We’ve written often of our preference for “factor” investing in equities, an approach that leads us to variously “tilt” portfolios toward characteristics that reflect observable “risk premia” in that they can be seen to have led to outperformance over time. There’s no guarantee that outperformance will come, though; there’s a risk that the premium won’t be realized. Such has been the case for some time now as the Magnificent 7 and other larger, growthier stocks have powered ahead of the rest of the market. Still, that converse trend has not crimped our preference for the approach:

• Maintaining a factor-based approach can prove challenging at times. And latching onto a growth train may seem the easier path in periods such as the past few years
• Market history shows relative performance tends to cluster in cycles, but the beginnings and ends of those cycles are unknowable in advance. Factor exposures may be indicative of variation in longer-term outcomes, but they are weak to useless as market timing tools
• As the growth side of the ledger [opinion alert!] grows more and more irrational, though, we find the historical evidence increasingly relevant

Matter of Factors

So long as one takes a longer-term view, data backing core emphases on relative size, valuation and profitability remain cogent. In Figure 1 we show the cumulative total return of small-cap value stocks, versus large-cap value stocks. Where the area is green, the top represents the index of small-cap value, while the bottom represents the index of large-cap value (and vice versa, where grey shows large-cap value outperformance). Though both series ended the period with about the same annualized return, there were meaningful interim returns gaps between the two groups of stocks. The grand relative gains in small-cap value stocks after the Tech Bubble (2000-01), the Great Financial Crisis (2007-09) and the COVID pandemic came only after the substantial relative declines prior to each crisis. The cyclicality of the difference in relative returns reflects both the promise of factor-based investing and the risks generally to be borne in pursuing any such methodology.

The cost of the potential near- and medium-term underperformance of a factor-based equity investment approach is the risk one must assume to achieve the potential premium that the approach may present. In Figure 2, we again use the two narrow extremes of the factor mix to support this observation. Over the past thirty years, small-cap value stocks (value stocks are those that measure less-expensive based on some ratio of price to company “fundamentals”, such as assets, earnings or revenue) have shown a tendency to underperform large-cap growth (growth is the inverse of value) stocks over shorter periods of time. But stretch the review period and a picture of more consistent—though still not pervasive—outperformance comes into focus. Where we consolidated the data in Figure 2, we show the entire detail in Figure 3 in order to convey the cyclicality of relative performance. The rolling periods expand from 1 year (indigo) to 20 years (yellow). The higher peaks and lower troughs of the 1-year rolling periods express not only the heightened short-term volatility of markets in general, but also the potentially substantial difference between the short-term performance of small-cap value stocks, versus large-cap growth stocks.

Discipline Trumps Timing

To achieve the potential gains presumably inherent to a factor-based investment strategy, though, we believe one must be systematic. That is, the definitions one uses to establish the relative weights of stocks in a portfolio must be reasonably stable and consistent. As important, we think, is to implement a multifactor approach in a manner that seeks to optimize the portfolio’s potential benefit from the targeted exposures. In the portfolios where we utilize multifactor approaches—multifactor equity investment methodologies being just one of the various investment approaches we deploy in client portfolios—we generally “tilt” exposures toward our preferred characteristics, aiming to boost expected returns without adding undue risk of underperformance relative to the market and without unnecessarily over-complicating the approach. The tilt aspect of our method reflects the notion that, while we tend to own some proportion of most stocks in a given investment universe (which in our portfolios tend to align with three quasi-regional exposures: U.S. stocks, international developed-market stocks and emerging-market stocks), we tend to maintain greater-than-market weights in stocks that express our preferred characteristics and lower-than-market weights in those that do not.

As part of that focus on efficiency, we generally seek to achieve our equity factor exposures exclusively via exchange traded funds (ETFs, and to a lesser extent these days mutual funds). The primary reason we take this stance is that ETFs allow the portfolio to evolve over time to optimize factor exposures without the undue realization of gains, either short- or long-term. The funds we choose also generally consider all factor exposures for each underlying holding (hence the multifactor moniker). One could instead choose single-factor funds (e.g., a small-cap fund or a value fund), but such a methodology generally is considered less optimal from an expected-return standpoint. The approach also adds unnecessary friction to the portfolio in that the exposures must be modulated via a rebalancing of the individual funds, a process that is largely more efficient when done within the fund itself.

Further, for most portfolios (we’d argue probably for all portfolios from a practical perspective), a fund-based approach trumps one that invests in individual stocks as well, given the far greater breadth of holdings that can be achieved in a fund—thousands of stocks, versus hundreds, perhaps even tens in an average account or household of accounts—and the potential greater efficiencies achieved by the single-portfolio scenario that a fund presents to all investors in the fund. Holding a larger number of stocks generally enables more optimal achievement of factor exposures, while the ETF construct generally enables more tax- and cost-efficient tailoring of those exposures as markets evolve over time. The costs of those funds in terms of expense ratios obviously matter, which is why we narrow our universe of multifactor funds to those at the less-expensive end of the spectrum. Present preferred multifactor funds carry expense ratios ranging from 0.12% to 0.17% for U.S.-focused funds, 0.18% to 0.23% for international developed stock funds and 0.33% to 0.39% for emerging market stock funds. These expenses ratios have changed over time, to date only becoming less expensive as the funds have matured.

