Wednesday, October 15, 2014

Speaking Updates & Ph.D. Fellowship Opportunity at The American College

I started the day in New York City. This morning I joined Joe Tomlinson and Dirk Cotton for a MarketWatch panel discussion with Bob Powell.  Marketwatch will be producing some stories and videos about that event over the next couple months. As well, Joe, Dirk, and I enjoyed our own little Algonquin Round Table at the Algonquin Hotel last night. We had a good discussion about bond ladders for retirement, and came away with some research ideas for comparing bond funds and bond ladders in retirement. 

Academy of Financial Services

The Annual Meeting for the Academy of Financial Services will be held in Nashville tomorrow and Friday, October 16 & 17. For anyone in Nashville, it looks to be a good event with lots of folks from the retirement income research world. Michael Kitces, David Blanchett, and Joe Tomlinson will all be there, for instance.  I'm also filling in as a last minute replacement for Larry Kotlikoff to deliver the luncheon keynote address, and I'll be speaking on "Toward Best Practices in Retirement Income Planning." 

Speaking of research...

Ph.D. Fellowship at The American College

The Ph.D. Program in Financial and Retirement Planning is currently progressing along well, with three cohorts of students working their way through the program. This is a distance-based program with live webinar classes and a few one-week residencies. So students are located all over the United States. Thanks to a generous donation from two former executives at New York Life, there is a doctoral fellowship available for a student in the program. The idea for the fellowship is to spend about 20 hours per week conducting research in exchange for program tuition being covered, as well as a $30,000 per year stipend.  

We have been struggling to fill this position, on account that all of the current Ph.D. students also work as full-time financial planners and cannot devote an extra 20 hours per week beyond their already rigorous Ph.D. studies. This fellowship could be attractive to a young person just finishing their bachelors or masters degree in financial planning, and who is ultimately seeking an academic job. Though such an individual might prefer a full-time residency Ph.D. program. Nonetheless, if you fit this description, please do not hesitate to consider The American College along with other more traditional Ph.D. programs at Texas Tech, Georgia, Missouri, or Kansas State.

A third possibility, and the primary reason I bring this up on my blog, is that the fellowship could be filled by a recent retiree who has time and energy and a passion for research, and who might consider a twilight career at least as a part-time academic. I know some of my blog readers fit into this category, so let me know if you are interested to learn more.  Ideally, the doctoral fellow would be someone within commuting distance from Bryn Mawr, PA.  But I think we can be flexible about that, as now with tools like Skype or Google Hangout, it is easy interact online almost as easily as in person. The information below also suggests that the fellowship is for someone who can demonstrate financial need. But don't let that stop you from considering this opportunity, as I don't think a lack of financial need would prevent a highly qualified applicant from receiving the award. Please see the announcement below and let me know if you have any interest or questions. 

The Sy Sternberg and Fred Sievert Doctoral Fellowship
The Sternberg-Sievert Doctoral Fellowship was created to provide financial support to an individual who has both the desire and demonstrated potential to pursue a career in retirement planning research in an academic or industry setting. Funding for the Fellowship is provided by industry trailblazers Sy Sternberg and Fred Sievert who both dedicated years of service to New York Life as Chairman of the Board/CEO and President of the company, respectively.
The Sternberg-Sievert Fellowship includes tuition and fees for the PhD in Financial and Retirement Planning as well as an annual $30,000 stipend for living expenses. The Fellow must be able to work at least 20 hours per week on The American College campus while pursuing the doctorate online. Primary responsibilities of the Fellow include assisting faculty with research projects and providing support to The College’s Centers of Excellence which include the New York Life Center for Retirement Income. In addition, the Sternberg-Sievert Fellow may be required to represent the Fellowship program at donor events and when media opportunities arise.
Applicants must be newly admitted to the doctoral program and be able to demonstrate financial need.

A master’s degree in finance, economics, consumer science, actuarial science, or related discipline from a regionally accredited institution is required. Residence within commuting distance of The American College’s Bryn Mawr, Pennsylvania campus is highly preferred but not required.

A demonstrated ability to read and interpret scholarly material is required; the capacity to write for scholarly publications is highly desirable; a background in data collection, data analysis, and/or experience using statistical software packages such as SAS or R is highly preferred.

