All Asset All Access

All Asset All Access, September 2018

In this issue, Research Affiliates discusses the funds’ long-term outcomes relative to peers, views on emerging market currencies and recent research centered on momentum.

Rob Arnott, founding chairman and head of Research Affiliates, explains the All Asset strategies’ historical return and diversification characteristics relative to peers; Brandon Kunz, senior vice president of multi-asset strategies, discusses the outlook for emerging market currencies; and Omid Shakernia, senior vice president of asset allocation, discusses how recent research informs the asset allocation process. As always, their insights are in the context of the PIMCO All Asset and All Asset All Authority funds.

Q: How has the All Asset suite fared over the long term relative to its peers within the asset allocation and alternative landscape?

Arnott: Before we turn to the results, a quick refresher as to why we launched the All Asset strategies bears mention. Recall that 16 years ago, we sought to create a different product – one not readily available in the marketplace. Our mission then – as it is today – was to address three investor concerns within a single package: 1) to improve long-term real return potential, especially when mainstream stocks and bonds offer low prospective returns; 2) to provide a comprehensive product to help investors diversify away from their overwhelming reliance on equity market risk; and 3) to counter mainstream assets’ vulnerability to inflation by emphasizing markets that are positively correlated with inflation. Even with benign inflation over the life of the funds, we’ve been able to deliver attractive real returns while maintaining our inflation-hedging potential.

While we prefer to gauge our progress against a variety of benchmarks,1 let’s now turn to the question above and observe whether we met our objectives relative to our “peers.” As a start, we’ll consider all mutual funds within All Asset’s Morningstar category group, Tactical Allocation, as well as a second group, Allocation and Alternative. We include the broader Allocation category (of which Tactical Allocation is a subcategory) in this second grouping because All Asset invests across multiple asset classes, and we include the Alternatives category since many investors use All Asset as a liquid diversifier against their mainstream stocks and bonds. 2

At its launch on 31 July 2002, the All Asset Fund had 19 Tactical Allocation peers and 629 peers in the second category group (541 in Allocation and 88 in Alternative). Fast-forward 16 years (to 31 July 2018), and nearly half the funds in the second category group have closed, shuttered or merged. What remain are 15 survivors in the Tactical Allocation category and 342 in the secondary category group (272 in Allocation and 71 in Alternative).

Figure 1 shows two tables of performance and rankings for the PIMCO All Asset and All Asset All Authority Funds. The first table highlights fund annualized performance for trailing one, three, five and 10-year periods, and since inception, as of 31 August 2018. The second table shows absolute ranks and group sizes for tactical allocation and the second category group (categories defined by Morningstar) for time horizons up to 10 years, also as of 31 August 2018. Data is detailed within, and links to current fund performance are available below the table.

For the most recent quarter-end performance data for the All Asset All Authority funds, please click on the links below:

Over the span of All Asset’s life, surviving funds within this second category group delivered on average a return of 5.90% per annum net of fees, a correlation to the S&P 500 of 79.1% and an equity beta of 0.64x. Similarly, the average fund within the Tactical Allocation category, the All Asset Fund’s Morningstar category, delivered an average return of 6.02% per annum net of fees, a correlation to the S&P 500 of 82.9% and an equity beta of 0.57x. Now compare this to a 60/40 portfolio (proxied by 60% S&P 500, 40% Bloomberg Barclays U.S. Aggregate Bond Index), which delivered on average a correlation to the S&P 500 of 98.7% and an equity beta of 0.60x. Isn’t it astounding that, over this horizon, this group of supposedly diversifying funds has on average displayed comparable or more equity risk than a balanced 60/40 portfolio?

In stark contrast, All Asset Fund’s since-inception annualized return, at 6.96% (institutional shares, net of fees) over the same timeframe, is more than 15% and 17% higher than the average fund in the surviving Tactical Allocation and secondary category groups, respectively. All Asset’s beta to the S&P 500 of 0.39x is within the lowest 15th percentile rank versus the  secondary category group and within the bottom decile versus the Tactical Allocation category, and its correlation of 61% similarly hovers near or within the bottom decile in both instances. To be sure, All Asset’s historical results may be an indication of why it is used by many investors as a vehicle for diversification. When equities are winning, investors don’t necessarily need for us to shoot the lights out. But when equities are languishing (or worse), investors typically need diversifying sources of return potential. In that context, it is certainly noteworthy that no funds within the Tactical Allocation group and just three across the larger second category group delivered a higher since-inception return at a comparable or lower beta to the S&P 500 than All Asset.

