investments over the long run. This approach may thus be quite sensible in the context of the accumulation phase of a DC plan, where the time horizon is naturally longer and the potential ability to generate outperformance may

encourage increased participation. In Exhibit 2, we look at several equity smart beta strategies as represented by a range of MSCI indexes and compare their simulated risk and return profile with a standard benchmark (i.e., the MSCI World Index). The exhibit illustrates how return-seeking factors, such as value, quality, small size, and momentum, on a stand-alone basis or in a multi-factor portfolio, have the potential to deliver incremental returns. Minimum volatility strategies, meanwhile, have the potential to mitigate the effects of volatile equity markets and cushion market drawdowns. Together with performance concerns, low appetite for volatility is indeed a key consideration when it comes to retirement plan-ning, and diversified solutions across all factor dimen-sions (such as a combination of multifactor and minimum volatility strategies) have the potential to address both of these behavioral attitudes. Smart beta strategies could thus potentially help achieve the goals of the different stages of the retirement journey and help in addressing risk–return trade-offs across different risk profiles.

E X H I B I T 1Global Smart Beta ETP Assets: $246 billion as of December 2015

Source: BlackRock Global Business Intelligence, SimFund. ETP f lows as of 12/31/2015. As of the end of Dec-2015. AUM for the categories are measured in USD. Figures in brackets represent the compounded annual growth rate (CAGR) of the assets since the end of 2011.



Transparency

Transparency is a defining attribute of smart beta strategies, which follow preset rules within the relevant indexes to determine the process for security selection, portfolio construction, and rebalancing. These rules are often published by a third-party provider and made avail-able to investors. Several research projects into consumer attitudes of long-term saving behaviors show that an infor-mation asymmetry between providers and participants exist and contribute to a sense of fear and suspicion (see National Employment Savings Trust Report [2014]). The ability to deliver a high level of transparency on the exposures provided is a move in the right direction, meaning plan participants can potentially feel more connected to their retirement savings when they get a better understanding of the exposures included in their investment portfolio and how this is likely to perform in different market environ-ments. Although information will not necessarily boost understanding, the increased transparency around how a

strategy is built and may perform in various market regimes can enable providers to improve their communication around potential DC plan outcomes.

Fee Reduction

After-fee performance and weighted portfolio cost continue to drive investment decisions in the DC space, with charge caps now a reality across several jurisdictions. For example, the U.K. government announced a package of changes including a 0.75% charge cap that would apply to all default funds of DC plans used for auto-enrollment from April 2015 (see Department for Work & Pensions [2015]). Introducing a cap on pension charges and abol-ishing active participant discounts (AMDs) have been important steps toward simpler and more transparent pen-sion plans and demonstrate an effort toward rebuilding trust in pensions as a long-term savings tool.

Smart beta strategies seek to provide investors with enhanced risk-adjusted returns, typically at a

E X H I B I T 2MSCI World Index and Smart Beta Simulated Annualized Risk and Returns (September 30, 2005–September 30, 2015)

Note: The above data refers to backtested performance, which is not a reliable indicator of future performance.

Sources: Blackrock, MSCI as of the end of September 2015. Based on USD denominated net total return indexes. Indexes Data for the time periods prior to the index inception date (Min Vol:MSCI World Minimum Volatility Index NR USD was launched on Apr. 14, 2008; Momentum: MSCI World Momentum Index NR USD was launched on Dec. 11, 2013; Low Size: MSCI World Mid Cap Equal Weighted Index NR USD was launched on Jul. 25, 2014; Value: MSCI World Enhanced Value Index NR USD and Quality: MSCI World Sector Neutral Quality Index NR USD were both launched on Aug. 11, 2014, Multifactor: MSCI World Diversified Multiple-Factor Index NR USD was launched on Sep. 4, 2015) is hypothetical back-tested data. The MSCI World Index was launched on Mar. 31, 1986.



lower cost than active strategies, while still retaining many of the benefits of investing in traditional index funds. Generally speaking, the cost of smart beta strat-egies lies between traditional index and active funds. Simply by looking at ETPs tracking smart beta indexes, 45% of the approximately 800 smart beta ETPs globally have expense ratios below 50 basis points (bps), with an average asset-weighted total expense ratio (TER) of 36 bps (see BlackRock [2015]).