Applicants must have a professional appearance and be able to demonstrate fluency in both speaking and writing in the English language.
Tuition funding and stipend will be renewed annually for up to four years from starting the doctoral program and is contingent on annual satisfactory academic standing and job performance reviews as the Sy Sternberg and Fred Sievert Doctoral Fellow.
To Apply:
Indicate your interest in being considered for the Fellowship on the doctoral program application form and write a formal letter to the Doctoral Fellowship Committee that explains your interest in becoming the Sy Sternberg and Fred Sievert Doctoral Fellow. Your letter should include a discussion of the specific qualifications that you believe will maximize your effectiveness as the Sternberg-Sievert Doctoral Fellow. Add the letter to your application packet.

Thursday, October 9, 2014

Next-Gen vs. Traditional VAs

Over the past several years, I've published a few articles questioning the value of deferred variable annuities with income guarantee riders (VA/GLWBs), including one in the Summer 2013 issue of the Journal of Retirement. These VAs with guarantees are marketed as offering upside potential, downside protection, and liquidity all in one convenient package. But my concern is that the impact of compounding fees over time creates an overwhelming cost to the VA/GLWB user, such that one could be better off by just combining stocks and simple income annuities. That was a conclusion in my article about the efficient frontier for retirement income

Along these lines, Jefferson National asked me to write a sponsored white paper [you are supposed to be a financial advisor to gain access to the paper, and this VA is not otherwise available directly to consumers] about their new Monument Advisor investment-only variable annuity designed to be used by financial advisors.  Fees for the Monument Advisor variable annuity add up to $240 per year for an account of any size, and the reason to consider this VA is because the advisor and client have already determined that there is value to the financial plan by seeking the tax deferral offered by variable annuities. Besides these tax deferral aspects, the VA otherwise basically behaves like a traditional investment account, at least after age 59.5.

So the question becomes: should someone seeking tax deferral through a variable annuity use the low-cost Monument Advisor investment only approach, or should they go ahead and proceed with traditional VA with guarantee riders, which may also include commissions, insurance, and guarantee fees?

In the article I reinterpret this question in terms of: what will be the difference in outcomes for someone using a lower-cost investment-only VA vs. someone using a higher cost VA with guarantees, in terms of the retirement income that can be supported.

Obviously, if the investment portfolio is depleted, someone will be happy to still have guaranteed income. But the value of that guaranteed income can be oversold. Fees in the VA/GLWB will have eaten away the account value more quickly, so that there will be no growth in benefits to keep pace with inflation, and there will be no liquidity either. As inflation erodes the value of the VA/GLWB's guaranteed income, the real value of this guaranteed income could become much less than the user realizes. When markets are down, a VA/GLWB ends up behaving like a SPIA, but with a lower payout rate. And the question is: what has the VA/GLWB user given up in the process of seeking the somewhat illusionary upside potential and liquidity for their assets? Again, the illusionary nature of these is that compounding fees eat away at the potential for either upside or liquidity when it may be most needed later in retirement. 

In the white paper, I first review the points made in favor of using VA/GLWBs, including tax deferral, the ability to lock in growth for a hypothetical benefit base during accumulation, the ability to guarantee income for life, and liquidity.

Then I construct a composite hypothetical VA/GLWB, based on the characteristics of those offered by 5 major companies. I look at maximum allowed equity allocations of both 60% and 100%, a guaranteed roll-up rate in the deferral period of 5.3% compounded, a 1.29% mortality and expense fee on the account value, a 1.35% rider fee on the benefit base (which can end up being a much higher percent of the remaining assets when the account value is less), a 4.8% guaranteed income withdrawal rate for a 65 year old, and annual fees of $39.

This compares to the investment-only VA with annual fees of $240 and a 1% annual advisory and investment fee applied to the account value.

With Monte Carlo simulations, I then investigate the amount of lifetime guaranteed income supported by the VA/GLWB, and then try to replicate the same withdrawals from the investment-only VA. 

Let me provide one example based from the article. Consider a 10 year accumulation period followed by a 30 year distribution period. There is a 58% chance that the VA/GLWB contract value will have hit zero (though the guaranteed income would still be provided). There is a 12.1% chance that the investment-only VA would be depleted while replicating the same payments. In the median outcome, the VA/GLWB would be depleted. In the median for the investment-only VA, the VA would have supported all of the income provided by the VA/GLWB and still have a real value of $159,709, relative to $100,000 at the start. Real wealth actually grew by 60%.