We deliberately aim for All Asset to be a diversifying portfolio. As such, we find it unsurprising that over the full timespan, All Asset Fund’s return per unit of mainstream equity beta has been in the top 7% and top 5% of the Tactical Allocation and secondary category groups, respectively. In bear markets when the S&P 500 was down since All Asset’s inception, All Asset cut the average loss for both surviving category groups by approximately half, with down-market-capture beating 93% and 88% of peers in the Tactical Allocation and secondary category groups, respectively.

How has All Asset All Authority Fund, All Asset’s sister fund, fared relative to its peers since its launch on 31 October 2003? Of the 23 mutual funds classified in the Tactical Allocation category and the 695 funds (598 in Allocation and 97 in Alternatives) in the secondary category group3 that existed at All Authority’s launch, just 18 for the former and a tad over half, or 356, for the latter have survived over this near-15-year span (282 in Allocation and 74 in Alternative). Among these survivors, All Authority’s return per unit of beta over this full span ranks within the highest decile of those peers and within the highest 12th percentile rank of its own category group, Tactical Allocation. Its average return in down markets beats 87% of its peers in the second category group (and 88% for solely Tactical Allocation peers).

Do these comparative outcomes surprise us? Hardly! They are entirely consonant with our mission of seeking to deliver high long-term real returns in a manner that provides investors strong diversification away from mainstream equity risk.

Q: Could you describe your outlook on emerging market (EM) currencies in light of their recent sell-off versus the U.S. dollar?

Kunz: We acknowledge the fear associated with recent predicaments in Argentina and Turkey, and the corresponding spillover effects leading to the pronounced sell-off in a broader basket of EM currencies. While it’s human nature to react swiftly and hit the sell button, a closer look at the countries making up the All Asset funds’ EM currency exposure reveals a different story. As discussed by my colleagues in a recent article,4 an examination of external debt, foreign exchange reserves and current account balances points to low risks of a funding crisis for most EM countries – particularly for countries with the largest weights in the underlying PIMCO EM funds across which we tactically manage exposure in the All Asset suite.

In our view, investing in EM currencies (i.e., buying EM currencies and investing in the short-term bills of the constituent countries) offers the highest risk-adjusted return prospects in all of All Asset’s opportunity set over the next five to seven years. As of 31 July, according to Research Affiliates’ long-term asset class return estimates, we forecast passive exposure to EM currencies (as represented by the J.P. Morgan ELMI index) to offer annualized nominal returns of 5.9% over the coming decade. Among our asset class return estimates, EM currencies trail only the 6.8% offered by EM local bonds (as represented by the J.P. Morgan GBI-EM Index), the 7.0% offered by developed ex U.S. equities (as represented by the MSCI EAFE Index) and the 9.0% offered by unhedged exposure to EM equities (as represented by the MSCI EM Index), all of which share one thing in common: Their currencies trade at discounts, EM in particular, to the U.S. dollar.

Our overall return forecast for EM currencies is driven by a host of individual modeling considerations, not the least of which is the yield of such exposure. As of 31 July, the current yield on passive exposure to EM currencies had risen to 4.6%, more than a percentage point higher than the 3.5% yield available at the end of 2017. Notably though, the exceedingly short duration of this investment renders today’s current yield a less reliable indication of what the average yield will be throughout the longer time horizons over which our return forecasts may be most accurate. It’s for this reason that we at Research Affiliates generate yield forecasts (i.e., equilibrium cash rates for each country) driven by GDP growth prospects, demographic trends, savings preferences and the speed at which central banks move toward equilibrium, among other considerations. After using these inputs to derive forecasts for the average cash rate of each EM country, we then combine them based on the weight of each constituent country within the passive index to derive today’s nominal yield forecast of 4.0% for EM currency exposure.5

In addition to creating cash rate forecasts, we also estimate movements in the real exchange rate between countries (i.e., currency valuation changes). For modeling purposes, these forecasts are decomposed into two parts: 1) reversion toward relative purchasing power parity (PPP) and 2) adjustments associated with productivity differentials between countries. On the relative PPP front, and after rolling up country-by-country estimates into the constituent weights of the passive index, EM currencies now trade at a 12.6% discount versus the U.S. dollar (as of 31 July 2018), nearly seven percentage points cheaper than their 5.7% discount versus the U.S. dollar a mere four months prior. Today, if we spread out reversion toward equilibrium PPP over a full decade, EM currencies would stand to appreciate by approximately 1.3% per year. (And continued negative EM currency returns of -3.01% in August, as represented by the JPM ELMI Plus index, only bolster this return potential).

Further EM currency appreciation is possible due to higher relative productivity growth. EM countries have faster-growing populations and younger workforces working up the steeper portion of their learning curves (i.e., undergoing higher productivity growth) than their older developed market counterparts that are closer to peak productivity (i.e., high productivity levels). Historically, higher productivity growth has led to higher real exchange rate appreciation, all else equal. Putting these two components together, we estimate EM currencies are now poised to appreciate by 1.9% per year on top of their already elevated 4.0% yield potential, leading to our all-in return forecast of 5.9% per annum over the coming decade.