IMPLEMENTING SMART BETA IN A TARGET DATE FUND

Modeling Assumptions

For the purposes of this section, we have used avail-able smart beta index data applied to various asset classes and regions (namely, developed and emerging market equities and commodities) and looked at implementing these in the context of a traditional glidepath (see Exhibit 3) both in the accumulation phase (i.e., when plan participants build up their savings for retirement) and the decumulation phase (i.e., the period during which accumulated assets are drawn upon to fund retirement or other income requirements). No explicit assumption is made on the appropriate level of risk at retirement or

on the range of asset classes that should be included. Such asset allocations are used as a proof of concept to assess, based on historical backtested simulation, the potential benefits of replacing, like for like, traditional benchmark exposures with smart beta alternatives.

We begin by building a hypothetical portfolio that replicates the broad asset allocation via tradi-tional market-capitalization-weighted indexes (“Proxy Portfolio” in the exhibits). The indexes used for the port-folio construction are all denominated in U.S. dollars (with no currency hedge) and are listed in Exhibit 4. The portfolio rebalances on an annual basis and no man-agement fees or other charges have been incorporated into the analysis. A second portfolio (“Smart Beta Port-folio” in the exhibits) is then constructed by replacing each building block with a smart beta index equivalent, whenever available: see Exhibit 5. In particular,

• The MSCI Daily TR Net World USD Index (i.e., world developed equity exposure) is being replaced by the MSCI World Minimum Volatility Index, the MSCI World Diversif ied Multiple-Factor Index, or a blend of the two indexes, where the percentage allocation to each one will depend on the number of years to retirement. As previously mentioned, the different potential outcomes of the

E X H I B I T 3Asset Allocation of a Theoretical Multi-Asset Target Date Fund

Notes: For illustrative purposes only. The allocations are based on a generic target date fund, which aims to ref lect changing investment needs by gradually altering the asset allocation as participants near their target retirement date. The allocation is designed to glide toward a split of approximately 40% global equities and 60% fixed income.



two smart beta strategies, as represented by these indexes, can make them more relevant for different stages of the retirement journey. While at the beginning of the accumulation phase, diversified exposure to return-seeking factors could deliver outperformance, increasing exposure to a min-imum volatility strategy can potentially help lower total risk while retaining equity market exposure as participants approach retirement. In practice,

we explore a weighting scheme that allocates the full equity exposure to the multifactor smart beta indexes for the period ranging from the inception of the hypothetical portfolio until 17 years prior to the end of the accumulation phase. At that point, the equity allocation gradually shifts from the mul-tifactor index into the minimum volatility one that will end up bearing the full equity exposure at the beginning of the decumulation period.

E X H I B I T 4Proxy Portfolio (January 1999 to February 2016)

Sources: BlackRock and Bloomberg.

E X H I B I T 5Smart Beta Portfolio (January 1999 to February 2016)

Sources: BlackRock and Bloomberg. Data for the time periods prior to the index inception date (MSCI World Minimum Volatility Index NR USD and MSCI Emerging Markets Minimum Volatility Index NR USD were launched on Apr. 14, 2008; MSCI World Diversified Multiple-Factor Index NR USD and MSCI Emerging Markets Diversified Multiple-Factor Index NR USD were launched on Sep. 4, 2015; Bloomberg Commodity 3 Month Forward TR Index was launched on July 14, 1998) are hypothetical backtested data.



• Similarly, the MSCI Emerging Markets IMI Index (i.e., emerging market equity exposure) is replaced by the MSCI Emerging Markets Minimum Vola-tility Index, the MSCI Emerging Markets Diver-sif ied Multiple-Factor Index, or a blend of the two indexes, where the percentage allocation to each one will depend on the number of years to retirement.

• Looking through to the decumulation phase, a fixed allocation to equities is assumed, and within such an allocation, a full allocation to minimum volatility indexes is implemented. This is based upon the argument that constant equity alloca-tion should be kept through retirement, when human capital is depleted and, with it, the ability to take considerable risks. This is particularly true in light of current trends, such as a longer lifespan and subsequent longer post-retirement planning horizon. However, reducing the equity allocation following retirement could leave plan participants poorly positioned, in particular after a market cor-rection, limiting their ability to capture a market rebound (see Daverman and O’Hara [2014]). Min-imum volatility strategies, with their aim to pro-vide exposure to equity market returns but with lower downside risk, can represent a viable way to implement such post-retirement fixed equity allocation.

• The dynamic nature of the allocation between minimum volatility (Min Vol) and diversif ied multifactor indexes (DMF) included in the equity exposure is illustrated in Exhibit 6.

• It is important to note that according to the MSCI methodology (see the MSCI Global Minimum Volatility Indexes Methodology as of January 2012 and MSCI Diversified Multi-Factor Indexes Methodology as of February 2015)3 both indexes are designed to limit sector and country exposures within a 5% band of the cap-weighted index and therefore retain the same broad market characteristics as cap-weighted indexes with tilts toward desirable factors. This means that they can be incorporated in portfolios as replacement for the parent indexes without incurring excessive sector or country biases.

