Retirement. Building a Dynamic Retirement Plan: Time-Segmented Bucketing Revisited

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1 GLOBAL INVESTMENT COMMITTEE NOVEMBER 2013 Retirement LISA SHALETT Head of Investment and Portfolio Solutions Morgan Stanley Wealth Management DANIEL HUNT Senior Asset Allocation Strategist Morgan Stanley Wealth Management ZI YE Quantitative Strategist Morgan Stanley Wealth Management Building a Dynamic Retirement Plan: Time-Segmented Bucketing Revisited Traditional approaches to retirement planning focus on wealth accumulation through a hypothetical target date and then implement a regular withdrawal plan assuming a relatively static asset allocation. Our research suggests that while this approach may be time-tested it may not be optimal for today s retirees who increasingly face more dynamic and complex risks like longer life spans, multigenerational family obligations, rising end-of-life health care costs and the threat of higher interest rates. Planning for financial goals and funding future liabilities that occur at different points in life through a timesegmented approach to asset allocation, we believe can provide retirees with better and more robust outcomes while delivering the clarity needed to help them stay on track.

2 GLOBAL INVESTMENT COMMITTEE / RETIREMENT Executive Summary W e recently revisited and refreshed Morgan Stanley s proprietary research and perspectives on a timesegmented bucketing (TSB) approach to retirement investing, incorporating several modeling enhancements. These include the leveraging of our new dual-horizon (seven years and 20-plus years) capital market return assumptions, the introduction of a broader and more robust definition of risk" and an analysis of new rebalancing methodologies that can be employed to better tailor strategies to investor-specific and potentially dynamic objectives. Our expanded definition of risk focuses on the broad and dynamic set of needs of clients in retirement, which is to say the de-cumulation phase of their wealth plan. While traditional accumulation phase strategies tend to measure risk by volatility and to set portfolio strategy based on volatility tolerance, our approach views risk from the client s perspective, in particular the probability of outliving one s money. We optimize the sustainable withdrawal rate, while setting portfolio strategy based both on a client s risk tolerance and risk capacity. That capacity is based on funding status, or progress toward specified goals. Our work revalidates that the TSB approach is adding value. The approach: (1) reduces the probability and magnitude of lifetime shortfall; (2) improves transparency to the client and reduces behavioral tendencies that lead to selling at inopportune times, in particular, during periods of volatility; (3) supports higher sustainable withdrawal rates than traditional approaches at a given success rate a particularly critical element in optimizing clients retirement savings in a period of low capital market returns; (4) reduces variability of planning outcomes and (5) best offsets the risk associated with the sequencing of returns, which hinge on circumstances such initial plan start date and others that effectively create unintended market timing bets. Importantly, much of the virtue of TSB can be attributed to how it differs from the methodology employed by traditional socalled target date approaches that reduce exposure to riskier assets during retirement. This in-retirement risk reduction actually increases the vulnerability of plans to volatility in the early years of de-cumulation. Note that this paradox explains why Morgan Stanley s target date solutions do not employ this approach, among other differences between our advice in this space and the conventional industry practice. TSB demonstrates that superior outcomes are achieved when equities and other risky assets are held over longer periods, which increases their portfolio weight in the out years, extending aggregate funding life. Finally, by incorporating dynamic rebalancing based on funding status calculated as the market value of portfolio assets divided by the present value of projected payments from the portfolio our approach enlists market volatility to tailor the strategy to fit the client. Clients seeking to maximize the probability of sustaining required income can use TSB harvesting to essentially lock in returns to risk assets in excess of their projected amounts. Conversely, clients assigning a high priority to legacy goals can utilize excess returns to dynamically increase exposure to higher risk, higher-returning asset classes, thereby increasing the probability and magnitude of accumulated legacy funds. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

3 Reframing Our Objectives T he last decade has been devastating for clients accumulating wealth to a recent or near-term target retirement date. Further complicating matters is that longer-term and especially intermediate-term forecasts imply that capital market returns will be below the averages of the last 70 years, making the challenge of retirement planning particularly acute. Meanwhile, baby boomers are approaching this milestone with a unique set of structural and emotional needs longer life spans, rising health care costs, reduced reliance on pension income, sandwich generation demands and potential changes to government sponsored benefits. In this way, retirement is not a destination it is a chapter. Traditional approaches to wealth management for retirees have historically assumed relatively stable and unchanging annual income needs, conservative risk tolerance and somewhat modest expectations around life expectancy as the inputs for a systematic withdrawal, or de-cumulation, plan. While this approach is disciplined and time-tested, it may no longer meet the needs of all of today s new retirees. Morgan Stanley Wealth Management s retirement framework extends retirement plan objectives beyond simply sustaining a paycheck to address multiple mini-phases of aging with different priority of needs safety, liquidity, income, growth, contingency and risk management through dynamic rebalancing. The fact is