Alpha Architect: A 3-Pronged Approach

September 12, 2018

[This ETF Industry Perspective is sponsored by Alpha Architect]

Alpha Architect is a research-driven firm that focuses heavily on educating investors on how to think about their assets from a long-term perspective. The firm offers five ETFs targeting academically supported factors and strategies. A unique aspect of the firm’s ETFs is their anti-closet-indexing philosophy and high active share, which exceeds 90% for each ETF offering. The $126 million Alpha Architect Value Momentum Trend ETF (VMOT), which packages the firm’s best ideas into a single package, debuted in 2017, and invests in the issuer’s other four ETFs. The market risk of the fund is managed via long-term trend-following indicators. Here, co-founder Wes Gray gets granular with the intricacies of the ETF’s strategy and what it offers investors.

ETF.com: Let’s dig deeper into your process with your Value Momentum Trend ETF and the associated index. There are a lot of moving pieces here. Please explain.
Gray: As the name implies, the Value Momentum Trend strategy seeks to combine our three factors into a single package (see Figure 1 below):

  1. Value Factor
  2. Momentum Factor
  3. Trend-Following Factor

In the end, the strategy doesn’t really fit neatly into a “bucket,” and is best classified as an “alternative.” The strategy is always long a global portfolio of stocks with intense value and momentum factor exposures, while the trend component manages the market exposure. If trends are positive, the strategy is essentially a long-only fund; however, as trends break down, the portfolio moves toward a market-neutral stance and is more akin to a traditional hedge fund strategy.

 

Figure 1

 

Also, we want to be clear up front regarding the VMOT strategy:

  1. First, the VMOT strategy is complex, and requires that an investor understand the mechanics of the approach.
  2. Second, because the VMOT strategy is unique and thus has the potential to deviate wildly from broad-based equity indexes, the strategy is only appropriate for investors with a long-term investment horizon, a willingness to invest the time to understand our processes, and the ability to stomach underperformance relative to standard equity benchmarks.

In short, VMOT is not for everyone.

ETF.com: Would you talk about the three factor components?
Gray: First, let’s tackle how we do “value.” Systematic value strategies, broadly described, are strategies that focus on the common stock of firms with low prices relative to fundamentals. The strategy has been discussed for nearly a century. Some claim value is dead, and we address this argument in a piece we called, “Alternative Facts About Formulaic Value Investing.” We don’t think value is dead; we simply believe value strategies can be painful, and the fact that investors think value is dead is potentially why it works in the first place. (A deeper discussion can be found here.)

Another point to highlight is that the “value is dead” argument is generally centered on systematic value strategies that use book-to-market as a metric to identify cheap stocks. Book-to-market is common among systematic value strategies, but we don’t use it at all. We are unique in the systematic value space because we focus on enterprise multiples as the centerpiece of our value approach. My colleague and co-founder of Alpha Architect Jack Vogel and I published a paper in the Journal of Portfolio Management, which suggests that enterprise multiples are arguably the “best” valuation metric, a premise supported by independent studies on U.S. stocks and international stocks.1

Our value strategy isn’t solely focused on “cheapness,” and incorporates other characteristics, such as quality and size, that we believe can enhance a plain-vanilla value strategy. A summary of our Quantitative Value strategy is described in Figure 2 and further described via our Quantitative Value Index process overview.2

 

Figure 2

 

ETF.com: How about momentum? And what makes your momentum different than others on the market, such as the methodology behind the iShares Edge MSCI U.S.A. Momentum Factor ETF (MTUM)?
Gray: Momentum is a strategy that focuses on the common stock of firms that have strong relative past performance. Momentum is generally considered to be more controversial than value, because the strategy refutes the core premise of the efficient market hypothesis, which states that stock prices always reflect fundamental values.

Nonetheless, Eugene Fama, the 2013 co-recipient of the Nobel Prize in Economics and father of the efficient market hypothesis, admits the following with respect to momentum: “The premier anomaly is momentum.”3 We have our own angles on the strategy and think our approach is both theoretically and empirically sound. A summary of our Quantitative Momentum strategy is described in Figure 3 and further described via our Quantitative Momentum Index process overview.4

 

Figure 3

 

Unlike value, and despite the empirical evidence, momentum is a more controversial factor topic. The core concern: Do the backtested results associated with momentum strategies survive after costs? Jack wrote a monster post on this subject here, which I recommend everyone read. We also covered a new paper by the folks at AQR in our blog, which sheds a lot of light on this argument.

Bottom line: There are scalability issues associated with high turnover academic-based momentum factor strategies.

And the point regarding scalability brings us full circle to the difference in our approach with others in the market. In past research, we’ve highlighted that momentum strategies are more effective when they are concentrated, have higher turnover, and are focused in smaller stocks (see here). In other words, generic academic momentum strategies have higher expected gross returns when they are structured to have the least amount of scale. This presents a conundrum for an asset manager because there is a trade-off between scalability and expected performance. The more scale you seek in the strategy, the lower the long-term expected returns are for the strategy.