• The Bloomberg Commodity TR Index (i.e., the commodity exposure) is replaced by the Bloomberg Commodity 3 Month Forward TR Index. This modif ied version of the standard benchmark is constructed by investing on the third month deferred forward derivative contract rather than on the front of the curve, in order to reduce the potential for negative roll yield (see the 2016 Bloomberg Commodity Index Methodology).4

The available backtested data for the selected smart beta indexes cover a period of 17 years, from

E X H I B I T 6Equity Allocation Breakdown of the Back-Tested Smart Beta Portfolio

Note: For illustrative purposes only.



January 1999 to date. As this history is not long enough to cover the full life of a DC plan, we run our analysis under three different scenarios where the time spans are from 1999 to a date that corresponds to the first stage of the accumulation, the end phase of the accumulation, and the decumulation period, respectively. As shown in Exhibits 3 and 6, the allocation across the various asset classes and the smart beta replacements varies con-siderably for the three cases considered. For each sce-nario, we back test the hypothetical performance of the proxy portfolio and its smart beta replacement, using the relevant weighting scheme. To clarify, these scenarios are as follows:

• Case 1. First stage of the accumulation period: An individual joins the plan in January 1999 and has 45 years to retirement.

• Case 2. Last stage of the accumulation period: An individual joins the plan in January 1999 and has 17 years to retirement.

• Case 3. Decumulation period: An individual retired in January 1999 and remains invested in a f lat post-retirement glidepath, assuming an initial drawdown and ongoing income of 8% of the retire-ment savings. No inf lation protection is taken into account.

Although these scenarios represent a high level approximation of what these portfolios could have deliv-ered in the context of a DC investment, we feel they provide good insight into the value smart beta strategies could bring relative to more traditional market-cap benchmark exposures. In the following subsections, we look at the results of the portfolio simulations in each of these three cases.

Case 1—First Stage of the Accumulation Period

As Exhibits 7 and 8 illustrate, the inclusion of mul-tifactor strategies, as represented by the MSCI World Diversif ied Multi-Factor Index and by the MSCI Emerging Markets Diversif ied Multi-Factor Index, with their aims to outperform the market with a level of risk similar to that of the parent index, generate an interesting pick up in terms of annualized performance in excess of 3.0% annualized over the simulated 17 years

E X H I B I T 8 Backtested Smart Beta Portfolio vs. Proxy Portfolio (January 1999 to February 2016)


E X H I B I T 7Backtested Smart Beta Portfolio versus Proxy Portfolio (January 1999 to February 2016)




for comparable levels of risk. This enhancement in the performance lends itself well to the growth objective of the earlier stages of the accumulation period, when young plan participants can take more equity risk with their financial capital in order to capture as much poten-tial growth as possible early on. Long-term diversified exposure to equity style factors can help in achieving this objective.

Case 2—Last Stage of the Accumulation Period

As Exhibits 9 and 10 illustrate, the increasing allo-cation to minimum volatility strategies, as represented by the MSCI World Minimum Volatility Index and the MSCI Emerging Markets Minimum Volatility Index, with their aims to mitigate the effects of volatile equity

markets and cushion potential drawdowns, generates an interesting pick up in terms of risk-adjusted returns. At the same time, the allocation to a long-term diver-sif ied exposure to such equity style factors as value, size, quality, and momentum still contributes to incre-mental returns, even though it decreases as retirement approaches. The overall result is an improvement of the return-to-risk ratio from 0.54 to 0.87 over the simu-lated 17 years and a reduction in the drawdown by more than 3%, making it a smoother journey to participants’ landing point.

Case 3—Decumulation Period

The last simulation looks at the performance of a f ixed-weightings portfolio for which the equity allocation of 35% is fully invested in minimum volatility strategies to seek exposure to and lower the downside risk and volatility of equities that are often beyond the average risk tolerance of retirees. At the same time, these strategies allow the portfolios to retain equity exposure for potential growth while taking on less risk—helping deal with the quandary of participants who can’t take a large drawdown but still have many years of decumulation. As Exhibit 11 illustrates, the theoretical simulated backtested decumulation portfolio reaches at the end of the 17 years a value that is, in percentage terms, almost double what the traditional Proxy Portfolio would have delivered.