that the minimum distributions that retirees require may change over time. This necessitates a plan that better aligns our measurement of risk to a client s actual concerns, such as not running out of money. Implicit in this approach is the acknowledgement that risk Figure 1. Time-Segmented Asset Allocation Process tolerance is not only multi-dimensional depending on time horizon, but also that it fluctuates based on market events. Exploiting that dynamic can improve efficiency and sustainable spending rates. Risk as Wealth Shortfall Given these expanded objectives and requirements of a retirement framework, Modern Portfolio Theory and mean-variance optimization approaches that define risk as volatility and assume that an investor has an arbitrary, declining risk tolerance over time are particularly challenged. Our approach optimizes portfolios by defining risk as the probability of running out of money given specific spending objectives. We have incorporated some of the best practices and thinking utilized by institutional pension managers to accomplish this. Specifically, we borrow the concept of matching the timing of asset funding with the timing of liabilities with the stream of required distributions from the investment portfolio. In this matching process, time horizon functions as a proxy for risk tolerance under the principle that risk assets are much less risky if held over long horizons. Secondly, we have adopted a dynamic rebalancing approach that utilizes the concept of a portfolio s intermediate-term funding status to proxy for risk capacity. This idea of risk capacity is a counterweight to the best observations of behavioral finance which notes the human propensities to abandon financial and retirement plans when markets are temporarily volatile and loss aversion kicks in. By measuring funding status, clients not only have increased transparency and clarity, they are afforded more confidence to harvest gains and losses or change spending behaviors in response to market events. Income Segment 1 Income Segment 2 Income Segment 3 Income Segment 4 Legacy Segment Income Segment 1 Income Segment 2 Income Segment 3 Income Segment 4 Legacy Segment Years Immediate Spending GIC Model 1 1 Years Growth Phase 7 Years GIC Model 2 1 Years Growth Phase 15 Years GIC Model 4 1 Years Growth Phase 22 Years GIC Model 6 1 Years 30+ Growth Phase 30 Years GIC Model 7 1 Invested for Income Invested for Growth For illustrative purposes only Source: Morgan Stanley Wealth Management Global Investment Committee 1. Please see Appendix 1 for the composition of GIC model portfolios. In our analysis, we use a simplified version of these portfolios with only three asset classes: cash, global bonds and global equities. We proxy the REITs and commodities allocation with global equities. 2. Our research suggests that the time-segmented approach is most effective when the four segments are of similar or same length. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

4 What is Time-Segmented Bucketing? T ime-segmented asset allocation involves segregating retirement assets into different portfolios to be drawn on sequentially to fund retirement income needs, with the size and risk orientation of the portfolios dependent on the size and timing of expected distributions. The approach evaluates an investor s income needs in retirement net of Social Security, pensions, royalties, rental income, annuities and any other predictable source of income, identifying the extent to which the longer periods of time necessary to weather market volatility are afforded. The illustration on the prior page (Fig. 1) depicts a simple example of time-segmented asset allocation using four fixedlength periods and a legacy segment thereafter, which is representative of circumstances common with our clients. Volatility and Time-Segmented Asset Allocation One of the most important attributes of a time-segmented approach to asset allocation is its recognition that risky assets that feature volatile return streams and higher expected returns are far less risky in a long-term context than in the short-term. As Figure 2 below illustrates, in the short term, riskier assets expose investors to the largest losses. However, the result flips when these same assets are held for a prolonged period of time. As can be seen in the chart, the portfolio that features the greatest downside over a one- and five-year horizon (denoted by the lower border of the floating bars), actually show the least downside over a 20-year horizon, where their worst case returns are superior. This finding is relatively insensitive to choices of data period. Figure 2. Range of Returns over Four Horizons Annualized Return 50 % Bucket 1 Bucket 2 Bucket 3 Bucket 4 Legacy Median yr 5yr 10yr 20yr Horizon For example, if we reach way back into the distant past, we find that in only 2% of the 20-year investment windows in the last century did US Treasury bonds manage to outperform US stocks. On the rare occasion that they did, the downside for stocks was not significant. In the single-worst 20-year period for equities during the last century, the one that started on the eve of the 1929 stock market crash, bonds outperformed stocks by just 39 basis points on an annualized basis. That translated into an 8% difference in accumulated wealth at the end of year 20. By contrast, equities outperformed bonds by 3% or more annualized in 65% of the 20- year holding periods. That resulted in an 81% or more difference in accumulated wealth. This analysis validates the ineffectiveness of selling in reaction to temporary departures from expected performance. Liquidating risky positions realizes losses and creates poor retirement outcomes. This helps to explain how TSB, which segregates riskier assets in time-delimited boxes, adds value over a traditional approach. TSB can also be applied to enhance income security. Indeed, the analysis described in this report supports the efficacy of capturing unexpected gains when they occur and converting them into increased income security, which, though not universally applicable, could represent a favorable option for more conservative investors 3. Given the market volatility