We calibrate these longer-term forecasts using shorter-horizon signals from our proprietary business cycle model and momentum considerations, which help inform tactical trading. With recent weakness in EM currency returns, 12-month momentum has now fallen from positive 2.2% at the end of June to negative 0.3% at the end of July. While the magnitude of this negative momentum is not large enough to materially impact our tactical trading, it does decrease our marginal willingness to increase EM currency exposure at this juncture. Offsetting this negative signal on the price momentum front to some degree is the signal from our business cycle model, which continues to indicate modestly below-average probability of economic slowdown for a GDP-weighted aggregation of EM countries (said differently, modestly above-average probability of accelerating GDP relative to recent trend growth).  As of the end of July, such slowdown probabilities stood at 43%; while this number is above the recent low of 41% at the beginning of the year, it remains well below its most recent peak of 67% in the third quarter of 2015. Nevertheless, at these levels the business cycle signal today for EM as a whole is not strong enough for us to merit larger tactical trades into procyclical EM currency exposure.

Given these tactical considerations, we remain comfortable maintaining today’s elevated exposure to EM currencies while we wait for stronger signals to justify further buying (or selling). Notably, the All Asset funds also hold tactically elevated exposure to EM local currency bonds and unhedged EM equity strategies, all of which stand poised to benefit from similar return tailwinds should real exchange rates converge toward equilibrium valuations over the coming decade.

Q: How have Research Affiliates’ ongoing research efforts contributed to enhancing the asset allocation process for the All Asset strategies?

Shakernia: The All Asset strategies are driven by a systematic, model-driven allocation process that encodes our core investment belief,6 which is that the largest and most persistent active management opportunity is long-horizon mean reversion. A key benefit of using a model-driven process is that it embeds an “emotion-free” discipline to harvest these persistent sources of return, which often requires taking uncomfortable contrarian trades. We seek to diversify away from mainstream assets, take profits from past winners and reallocate into out-of-favor assets, all while accounting for shorter-term price movements.

So are the series of models that drive the All Asset strategies a static, unchanging asset allocation infrastructure; a “set it and forget it” process? Of course not! The asset allocation team at Research Affiliates engages in a continuous process of research toward enhancing our models, refining both our inputs (insights into the capital markets’ expectations of return and risk) and outputs (improvements in the “craftsmanship” of our portfolio implementation). This process involves a thorough assessment of relevant published research across academic and practitioner communities, as well as leveraging the substantial in-house research we conduct at Research Affiliates – much of which we end up publishing as well.

The primary inputs to our asset allocation process are our long-term capital market forecasts.7 One area of active research has been on refinements to our expectations of fair value for equities and bonds. We have presented our recent research in this area in several Research Affiliates articles titled the “Holy Grail,”8 “CAPE Fear”9 and “The Bubble That Never Came.”10 Our empirical research findings suggest that 1) accounting for macroeconomic volatility helps refine our estimation of equity fair value, 2) CAPE (cyclically adjusted price-to-earnings ratio) is a powerful predictor of long-term market returns, in our opinion; and 3) macroeconomic fundamentals meaningfully drive real interest rates, and as such, low yields do not imply U.S. Treasuries are overvalued. Given that short-term return forecasts always come with wide bands of uncertainty, the modeling benefits from input enhancements tend to be realized over a longer horizon, as compared to the modeling benefits from output enhancements.

Let’s now turn to recent enhancements to the allocation process related to the model output, or our portfolio craftsmanship. Based on research findings, we have included a process of monthly staggered rebalancing within the All Asset strategies in order to complement our longer-horizon mean reversion estimates with shorter-term momentum. Essentially, we create 12 “tranches” of the model and rebalance one-twelfth of the portfolio each month, thus intentionally staggering our trading to target. Intuitively, this process is akin to creating one-year holding periods for each tranche. By extending each tranche’s holding period to one year, we allow recent winners to drift higher in allocation before rebalancing, enabling us to ride momentum: seeking to harvest incremental return from time series momentum11 while also materially reducing strategy turnover.

As before, model enhancements such as these are backed by our investment research findings. This particular example draws from our recent research article, “Hobbled by Benchmarks,”12 in which we examine a 30-plus-year backtest of a tactical asset allocation process for a broadly diversified universe of 15 major asset classes. We studied the efficacy of tactical asset allocation based on the following components of asset class expected returns: carry (starting yield plus long-term average real income growth) and value (an asset class’s negative trailing-five-year returns). Carry is a proxy for asset class expected returns if valuations stay constant, while value is a proxy for expected returns if valuations mean-revert toward historical norms.