Ultimately there is no single answer about what is right, as it depends on a person's preferences, but this analysis helps to make clear about the tradeoffs involved. With the VA/GLWB, some guaranteed income will always be provided, though in real terms it may end up being quite low. The effect of the compounding fees is dramatic. It is much less likely that there will be any liquidity, because fees eat away at the contract value.  In this example, there was a 12.1% chance of running out of assets with the investment-only approach. But in the median outcome, the investment-only approach could have matched income from the VA/GLWB and still experience real asset growth of almost 60%. That's the true cost of the guarantee. And making these costs more clear is the point of the white paper.


Retirement Income Research in the new issue of the Journal of Personal Finance

The Fall 2014 issue of the Journal of Personal Finance is available. It's the first issue in which Joseph Tomlinson and I have served as co-editors. A more complete announcement about the journal and its articles is included below, but first I'd like to highlight the two articles in the issue that are of more direct relevance to retirement income research. 

Portfolio Size Matters

First, the lead article by Gordon Irlam is about dynamic asset allocation over the lifecycle. I think this is a fascinating article and is well worth reading. In a recent post, I mentioned that there are three general ways to approach dynamic asset allocation: mechanical glidepaths based on age, valuation-based allocation, or the funded ratio. Gordon's research works at the intersection of mechanical glidepaths and the funded ratio, as he finds that the optimal asset allocation does depend not only on age, but it also very much depends on the ratio of one's portfolio wealth to their desired spending amount in retirement (the Relative Portfolio Size [RPS] which is 1 / withdrawal rate). 

In other words, target date funds are inadequate because they base asset allocation only on age, when the funded status of the individual (the RPS) is just as important to determining optimal asset allocation. Of course, the point of target date funds is to move people in the right direction when they don't care about investing and have no idea what their RPS is, but more sophisticated investors should be able to do better than just using a mechanical glidepath.

Calculations are made using dynamic programming, which works backward to determine the optimal asset allocation at a particular age after accounting for what will be optimal at subsequent ages. He analyzes cases with a fixed life expectancies and variable life expectancies, and also for cases with and without a motive to leave a bequest. A summary of what his figures show is:

Figure 1: Success rates are naturally higher when the RPS is higher (implying the ability to use a lower withdrawal rate to meet one's goal). The highest RPS is needed in the years around the retirement date and after. After withdrawals begin, there is less opportunity for the portfolio to grow.

Figure 2: Optimal stock allocations decrease as the RPS gets larger at any particular age. Those able to use quite low withdrawal rates to meet their goals and who have no bequest motive have already won the game (in the language of William Bernstein), and so they can make due with a low stock allocation. Conversely, those with a low RPS will maximize the chances to meet their spending goals with a more aggressive stock allocation. Taking more risk is the Hail Mary pass to try and make the plan work. 

Figure 3: This figure moves away from a fixed age of death to a variable age of death. It increases the role for balanced portfolios later in life, since uncertainty remains for how long one can be expected to remain alive.

Figure 4: This figure is really interesting, because it shows the optimal lifetime asset allocations for various individual Monte Carlo simulations. Note that there is a general tendency for a U-shaped lifetime asset allocation path. Stocks allocations are highest when young, lowest near the retirement date, and then increase again at higher ages. This is where my research with Michael Kitces about the rising equity glidepaths fits in.  It's not that the rising glidepath is always optimal, but we think it is the best approximation that can be made for someone if we are not otherwise able to incorporate information about their funded status or RPS. The figure shows that in some simulations, the stock allocation does continue to decrease at higher and higher ages. Those would be simulations where things went quite well and the RPS continues to grow throughout retirement, so it is not necessary to have any stocks.  Remember, at this stage in the research we are just looking at the optimal asset allocations to meet a fixed spending goal. There is no need for further upside potential because spending will not increase and we don't care about leaving a bequest. 

Figure 5: Now he adds a bequest motive. The retiree also cares about leaving a bequest. This is a very interesting figure because it introduces higher stock allocations at low and high ages for people with very high RPS levels. As such, if Figure 4 was re-done with the bequest motive, I'm pretty sure that Figure 5 implies that a U-shaped lifetime asset allocation will apply to even more simulations (i.e. have the lowest stock allocation at retirement, and have higher stock allocations when young or old). 