experienced from 2000 through 2013, it is worthwhile to consider how time-segmented asset allocation would have performed. We back-tested the timesegmented approach for three periods, each corresponding to the start of a difficult time for investors: 1973, 2000 and The period beginning in 1973 covers 30 years starting at the top of the Nifty Fifty bull market in large cap US stocks right before the subsequent equity and bond bear markets of the 1970s and ending in the trough of the dot com ' bubble burst at the end of In each other instance, the back-tested period concluded at the end of June As you will see in that section, the time-segmented approach produced encouraging results compared with portfolios by other means but with similar risk-reward characteristics. There are limits to what time segmentation can do. For investors who require a high degree of certainty, annuities, life insurance and other products with income guarantees may represent the most appropriate cornerstone of their financial plan. For investors whose tolerance of portfolio volatility declines significantly as they age, a constant allocation during retirement, such as is featured in Morgan Stanley s target- date fund advice may be the better choice. However, for those who are more likely to utilize harvesting rules in a disciplined fashion, and who can avoid emotional decision-making under an approach that makes asset and liability matching more transparent, time segmentation may offer significant advantages. 3 Please note that the time-segmented approach does not include an investor-suitability condition. Investors, in conjunction with their Financial Advisors, should ensure that the aggregate portfolio (combining all segments and the legacy fund) is consistent with the investor s investment objectives and circumstances at all times. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

5 TSB Improves on Traditional Retirement Approaches I n this section, the time-segmented asset allocation approach is compared with three possible and realistic alternatives. The first alternative is systematic withdrawal, in which an investor utilizes a single portfolio that is regularly rebalanced to its target allocation as a way to adjust for the effects of market action and portfolio distributions. The target allocation under this scenario is set to average the same asset allocation as the time-segmented approach to assure that the risk-return characteristics of the timesegmented and systematic-withdrawal methodologies are comparable over the full time period. The second alternative is a buy and hold approach, in which a single portfolio is also set to match the average allocation of the time-segmented approach. The key difference is that the investor will not rebalance the allocation and thus, the portfolio s asset allocation is allowed to drift with the effect of market action. The third alternative is a traditional target date approach, in which a portfolio, set to match the average allocation of the timesegmented approach, steadily reduces its risk profile over the years. This approach is typically utilized by target date funds currently in the marketplace (Morgan Stanley s target date fund is an exception) and is popular with defined contribution plan sponsors. To analyze the pros and cons of each approach across a wide range of possible outcomes, we applied 10,000 Monte Carlo simulations of the wealth and spending patterns of a 65-year-old couple with investable assets of $1 million and an investment horizon of 30 years 4. For simplicity sake, we ignored other sources of income. For the time-segmented approach, five Global Investment Committee (GIC) model portfolios were selected to fill four time segments and the legacy fund. The GIC maintains strategic and tactical portfolios for eight investor risk profiles with Model 1 being the most conservative and Model 8 the most aggressive. In this analysis, the strategic portfolios were utilized without any active management overlay from tactical shifts or active manager contributions. The first four model portfolios were assigned to segments of similar length. As illustrated in Figure 1, the 65-year-old couple s 30-year investment horizon means that they would utilize four seven-and-a-half-year segments. Figure 3. The analysis involves the following 10 key assumptions and decision rules: 1) The GIC s strategic (seven years) and secular (20-plus years) assumptions represent reasonable and unbiased estimates of future returns, volatility and correlations of asset classes over the entire investment horizon 5. 2) Distributions grow at the rate of inflation to maintain purchasing power 6. 3) Returns are normally distributed and are assumed to be independent from one period to another. 4) Transactions and tax costs are not considered in the analysis. 5) The composition of GIC model portfolios remains constant. Tactical, or opportunistic, adjustments are not made to any of the portfolios. 6) Rebalancing, where required, is conducted on a quarterly basis. 7) In the time-segmented approach, if a segment depletes before the time horizon it was meant to cover ends, funds are drawn from segment four to cover withdrawals. If segment four is also depleted, the legacy fund will be drawn upon. Conversely, if excess funds remain at the end of a segment s time period, these funds will be allocated to the legacy fund. 8) In the systematic withdrawal and traditional target date approaches, withdrawals are funded by all asset classes in approximately the same proportions as the target portfolio, in the case of systematic withdrawal, the initial portfolio. This ensures quarterly rebalancing to the appropriate weightings. 9) In the buy and hold approach, withdrawals are funded in exact proportion to the portfolio at any given time, so that the asset allocation is not affected by withdrawals. 10) The share of the initial portfolio assigned to each time segment is derived by discounting the future funding required to generate the targeted payments for each sequential period using the weighted-average expected return of the GIC model portfolio asset allocations for each time segment. Applying the assumptions and decision rules described above, the aggregated portfolios resulted in the initial and time-weighted average asset allocations shown in the table below (Fig. 3). Time Segment Initial Time Segment Average Systematic Withdrawal Initial Systematic Withdrawal Average Buy and Hold Initial Buy and Hold Average Traditional Target Date Initial Traditional Target Date Average Cash 19% 11% 11% 11% 11% 7% 4% 11% Bond 50% 30% 30% 30% 30% 22% 22% 30% Equity 30% 59% 59% 59% 59% 71% 74% 59% 4 Monte Carlo simulation involves repeated sampling of variables. It is used in finance to estimate the effect of risk on securities or strategies. 5 For further information, see the Annual Update of Capital Market Assumptions, published in the first quarter on an annual basis. 6 We assume a 2.0% inflation rate over the entire analysis horizon. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