As Figure 2 shows, a staggered rebalancing approach has historically delivered positive excess returns by improving the efficacy of both the carry and valuation signals, with incremental gains peaking at about 12 months. The result is intuitive: The efficacy of tactical asset allocation based on carry and value improves when we slow down the rebalancing frequency (through staggered rebalancing) to better match the long-horizon nature of those signals. Since the All Asset strategies are primarily a valuation-driven investment approach that executes a contrarian philosophy across a similarly broad universe of asset classes, we believe these results are directly applicable: We therefore now include staggered rebalancing into our process in seeking to enhance our tactical allocation performance while also significantly reducing turnover, along with its associated market impact and transactions costs.

Figure 2 is a table showing the efficacy of tactical asset allocation based on carry and value signals improves when rebalancing frequency is slowed down to better match the long-horizon nature of those signals. Excess return is the highest at 18-month rebalancing periods, at 0.84% for carry and 1.39% for value. Details for seven relancing periods, excess return, and turnover are within.

Further reading

Recent editions of All Asset All Access offer in-depth insights from Research Affiliates on these key topics:

  • Outlook for emerging markets and the distinction between real and nominal returns (August 2018)
  • Views on the Powell Fed and positioning for a potential inflation surprise (July 2018)
  • What drives short U.S. equity positions and how momentum can complement value investing (June 2018)
  • The economic and market impact of protectionist trade policies (May 2018)
  • The longevity of tech-dominated corporate earnings growth (April 2018)
  • Positioning for volatile markets and the link between equity valuations and macro conditions (March 2018)

The All Asset strategies represent a joint effort between PIMCO and Research Affiliates. PIMCO provides the broad range of underlying strategies – spanning global stocks, global bonds, commodities, real estate and liquid alternative strategies – each actively managed to maximize potential alpha. Research Affiliates, an investment advisory firm founded in 2002 by Rob Arnott and a global leader in asset allocation, serves as the sub-advisor responsible for the asset allocation decisions. Research Affiliates uses their deep research focus to develop a series of value-oriented, contrarian models that determine the appropriate mix of underlying PIMCO strategies in seeking All Asset’s return and risk goals.

1 As an example, in the August 2018 issue, we discussed the concept of sustainable spending income. In previous editions, we’ve shared our thoughts on how All Asset has fared relative to both its official and other applicable benchmarks.

2 For the Tactical Allocation and the second category group, we looked at the oldest share class of all U.S.-domiciled funds classified within the broad Morningstar category groups, Allocation and Alternative, with the exception of Target-Date subcategories. Included within the Allocation category is the Tactical Allocation subcategory, which is where the All Asset and All Asset All Authority Funds are classified. Both universes include only surviving funds with available tickers and return data.

3 We use the same criteria as for the analysis of All Asset (e.g., we exclude Target-Date subcategories from the sample, use the oldest share class of each strategy, and focus on only U.S.-domiciled mutual funds).

4 Chris Brightman, Michele Mazzoleni and Jonathan Treussard, “Pundits Predicting Panic in Emerging Markets,” Research Affiliates (June 2018).

5 For more of an apples-to-apples comparison for our forecasted yield versus current yield, one can adjust the latter downward by our 1.6% relative inflation differential forecast between the U.S. and the EM region (here again represented by the J.P. Morgan ELMI index).

6 For details, please read the Research Affiliates paper, “Our Investment Beliefs,” by Chris Brightman, Jonathan Treussard and Jim Masturzo (October 2014).

7 The Research Affiliates Asset Allocation Interactive tool specifies long-term return and volatility estimates for a wide range of asset classes.

8 Michele Mazzoleni, Omid Shakernia and Michael Aked, “Quest for the Holy Grail: The Fair Value of the Equity Market,” Research Affiliates (March 2017)

9 Rob Arnott, Vitali Kalesnik and Jim Masturzo, “CAPE Fear: Why CAPE Naysayers Are Wrong,” Research Affiliates (January 2018)

10 Michele Mazzoleni and Ashish Garg, “The Bubble That Never Came (and Other Misconceptions about Treasury Bonds),” Research Affiliates (October 2017)

11 Brian Hurst, Yao Hua Ooi and Lasse Heje Pedersen, “A Century of Evidence on Trend-Following Investing,” The Journal of Portfolio Management, 44(1), 15-29 (Fall 2017)

12 Michael Aked, Rob Arnott, Omid Shakernia and Jonathan Treussard, “Hobbled by Benchmarks,” The Journal of Portfolio Management, 44(2), 74-88 (2018)

The Author

Robert Arnott

Founder and Chairman, Research Affiliates

Brandon Kunz

Partner, Head of Multi-Asset Solution Distribution, Research Affiliates

Omid Shakernia

Multi-Asset Strategies, Research Affiliates


Related Funds


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