He finishes the article with some sensitivity analysis about how changing assumptions would change the optimal asset allocations, and he also shows how a more optimal asset allocation strategy that includes the RPS will reduce the amount of wealth needed at retirement relative to various rules of thumb or target date fund glidepaths.

Gordon is doing great work, and he has developed to allow users the opportunity to test their approach for different circumstances. 

The Actuarial Approach

In the next article, Ken Steiner proposes an actuarial approach to planning for taking withdrawals from savings to support retirement. Ken is a retired fellow at the Society of Actuaries, and he hosts the blog, How Much Can I Afford to Spend in Retirement?  The five step actuarial process he outlines includes:

1. Gather data

2. Make relevant assumptions about future market returns, future inflation, and remaining time horizon

3. Calculate the preliminary spendable amount, which is a mathematical calculation of the sustainable spending amount that would lead precisely to portfolio depletion (or the desired bequest amount) and the end of the planning horizon

4. Apply a smoothing technique for spending so that annual spending doesn't fluctuate too much based on what is calculated in step 3.  

5. Store the results for next year's analysis.

He finishes the article with a comparison for how his approach performs against an RMD strategy, the 4% rule, and a strategy of withdrawing 4% of the remaining blaance each year. 

This article is highly worthwhile as well.

And now for the journal announcement:

Journal of Personal Finance
Vol 13 Issue 2

The Journal of Personal Finance with co-editors Wade D. Pfau and Joe Tomlinson is available to you. The Journal is distinctive in that it is practitioner oriented and a refereed academic journal that promotes research to examine the impact of financial issues on households as well as research on the practice and profession of financial planning. The IARFC supports the academic community of the financial services industry. Take advantage of this resource written by your peers.

The Journal of Personal Finance is a member benefit of the International Association of Registered Financial Consultants (IARFC).

You can access the full online version by logging into your membership or by joining the IARFC. 
Hard copies are available to Members and Non-Members at the IARFC Store:

Journal of Personal Finance
editors' notes
Click Here to Access Your JPF

This issue begins with a paper by Gordon Irlam that applies the economists' life-cycle finance approach to determining optimal asset allocations for retirement. The author demonstrates the inappropriateness of the common rule of thumb that stock allocations should be determined by age.

He demonstrates that portfolio size also needs to be considered. Applying the life-cycle finance approach and the use of accompanying tools such as stochastic dynamic programming is gaining more attention as a research area, and it shows promise for developing practical applications.

The second paper by Janet Koposko and Douglas Hershey deals with the impact of early life influences on planning for retirement many years later. The authors conduct a survey of college students who report the extent of childhood personal finance lessons learned, and the study relates this early experience to expectations of future planning and anticipated satisfaction with retirement. They find that early experiences are likely to carry even much later in life.

The next paper by Chad Smith and Gustavo Barboza bears some similarity to the Koposko/Hershey paper, but focuses on the impact of early influences on how college students deal with current financial issues. They find that financial lessons imparted from parents to students can play a strong role in reducing the financial burdens students assume. They also find that overconfidence can play a role in leading students to take on too much debt.

In the next paper, Ken Steiner proposes an actuarial approach to planning for taking withdrawals from savings to support retirement. His particular method bears similarities to the approach actuaries take in dealing with pension plans, and involves taking a fresh look at assets and liabilities each year, and making changes to the spending plan as appropriate.

He also suggests a smoothing technique to avoid too much disruption to spending plans. Next, we present a short paper by David Swingler that may appeal to those interested in financial math. He is an engineering professor, and he demonstrates the process he has gone through to develop a rule-of-thumb to apply to a common problem in finance math regarding the present value of a series of future payments.

The paper by Terrance Martin, Michael Finke, and Philip Gibson deals with the important issue of how race and trust affect the decision to seek financial planning services and the accumulation of retirement wealth. The study reports differences between black and Hispanic households in terms of the impact of low trust on financial planning decisions.

Finally, Michael Guillemette, Russell James, and Jeff Larsen provide us with a paper in the relatively new subject area of applying neuroscience to financial planning research. They report on experiments to test whether loss aversion is altered when subjects are placed under higher cognitive load, with more demands placed on mental processing. We will likely be seeing more neuroscience research in areas such as risk tolerance assessment.

