*This post is available for download as a PDF here.*

**Summary**

- In a world of anemic asset returns, tax management may help significantly contribute to improving portfolio returns.
- Ideally, asset location decisions would be made with full investor information, including goals, risk tolerances, tax rates, and distribution of wealth among account types.
- Without perfect information, we believe it is helpful to have both tax-deferred and tax-managed model portfolios available.
- We explore how tax-adjusted expected returns can be created, and how adjusting for taxes affects an optimized portfolio given today’s market outlook.

*Before we begin, please note that we are not Certified Public Accountants, Tax Attorneys, nor do we specialize in tax management. Tax law is complicated and this commentary will employ sweeping generalizations and assumptions that will certainly not apply to every individual’s specific situation. This commentary is not meant as advice, simply research. Before making any tax-related changes to your investment process, please consult an expert.*

**Tax-Managed Thinking**

We’ve been writing a lot, recently, about the difficulties investors face going forward.[1][2][3] It is our perspective that the combination of higher-than-average valuations in U.S. stocks and low interest rates in core U.S. bonds indicates a muted return environment for traditionally allocated investors going forward.

There is no silver bullet to this problem. Our perspective is that investors will likely have to work hard to make many marginal, but compounding, improvements. Improvements may include reducing fees, thinking outside of traditional asset classes, saving more, and, for investors in retirement, enacting a dynamic withdrawal plan.

Another potential opportunity is in tax management.

I once heard Dan Egan, Director of Behavioral Finance at Betterment, explain tax management as an *orthogonal* improvement: i.e. one which could seek to add value *regardless *of how the underlying portfolio performed. I like this description for two reasons.

First, it fits nicely into our framework of compounding marginal improvements that do not necessarily require just “investing better.” Second, Dan is the only person, besides me, to use the word “orthogonal” outside of a math class.

Two popular tax management techniques are tax-loss harvesting and asset location. While we expect that tax-loss harvesting is well known to most (selling investments at a loss to offset gains taken), asset location may be less familiar. Simply put, asset location is how investments are divided among different accounts (taxable, tax-deferred, and tax-exempt) in an effort to maximize post-tax returns.

**Asset Location in a Perfect World**

Taxes are a highly personal subject. In a perfect world, asset location optimization would be applied to each investor individually, taking into account:

- State tax rates
- Federal tax rates
- Percentage of total assets invested in each account type

Such information would allow us to run a very simple portfolio optimization that could take into account asset location.

Simply, for each asset, we would have three sets of expected returns: an after-tax expected return, a tax-deferred expected return, and a tax-exempt expected return. For all intents and purposes, the optimizer would treat these three sets of returns as completely different asset classes.

So, as a simple example, let’s assume we only want to build a portfolio of U.S. stocks and bonds. For each, we would create three “versions”: Taxable, Tax-Deferred, and Tax-Exempt. We would calculate expected returns for *U.S. Stocks – Taxable*, *U.S. Stocks – Tax-Deferred*, and *U.S. Stocks – Tax-Exempt*. We would do the same for bonds.

We would then run a portfolio optimization. To the optimizer, it would look like six asset classes instead of two (since there are three versions of stocks and bonds). We would add the constraint that the sum of the weights to Taxable, Tax-Deferred, and Tax-Exempt groups could not exceed the percentage of our wealth in each respective account type. For example, if we only have 10% of our wealth in Tax-Exempt accounts, then *U.S. Stocks – Tax Exempt + U.S. Bonds – Tax Exempt must be *equal to 10%.

Such an approach allows for the explicit consideration of an individual’s tax rates (which are taken into account in the adjustment of expected returns) as well as the distribution of their wealth among different account types.

Case closed.[4]

**Asset Location in a Less Than Perfect World**

Unfortunately, the technology – and expertise – required to enable such an optimization is not readily available for many investors.

As an industry, the division of labor can significantly limit the availability of important information. While financial advisors may have access to an investor’s goals, risk tolerances, specific tax situation, and asset location break-down, asset managers do not. Therefore, asset managers are often left to make sweeping assumptions, like infinite investment horizons, defined and constant risk tolerances, and tax indifference.

Indeed, we currently make these very assumptions within our QuBe model portfolios. Yet, we think we can do better.

