Stocks continued their ascent to new highs into the new year, led by names at the forefront of artificial intelligence (AI) such as Meta, NVIDIA, Amazon, AMD, and Super Micro Computer. International stocks also edged higher, with the MSCI Europe, Asia, and Far East (EAFE) Index climbing 5.8% through the first quarter (MSCI) while bonds have treaded water at close to breakeven for the year thus far.
On the economic front, inflation has continued to inch lower, although the Federal Reserve continues to be concerned about labor and housing costs. The Fed is expecting two or three rate cuts this year based on their latest Summary of Economic Projections, with the first cut likely occurring in June or September. These rate cuts would modestly stimulate the economy and likely start to reverse the trend of generally poor bond returns observed over the last two years.
Stock Investing – S&P 500 Concentration Highest Since Early 2000s
Circling back to the stock market, while the high-flying AI companies have enjoyed big gains over the last year, a new risk is appearing in indexes and index funds – concentration risk. Most indexes use “market-capitalization” weighting in their construction, which weights companies by their relative size. When a small cohort of large stocks generate outsized gains versus the rest of the market (such as AI over the last year), it can result in concentration. This means the index is overallocated to a handful of stocks or sectors relative to general portfolio construction and diversification guidelines.
The S&P 500 has long been considered the primary index for gaining and benchmarking diversified exposure to large-cap US companies. For the first time in over two decades, this index is becoming concentrated, with six stocks making up over a quarter of the index and the allocation to the technology sector (including Meta) recently crossing above 30%, an allocation not seen since the late 90s/early 2000s dot-com bubble.
So, the US market is getting concentrated. What’s the big deal? Concentration can be a good thing if the overallocated portfolio holdings are going up, but it leaves a portfolio vulnerable when things turn lower, and that can sting. Now, do we see an imminent downturn in technology? No, not at all, but we do know that trees can’t grow to the sky and that valuations eventually matter when considering long-run returns. Below is a table of S&P sector ETF trailing P/E ratios highlighting the discrepancy in valuations between technology and other sectors and the potential long-term headwinds big tech companies may face if AI’s profitability fails to meet investor expectations.
Factor Investing
To enhance long-run risk-adjusted returns as well as control for things like overconcentration, we opt for an evidence-based method of populating our domestic stock portfolios – factor investing. Factor or “smart-beta” investing seeks to take the best ideas from index investing (low cost, rules-based portfolio construction, and diversification) and active investing (the potential to identify stocks with the best prospects for outperformance). The basis for factor strategies is rooted in decades of award-winning academic literature and has guided names like Benjamin Graham, Eugene Fama, Warren Buffet, and Cliff Asness to great success.
It works like this – utilizing big data, one can identify specific characteristics of stocks or companies that are associated with generating either long-term outperformance or risk reduction. Research goes into identifying these characteristics, or “factors,” and determines whether the factor’s positive characteristics are robust across different markets, cycles, and time periods. Some factors you may have heard of include:
- Dividend aristocrats – stocks that have a history of consistently increasing their dividends tend to outperform on a risk-adjusted basis (Watts, Barrera, Soe, & Chirputkar, September 2023, “S&P 500 Dividend Aristocrats: The Importance of Stable Dividend Income”).
- Value – stocks in cyclical sectors and stocks that people dislike tend to outperform (Fama & French, 1992, “The Cross-Section of Expected Stock Returns”).
- Momentum – stocks that have recently performed well tend to keep outperforming due to herding behavior, but leadership doesn’t typically last more than a year once identified (Jegadeesh & Titman, 1993, “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency”).
- Quality – the stocks of “high-quality companies,” defined as companies with high total returns on assets, low leverage, and consistent earnings, tend to outperform other stocks on a risk-adjusted basis (Novy-Marx, 2012, “The Other Side of Value: The Gross Profitability Premium”).
Once stocks exhibiting factor characteristics are identified, they can be combined into a “factor portfolio.” Since creating and managing the portfolio is rules-driven and doesn’t require a team of analysts, factor funds are usually inexpensive to own, and with some programming knowledge, you can even create your own factor portfolios (what we do with individual stock strategies).
The value of factor investing tends to show itself over very long time periods, sometimes decades. Year-to-year, the variance between factor strategies and indexes such as the S&P 500 can be large, and that’s normal. A recent instance of this is momentum factor, which performed poorly in 2023 because it underweighted to technology stocks. Below are annual return histories for a momentum factor fund we use in portfolios (MTUM) versus an S&P 500 index fund. In spite of MTUM’s poor performance in 2023, its ten-year track record, which includes its close to 20% year-to-date return, shows MTUM still outperforming the S&P 500 over the last decade.
Another factor fund we use is the iShares Core Dividend Growth fund, which buys stocks with five-plus-year histories of consistently increasing their dividends. This fund employs a variation of a factor called the “dividend aristocrat factor.” The fund, which was incepted in mid-2014, has similarly ebbed and flowed compared to the S&P 500 index but outperforms on a risk-adjusted basis, returning on average 0.94% per each unit of risk annually (standard deviation) versus the S&P 500’s 0.82%.
As investors dedicated to empiricism, we’re strong believers in the long-term value of factor investing. We view the benefits of factor investing as low-hanging “investment fruit,” offering cost-efficient return enhancement and portfolio risk mitigation.
Zooming Back Out – What’s Over- and Undervalued?
We have already pointed out that some big-cap stocks (mainly technology/AI stocks) are relatively expensive compared to historical valuations, and while further gains over the coming months are certainly possible and maybe even likely, there could be sector headwinds over a multi-year horizon. What about the rest of the market?
Within the US, several sub-asset classes are trading at reasonable valuations. For one, and as mentioned in our January commentary, the forward P/E ratios of the S&P Small Cap 600 and S&P Mid Cap 400 indexes are slightly below their average level for the past 15 years, indicating modest undervaluation and a potential tailwind going forward for companies within these indices. This is in contrast to the big-cap S&P 500’s forward P/E ratio, which is near its highest level in 20 years.
All things considered, we’re optimistic about smaller companies, although some individual industries (e.g., regional banks) will likely have some hurdles to overcome before posting any material growth in stock price or profitability. And, regarding large companies, we view the best approach as being tactical, using factor investing over index investing, and placing critical emphasis on diversification and avoiding overconcentration.
What About Everything Else?
Each year, we run long-term risk and return forecasts for each of the asset classes we consider using in portfolios. Once created, these forecasts are used to help us design strategies that seek to minimize risk for a given expected return. We use variables such as economic growth, yield, inflation, currency dynamics, valuations, net share issuance, and loan default trends to construct these forecasts for both stocks and bonds. Our latest forecasts have suggested the following strategic over/underweights for the following asset classes:
To sum up, our risk and return forecasts are projecting short-term bonds as stronger buy candidates than longer-term bonds over the next decade, corporate bonds over government Treasuries, and international stocks over domestic stocks.
Final Thought – Cycles and Sticking to a Discipline
The market has a pronounced cyclical nature – there are periods when bonds outperform stocks, international stocks outperform domestic companies, and different investing styles outperform others. For this reason, it’s important to follow an evidence-based investment process throughout different market cycles. And sometimes, sticking to a process can be difficult – especially when it may not particularly feel good (for example, buying downtrodden cyclical stocks during a market correction – a value factor strategy).
As we continue to implement and refine our investment strategies in the years to come, always know every decision we make for portfolios is empirically driven and designed to maximize your long-run risk-adjusted returns. As always, we are grateful for the opportunity to serve you and will remain dedicated to helping you build your best financial future.