For us, the momentum portfolio construction decision was easy, because we are a boutique and are not burdened with what Warren Buffett calls the “fat wallet problem.” We have the flexibility to manage a more concentrated higher-turnover version of momentum, relative to our 800 lb gorilla competitors in the marketplace, and we have done so. Both approaches are fine, but they involve costs and benefits. In expectation, our portfolio should deliver more momentum factor exposure over the long haul, but we will also have much higher volatility and tracking error relative to portfolios that more closely resemble broad indexes and/or focus on mega-cap stocks.5

ETF.com: What about the trend component?
Gray: Eric Balchunas of Bloomberg has referred to trend following on stock strategies as “investing with an airbag.” I think he nails the intent of the trend-following concept: minimize the probability of extreme losses (e.g., losing over half your wealth). Will it work all the time? Of course not. Will it eliminate day-to-day volatility? No way! In the end, if you are long-term trend following, most of the time you are a buy-and-hold investor in stocks, which can bounce all over the place and cause a ton of hate and discontent. But we believe trend following is a possible way to manage your tail risk and deliver something different than buy-and-hold, which could also be deemed “buy-and-suffer.” The last thing the world needs is another buy-and-hold closet-indexing market-beta investment.

ETF.com: How does the trend aspect work in the portfolio?
Gray: We like to keep things as simple as possible, but no simpler. We use long-term trend rules to determine the level at which we need to hedge the portfolio’s beta. The two rules we use are a 12-month moving average rule and a 12-month time-series momentum rule (the two are related, but not the same).

The rules are assessed separately to the U.S. and international portions of the portfolio. (Here are some details on our trend-following system, and Figure 4 outlines the core concept). If the trends are positive, we are long-only. When the trends turn negative, we start to layer in hedges on the portfolio. And if trends are all around negative, the portfolio can become essentially market-neutral (i.e., fully hedged). This dynamic beta exposure of the portfolio is somewhat unique in the liquid alternatives space.

 

Figure 4

 

ETF.com: What are the potential pitfalls?
Gray: There are plenty of issues with trend following. The first misconception is that trend-following is a voodoo science and doesn’t work. This is the main conclusion when statistically analyzing a buy-and-suffer portfolio relative to a trend-followed portfolio.

For example, the t-stats for differences on monthly average returns are unlikely to be different and may even favor buy-and-suffer in many samples. The Sharpe ratios may also be worse than those of buy-and-suffer. These facts often lead many researchers to suggest trend-following is futile, and this is without considering transaction costs and taxes. There is a lot of truth to these arguments; however, the goal of trend-following is to minimize large drawdowns, not necessarily maximize returns.

Will these rules continue to provide tail protection in the future? Nobody really knows. However, we believe investor psychology will likely provide chart patterns that slowly grind to the upside during bull markets, but crater at a rapid rate during bear markets. Long-term trend-following rules will likely be successful in these environments.

The second misconception is that trend-following is a perfect solution. Many who read articles highlighting the benefit of trend-following (in the past, they helped reduce drawdowns for five asset classes) fall in love with the idea without fully understanding how the rules work. Among the possible pitfalls are negative tax consequences associated with the strategy; “flash crashes” such as in October 1987; and painful whipsaw events that cause the strategy to sell stocks in a downturn—right before they turn positive again.

So, for an investor contemplating the use of trend rules, we recommend they study the potential negative consequences of these rules.

ETF.com: Who is the ideal investor for the strategy?
Gray: As I mentioned at the outset, this isn’t for everyone. And if you are a financial advisor with tracking error constraints (i.e., they can’t deviate too far from a benchmark without getting fired), we recommend VMOT as an allocation in an alternative bucket or in a core-satellite framework.

We also recommend that anyone interested in the strategy fully understand all the moving parts. The appropriate benchmark for something like this is arguably a global long/short hedge fund index or a portfolio that is around 50% cash and 50% in a passive global equity portfolio (the average beta on the Index is around .5). The strategy is unique and not going to track the S&P 500, so having appropriate expectations is important.

On the flip side, we need to be as transparent as possible about the methodology, and always open to questions on the “how” and “why” so investors better understand the risk and rewards associated with the approach. Our firm’s mission is to empower investors through education, and we are always available via our website. Investors should always feel welcome to ask us questions about our approach.


1 There’s always the concern that our favorite metric suffers from data-mining, and we address this question in a new working research paper, “Why Do Enterprise Multiples Predict Expected Stock Returns?Long story short, the metric appears to capture a risk premium and a behavioral premium, whereas book-to-market is relatively ineffective at capturing these expected premiums.

2 If you are an uber geek, we published a book on the subject of systematic value investing
3 Fama, E. and K. French, 2008, Dissecting Anomalies, The Journal of Finance, 63, pg. 1653-1678.
4 If you are an uber geek, we published a book on the subject of systematic momentum investing.
5 Probably the best discussion of this trade-off between scalability and performance is described by my friend Pat O’Shaughnessy in his article, “Alpha or Assets,” which I highly recommend reading.

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