As new co-editors, we welcome the submission of research papers that uncover new insights in personal finance and show the potential to have an impact on the financial advice provided to individuals.

- Joseph A. Tomlinson, FSA, CFP™
- Wade D. Pfau, Ph.D., CFA

The Journal encourages submission of manuscripts in topics related to household financial decision making. More information regarding the Journal of Personal Finance
can be found by visiting the website


The IARFC, International Association of Registered Financial Consultants, is a non-profit professional association of financial consultants across the United States and more than 25 countries. Founded in 1984, the association serves, educates and trains financial practitioners to help their clients wisely "spend, save, invest, insure and plan for the future to achieve financial independence and peace of mind."
International Association of Registered Financial Consultants

Monday, October 6, 2014

Celebrating 20 Years of the 4% Rule

In was 20 years ago today...

The October 1994 issue of the Journal of Financial Planning contained William Bengen's article, "Determining Withdrawal Rates Using Historical Data." This article has had a truly profound effect on retirement income planning. In fact, one might argue that the article gave birth to retirement income planning. With this article, it becomes clear that post-retirement and pre-retirement investing are different beasts, as sequence of returns risk plays a bigger role when distributions are taken from the portfolio. In celebration of this 20-year anniversary, the Journal of Financial Planning currently has Bengen's original article on its main webpage. As well, Jonathan Guyton has written a wonderful cover story about Bengen's work, placing it in the historical context of where financial planning was in the 1990s, and how much things have changed in the past 20 years. 

That history lesson is especially valuable for me. In the article you will see excerpts from a short interview I had with the journal. One of the questions which was cut was: where was I 20 years ago? Well, I was just getting underway with my senior year of high school. It would still be a long time before I heard about the article. 

It's also worth noting that precisely 10 years ago in October 2004, Jonathan Guyton's first groundbreaking article on decision rules to guide retirement spending in response to portfolio performance was published.

In recognition of this anniversary, last week I spoke with financial planner Joshua Sheets on his Radical Personal Finance podcast about the history of the 4% rule. You can hear the podcast here.

Thursday, October 2, 2014

Meet Dirk Cotton, Joseph Tomlinson, Robert Powell and me in Manhattan on October 15

Details are below for this free event sponsored by MarketWatch:

MarketWatch Retirement Adviser: From Savings to Income
You’re invited: If you are planning to be in New York Oct. 15, we’d like to invite you to a free breakfast and panel discussion on how to convert retirement savings into retirement income. This Retirement Adviser event will be moderated by MarketWatch Senior Columnist and Retirement Weekly Editor Robert Powell. His guest panelists will be Wade D. Pfau, Professor of Retirement Income at The American College; Joseph A. Tomlinson, an actuary and financial planner based in Greenville, Maine; and Dirk Cotton, a financial planner in Chapel Hill, N.C. and former Fortune 500 executive. The panel will discuss withdrawal and income planning strategies, annuities, tax planning and more, and answer your questions. The event is free and begins with breakfast at 8:30 a.m. Seating is limited. For more information or to RSVP, please email by Monday, Oct. 13.

Friday, September 26, 2014

Webinar on September 30: Reasonable Portfolio Return Assumptions In Today’s Market

On Tuesday, September 30, from 1pm to 2:30 Eastern time, I will be presenting a webinar with Watermark Adviser Solutions. Anyone is welcome to attend, but please understand that the presentation is technically meant for financial advisers.
The webinars have limited capacity, and previous webinars did fill up quickly. If you sign up but then determine that you cannot attend, could you please consider cancelling your registration to make room for someone else? Thanks.

This webinar is about estimating portfolio return assumptions, and there will be lots of new material included. 

To register for this event, please follow this link:

Reasonable Portfolio Return Assumptions In Today’s Market

We hope you will join us.

Here is a general description:

As many know, there is a significant demand for financial advisers to evolve from providing only wealth management. We hear and believe that advisers should also offer retirement income planning as it is particularly relevant given the needs of today’s investors. The difference between traditional wealth management and retirement income planning is that traditional wealth management is only focused on growing wealth without regard to how the wealth will be used. Retirement income planning is a more complex planning problem which recognizes the need to sustain an income stream from the investment portfolio over the long-term. This is the situation facing thousands of investors today who are quickly approaching or already in retirement.