For example, consider investors at either end of the spectrum of asset location. On the one end, we have investors with the vast majority of their assets in tax-deferred accounts. On the other, investors with the vast majority of their wealth in taxable accounts. Even if two investors at opposite ends of the spectrum have an identical risk tolerance, their optimal portfolios are likely different. Painting with broad strokes, the tax-deferred investor can afford to have a larger percentage of their assets in tax-inefficient asset classes, like fixed income and futures-based alternative strategies. The taxable investor will likely have to rely more heavily on tax-efficient investments, like indexed equities (or active equities, if they are in an ETF wrapper).

Things get much messier in the middle of the spectrum. We believe investors have two primary options:

- Create an optimal tax-deferred portfolio and try to shift tax-inefficient assets into the tax-deferred accounts and tax-efficient assets into taxable accounts. Investor liquidity needs need to be carefully considered here, as this often means that taxable accounts will be more heavily tilted towards more volatile equities while bonds will fall into tax-deferred accounts.
- Create an optimal tax-deferred portfolio and an optimal taxable portfolio, and invest in each account accordingly. This is, decidedly, sub-optimal to asset location in a perfect world, and should even under most scenarios be sub-optimal to Option #1, but it should be preferable to simply ignoring taxes. Furthermore, it may be easier from an implementation perspective, depending on the rebalancing technology available to you.

With all this in mind, we have begun to develop tax-managed versions of our QuBe model portfolios, and expect them to be available at the beginning of Q4.

**Adjusting Expected Returns for Taxes**

To keep this commentary to a reasonable length (as if that has ever stopped us before…), we’re going to use a fairly simple model of tax impact.

At the highest level, we need to break down our annual expected return into three categories: unrealized, externally realized, and internally realized.

- Unrealized: The percentage of the total return that remains un-taxed. For example, the expected return of a stock that is bought and never sold would be 100% unrealized (ignoring, for a moment, dividends and end-of-period liquidation).
- Externally Realized: The percentage of total return that is taxed due to asset allocation turnover. For example, if we re-optimize our portfolio annually and incur 20% turnover, causing us to sell positions, we would say that 20% of expected return is externally realized.
- Internally Realized: The percentage of total return that comes from internal turnover, or income generated, within our investment. For example, the expected return from a bond may be 100% internally realized. Similarly, a very active hedge fund strategy may have a significant amount of internal turnover that realizes gains.

Using this information, we can fill out a table, breaking down for each asset class where we expect returns to come from as well as within that category, what type of tax-rate we can expect. For example:

For example, in the table above we are saying we expect 70% of our annual U.S. equity returns to be unrealized while 30% of them will be realized at a long-term capital gains rate. Note that we also explicitly estimate what we will be receiving in qualified dividends.

On the other hand, we only expect that 35% of our hedge fund returns to be unrealized, while 15% will be realized from turnover (all at a long-term capital gains rate) and the remaining 50% will be internally realized by trading within the fund, split 40% short-term capital gains and 60% long-term capital gains.For example, in the table above we are saying we expect 70% of our annual U.S. equity returns to be unrealized while 30% of them will be realized at a long-term capital gains rate. Note that we also explicitly estimate what we will be receiving in qualified dividends.

Obviously, there is a bit of art in these assumptions. How much the portfolio turns over within a year must be estimated. What types of investments you are making will also have an impact. For example, if you are investing in ETFs, even very active equity strategies can be highly tax efficient. Mutual funds on the other hand, potentially less so. Whether a holding like Gold gets taxed at a Collectible rate or a split between short- and long-term capital gains will depend on the fund structure.

Using this table, we can then adjust the expected return for each asset class using the following equations:

Where,

In English,

- Take the pre-tax return and subtract out the amount we expect to come from qualified dividend yield.
- Take the remainder and multiply it by the total blended tax rate we expect from externally and internally realized gains.
- Add back in the qualified dividend yield, after adjusting for returns.

As a simple example, let’s assume U.S. equities have a 6% expected return. We’ll assume a 15% qualified dividend rate and a 15% long-term capital gains rate. We’ll ignore state taxes for simplicity.

Our post-tax expected return is, therefore 6% – (6%-2%)*(30%*15%) – 2%*15% = 5.52%.

