Here’s A Portfolio Based On JP Morgan’s 2017 Outlook

February 16, 2017

This article is part of a regular series of thought leadership pieces from some of the more influential ETF strategists in the money management industry. Today's article is by Corey Hoffstein, co-founder and chief investment strategist of Boston-based Newfound Research.

J.P. Morgan recently released its 2017 long-term capital market assumptions, a valuable resource for investors looking to leverage institutional research in their own asset allocation decisions.

For those unfamiliar, capital market assumptions outline the expected return, volatility and correlation parameters that can be fed into a portfolio optimization process.

The full report sits at a hefty 94 pages. Before using the research, we believe it is prudent for investors to read the full report to understand the methodologies employed. For those less interested in narrative and more interested in implications, there is an easier way to gain insight: Build a portfolio.

That is exactly what we have done.

Using the capital market assumptions, we have built mean-variance optimal portfolios at varying risk levels. The results may surprise you. 



For a larger view, please click on the image above.


While traditionally built portfolios rely heavily on stocks and bonds, portfolios built leveraging J.P. Morgan’s capital market assumptions steer away from them. For example, the portfolio designed to have a similar risk profile as a 100% global equity portfolio (the far right of the above graph) holds less than 50% in global equities.

Alternative Income Favored

Credit-based and alternative income asset classes dominate portfolios across the risk spectrum. These asset classes are emerging market debt (USD), emerging market debt (local currency), high-yield bonds, bank loans and REITs.

Why the optimization ends up relying so heavily on credit-based asset classes can be seen in the below scatter plot of expected returns and volatilities.



For a larger view, please click on the image above.


With equity exposures in yellow and credit exposures in blue, we can see that similar return levels are expected to be achieved at significantly less risk. High-yield bonds, for example, are expected to only earn 0.5% less a year than U.S. large-cap stocks, but with 40% less volatility.

Consider, similarly, that bank loans are expected to have a risk profile in line with intermediate-term U.S. Treasurys and investment-grade corporate bonds (the two green dots below bank loans in the above graph), but with nearly double the return.

The result is that the optimizer ends up using credit in place of both stocks and bonds.


Part of the beauty of a completely systematic approach like portfolio optimization is that it is agnostic to what the investments actually are. While investors may be reluctant to go so far outside their own comfort zone, a computer simply sees numbers and performs rote calculations to find the optimal risk/reward trade-off.

Why use riskier stocks when emerging market debt and high yield can be used instead? Why use lower returning bonds when bank loans fit the bill?

This agnosticism to what the allocations represent results in what might seem, to many, a rather unusual—albeit thought-provoking—portfolio.

So while on the one hand J.P. Morgan’s outlook provides evidence that investors should strive to incorporate many of these credit-based exposures, on the other, it may be totally untenable for most investors. We should acknowledge that the optimal portfolio is first and foremost the one an investor can stick to.

We explicitly model this trade-off in our model research portfolios. Those interested in learning more about how we do it can read our white paper, “A Modern, Behavior-Aware Asset Allocation.”


Balancing Short-Term Risk & Long-Term Opportunity

It is also important to recognize that not only are J.P. Morgan’s capital market assumptions estimates, but that they are estimates for annualized returns for the next seven to 10 years.

Today if we use the BofA Merrill Lynch US High Yield Option-Adjusted Spread as a measure of “value,” credit-based instruments are not cheap. In fact, sitting at 3.93% at the time of writing puts us in the most expensive quartile of markets going back to 1996.

In Newfound’s Multi-Asset Income portfolio, we seek to balance potential short-term risk and long-term opportunity in two ways. First, we strategically allocate using a Sharpe parity approach, dynamically emphasizing the asset classes that provide the most yield with the least volatility. We then apply a trend-following process to remove asset classes we deem to be exhibiting significant downside risk.

We believe this dual approach to managing risk can help create a stable, balanced portfolio in healthy market environments while providing a means of de-risking in unhealthy ones.

For do-it-yourselfers, there are a variety of ETFs available today in each of these credit categories that can be used to incorporate exposure.

Regardless of approach, the implications behind J.P. Morgan’s capital market assumptions are clear: Credit-based exposures will be key to unlocking the optimal risk/reward trade-off for portfolios over the next decade.

Newfound Research uses BKLN, SNLN, PCY, EMLC, HYG, JPHY and VNQ in its portfolios and may hold positions at the time of publishing. Founded in August 2008, Newfound Research is a quantitative asset management firm based in Boston. Investing at the intersection of quantitative and behavioral finance, Newfound Research is dedicated to helping clients achieve their long-term goals with research-driven, quantitatively managed portfolios, while simultaneously acknowledging that the quality of the journey is just as important as the destination. For more information about Newfound Research, call us at 617-531-9773, visit us at or email us at [email protected]. For a list of relevant disclosures, click here.


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