In addition, these investors face today’s low interest rate environment, where investment returns can be expected to be less than their historical averages. What was a reasonably conservative return assumption for investors in the early 1980s, since interest rates were much higher at that time, is likely much too high for a prudently invested portfolio looking forward from today over the next several years. There appears to be numerous ways that exist for estimating future stock returns, and experts disagree about which is the most appropriate. Some of the methodologies can even become quite technical.

During this webinar, our Director of Retirement Research, Dr. Wade Pfau, will look to identify a few basic methods which will give a broad range about future stock and bond returns in order to provide a good indication about the possibilities for today’s investors. The goal of our webinar is to help our financial adviser audience not only continue to understand a framework for retirement income planning, but also identify more accurate methods to use in the planning process with their clients.

Thursday, September 18, 2014

A Challenge and a Response for Rising Equity Glidepaths in Retirement

Jared Kizer of the BAM ALLIANCE recently wrote an article called, “An Analytical Evaluation of Rising Glidepath Claims” which concludes that there is no value in using a rising equity glidepath during retirement, contrary to the conclusions that we (Wade Pfau and Michael Kitces) reached in research published in the January 2014 Journal of Financial Planning. We welcome feedback and criticism of our research and are willing to make changes when justified (in fact, just this week we released our own follow-up research showing that rising equity glidepaths are only best in a narrow set of specific circumstances, albeit ones that are present today). But in this case, while we both have a lot of respect for the research and books generated by Jared and his colleagues at the BAM ALLIANCE (such that we took his article quite seriously), we don’t think his criticisms hold under scrutiny.

As the BAM ALLIANCE P.R. department has shared Jared’s article with a large number of media outlets, we feel it’s important to explain why we disagree with the conclusions in Jared’s article. The issue, though, is that we think there are some important problems with Jared’s statistical methodology, and so the discussion in his article and here will be hard to follow for readers who haven’t taken or don’t recall much of what they learned in their statistics or econometrics classes. Nonetheless, after the national media blast, Michael and I need to get our side of the story out there as well.

Probability of Failure

The article begins by making a useful point that if one strategy has a success rate of 80 percent while another is 81 percent, then you can’t really say with confidence that the second strategy works better. There will always be a degree of randomness in the results, and even if the difference in success rates is “statistically significant” in the way that statisticians like to use the term, there is still not much real world practical difference between the numbers.

This is why Michael and I generally frame the results as it being possible with a rising equity glidepath to get just as good of outcome, or possibly even better, using a lower average equity allocation. For example, starting retirement at 30% stocks and slowly increasing to 60% stocks can do just as well, and maybe even better, than just sticking with the 60% stock allocation over the whole retirement period (presuming the client had the tolerance to own 60% stocks in the first place and would have done so absent further advice). We did not attempt to test whether this result is “statistically significant” as an improvement, because the mere fact that a portfolio with significantly less equities getting the same result is still meaningful, though we did find indications that there may be some modest improvement in outcomes as well. In the quote Jared used from our article, we said that rising glidepaths have “the potential” to improve outcomes. The safe withdrawal research says that retirees should hold 50-75% stocks over their whole retirement as a way to minimize the risk of depleting their wealth, and we are saying that this isn’t necessarily the case. Those not comfortable with such high stock allocations can have some comfort with our conclusions.

When Jared gets to the first table in his article, he’s approaching this matter from an entirely different perspective. He’s asking a different research question than what we considered. Table 1 is showing whether rising equity glidepaths as a whole (representing the 55 different rising glidepaths we considered) can support a higher average success rate for the 4% rule than declining equity glidepaths as a whole (representing 55 more cases). The answer he finds is that there is not much statistical evidence to suggest that rising glidepaths are superior as a whole. Also, which has the higher average success rate depends on the choice of capital market expectations – which we actually wanted to illustrate, and is why we tested the analysis with a wide range of capital market assumptions.