We can follow the same broad steps for all asset classes, making some assumptions about tax rates and expected sources of realized returns.

(For those looking to take a deeper dive, we recommend Betterment’s *Tax-Coordinated Portfolio *whitepaper[5]*, *Ashraf Al Zaman’s *Tax Adjusted Portfolio Optimization and Asset Location* presentation[6], and Geddes, Goldberg, and Bianchi’s *What Would Yale Do If It Were Taxable? *paper[7].)

**How Big of a Difference Does Tax Management Make? **

So how much of a difference does taking taxes into account really make in the final recommended portfolio?

We explore this question by – as we have so many times in the past – relying on J.P. Morgan’s capital market assumptions. The first portfolio is constructed using the same method we have used in the past: a simulation-based mean-variance optimization that targets the same risk level as a 60% stock / 40% bond portfolio mix.

For the second portfolio, we run the same optimization, but adjust the expected return[8] for each asset class.

We make the following assumptions about the source of realized returns and tax rates for each asset class (note that we have compressed the above table by combining rates together after multiplying for the amount realized by that category; e.g. realized short below represents externally and internally realized short-term capital gains).

Again, the construction of the below table is as much art as it is science, with many assumptions embedded about the type of turnover the portfolio will have and the strategies that will be used to implement it.

Collectible | Ordinary Income | Realized Short | Realized Long | Unrealized | Dividend | |

Alternative – Commodities | 0% | 0% | 10% | 20% | 70% | 0% |

Alternative – Event Driven | 0% | 0% | 26% | 53% | 21% | 0% |

Alternative – Gold | 30% | 0% | 0% | 0% | 70% | 0% |

Alternative – Long Bias | 0% | 0% | 26% | 53% | 21% | 1% |

Alternative – Macro | 0% | 0% | 26% | 53% | 21% | 0% |

Alternative – Relative Value | 0% | 0% | 26% | 53% | 21% | 0% |

Alternative – TIPS | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – Cash | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – Govt (Hedged) ex US | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – Govt (Not Hedged) ex US | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – INT Treasuries | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – Investment Grade | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – LT Treasuries | 0% | 100% | 0% | 0% | 0% | 0% |

Bond – US Aggregate | 0% | 100% | 0% | 0% | 0% | 0% |

Credit – EM Debt | 0% | 100% | 0% | 0% | 0% | 0% |

Credit – EM Debt (Local) | 0% | 100% | 0% | 0% | 0% | 0% |

Credit – High Yield | 0% | 100% | 0% | 0% | 0% | 0% |

Credit – Levered Loans | 0% | 100% | 0% | 0% | 0% | 0% |

Credit – REITs | 0% | 100% | 0% | 0% | 0% | 0% |

Equity – EAFE | 0% | 0% | 10% | 20% | 70% | 2% |

Equity – EM | 0% | 0% | 10% | 20% | 70% | 2% |

Equity – US Large | 0% | 0% | 10% | 20% | 70% | 2% |

Equity – US Small | 0% | 0% | 10% | 20% | 70% | 2% |

We also make the following tax rate assumptions:

- Ordinary Income: 28%
- Short-Term Capital Gains: 28%
- Long-Term Capital Gains: 28%
- Qualified Dividend: 15%
- Collectibles: 28%
- Ignore state-level taxes.

The results of both optimizations can be seen in the table below.