6 Research Results T he figures below (Figs. 4 and 5) display the outcomes from the simulations. For each case, the success rate is defined as the percentage of simulations in which the 65-year-old couple would not outlive their wealth. Figure 4 depicts the withdrawal rates commensurate with 99%, 95% and 90% success-rate thresholds. Of course, the higher the required success rate, the lower the required withdrawal rate, and vice versa. The average portfolio ending values which are a measure of the funds remaining at the end of the investment horizon are also shown. Considering the couple in our example started with $1 million, these ending values are significant for two reasons: The requirement of a high success rate meant the average simulation outcome resulted in the investor having money to spare, and the powerful effect of compounding over long investment horizons. In Figure 5, below, we have reorganized the data so that the withdrawal rate is set to a constant consistent with a 95% success rate under the time-segmented approach. Other data present the average ending values, volatility and percentile ending values. Figure 4. Maximum Initial Withdrawal Rate Figure 5. Portfolio Ending Value Several observations emerge from the analysis. First, the timesegmented approach allows greater withdrawal rates, especially when higher success rates are required. Our case study couple achieved a 3.6% withdrawal rate (see Fig. 4) with a 95% successrate under a time-segmented approach versus a 3.4% withdrawal rate for systematic withdrawal and buy and hold, and a 3.3% withdrawal rate under the traditional target-date approach. Figure 5 reveals that under the same withdrawal requirement, TSB is actually the best way to protect investments in the worstcase scenarios, which is represented by the fifth percentile (denoted again by the lower border of the floating bars). To us, this combination represents a crucial advantage. Many investors seek to maximize the cash flows that will support their lifestyles. For such investors, the ending value is a secondary consideration. The reason for the higher successful withdrawal rate in the timesegmented approach and lower chance of negative ending values lies in the way portfolios evolve over time. On average, the aggregate portfolio derived by combining all of the individual segments grows riskier over time, as the most-conservative segments are depleted first. This, relative to other methodologies, helps limit the devastating effects of the greatest threat to success: needing to sell assets during bear markets in the early years of the plan. While the time-segmented approach requires the monitoring of multiple segments, it is also intuitive, easily understood, disciplined and widely accepted. By contrast, the traditional target-date approach manages the dubious distinction of the lowest sustainable withdrawal rates and the largest shortfall in the fifth percentile of investment outcomes (see Figs. 4 and 5). As might be expected given its near inversion of TSB prescribed advice, the reasons for the poor performance of the traditional target date are the flip side of what makes it attractive; higher initial allocations to risky investments and the forced de-risking it prescribes magnifies the deleterious impact of adverse market moves early in retirement. Clearly, while mechanically reducing the allocation to risk assets during retirement reflects a declining appetite for volatility as investors age, it is also an inefficient way to invest in retirement. In contrast to the traditional target-date approach, the buy and hold shows more competitive sustainable withdrawal rates while featuring the best upside and average ending values of the four methodologies. The outperformance in the upside and average case, however, is the result of increasing portfolio concentrations in riskier asset classes in those scenarios, as these asset classes will experience higher returns in average and favorable market conditions. The cost of bearing this additional risk is apparent in the middling success probabilities of the buy and hold approach, probabilities that are furthermore sensitive to what is assumed about equity market volatility compared with both the timesegmented and systematic withdrawal methods. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

7 Figure 6. Time Segment 100% Cash Bond Equity yr Systematic Withdrawal 100% Cash Bond Equity yr Buy and Hold 100% Cash Bond Equity yr Traditional Target Date 100% 90 Cash Bond Equity yr It is also true that a buy and hold investor must be willing to endure higher portfolio volatility, which only increases through retirement, a fact that would be disconcerting to many. As Figure 5 reveals, this entails the risk of negative balances at the fifth percentile. Like the buy and hold approach, the systematic withdrawal approach trades somewhat lower sustainable withdrawal rates for higher ending values, on average $3.3 million under systematic withdrawal and $2.6 million under time-segmented bucketing. Notably, sustainable withdrawal rates are similar between the two approaches when the required success rate is lower, 3.9% versus 3.8% at a 90% success rate. One of the more important advantages of the systematic withdrawal approach is that it does not require the allocation to risky assets in the overall