Are rising equity glidepaths superior as a whole? Perhaps not, but that wasn’t what we were saying in the first place. As Michael explains it by analogy – our study set out to determine if reputable fund manager DFA funds provides better performance than other mutual fund families or traditionally-weighted index funds, so we compared the long-term track record of DFA to the other fund families and index funds, and concluded that DFA funds do in fact provide a benefit. Jared’s analysis is the equivalent of then coming back in, and measuring whether the AVERAGE of DFA funds AND ALL OTHER MUTUAL FUNDS outperform the indexes, with the conclusion that they do not because all the fund managers in the aggregate are underperforming by the average of their fees. He then concludes that DFA cannot possibly provide value, because the average fund manager underperforms the index. Yet the conclusion is not actually logically coherent; even if the average of all mutual funds underperform an index, it’s not proof that a particular fund can’t still be superior. We were looking for whether the best fund (or in this case, the best glidepath strategy) can be superior, not whether the average fund (or average glidepath strategy) is superior, while Jared just measured the average and then used it to make a logically inappropriate conclusion about a particular fund/glidepath strategy.

Furthermore, by including the average of all the glidepaths we tested, Jared’s analysis ends up including scenarios that we presented for the sake of thoroughness, not because we were ever actually advocating them (even after the study was published). We're more interested in whether rising glidepaths will work for situations that real retirees might consider, i.e. we don’t care too much if a 0% to 10% glidepath isn’t as good as a 10% to 0% glidepath, since neither should be very realistic choices in the first place. 

In addition, there is an important problem with what Jared does here, though he doesn’t start to discuss the problem until later in the article. The issue is that our collection of rising equity glidepaths will have a lower average stock allocation than our collection of declining equity glidepaths. Looking just at initial stock allocations, the rising glidepaths have an average value of 30% stocks, and the declining glidepaths have an average value of 70% stocks. With the 2nd set of capital market expectations, the success rate for the 4% rule with a fixed 30% stock allocation is 51%, and the success rate is 66% for a fixed 70% stock allocation.

So our rising glidepaths have a severe hurdle to overcome, especially in scenarios where the capital market assumptions are assumed to be especially bad for bonds relative to stocks. Just having the rising equity glidepaths remain competitive on these average success rate measures is a good sign, and while some investors are very pessimistic about markets and might use those low capital market assumptions, others are more optimistic about returns and the rising glidepaths hold up even better in those environments.

But the bottom line is that something close to the same basic outcomes is being achieved with a collection of glidepaths using a lower stock allocation. Risk averse retirees can feel much better now. Actually, this really was our point all along. And saying that the rising equity glidepath represents a more conservative strategy is not an indictment of rising equity glidepaths; it was actually our point!

Magnitude of Failure

Next Jared looks at the magnitudes of failure.  His second table actually shows support for rising glidepaths. He shows that the magnitudes of failure (based on our own data and results) are less severe with rising glidepaths in all three cases for capital market expectations, and that all of these results are highly statistically significant. Apparently unsatisfied with this conclusion, though, he now brings up the issue that rising glidepaths have lower average stock allocations, and suggests that perhaps the favorable results of the rising glidepaths are simply being driven by the fact that they have lower average stock allocations. Fine (since we actually made that point as well!). The problem is that his next choice of regression is not an appropriate way to try to conclude that it is only the lower stock allocations that matter, and not the direction of the glidepath as well.

Even though he left Table 1 as is (which shows the probabilities of success across the strategies, as analyzed earlier), despite this issue of average stock allocations being different, he decides that we cannot use Table 2 (which shows the same results as Table 1 but looks at magnitudes of failure instead) because now he is concerned the rising glidepaths have less stocks. To account for this, he creates a regression model to see how the magnitude of failure relates to two variables: the starting equity allocation and a dummy variable equal to “1” if it’s a rising glidepath and “0” for declining glidepaths. Running this regression suggests that it’s the initial stock allocation that matters, and that the fact that one uses a rising equity glidepath provides a net negative contribution to the results for one of the three sets of capital market expectations (results are not significant in the other two cases). In other words, this is where he really concludes that rising glidepaths are bad, and any benefit we showed actually relates (in his view) only to the fact that the retiree starts at a lower stock allocation, and not to what subsequent glidepath is.

This regression is where we have the biggest disagreement with Jared’s methodology. As indicated, his two variables are initial stock allocation and whether it is a rising glidepath path or a declining glidepath. This choice of variables effectively discards the important information about the magnitude of changes in the glidepath. In other words, there is nothing in his regression to distinguish the important difference between starting at 20% stocks and ending at 30% stocks or ending at 100% stocks. There would be 10 rising glidepaths which start at 0% stocks, and there would be 10 declining glidepaths which start at 100% stocks, and they all appear exactly the same in his regression analysis. But they are not the same! He ignores the magnitude of changes in the glidepath, which can be very material (in terms of both risk and outcome).