E X H I B I T 9Smart Beta Portfolio vs. Proxy Portfolio (January 1999 to February 2016)


E X H I B I T 1 0Smart Beta Portfolio vs. Proxy Portfolio (January 1999 to February 2016)




CONCLUSIONS

As we have highlighted in this article, DC plan participants face complex, dynamic, and multifaceted challenges in working toward their financial goals for retirement. Early in the accumulation phase, the main focus is on growth and ways to create and sustain it. Approaching retirement and after retirement, the main considerations tend to concentrate around the afford-able post-retirement income a participant’s savings can support. These challenges are top of the agenda for plan sponsors, consultants, and providers who are looking for ways to deliver better value to participants and poten-tially inf luence their behavior throughout their retire-ment journey. We think product innovation, including smart beta, can potentially be an effective next step in exploring new ways to deliver value to end participants.

ENDNOTES

1Note the following for all exhibits: Index returns are for illustrative purposes only and do not represent any actual investment. Index performance returns do not ref lect any management fees, transaction costs or expenses. Indexes are unmanaged and one cannot invest directly in an index. Past performance does not guarantee future results. Data for time periods prior to the index inception date are hypothetical and are provided for informational purposes only, to indicate historical performance had the index been available over the

relevant time period. Hypothetical data results are based on criteria applied retroactively with the benefit of hindsight and knowledge of factors that may have positively affected its performance, and cannot account for risk factors that may affect the actual investment performance. The actual performance of the investment may vary significantly from the hypothetical index performance due to transaction costs, liquidity or other market factors. Index methodology avail-able upon request.

2Source: BlackRock Global Business Intelligence, Sim-Fund. ETP f lows as of December 31, 2015.

3For the January 2012 MSCI Global Minimum Volatility Indexes Methodology, see https://www.msci.com/eqb/methodology/meth_docs/MSCI_Minimum_Volatility_Methodology_Jan12.pdf. For the February 2015 MSCI Diversif ied Multi-Factor Indexes Methodology, see https://www.msci.com/eqb/methodology/meth_docs/MSCI_Diversif ied_Multi-Factor_Indexes_Methodology_Feb15.pdf.

4For the 2016 Bloomberg Commodity Index Meth-odology, see www.bloombergindices.com/bloomberg-commodity-index-family/.

REFERENCES

“BlackRock Smart Beta Guide.” White paper, Black-Rock, December 2015. Available at https://www.blackrock.com/au/intermediaries/literature/whitepaper/blackrock-smart-beta-guide-en-au.pdf.


E X H I B I T 1 1 Smart Beta Portfolio Decumulation vs. Proxy Portfolio (January 1999 to February 2016)



Daverman, T., and M. O’Hara. “Reexamining ‘To versus Through’ New Research into an Old Debate.” White paper, BlackRock, May 2014. See https://www.blackrock.com/institutions/en-us/literature/whitepaper/to-versus-through-whitepaper.pdf.

Department for Work & Pensions. “The Charge Cap: Guid-ance for Trustees and Managers of Occupational Schemes.” U.K. Government, April 2015. See https://www.gov.uk/government/publications/the-charge-cap-guidance-for-trustees-and-managers-of-occupational-schemes.

NEST. National Employment Savings Trust Corporation Annual Report and Accounts 2013/14. London: Controller of Her Majesty’s Stationery Office, 2014.

Goby, V., and J. Lewis. “Using Experiential Learning Theory and the Myers-Briggs Type Indicator in Teaching Business Communication.” Business Communication Quarterly, Vol. 63, No. 3 (2000), pp. 39-48.

Staal, A., M. Corsi, S. Shores, and C. Woida. “A Factor Approach to Smart Beta Development in Fixed Income.” The Journal of Index Investing, Vol. 6, No. 1 (Summer 2015), pp. 98-110.

DisclaimerThe opinions expressed are as of April 2016 and are subject to change at any time due to changes in market or economic conditions. This material is not intended to be relied upon as a forecast, research, or investment advice, and is not a recommendation, offer, or solicitation to buy or sell any securities or to adopt any investment strategy. The opinions expressed are those of the authors, and may change as subsequent conditions vary. Individual portfolio managers for BlackRock may have opinions and/or make investment deci-sions that, in certain respects, may not be consistent with the information contained in this document. The information and opinions contained in this material are derived from proprietary and non-proprietary sources deemed by BlackRock to be reliable, are not necessarily all-inclusive and are not guaranteed as to accuracy. Past performance is no guarantee of future results. There is no guarantee that any of these views will come to pass. Reliance upon information in this material is at the sole discretion of the reader.

To order reprints of this article, please contact Dewey Palmieri at [email protected] or 212-224-3675.


Documents

THE JOURNAL OF INDEX INVESTING Influencing … · SUMMER 2016 THE JOURNAL OF INDEX INVESTING Transparency Transparency is a defining attribute of smart beta strategies, which follow