Tax-Deferred | Tax-Managed | |

Equity – US Large | 3.9% | 5.3% |

Equity – US Small | 5.9% | 7.0% |

Equity – EAFE | 3.3% | 4.8% |

Equity – Emerging Markets | 11.1% | 12.0% |

Sum | 24.2% | 29.1% |

Bond – US Aggregate | 0.1% | 0.1% |

Bond – Int US Treasuries | 0.6% | 0.4% |

Bond – LT US Treasuries | 12.4% | 12.2% |

Bond – Investment Grade | 0.0% | 0.0% |

Bond – Govt (Hedged) ex US | 0.3% | 0.1% |

Bond – Govt (Not Hedged) ex US | 0.3% | 0.2% |

Sum | 13.8% | 13.1% |

Credit – High Yield | 6.2% | 3.9% |

Credit – Levered Loans | 11.8% | 8.9% |

Credit – EM Debt | 4.2% | 2.7% |

Credit – EM Debt (Local) | 5.2% | 3.5% |

Credit – REITs | 8.6% | 8.1% |

Sum | 36.0% | 27.1% |

Alternative – Commodities | 4.0% | 3.9% |

Alternative – Gold | 11.3% | 13.9% |

Alternative – Macro | 6.8% | 8.6% |

Alternative – Long Bias | 0.1% | 0.1% |

Alternative – Event Driven | 1.6% | 2.2% |

Alternative – Relative Value | 0.5% | 1.3% |

Alternative – TIPS | 1.6% | 0.8% |

Sum | 26.0% | 30.8% |

Broadly speaking, we see a shift *away *from credit-based asset classes (though, they still command a significant 27% of the portfolio) and *towards *equity and alternatives.

We would expect that if the outlook for equities improved, or we reduced the expected turnover within the portfolio, this shift would be even more material.

It is important to note that at least some of this difference can be attributed to the simulation-based optimization engine. Percentages can be misleading in their precision: the basis point differences between assets within the bond category, for example, are not statistically significant changes.

And how much difference does all this work make? Using our tax-adjusted expected returns, we estimate a 0.20% increase in expected return between tax-managed and tax-deferred versions right now. As we said: no silver bullets, just marginal improvements.

**What About Municipal Bonds?**

You may have noticed municipal bonds are missing from the above example. What gives?

Part of the answer is theoretical. Consider the following situation. You have two portfolios that are identical in every which way (e.g. duration, credit risk, liquidity risk, et cetera), except one is comprised of municipal bonds and one of corporate bonds. Which one do you choose?

The one with the higher post-tax yield, right?

This hypothetical highlights two important considerations. First, the idea that municipal bonds are for taxable accounts and corporate bonds are for tax-deferred accounts overlooks the fact that investors should be looking to maximize post-tax return *regardless* of asset location. If municipal bonds offer a better return, then put them in both accounts! Similarly, if corporate bonds offer a more attractive return after taxes, then they should be held in taxable accounts.

For example, right now the iShares iBoxx $ Investment Grade Corporate Bond ETF (LQD) has a 30-day SEC yield of 3.16%. The VanEck Vectors ATM-Free Intermediate Municipal Index ETF (ITM) has a 30-day SEC yield of just 1.9%. However, this is the taxable equivalent to an investor earning a 3.15% yield at a 39.6% tax rate.

In other words, LQD and ITM offer a nearly identical return within in a taxable account for an investor in the highest tax bracket. Lower tax brackets imply *lower *taxable equivalent return, meaning that LQD may be a superior investment for these investors. (Of course, we should note that municipal bonds are not corporate bonds. They often are often less liquid, but of higher credit quality.)

Which brings up our second point: taxes are highly personal. For a wealthy investor, an ordinary income tax of 35% could make municipal bonds far more attractive than they are for an investor only paying a 15% ordinary income tax rate.

Simply put: solving the when and where of municipal bonds is not always straight forward. We believe the best approach is account for them as a standalone asset class within the optimization, letting the optimizer figure out how to maximize post-tax returns.

**Conclusion**

We believe that a low-return world means that many investors will have a tough road ahead when it comes to achieving their financial goals. We see no silver bullet to this problem. We do see, however, many small steps that can be taken that can compound upon each other to have a significant impact. We believe that asset location provides one such opportunity and is therefore a topic that deserves far more attention in a low-return environment.

[1] See *The Impact of High Equity Valuations on Safe Withdrawal Rates – * https://blog.thinknewfound.com/2017/08/impact-high-equity-valuations-safe-retirement-withdrawal-rates/

[2] See *Portfolios in Wonderland & The Weird Portfolio* – https://blog.thinknewfound.com/2017/08/portfolios-wonderland-weird-portfolio/

[3] See *The Butterfly Effect in Retirement Planning* – https://blog.thinknewfound.com/2017/09/butterfly-effect-retirement-planning/

[4] Clearly this glosses over some very important details. For example, an investor that has significant withdrawal needs in the near future, but has the majority of their assets tied up in tax-deferred accounts, would significantly complicate this optimization. The optimizer will likely put tax-efficient assets (e.g. equity ETFs) in taxable accounts, while less tax-efficient assets (e.g. corporate bonds) would end up in tax-deferred accounts. Unfortunately, this would put the investor’s liquidity needs at significant risk. This could be potentially addressed by adding expected drawdown constraints on the taxable account.