Finally, we generally scale multifactor tilts in line with a portfolio’s overall risk tolerance so that higher-risk models carry more pronounced emphases on these factors. The approach aligns with observation that stronger tilts widen the potential for the performance of the portfolio to diverge from that of the broader market (in industry parlance, stronger tilts increase potential tracking error). That potential performance divergence can be in both directions (higher and lower potential returns), with the expected bias that the longer-term relative performance will be higher. The graduated tilts also acknowledge the fact that, in order to achieve the premium bit of the risk premium, one must endure the risk of near- and medium-term underperformance. As noted earlier, we seek to reduce the potential downside performance gap through tilts, rather than via an exclusive focus on stocks expressing more favorable characteristics.

FAIr Value

In summary, we think this disciplined, long-term, evidence-based approach seeks to enhance expected returns while acknowledging the inherent cyclicality and potential for periods of underperformance. As shown in Figure 3, we’re in the midst of substantial long-term small-cap value underperformance relative to large-cap growth stocks. Given the narrowness of the comparison, the gap overemphasizes the relative underperformance of multifactor-tilted portfolios, as a tilted portfolio would have maintained some exposure to the larger and growthier side of the spectrum. In recent times, actually, this underperformance mostly has been a U.S.-based phenomenon; multifactor approaches have tended to outperform in international stock markets over the past several years. The underperformance of small/value is notable, nonetheless, for its depth and duration.

So, what does that underperformance tell us about the future? Perhaps nothing. Potentially something. We’ve many reasons to be concerned about exposure to U.S. equity markets. But, then again, when ain’t that been true? We’ll leave aside the “if” for now, as any concerns about the magnitude of stock exposure may be far more easily handled via a change in allocation between equity and fixed income (feel free to reach out to an advisor to discuss). This month’s commentary discusses the “how” of equity exposure. And in that context, we continue to find that investor expectations for going-forward fundamental growth related to generative artificial intelligence (genAI)—expectations clearly reflected in the relative performance and present valuations of a host of large-cap growth stocks—greatly outpace practical medium- and perhaps even long-term potential for end-use revenue to sufficiently compensate for the rather outlandish monies being dedicated to genAI infrastructure. Said more concretely, there’s a valuation disconnect, in our minds, that may contract before a more realistic view of the potential profitability of genAI broadly takes hold.

Again, research has shown little reason to believe factor investments can be timed to market opportunities. And in our experience, the shifts in investor sentiment that have reversed trends in factor underperformance have come quickly and without immediately obvious triggers, as we show in Figure 4. Seems investor opinions may be consolidating toward a more rational view here, as small-cap value stocks are on track for their third month of outperformance relative to large-cap growth stocks. But time will tell. Meantime, we continue to find a strategy that tilts against the rising tide of genAI exuberance a sensible stance for those similarly concerned about the potential for eventual investor disappointment.

Important Information

Signature Resources Capital Management, LLC (SRCM) is a Registered Investment Advisor. Registration of an investment adviser does not imply any specific level of skill or training. The information contained herein has been prepared solely for informational purposes. It is not intended as and should not be used to provide investment advice and is not an offer to buy or sell any security or to participate in any trading strategy. Any decision to utilize the services described herein should be made after reviewing such definitive investment management agreement and SRCM’s Form ADV Part 2A and 2Bs and conducting such due diligence as the client deems necessary and consulting the client’s own legal, accounting and tax advisors in order to make an independent determination of the suitability and consequences of SRCM services. Any portfolio with SRCM involves significant risk, including a complete loss of capital. The applicable definitive investment management agreement and Form ADV Part 2 contains a more thorough discussion of risk and conflict, which should be carefully reviewed prior to making any investment decision. All data presented herein is unaudited, subject to revision by SRCM, and is provided solely as a guide to current expectations.

“Small-cap value stocks” are represented by the Bloomberg U.S. 2500 Value Total Return Index, which comprises the smaller 2,500 of the largest 3,000 U.S. companies with superior value factor scores based on their earnings yield, valuation, dividend yield and growth.

“Large-cap growth stocks” are represented by the Bloomberg 500 Growth Total Return Index, which comprises the largest 500 of the largest 3,000 U.S. companies with superior growth factor scores based on their earnings yield, valuation, dividend yield, and growth.

Past performance is not a guarantee or reliable indicator of future results. The opinions expressed herein are those of SRCM as of the date of writing and are subject to change. The material is based on SRCM proprietary research and analysis of global markets and investing. The information and/or analysis contained in this material have been compiled, or arrived at, from sources believed to be reliable; however, SRCM does not make any representation as to their accuracy or completeness and does not accept liability for any loss arising from the use hereof. Some internally generated information may be considered theoretical in nature and is subject to inherent limitations associated thereby. Any market exposures referenced may or may not be represented in portfolios of clients of SRCM or its affiliates, and do not represent all securities purchased, sold or recommended for client accounts. The reader should not assume that any investments in market exposures identified or described were or will be profitable. The information in this material may contain projections or other forward-looking statements regarding future events, targets or expectations, and are current as of the date indicated. There is no assurance that such events or targets will be achieved. Thus, potential outcomes may be significantly different. This material is not intended as and should not be used to provide investment advice and is not an offer to sell a security or a solicitation or an offer, or a recommendation, to buy a security. Investors should consult with an advisor to determine the appropriate investment vehicle.