Our Alpha Signals: What’s Worked Thus Far
The WisdomTree U.S. Multifactor Index (WTUSMF), launched in June 2017, selects its basket of 200 stocks based on four equally weighted alpha signals: Low Correlation, Momentum, Quality and Value. While 14 months is a short time frame in which to analyze the returns of factors proven to outperform over years and decades, we will review which factors have worked thus far, and how WTUSMF is positioned from a factor and fundamental characteristic perspective after its most recent quarterly rebalance.
Technical and Fundamental Factor Returns
Using S&P 500 Index constituents, we can analyze the performance across the four factors by using WisdomTree’s methodology, and the relative performance between the Good and Bad categories.
By design, the Good, Okay and Bad categories each contain roughly a third of the total market cap of the S&P 500. In comparing the Good baskets, we can see that Quality has been the best-performing factor in terms of absolute return, returning 25.15%, while Low Correlation has been the worst-performing factor. The Good basket underperformed the Bad basket by more than 17%.
S&P 500 Factor Returns
We can make a few conclusions from these factor returns:
- Big Companies Outperforming: The run in the S&P 500 has been powered by a narrowing segment of the market, the biggest companies in the Index. Because these biggest companies are more highly correlated with the returns of a market cap-weighted index, they tend to rank poorly according to our Low Correlation factor and are in the Bad category. We can see an almost 1,800 basis point spread between Good/Bad correlation groups.
- Momentum and Quality, Late Cycle: Momentum and Quality factors typically outperform late in the cycle, and we are seeing that play out in real time. For WTUSMF, Momentum is uniquely designed to use risk-adjusted returns rather than absolute returns. This is to tap into the long-term absolute return potential of the factor, but with an eye towards improving risk-adjusted returns.
- Quality and Growth in favor, Value Out: Seeing Good Value underperforming Bad Value (i.e., expensive “growth stocks”) also comes as no surprise, as this has been a persistent trend for several years now and is typical in the middle-to-late stage of a bull market. Many investors seem to be bracing their portfolios for Value mean-reversion, but recent returns suggest we are not quite there yet.
We have done an analysis on long-term returns for these factors, which helps support our conviction in their long-term staying power.
Low Correlation: What It Means for the “Tech Behemoths”
Two of the top contributors to the returns of the S&P 500, particularly in 2018, have been Apple and Amazon. Since its inception, WTUSMF has been under-weight in Apple by 3.36% and in Amazon by 2.33%. As a result, these companies have been the two biggest detractors from performance relative to the S&P 500,1 making the outperformance of WTUSMF even more impressive.
In the table below we show our factor scores which rank companies between 0-100%, of Apple and Amazon at each of our five live quarterly rebalances. At our most recent September rebalance, Apple was included in WTUSMF for the third time, this time on the back of an improved Momentum score.
In our eligible universe of 800 stocks, both companies have tended to rank in the bottom third by Low Correlation. To be included, their scores for the other three factors need to make up for that low score. At this September’s rebalance, Apple had scores in the top third on the other three factors, which offset an 18% Low Correlation score.
Quarterly Rebalance Scores
Balanced Factor Exposures
While we believe different factors perform well during different times of the cycle, it is difficult to forecast which stage of the cycle we are in. This means that an equal weighting of our four desired factors is a natural starting point.
In the table below we show the index weights of WTUSMF and the S&P 500 in the Good, Okay and Bad groups, as of the WTUSMF rebalance screening date. As mentioned above, we see that the S&P 500 has roughly one-third of its weight in each group. The WisdomTree Index has its weight evenly distributed across factors, with weights of roughly 52% to 56% in each Good group and, just as importantly, significant under-weights in the Bad groups. What this tells us is that WTUSMF is tapping into the material factor tilts as we designed it to, without giving too much influence to any single factor. While each factor tilt was improved by the rebalance, the biggest changes came from the two technical factors, Momentum and Correlation, which we often see, given the fast-moving nature of these factor scores.
Lower Price/Earnings and Improved Quality Metrics
Another way our factor tilts manifest themselves is in the valuations of WTUSMF compared to the S&P 500. The Value tilt is evident in the price-to-earnings (P/E) discount, and higher Quality from return-on-equity (ROE) and return-on-asset (ROA) improvements relative to the market. Another factor that we tap into via our alternative weighting mechanism is Size, which can be seen in our material over-weight to mid-caps.
Our quarterly rebalance plays a critical role in maintaining balanced factor exposures that should drive long-term outperformance. Over this time frame, Momentum and Quality have been the best-performing factors, while Low Correlation and Value have lagged. Given the cyclicality of factors and the challenges of factor timing, we believe our high factor tilt and higher active share approach is positioned to add relative value across different market environments.
1Sources: WisdomTree, FactSet. Data from 6/29/17 to 8/31/18. Holdings for WTUSMF are displayed daily on the website. Holdings subject to change.
Matt Wagner joined WisdomTree in May 2017 as a member of the Research team. He is responsible for research on WisdomTree’s products and communicating the firm’s views on the markets. Matt started his career at Morgan Stanley, working as an analyst in Treasury Capital Markets from 2015 to 2017 where he focused on unsecured funding planning, execution and risk management. Matt graduated from Boston College in 2015 with a B.A. in International Studies with a concentration in Economics. Matt is a holder of the Chartered Financial Analyst designation.