[5] https://www.betterment.com/resources/research/tax-coordinated-portfolio-white-paper/

[6] http://www.northinfo.com/documents/337.pdf

[7] https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2447403

[8] We adjust volatility as well.

## Addressing Low Return Forecasts in Retirement with Tactical Allocation

By Nathan Faber

On September 25, 2017

In Risk Management, Sequence Risk, Weekly Commentary

This post is available for download as a PDF here.SummaryOver the past few weeks, we have written a number of posts on retirement withdrawal planning.

The first was about the potential impact that high core asset valuations – and the associated muted forward return expectations – may have on retirement.

The second was about the surprisingly large impact that small changes in assumptions can have on retirement success, akin to the Butterfly Effect in chaos theory. Retirement portfolios can be very sensitive to assumed long-term average returns and assumptions about how a retiree’s spending will evolve over time.

In the first post, we presented a visualization like the following:

Historical Wealth Paths for a 4% Withdrawal Rate and 60/40 Stock/Bond AllocationSource: Shiller Data Library. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.The horizontal (x-axis) represents the year when retirement starts. The vertical (y-axis) represents the years post-retirement. The coloring of each cell represents the savings balance at a given point in time. The meaning of each color as follows:

Green:Current account value greater than or equal to initial account value (e.g. an investor starting retirement with $1,000,000 has a current account balance that is at least $1,000,000).Yellow:Current account value is between 75% and 100% of initial account valueOrange:Current account value is between 50% and 75% of the initial account value.Red:Current account value is between 25% and 50% of the initial account value.Dark Red:Current account value is between 0% and 25% of initial account value.Black: Current account value is zero; the investor has run out of money.We then recreated the visualization, but with one key modification: we adjusted the historical stock and bond returns downward so that the long-term averages are in line with realistic future return expectations[1] given current valuation levels. We did this by subtracting the difference between the actual average log return and the forward-looking long return from each year’s return. With this technique, we capture the effect of subdued average returns while retaining realistic behavior for shorter-term returns.

Historical Wealth Paths for a 4% Withdrawal Rate and 60/40 Stock/Bond Allocation with Current Return ExpectationsSource: Shiller Data Library. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.One downside of the above visualizations is that they only consider one withdrawal rate / portfolio composition combination. If we want the see results for withdrawal rates ranging from 1% to 10% in 1% increments and portfolio combinations ranging from 0/100 stocks/bonds to 100/0 stocks/bonds in 20% increments, we would need sixty graphs!

To distill things a bit more, we looked at the historical “success” of various investment and withdrawal strategies. We evaluated success on three metrics:

relative to starting wealth. [2]As a quick refresher, below we present the ASR for various withdrawal rate / risk profile combinations over a 30-year retirement horizon first using historical returns and then using historical returns adjusted to reflect current valuation levels. The CSR and Ulcer Index table illustrated similar effects.

Absolute Success Rate for Various Combinations of Withdrawal Rate and Portfolio Composition – 30 Yr. HorizonAbsolute Success Rate for Various Combinations of Withdrawal Rate and Portfolio Composition with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. HorizonSource: Shiller Data Library. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.Overall, our analysis suggested that retirement withdrawal rates that were once safe may now deliver success rates that are no better – or even worse – than a coin flip.

The combined conclusion of these two posts is that the near future looks pretty grim for retirees and that an assumption that is slightly off can make the outcome even worse.

Now, we are going to explore a topic that can both mitigate low growth expectations and adapt a retirement portfolio to reduce the risk of a bad planning assumption. But first, some history.

How the 4% Rule StartedIn 1994, Larry Bierwirth proposed the 4% rule, and William Bengen expanded on the research in the same year.[3], [4]

In the original research, the 4% rule was derived assuming that the investor held a 50/50 stock/bond portfolio, rebalanced annually, withdrew a certain percentage of the initial balance, and increased withdrawals in line with inflation. 4% is the highest percentage that could be withdrawn without ever running out of money over an historical 30-year retirement horizon.

