by Maz Jadallah
This past quarter, the S&P 500 returned its best performing quarter since Q4 2013 with a 7.7% return. Large cap stocks were the clear winners as investors sought the relative safety of higher cap stocks. The Dow did even better at 9.63%. Reinforcing investors’ flight to quality, the S&P 500 Quality Factor returned 9.87%, edging out the Momentum Factor for the first time over the prior four quarters. After a banner first half, small cap stocks lagged significantly while international markets continued to struggle under the weight of the ongoing trade feud with China and slowing GDP growth abroad.
For US stocks, the quarter looked very different from the first half of the year with the S&P 500’s performance in the quarter representing 73% of the index’s year to date return. That number is even higher at 106% for the S&P 500 Quality factor. The concentration in returns, generally a trouble sign, taken together with a scary start in October, makes one wonder whether US market indexes will struggle ahead. As we end the first week of trading in October the S&P 500 is 4.3% away from breaching it’s 200-day simple moving average. The Russell 2000 is only 0.78% away from breaching its 200-day average.
Irrespective of your view of what will happen next, many investors and their advisors are thinking about how to “play defense”. This basically means moving away from growth and momentum stocks, which have been the main drivers of performance over the last several years, and into stocks/assets that are negatively correlated. S&P had a chart (below) in their most recent “factor dashboard” that shows which factors have negative exposure to the momentum factor, tend to outperform when momentum underperforms and have a low degree of portfolio overlap. Turns out if you want to play defense, allocating to the Low Volatility High Dividend factor is a great bet.
But should you be playing defense at all? If you’re a long-term investor (not a trader), why should you do anything different today than what you did last month? Consider also that while playing defense can have benefits during drawdown periods, it also has a cost component. For example, over the past 12 months, as interest rates have risen, the Low Vol High Dividend factor in the chart above has returned just 5.3% vs. 17.9% for the S&P 500. Low Vol stocks overall (regardless of dividend yield) returned 10.7%. That’s potentially a lot to give up for short term benefits, especially if you get the timing wrong (and you will). See Does Market Timing Work by Charles Schwab.
Playing a Better Offense
Maybe instead investors should be thinking about playing better offense. Rather than trying to time the downturns in the market, playing better offense means that you’re playing the long game. The most important long game question for equity investors (in my opinion) is what do we know about the investing environment that is going to be different in the next five years than in the past five or ten? To me, that boils down to one thing – the direction of interest rates.
Increasing interest rates don’t necessarily mean poor stock performance but the odds that investors will return 10% or better are dramatically less during periods of increasing interest rates. If you, like many investors, have become a pure market index investor (and who could blame you given the market’s impressive returns since the financial crisis) that’s a really important question for you to consider. In the end, you either have to accept the odds for lower returns (stick with your playbook) or adjust your portfolio to try and counter that probability (new playbook). Both decisions are perfectly fine as long as you are comfortable with the outcomes.
For investors looking to counter potentially lower market returns, the antidote widely prescribed by asset management’s illuminati is to be more selective on both the stock and bond side of your portfolio. The prevailing wisdom is that “security” selection is going to become more important as increasing interest rates can affect industry sectors differently, and as equity correlations remain low while dispersions, the spread between good securities and bad securities, increase.
Unfortunately, being selective at either the security or manager level has historically been difficult for investors. Manager selection is hard even for the savvy investor while high fees, lock ups and adverse tax consequences all conspire to have made this a very difficult place to do well. Again, if we can rely on Vanguard and Morningstar for guidance, the prevailing wisdom in selecting active strategies has been to first look at fees since they have been predictive of the managers’ performance in the future. If you know nothing else, choose active strategies with low fees. Unfortunately, that still leaves thousands of funds to choose from!
The Moneyball Offense
As investors, what we need to make better manager selection decisions is a “moneyball” approach. We want batting averages for every manager where every disclosed stock the manager selects (every “at bat”) gets counted in the average. We want to know how often the manager gets on base (win rate), how often they hit a home run, how they play in different game environments (markets) and against different types of pitches (small, large, sector). Finally, we want a way to leverage this knowledge cheaply, easily and efficiently.
Thanks to the digitization of financial data and the accessibility of computational power, investors can now assess these types of characteristics for stock picking manager. At AlphaClone, we use the 13F-HR dataset to calculate “batting averages” for ~500 managers in our universe. Read “Clone Scores – How We Pick Managers” for a closer look into our process.
The results speak for themselves, the AlphaClone Hedge Fund Masters Index has returned 19.6% year to date as of quarter end vs 10.6% for the S&P 500 (the index was launched in December 2017). The best part is that by offering our index as an exchange traded fund (ETF), investors can retain all the benefits of passive construction including relatively low fees, transparency, tax efficiency and liquidity.
The 13F dataset and some thoughtful analysis offers investors a new way to discover and access skilled managers. Digitization of data and computational technology have changed almost every aspect of our life, it’s about time they helped us make more informed investment manager decisions.