portfolio to grow over time, which is likely to make it more palatable for those whose tolerance for portfolio volatility declines with age. Also, like the time-segmented approach, the systematic withdrawal approach is widely accepted, sound and disciplined. Its main drawbacks relative to TSB are that it requires more frequent rebalancing and is more vulnerable to poor market returns early in retirement. Thus, while there are advantages and disadvantages to all four methodologies, time segmentation and systematic withdrawal seem to hold a clear advantage over buy and hold or traditional target-date for those who place an emphasis on not running out of income or principal before a set date. That said, for clients who require maximum withdrawal rates and who can stomach the increasing portfolio volatility during retirement including refraining from liquidating assets during periods of capital market duress we prefer the time-segmented approach because of the attractiveness of its tradeoff between the risk of failure and withdrawal rates, as well as the disciplined and transparent assetliability matching inherent in the methodology. For investors for whom increasing portfolio volatility during retirement isn t likely to sit well, or who do not require maximum withdrawal rates, a systematic withdrawal approach may be more appropriate even with its less-favorable downside extremes. Harvesting, Legacy, Fear and Greed T o the degree that a time-segmented approach encourages investors to stay on plan, there are two additional advantages for investors to consider. First, the approach can be tailored in several ways to fit investor objectives. For example, TSB can be married with opportunistic legacy-seeking or disciplined harvesting, in which the retiree converts excess funds generated by better-than-anticipated performance into either the final legacy bucket, which holds the longest-term assets, or the segment one account for current or near-term spending. Legacy seeking tends to maximize the funds available at the end of the specified horizon while placing excess funds into a segment one account tends to improve the probability of success in achieving future income security. Both approaches illustrate the ways in which TSB can be Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

8 Figure 7. Time Segment Time Segment Harvesting Harvesting Legacy Legacy Seeking Emotional Emotional Initial Average Initial Average Seeking Initial Average Initial Average Cash 19% 11% 19% 17% 19% 7% 19% 48% Bond 50% 30% 50% 40% 50% 18% 50% 18% Equity 30% 59% 30% 43% 30% 75% 30% 34% enhanced by adding dynamic elements to the strategy to better target specific investment objectives. The second benefit of TSB is that it tempers emotional decision making making decisions in reaction to market movements which can be harmful to a long-term plan. To study this effect, we created a hypothetical emotional reaction portfolio in which the holdings were converted to cash following an equity market downturn of 10% or more, and the initial weightings of the portfolio were not re-established until after a 20% recovery from the time the portfolio was converted to cash. The findings from the Monte Carlo simulation (Fig. 7 above) show that, as anticipated, the harvesting and legacy-seeking strategies led to more and less conservatively weighted average allocations to equities, respectively, than in the case of the basic time-segmented approach. For the hypothetical 65-year-old couple, the average equity allocation was 59% for the time-segmented approach, versus 43% when the harvesting discipline was incorporated and 75% when the legacy-seeking strategy was followed 7. More interestingly, the emotional reaction strategy resulted in the lowest average equity allocation, 34%. Not surprisingly, profound differences arise in the simulated Figure 8. Maximum Initial Withdrawal Rate investment results. The disciplined harvesting strategy improves success rates but at the cost of much reduced ending values and more frequent rebalancing activity (Fig. 10, page 9). In the case of the 65-year-old couple, harvesting improved the withdrawal rate at the 95% success-rate threshold to 3.7% from 3.6% in the base case. 7 Harvesting and legacy seeking occur whenever any time segment s value is greater than the discounted value of future payments from it, using the applicable portfolio s expected return as the discount rate. However, the average ending balance fell to $1.5 million from $2.1 million. Harvesting contributed a more noticeable benefit at the 99% success-rate threshold where it improved the withdrawal rate to 3.3% from 3.1% potentially entailing a meaningful difference in lifestyle. Of course, harvesting does not need to be Figure 9. Portfolio Ending Value implemented as mechanistically as it has been here or indeed using this particular mechanism. Different thresholds under which harvesting would be triggered, different harvesting frequencies and subsets of retirement under which harvesting would take place are some of the ways the strategy could be modified on a case by case basis. In our opinion, the harvesting analyzed here is one point along a continuum of strategies that should be considered by investors who place a very high value on income security and not fully depleting their principal. As a near reciprocal to the harvesting strategy both in intent and approach, it is not surprising that the legacy-seeking strategy has the opposite effect on outcomes to harvesting. Here, the projected value left in the portfolio at the end of the investment horizon is substantially greater than any other strategy tested thus far, including buy and hold. The enhanced legacy results come at a cost to the maximum sustainable withdrawal rates at the 95% success-rate threshold, which falls from 3.6% in the base case to 3.4%. The cost at a 90% success-rate threshold, however, is much smaller, 3.8% versus 3.9%. Note as well that, just as with the harvesting strategy, the legacy-seeking strategy tested here represents one version of a method of applying surplus funds to higher-risk time buckets, and one that could be modified in any of several different ways. Indeed, it is even possible to combine harvesting and legacy seeking Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