The reason Jared set up the regression this way is because believes that the initial stock allocation is the best available estimate for what the average stock allocation will be for the whole retirement. While a portfolio that glides from 30% in stock to 60% over 30 years would have an average allocation of 45% over time, Jared emphasizes that if the portfolio is being spent down, the dollar-weighted allocation will be closer to 30% than 60% (or that it’s at least a close enough approximation even though the dollar-weighted average will vary in each particular Monte Carlo simulation). But we think it is a severe mistake to completely ignore information we have about the magnitude of change in the glidepath. A 0% stock allocation which ends at 10% stocks will not create the same experience for a retiree as a 0% stock allocation that ends at 100% stocks. To say that both are equally well represented by the fact that their initial allocation was 0% is insufficient when one ends at 10% and the other ends at 100%. A proper regression model should do something to account for this.

So how do we correct the problem? Well, we're not all that enamored with this regression approach in the first place. The number of datapoints is somewhat artificial based on the fact that we looked at the glidepaths in 10 percentage point increments. There would have been 15 rising glidepaths if we used 20 percentage point increments, and there would have been 5,050 rising glidepaths if we used 1 percentage point increments, creating strange artificial thresholds to finding significance in the first place. That being said, I think it is still fair to overweight the initial equity allocation (as with a portfolio that spends down, the dollar-weighted allocation will be closer to the starting percentage than the ending), but let’s also do something to avoid wasting the information about how quickly the glidepath changes. For example, we could let the regression variable be equal to:

0.7 * starting equity allocation  +  0.3 * ending equity glidepath

This is still reflecting the importance of the initial stock allocation, but it is also letting the changes in glidepath play a role as well. I simply can’t understand why Jared believes that only considering the initial stock allocation is a better way to investigate this. We can re-run the regression with this new variable, and then we can look at the coefficient on the dummy variable and decide about the rising glidepath.  Here is our version of his third table in which we use this new variable better reflecting the average stock allocation over the retirement:

Dummy Variable Coefficient
Capital Market Expectations I
Capital Market Expectations II
Capital Market Expectations III

Again, we're not so excited about this regression approach in the first place, but in the context of how Jared presented his results, this table shows overwhelming evidence in favor of rising equity glidepaths. The coefficients on the rising glidepath dummy are all positive, suggesting that once we control for our approximation of the average stock allocation over retirement, rising glidepaths give substantially better results in terms reducing the magnitude of failure, relative to declining glidepaths. In addition, those t-statistics are quite large, suggesting that the results are all highly statistically significant. This table is very good news for rising glidepaths.

The important difference, and why this regression is better than the one Jared used, is that this regression also allows the degree of change in the glidepath to play a role as well. As we explained before, Jared’s approach threw away too much information because it only used the starting equity allocation. 

Beyond that, it’s also worth noting once again that we can view the fact that the rising equity glidepath is a path to starting with a more conservative portfolio is also a benefit of implementing the glidepath strategy itself. Continuing the earlier example of analyzing the benefits of using DFA funds, a Kizer-style regression analysis on DFA fund holdings might easily find that DFA funds are disproportionately tilted towards small-cap and value stocks (which isn’t surprising, as DFA’s philosophy is to implement the small-cap and value tilts of the Fama/French three-factor model). By Kizer’s methodology, this implies that using DFA funds has no benefit, because the actual benefits are simply a result of the small-cap and value tilts, not recognizing that the whole point of using DFA funds was to implement those exact tilts in the first place. In addition, while DFA’s beneficial results might be dominated by their small-cap and value tilts, they arguably provide some value in their particular implementation of the strategy as well, yet it clearly seems too narrow to suggest that DFA’s only benefit is the way they invest the tilts and not the fact that they decided to apply the tilts in the first place. Similarly, while we’d actually concur that a significant (though not exclusive) factor of the rising equity glidepath is that its initial equity weighting is lower, the path of the glidepath itself over time does matter too, and the overall value of the strategy is not just about the path of the glidepath but also the fact that it creates a framework to make it acceptable to own that lower initial equity allocation in the first place!