Graphically, the 4% rule is the minimum value shown below.

Maximum Inflation Indexed Withdrawal to Deplete a 60/40 Portfolio Over a 30 Yr. HorizonSince its publication, the rule has become common knowledge to nearly all people in the field of finance and many people outside it. While it is a good rule-of-thumb and starting point for retirement analysis, we have two major issues with its broad application:

For example, if we adjust the stock and bond historical returns using the estimates from Research Affiliates (discussed previously) and replicate the analysis Bengen-style, the safe withdrawal rate is a paltry 2.6%.

Maximum Inflation Indexed Withdrawal to Deplete a 60/40 Portfolio Over a 30 Yr. Horizon using Current Return EstimatesSource: Shiller Data Library and Research Affiliates. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.While this paints a grim picture for retirement planning, it’s not likely how one would plan their financial future. If you were to base your retirement planning solely on this figure, you would have to save 54% more for retirement to generate the same amount of annual income as with the 4% rule, holding everything else constant.

In reality, even with the low estimates of forward returns, many of the scenarios had safe withdrawal rates closer to 4%. By putting a multi-faceted plan in place to reduce the risk of the “bad” scenarios, investors can hope for the best while still planning for the worst.

One aspect of a retirement plan can be a time-varying asset allocation scheme.

Temporal Risk in RetirementConventional wisdom says that equity risk should be reduced as one progresses through retirement. This is what is employed in many “through”-type target date funds that adjust equity exposure beyond the retirement age.

If we heed the “own your age in bonds” rule, then a retiree would decrease their equity exposure from 35% at age 65 to 5% at the end of a 30-year plan horizon.

Unfortunately, this thinking is flawed.

When a newly-minted retiree begins retirement, their success is highly dependent on their first few years of returns because that is when their account values are the largest. As they make withdrawals and are reducing their account values, the impact of a large drawdown in dollar terms is not nearly as large. This is known as

sequence risk.As a simple example, consider three portfolio paths:

These returns work about to the expected returns on a 60/40 portfolio using Research Affiliates’ Yield & Growth expectations, and the drawdown is approximately in line with the drawdown on a 60/40 portfolio over the past decade. We will assume 4% annual withdrawals and 2% annual inflation with the withdrawals indexed to inflation.

3 Portfolios with Identical Annualized Returns that Occur in Different OrdersPortfolio C fares the best, ending the 30-year period with 12% more wealth than it began with. Portfolio B makes it through, not as comfortably as Portfolio C but still with 61% of its starting wealth. Portfolio A, however, starts off stressful for the retiree and runs out of money in year 27.

Sequence risk is a big issue that retirement portfolios face, so how does one combat it with dynamic allocations?

The Rising Glide Path in RetirementKitces and Pfau (2012) proposed the rising glide path in retirement as a method to reduce sequence risk.[5] They argued that since retirement portfolios are most exposed to market risk at the beginning of the retirement period, they should start with the lowest equity risk and ramp up as retirement progresses.

Based on Monte Carlo simulations using both capital market assumptions in line with historical values and reduced return assumptions for the current environment, the paper showed that investors can maximize their success rate and minimize their shortfall in bad (5

^{th}percentile) scenarios by starting with equity allocations of between 20% and 40% and increasing to 60% to 80% equity allocations through retirement.We can replicate their analysis using the

reducedhistorical return data, using the same metrics from before (ASR, CSR, and the Ulcer Index) to measure success, comfort, and stress, respectively.Absolute Success Rate for Various Equity Glide Paths with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateComfortable Success Rate for Various Equity Glide Paths with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateUlcer Index for Various Equity Glide Paths with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateSource: Shiller Data Library and Research Affiliates. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.Note that the main diagonal in the chart represents static allocations, above the main diagonal represents the decreasing glide paths, and below the main diagonal represents increasing glide paths.

Since these returns are derived from the historical returns for stocks and bonds (again, accounting for a depressed forward outlook), they capture both the sequence of returns and shifting correlations between stocks and bonds better than Monte Carlo simulation. On the other hand, the sample size is limited, i.e. we only have about 4 non-overlapping 30 year periods.