9 Figure 10. Projected Range of Portfolio Value per Time Bucket strategies at different stages in retirement, and depending on metrics like funding levels. These dynamic strategies and others like them are areas where we anticipate additional research will help us advance and improve on the retirement investing methodologies that are the subject of this paper. Backtesting T he analysis so far has centered on Monte Carlo simulations and shed light on possible future outcomes. Given the volatility in the recent past, however, how would the timesegmented, systematic-withdrawal and buy and hold methodologies have performed over different periods investors have actually experienced? Three periods with challenging starting points were selected to answer this question: the 30-year period from January 1973 to December 2002, the 13-and-a-half year period from January 2000 to June 2013, and the shorter five-and-ahalf year period from January 2008 to June The year 1973 was selected as it captures the equity and bond bear markets and high-inflation environment of the 1970s. The starting point of the second period was selected to include the post-tech bubble bear market. The most recent and shortest period focuses exclusively on the post-financial-crisis bear market. The historical back test is consistent with our initial assessment from the Monte Carlo simulation. In each of the sample periods tested, the time-segmented approach allowed an investor to withdraw greater amounts for the same success rates (Fig. 11). Additionally, for each of the sample periods and for every given initial withdrawal rate, investors were left with greater ending values using the time-segmented approach than any of the other approaches (Fig. 12, page 10). In this instance at least, the historical analysis displays an even greater advantage for the timesegmented methodology than we observed in the Monte Carlo simulation. In each case over all three periods, the time-segmented approach led to larger ending values than the other three methods. Figure 11. Maximum Initial Withdrawal Rate Jan Jun Time Segment Systematic Withdrawal Buy and Hold Traditional Target Date Maximum Initial Withdrawal Rate 5.6% 5.1% 5.0% 5.1% Ending Value $0.9M $0.9M $0.8M $0.8M Maximum Initial Jan % 4.3% 4.2% 3.9% Withdrawal Rate Jun Ending Value $0.7M $0.7M $0.7M $0.6M Maximum Initial Jan % 4.5% 4.3% 4.3% Withdrawal Rate Dec Ending Value $0.1M $0.0M $0.4M $0.1M Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

10 Figure 12. Ending Portfolio Value Further Considerations for Retirement Planning T he time segmented bucketing approach to portfolio construction and management is a first but not only element of a comprehensive de-cumulation oriented retirement plan. The Morgan Stanley Wealth Management retirement framework aims to take a complete 360-degree view of assets, liabilities and cash flow needs with an eye toward expanding the choices that retirees might consider and explaining the risks we might face as they age. How much annual income do retirees really need when factoring in age-adjusted health care costs? How might choices about real estate impact cost of living and inflation forecasts? Examples of forthcoming research include: Utilizing the funding ratio to determine when and how much a retiree should devote toward annuitization and guaranteed income products; understanding the role that various life insurance products can play in funding potential legacy goals or tax liabilities; determining when health related risks make long-term care insurance optimal; contemplating how to adjust spending levels to dynamically build new contingencies into plans and advice on how couples can optimize Social Security benefit elections. Conclusion T oday s retirees face an increasingly complex planning challenge, with much more dynamic life-style choices: longer life spans; multigenerational financial obligations and rising health care costs, all set against an unprecedented capital markets backdrop of low growth and potentially rising interest and inflation rates. Our research suggests that a time-segmented bucketing approach to retirement planning delivers a superior alternative to traditional planning methods while creating the adaptability to the dynamic demands of the current environment. By optimizing the sustainable withdrawal rate and minimizing the likelihood that a retiree will outlive his or her money, timesegmented bucketing creates a plan that provides the clarity and transparency that gives investors the confidence to stick with their plan and achieve their lifetime goals. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

11 Appendix 1 4 Global Investment Committee Strategic Asset Allocation Models Without Certain Alternatives Allocations as of October 2013 Global Fixed Global Equities and Alternative Global Equities, Global Fixed Income and Alternative Investments Income Investments Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Model 7 Model 8 Cash 30% 18% 13% 8% 5% 3% - - Global Equities US Large-Cap Equity Growth Value US Mid-Cap Equity Growth Value US Small-Cap Equity Growth Value Europe Equity Developed Asia Equity Japan Equity Asia Pacific ex Japan Equity Emerging Markets Equity Total Equity Total US Equity Total International Equity Total Emerging Markets Equity Global Fixed Income Investment Grade Fixed Income Short-Term Fixed Income US Fixed Income International Fixed Income Inflation-Linked Securities High Yield Emerging Markets Fixed Income Total Fixed Income Alternative Investments REITs Commodities Diversified Ex Precious Metals Precious Metals Hedged Strategies Managed Futures Private Real Estate Private Equity Total Alternative Investments Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

