Portfolios in Wonderland & The Weird Portfolio

September 7, 2017

8 minute read

The current outlook for stocks, bonds, and traditionally allocated portfolios is near all-time historical low levels.
Even though short-term performance may vary, investors looking for long-term success may have to expand their investment palette to earn returns anywhere close to those realized in the past.
A mean-variance optimal portfolio using the current market forecasts relies heavily on more unique asset classes such as U.S. Small Caps, Emerging Market Debt (Local Currency), and Levered Loans.
While investors may not be willing to hold such a weird looking “60/40” portfolio, thinking outside the box may be necessary going forward.

Note: After recent podcasts with Meb Faber and Jeremy Schwartz, we received a large number of requests for our “Portfolios in Wonderland” presentation and the “weird” portfolio I discussed that was a result of the current market environment. We thought we would take the content within the presentation and make it available as a commentary.

Portfolios in Wonderland

“Begin at the beginning,” the King said, very gravely, “and go on till you come to the end: then stop.”

At the beginning of each year, many institutions publish their capital market assumptions, providing an outlook for expected returns, volatilities, and correlations. These glossy brochures go well beyond data, however, and often veer wildly into what we like to call macro tourism: data-based market prognostications about macro-economic conditions and their implications for markets.

Unfortunately, for most investors, while macro tourism makes for an entertaining read, the track record of most predictors is quite poor. Simply put, markets do not behave in the linear, domino-like fashion that most predictions are laid out as. There are simply too many non-linear relationships to make accurate predictions; it is like trying to predict the exact weather in Boston a year out.

That said, if we are willing to restrain ourselves, meaningful forecasts can be made. We may not be able to predict the exact weather, but there is a good chance the temperature will be between 65℉ and 80℉.

While exact predictions may be futile, evidence suggests that by taking a long-term view (7-10 years) and focusing on stable variables, we can make similar long-term forecasts for most major asset classes. For U.S. investors, simply getting an understanding of what will likely happen with U.S. stocks and bonds can provide a tremendous amount of insight for the rest of our financial plan.

So, let’s begin with U.S. equities. Here, we turn to the Shiller CAPE. For those not familiar yet with this metric, it is a 10-year smoothed price-to-earnings measure for the U.S. equity market. The aim of smoothing over 10-year periods is to get a measure that is less sensitive to market cycles, creating a “cyclically-adjusted” P/E (“CAPE”).

We can see that today’s CAPE is highly elevated compared to past measures.

The implication of a high CAPE reading is that stocks are expensive: you are paying more per unit of fundamental value.

In our piece Anatomy of a Bull Market, and the subsequent follow-up, we demonstrated that over the long-run, valuation changes have contributed little to U.S. equity performance. While they can vary wildly in the short-run, they have historically exhibited mean-reverting behavior: cheap tends to get more expensive, and expensive tends to get cheaper.

In the short-run (7-10 year periods), however, valuation changes can have a very meaningful impact on returns. Where the Shiller CAPE sits today, if real earnings grew at 2% a year, the market would have to return 0% for the next 13 years for the Shiller CAPE to revert back to its long-term average. Even if earnings accelerate and grow at 4% a year, it would still take nearly a decade of 0% returns.

The other option, of course, is that we experience a bear market and price falls fast enough to cause the Shiller CAPE to revert. A 30% decline in prices would just-about do it.

Now, we’re not here to forecast gloom and doom. Rather, we believe there are a few simple, potential answers. One is that Shiller CAPE is simply the wrong measurement of valuation. Another is that this time really is different: valuations, for a variety of reasons, are simply structurally higher and will remain that way. Or, we could simply argue that we expect market returns to be lower than average going forward, allowing earnings to catch up.

If we “hope for the best and prepare for the worst,” assuming the latter case is prudent. Using earnings growth, dividend yield, and valuation figures, we can forecast expected equity returns over the next 7-10 years. The current estimate – around 3.5% after inflation – is incredibly low by historical standards.

Estimating the expected future return for bonds is much easier. Buying a bond today and holding it to maturity ensures that you lock in the yield-to-worst, regardless of what happens with interest rates.

What about bond funds? For most funds – which are near constant maturity/duration in nature – changing rates have not made as large an impact as most people might assume. This was the topic of our prior commentary Did Declining Rates Actually Matter?, whose results are depicted below.

What we find is that while declining rates did have an impact on bond index returns, the vast majority of the return was due to the actual coupon level itself. In other words, what we should focus on, in the current environment, is not trying to accurately predict whether rates will go up or down, but rather the coupon yield we will be receiving.

Which is, today, incredibly low.

“Why, sometimes I've believed as many as six impossible things before breakfast.”

Believing that traditional core U.S. fixed income will deliver a return profile anything close to what they have historically delivered is misguided at best. We can actually use a very simple rule – the “2x duration minus 1” rule – to forecast bond fund returns. This rule is highly useful because it is derived to provide guidance regardless of what interest rates do.[1]

Simply, we take the current year and add to it 2x the duration of the bond fund and subtract one. This provides us the forecast year. The current yield-to-maturity – or, yield-to-worst – is then our estimate through that year.

AssetYield to MaturityDurationThroughPredicted Nominal ReturnPredicted Real  ReturnU.S. Aggregate Bonds2.59%5.720282.59%0.29%1-3 Yr. Treasuries1.37%1.920201.37%-0.93%3-7 Yr. Treasuries1.91%4.520251.91%-0.39%7-10 Yr. Treasuries2.34%7.520312.34%0.04%10-20 Yr. Treasuries2.55%10.020362.55%0.25%20+ Yr. Treasuries3.00%17.320503.00%0.70%IG Corporates3.53%8.220323.53%1.23%

Source: iShares. Calculations by Newfound Research. Figures as of June 2017.