Nevertheless, these data show that there was not a huge benefit or detriment to using either an increasing or decreasing equity glide path in retirement based on these metrics. If we instead look at minimizing expected shortfall in the bottom 10% of scenarios, similar to Kitces and Pfau, we find that a glide path starting at 40% rising to around 80% performs the best.

However, it will still be tough to rest easy with a plan that has an ASR of around 60 and a CSR of around 30 and an expected shortfall of 10 years of income.

With these unconvincing results, what can investors do to improve their retirement outcomes through prudent asset allocation?

Beyond a Static Glide PathThere is no reason to constrain portfolios to static glide paths. We have said before that the risk of a static allocation varies considerably over time. Simply dictating an equity allocation based on your age does not always make sense regardless of whether that allocation is increasing or decreasing.

If the market has a large drawdown, an investor should want to avoid this regardless of where they are in the retirement journey. Missing drawdowns is always beneficial as long as enough upside is subsequently realized.

In recent papers, Clare et al. (2017 and 2017) showed that trend following can boost safe withdrawal rates in retirement portfolios by managing sequence risk. [6],[7]

The million-dollar question is, “how tactical should we be?”

The following charts show the ASR, CSR, and Ulcer index values for static allocations to stocks, bonds, and a simple tactical strategy that invests in stocks when they are above their 10-month simple moving average (SMA) and in bonds otherwise.

The charts are organized by the minimum and maximum equity exposures along the rows and columns. The charts are symmetric across the main diagonal so that they can be compared to both increasing and decreasing equity glide paths.

The equity allocation is the minimum of the row and column headings, the tactical strategy allocation is the absolute difference between the headings, and the bond allocation is what’s needed to bring the total allocation to 100%.

For example, the 20% and 50% column is a portfolio of 20% equities, 30% tactical strategy, and 50% bonds. It has an ASR of 75, a CSR of 40, and an Ulcer index of 22.

Absolute Success Rate for Various Tactical Allocation Bounds Paths with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateComfortable Success Rate for Various Tactical Allocation Bounds with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateUlcer Index for Various Tactical Allocation Bounds with Average Stock and Bond Returns Equal to Current Expectations – 30 Yr. Horizon with a 4% Initial Withdrawal RateSource: Shiller Data Library and Research Affiliates. Calculations by Newfound Research. Analysis uses real returns and assumes the reinvestment of dividends. Returns are hypothetical index returns and are gross of all fees and expenses. Results may differ slightly from similar studies due to the data sources and calculation methodologies used for stock and bond returns.These charts show that being tactical is extremely beneficial under these muted return expectations and that being highly tactical is even better than being moderately tactical.

So, what’s stopping us from going whole hog with the 100% tactical portfolio?

Well, this is a case where a tactical strategy can reduce the risk of not making it through the 30-year retirement at the risk of greatly increasing the ending wealth. It may sound counterintuitive to say that ending with too much extra money is a risk, but when our goal is to make it through retirement comfortably, taking undue risks come at a cost.

For instance, we know that while the tactical strategy may perform well over a 30-year time horizon, it can go through periods of significant underperformance in the short-term, which can lead to stress and questioning of the investment plan. For example, in 1939 and 1940, the tactical strategy underperformed a 50/50 portfolio by 16% and 11%, respectively.

These times can be trying for investors, especially those who check their portfolios frequently.[8] Even the best-laid plan is not worth much if it cannot be adhered to.

Being tactical enough to manage the risk of having to make a major adjustment in retirement while keeping whipsaw, tracking error, and the cost of surpluses in check is key.

Sizing a Tactical SleeveIf the goal is having the smallest tactical sleeve to boost the ASR and CSR and reduce the Ulcer index to acceptable levels in a low expected return environment, we can turn back to the expected shortfall in the bad (10

^{th }percentile) scenarios to determine how large of a tactical sleeve to should include in the portfolio. The analysis in the previous section showed that being tactical could yield ASRs and CSRs in the 80s and 90s (dark green). This, however, requires a tactical sleeve between 50% and 70%, depending on the static equity allocation.Thankfully, we do not have to put the entire burden on being tactical: we can diversify our approaches. In the previous commentaries mentioned earlier, we covered a number of topics that can improve retirement results in a low expected return environment.