12 Disclosures Morgan Stanley Wealth Management ( Morgan Stanley Wealth Management ) is the trade name of Morgan Stanley Smith Barney LLC, a registered broker-dealer in the United States. This material has been prepared for informational purposes only and is not an offer to buy or sell or a solicitation of any offer to buy or sell any security or other financial instrument or to participate in any trading strategy. Past performance is not necessarily a guide to future performance. The author(s) (if any authors are noted) principally responsible for the preparation of this material receive compensation based upon various factors, including quality and accuracy of their work, firm revenues (including trading and capital markets revenues), client feedback and competitive factors. Morgan Stanley Wealth Management is involved in many businesses that may relate to companies, securities or instruments mentioned in this material. 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Morgan Stanley Wealth Management has no obligation to provide updated information on the securities/instruments mentioned herein. The securities/instruments discussed in this material may not be suitable for all investors. The appropriateness of a particular investment or strategy will depend on an investor s individual circumstances and objectives. Morgan Stanley Wealth Management recommends that investors independently evaluate specific investments and strategies, and encourages investors to seek the advice of a financial advisor. The value of and income from investments may vary because of changes in interest rates, foreign exchange rates, default rates, prepayment rates, securities/instruments prices, market indexes, operational or financial conditions of companies and other issuers or other factors. Estimates of future performance are based on assumptions that may not be realized. Actual events may differ from those assumed and changes to any assumptions may have a material impact on any projections or estimates. Other events not taken into account may occur and may significantly affect the projections or estimates. Certain assumptions may have been made for modeling purposes only to simplify the presentation and/or calculation of any projections or estimates, and Morgan Stanley Wealth Management does not represent that any such assumptions will reflect actual future events. Accordingly, there can be no assurance that estimated returns or projections will be realized or that actual returns or performance results will not materially differ from those estimated herein. This material should not be viewed as advice or recommendations with respect to asset allocation or any particular investment. This information is not intended to, and should not, form a primary basis for any investment decisions that you may make. Morgan Stanley Wealth Management is not acting as a fiduciary under either the Employee Retirement Income Security Act of 1974, as amended or under section 4975 of the Internal Revenue Code of 1986 as amended in providing this material. Morgan Stanley Wealth Management and its affiliates do not render advice on tax and tax accounting matters to clients. This material was not intended or written to be used, and it cannot be used or relied upon by any recipient, for any purpose, including the purpose of avoiding penalties that may be imposed on the taxpayer under U.S. federal tax laws. Each client should consult his/her personal tax and/or legal advisor to learn about any potential tax or other implications that may result from acting on a particular recommendation. International investing entails greater risk, as well as greater potential rewards compared to U.S. investing. These risks include political and economic uncertainties of foreign countries as well as the risk of currency fluctuations. These risks are magnified in countries with emerging markets, since these countries may have relatively unstable governments and less established markets and economies. Bonds are subject to interest rate risk. When interest rates rise, bond prices fall; generally the longer a bond s maturity, the more sensitive it is to this risk. Bonds may also be subject to call risk, which is the risk that the issuer will redeem the debt at its option, fully or partially, before the scheduled maturity date. The market value of debt instruments may fluctuate, and proceeds from sales prior to maturity may be more or less than the amount originally invested or the maturity value due to changes in market conditions or changes in the credit quality of the issuer. Bonds are subject to the credit risk of the issuer. This is the risk that the issuer might be unable to make interest and/or principal payments on a timely basis. Bonds are also subject to reinvestment risk, which is the risk that principal and/or interest payments from a given investment may be reinvested at a lower interest rate. Bonds rated below investment grade may have speculative characteristics and present significant risks beyond those of other securities, including greater credit risk and price volatility in the secondary market. Investors should be careful to consider these risks alongside their individual circumstances, objectives and risk tolerance before investing in high-yield bonds. High yield bonds should comprise only a limited portion of a balanced portfolio. Interest on municipal bonds is generally exempt from federal income tax; however, some bonds may be subject to the alternative minimum tax (AMT). Typically, state tax- exemption applies if securities are issued within one s state of residence and, if applicable, local tax-exemption applies if securities are issued within one s city of residence. A taxable equivalent yield is only one of many factors that should be considered when making an investment decision. Morgan Stanley Wealth Management and its Financial Advisors do not offer tax advice; investors should consult their tax advisors before making any tax-related investment decisions. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER

13 Growth investing does not guarantee a profit or eliminate risk. The stocks of these companies can have relatively high valuations. Because of these high valuations, an investment in a growth stock can be more risky than an investment in a company with more modest growth expectations. Value investing does not guarantee a profit or eliminate risk. Not all companies whose stocks are considered to be value stocks are able to turn their business around or successfully employ corrective strategies which would result in stock prices that do not rise as initially expected. Alternative investments which may be referenced in this report, including private equity funds, real estate funds, hedge funds, managed futures funds, and funds of hedge funds, private equity, and managed futures funds, are speculative and entail significant risks that can include losses due to leveraging or other speculative investment practices, lack of liquidity, volatility of returns, restrictions on transferring interests in a fund, potential lack of diversification, absence and/ or delay of information regarding valuations and pricing, complex tax structures and delays in tax reporting, less regulation and higher fees than mutual funds and risks associated with the operations, personnel and processes of the advisor. Investing in commodities entails significant risks. Commodity prices may be affected by a variety of factors at any time, including but not limited to, (i) changes in supply and demand relationships, (ii) governmental programs and policies, (iii) national and international political and economic events, war and terrorist events, (iv) changes in interest and exchange rates, (v) trading activities in commodities and related contracts, (vi) pestilence, technological change and weather, and (vii) the price volatility of a commodity. In addition, the commodities markets are subject to temporary distortions or other disruptions due to various factors, including lack of liquidity, participation of speculators and government intervention. Physical precious metals are non-regulated products. Precious metals are speculative investments, which may experience short-term and long term price volatility. The value of precious metals investments may fluctuate and may appreciate or decline, depending on market conditions. If sold in a declining market, the price you receive may be less than your original investment. Unlike bonds and stocks, precious metals do not make interest or dividend payments. Therefore, precious metals may not be suitable for investors who require current income. Precious metals are commodities that should be safely stored, which may impose additional costs on the investor. The Securities Investor Protection Corporation ( SIPC ) provides certain protection for customers cash and securities in the event of a brokerage firm s bankruptcy, other financial difficulties, or if customers assets are missing. SIPC insurance does not apply to precious metals or other commodities. Treasury Inflation Protection Securities (TIPS) coupon payments and underlying principal are automatically increased to compensate for inflation by tracking the consumer price index (CPI). While the real rate of return is guaranteed, TIPS tend to offer a low return. Because the return of TIPS is linked to inflation, TIPS may significantly underperform versus conventional U.S. Treasuries in times of low inflation. Equity securities may fluctuate in response to news on companies, industries, market conditions and general economic environment. Asset allocation and diversification do not assure a profit or protect against loss in declining financial markets. The indices are unmanaged. An investor cannot invest directly in an index. They are shown for illustrative purposes only and do not represent the performance of any specific investment. The indices selected by Morgan Stanley Wealth Management to measure performance are representative of broad asset classes. Morgan Stanley Wealth Management retains the right to change representative indices at any time. REITs investing risks are similar to those associated with direct investments in real estate: property value fluctuations, lack of liquidity, limited diversification and sensitivity to economic factors such as interest rate changes and market recessions. Investing in foreign emerging markets entails greater risks than those normally associated with domestic markets, such as political, currency, economic and market risks. Because of their narrow focus, sector investments tend to be more volatile than investments that diversify across many sectors and companies. Certain securities referred to in this material may not have been registered under the U.S. Securities Act of 1933, as amended, and, if not, may not be offered or sold absent an exemption therefrom. Recipients are required to comply with any legal or contractual restrictions on their purchase, holding, sale, exercise of rights or performance of obligations under any securities/instruments transaction. Hypothetical Performance General: Hypothetical performance should not be considered a guarantee of future performance or a guarantee of achieving overall financial objectives. Asset allocation and diversification do not assure a profit or protect against loss in declining financial markets. Hypothetical performance results have inherent limitations. The past performance shown here is simulated performance based on benchmark indices, not investment results from an actual portfolio or actual trading. There can be large differences between hypothetical and actual performance results achieved by a particular asset allocation. Actual performance results of accounts vary due to, for example, market factors (such as liquidity) and client-specific factors (such as investment vehicle selection, timing of contributions and withdrawals, restrictions and rebalancing schedules). Clients would not necessarily have obtained the performance results shown here if they had invested in accordance with any GIC asset allocation, idea or strategy for the periods indicated. Despite the limitations of hypothetical performance, these hypothetical performance results may allow clients and Financial Advisors to obtain a sense of the risk / return trade-off of different asset allocation constructs. Indices used to calculate performance: The hypothetical performance results in this report are calculated using the returns of benchmark indices for the asset classes, and not the returns of securities, fund or other investment products. Please refer to important information, disclosures and qualifications at the end of this material. MORGAN STANLEY WEALTH MANAGEMENT NOVEMBER