It should be no surprise, then, that forecasted U.S. aggregate real returns are near all-time lows.

What makes the current market environment so strange is that while stock and bond valuations have historically been negatively correlated, they became simultaneously cheap in the 1980s and are now simultaneously expensive.

While the negative correlation allowed a traditionally constructed 60/40 stock/bond mix to provide a semi-constant expected return profile (or, at least, a reasonably floored one) from 1880-1970, the post 1970 period has seen the portfolio shift from very cheap to very expensive.

This means that the outlook for a 60/40 portfolio today is near the lowest it has ever been: our rough math puts the real-return near 2.2%.

“My dear, here we must run as fast as we can, just to stay in place. And if you wish to go anywhere you must run twice as fast as that.”

There is a significant danger of low expected returns for financial planning. Old rules – using a 60/40 portfolio with a 4 or 5% withdrawal rate – may no longer be safe. We highlighted this risk in our recent commentary Impact of High Equity Valuations on Safe Withdrawal Rates. Below are two graphs from that commentary. In the first, the historical results of applying a 4% withdrawal rate to a 60/40 stock/bond allocation. In the second, the same rules applied, but historical results are adjusted downward such that the long-term average return matches the future long-term expected returns.

We see that what was once safe may no-longer be. There is no silver bullet to this problem. Rather, a number of solutions will likely be necessary. While we will be writing several follow-up articles in the coming weeks, some immediate ideas for dealing with this problem are:

Increased savings rates during accumulation.
Significantly reducing fees during retirement.
Dynamic withdrawal plans.
Active risk-management plans to address sequence risk.
Looking outside traditional stocks and bonds for other return generators.

The Weird Portfolio

Fortunately, one of the many positive trends of the last two decades has been the down-stream movement of many asset classes and investment styles once relegated to the world of accredited investors, into low-cost, liquid fund packaging. Exposures like levered loans and emerging market debt, and strategies like equity long/short and global macro, are now available for investor use to complement a traditionally allocated stock/bond portfolio.

If J.P. Morgan’s outlook is right, these types of positions may be more important today than ever before.

Plotting expected return versus risk allows us to see that positions like U.S. Large Cap equities and U.S. Aggregate Bonds may no longer be attractive. Rather, positions like U.S. Small Caps, Emerging Market Debt (Local Currency), and Levered Loans may provide much more bang for the investment buck.

One of our favorite exercises is to take capital market assumptions like these and run them through a traditional mean-variance optimization, targeting the same risk profile of a standard 60/40 stock/bond mix.[2] Unlike us, the optimizer has no attachment to a particular asset class: it simply looks to maximize return for our stated risk target.

The result, today, is a pretty weird looking portfolio.

(We should note that if we perform the same exercise using capital market assumptions from BNY Mellon, BlackRock, or Research Affiliates, the results are very similar).

We see:

Despite targeting the same risk profile of a 60/40 portfolio, traditional equities and bonds only make up about 1/3^rd.
U.S. large-caps and U.S. aggregate bonds are almost nowhere to be found.
Equity exposure is dominated by emerging market and U.S. small-cap exposure.
Bond exposure is almost entirely long-dated U.S. Treasuries. This may seem odd, given that long-term Treasuries offer one of the worst risk-reward trade-offs according to J.P. Morgan’s outlook. However, J.P. Morgan’s correlation assumptions make them an incredible diversifier to increased volatility of the equity sleeve.
Traditional “return generators” are largely replaced by credit-like exposures (e.g. high yield bonds, levered loans, emerging market debt, and REITs).
Traditional “risk mitigators” are largely replaced by diversifying alternative exposures.

We’ll be the first to admit that almost no investor would be willing to actually hold this portfolio. With nearly 25% of the portfolio in gold and long-term U.S. Treasuries, the tracking error alone would drive most investors mad.

And all just for what amounts to a 1% bump in expected return. While 1% may not seem like much, in a low-return world it is nearly a 25% increase from a traditional stock/bond mix.

While few would feel comfortable implementing this weird portfolio outright, we believe that this exercise provides at least a hint of guidance for investors today: thinking outside the box may be necessary going forward.

Conclusion

“But I don’t want to go among mad people," Alice remarked.

"Oh, you can’t help that," said the Cat: "we’re all mad here. I’m mad. You’re mad."

"How do you know I’m mad?" said Alice.

"You must be," said the Cat, "or you wouldn’t have come here.”

[1] See For Constant-Duration or Constant-Maturity Bond Portfolios, Initial Yield Forecasts Return Best near Twice Duration by Gabriel Lozada for technical details.

[2] Technically, we run a simulation-based mean-variance optimization in effort to account for estimation risk and come up with a more stable allocation profile.

Corey is co-founder and Chief Investment Officer of Newfound Research, a quantitative asset manager offering a suite of separately managed accounts and mutual funds. At Newfound, Corey is responsible for portfolio management, investment research, strategy development, and communication of the firm's views to clients.

Prior to offering asset management services, Newfound licensed research from the quantitative investment models developed by Corey. At peak, this research helped steer the tactical allocation decisions for upwards of $10bn.

Corey is a frequent speaker on industry panels and contributes to ETF.com, ETF Trends, and Forbes.com’s Great Speculations blog. He was named a 2014 ETF All Star by ETF.com.

Corey holds a Master of Science in Computational Finance from Carnegie Mellon University and a Bachelor of Science in Computer Science, cum laude, from Cornell University.

You can connect with Corey on LinkedIn or Twitter.