While each modification might only result in a small, incremental improvement in retirement outcomes, the compounding effect can be very beneficial.

The chart below shows the required tactical sleeve size needed to minimize shortfalls/surpluses for a given improvement in the annual returns (0bp through 150bps).

Tactical Allocation Strategy Size Needed to Minimize 10% Expected Shortfall/Surplus with Average Stock and Bond Returns Equal to Current Expectations for a Range of Annualized Return Improvements – 30 Yr. Horizon with a 4% Initial Withdrawal RateFor a return improvement of 125bps per year over the current forecasts for static U.S. equity and bond portfolios, with a static equity allocation of 50%, including a tactical sleeve of 20% would minimize the shortfall/surplus.

This portfolio essentially pivots around a static 60/40 portfolio, and we can compare the two, giving the same 125bps bonus to the returns for the static 60/40 portfolio.

Comparison of a Tactical Allocation Enhanced Portfolio with a Static 60/40 Portfolio with Average Stock and Bond Returns Equal to Current Expectations + 125bps per year – 30 Yr. Horizon with a 4% Initial Withdrawal RateIn addition to the much more favorable statistics, the tactically enhanced portfolio only has a downside tracking error of 1.1% to the static 60/40 portfolio.

Conclusion: Being Dynamic in RetirementFrom this historical analysis, high valuations of core assets in the U.S. suggest a grim outlook for the 4% rule. Predetermined dynamic allocation paths through retirement can help somewhat, but merely specifying an equity allocation based on one’s age loses sight of the changing risk a given market environment.

The sequence of market returns can have a large impact on retirement portfolios. If a drawdown happens early in retirement, subsequent returns may not be enough to provide the tailwind that they have in the past.

Investors who are able to be fee/expense/tax-conscious and adhere to prudent diversification may be able to incrementally improve their retirement outlook to the point where a modest allocation to a sleeve of tactical investment strategies can get their portfolio back to a comfortable success rate.

Striking a balance between shortfall/surplus risk and the expected experience during the retirement period along with a thorough assessment of risk tolerance in terms of maximum and minimum equity exposure can help dictate how flexible a portfolio should be.

In our QuBe Model Portfolios, we pair allocations to tactically managed solutions with systematic, factor based strategies to implement these ideas.

While long-term capital market assumptions are a valuable input in an investment process, adapting to shorter-term market movements to reduce sequence risk may be a crucial way to combat market environments where the low return expectations come to fruition.

[1] Specifically, we use the “Yield & Growth” capital market assumptions from Research Affiliates. These capital market assumptions assume that there is no valuation mean reversion (i.e. valuations stay the same going forward). The adjusted average nominal returns for U.S. equities and 10-year U.S. Treasuries are 5.3% and 3.1%, respectively, compared to the historical values of 9.0% and 5.3%.

[2] Normally, the Ulcer Index would be measured using true drawdown from peak, however, we believe that using starting wealth as the reference point may lead to a more accurate gauge of pain.

[3] Bierwirth, Larry. 1994. Investing for Retirement: Using the Past to Model the Future. Journal of Financial Planning, Vol. 7, no. 1 (January): 14-24.

[4] Bengen, William P. 1994. “Determining Withdrawal Rates Using Historical Data.” Journal of Financial Planning, vol. 7, no. 4 (October): 171-180.

[5] Pfau, Wade D. and Kitces, Michael E., Reducing Retirement Risk with a Rising Equity Glide-Path (September 12, 2013). Available at SSRN: https://ssrn.com/abstract=2324930

[6] Clare, A. and Seaton, J. and Smith, P. N. and Thomas, S. (2017). Can Sustainable Withdrawal Rates Be Enhanced by Trend Following? Available at SSRN: https://ssrn.com/abstract=3019089

[7] Clare, A. and Seaton, J. and Smith, P. N. and Thomas, S. (2017) Reducing Sequence Risk Using Trend Following and the CAPE Ratio. Financial Analysts Journal, Forthcoming. Available at SSRN: https://ssrn.com/abstract=2764933

[8] https://blog.thinknewfound.com/2017/03/visualizing-anxiety-active-strategies/