The markets provided some drama in the first quarter which contrasted starkly with an amazingly tranquil year in 2017. Although 2018 picked up where 2017 left off with low volatility and steadily appreciating markets, a massive spike in volatility emerged in early February that spooked investors. Markets quickly recovered but volatility remained elevated. As if to punctuate the new market tone, the S&P 500 finished four of the last five trading days of the quarter with moves of more than one per cent.
Of course there are many potential causes of anxiety. Continued tightening by the Federal Reserve, massive fiscal deficits, increasing concerns about tariffs and trade wars, the potential for higher inflation, and increasing backlash against many of the big tech stocks count among many legitimate concerns. The critical question for investors is: Is this increased volatility just a normal adjustment in an otherwise healthy market or is it a symptom of something more serious?
On most counts, major aspects of the investment landscape have not changed in any material way. Risk factors such as the Fed's plan to tighten slowly have been well communicated and implemented accordingly. The economy continues to grow modestly. Although revelations about data privacy breaches have gotten a lot more attention lately, they are not new. On the geopolitical front, concerns have increased about a trade war with China, but that is a lower risk than a real nuclear war with North Korea.
Another steady aspect of the landscape is tolerance for risk. As the Financial Times noted [here], "The last time the stock market showed this much enthusiasm for a handful of tech companies addicted to profitless growth, it was the height of the dotcom boom." While Tesla, a poster child of profitless growth, gave up some of its gains in the quarter, Spotify had a successful (and unique) public offering in the quarter which perpetuated the notion of "tying valuations to the promise of unspecified future profits."
Broad acceptance of risk was also demonstrated by the fact that stocks remain expensive across the board. As John Hussman reports [here], "the current episode of overvaluation has been much, much broader than we observed during the 2000 tech bubble." In contrast to the environment in which "many stocks were quite reasonably priced even at the 2000 peak," Hussman notes, "Today ... valuations are uniformly extreme across the entire stock market."
Risk tolerance also extends down to the small cap Russell 2000 index. As Grants Interest Rate Observer reported in its April 4, 2018 edition, "At year-end 2016, 33.9% of Russell  component companies were making net losses. It was close to the highest such percentage in any non-recession year since 1984." And now, five quarters later, "Upwards of one-third of the Russell's corporate components continue to show net losses."
Some things have changed though, and it is worth examining them. The most noticeable one is performance. Prior to the most recent quarter, the S&P 500 index produced positive total returns in nine consecutive quarters. In 2017, each quarter posted significant mid-single digit gains. Such steady and commendable performance made it feel comfortable to just stay invested. It certainly boosted momentum and trend following strategies.
In the first quarter of 2018, however, not only did volatility rise, but major indexes fell. This was at least somewhat odd as earnings for the quarter finally promise to show strong year-over-year gains. At very least, the break in the pattern of gains serves as a healthy reality check that investors can actually lose money in the markets. At worst, the pause in performance significantly undermines a lot of incremental demand for stocks.
In addition, although small caps have continued to indicate a high degree of risk tolerance, leadership in that group has changed. As Grants also reported in regards to Russell 2000 companies, "The difference, today, is that those [money-losing] companies are not the ones whose shares lead the index, as they did in 2011-2015. That honor increasingly falls to the businesses that actually make a profit." This represents a real change in market complexion.
Further, while big tech companies continued to lead major indexes, that leadership may not be providing such a positive commentary on the market as investors assume. Rob Arnott, chairman of Research Affiliates, provides an alternative explanation for such leadership in the FT [here]. He sees "a connection between the extent of demand for Faangs and the small supply of publicly traded 'new-tech stocks'." He explains that, "To the extent that you have excitement building in the sector and a decent chunk of it uninvestable, that excitement will lead some people to buy Netflix as a surrogate for buying Uber." In other words, "The dearth of new tech disrupters opting to go public is not the only reason why Faangs have performed so well."
All of this just goes to highlight many of the mixed signals that many investors are struggling to interpret. In this sense, current market indicators are like a Rorschach test, you can pretty much see what you want to see in them. In light of this ambiguity and given the abstract nature of many of the risks, what can or should investors do? How can investors translate what they know into actions that will make their portfolios better off?
The good news is that there is a useful and accessible framework that can help clarify spending and investment decisions. It is known as opportunity costs and is a basic, but powerful concept that deserves a refresher every once in a while. Tim Harford captured the idea in the FT [here] by stating, "We should judge the value of anything by what we had to give up to get it."
Harford provides an illustration (albeit somewhat dated) of a person deciding between two stereo systems. One costs $1000 and the other costs $700. Tough choice. But then, "The salesman asks, 'Would you rather have the [more expensive] Pioneer, or the Sony and $300 worth of CDs?', and the indecision evaporates. The Sony it is." As Harford explains, "It is not that the indecisive shopper couldn't work this out, but that the explicit trade-off never crossed his or her mind."
As it turns out, this is very similar to the type of challenge investors often face. On one hand, many risks are of a qualitative, abstract nature and on the other, investors often have only vague notions of what to expect in return for those risks. Too often, then, opportunity costs never "cross the mind" of investors and no explicit tradeoff can be made. Fortunately, there is a way to quantify the opportunity costs for investors and that is done by calculating expected returns.
The best way to determine expected returns takes some work. It starts with the simple notion that the value of a stock equals the sum of its cash flows discounted at an appropriate cost of capital. Current earnings estimates provide a good starting point for cash flows. In addition, as we noted in a previous blog post [here], adjustments can be made to GAAP results to disentangle the mixture of expenses and investments in reported financial statements. With such adjustments, economic returns on economic capital can be calculated from which a reasonable trajectory of cash flows can be determined. Then, given the stock price, the cost of capital can be derived. This derived cost of capital is just another expression for the company's expected return and as such, provides a useful measure of opportunity cost.
Of course this process is not perfect and for any given company it may overlook important company-specific fundamentals. For example, an early stage biotech company may be working on a very promising therapy that may not be fully monetized for several years. In this case, earnings estimates for the current fiscal year will fail to capture the economic potential of the company. Conversely, companies with cyclically or idiosyncratically high operating margins in the current year will have their economic potential over-represented by this approach.
Nonetheless, applying this approach to a universe of about 2000 US non-financial companies with earnings estimates produces a large enough sample from which to observe some important patterns. The most striking pattern is that for a little over one-third of the companies in the universe, current stock prices imply a real expected return of less than zero. About one-fourth imply a nominal expected return of less than zero. While this group includes some biotech companies and early stage tech companies, the size of the group is far too large for such benign causes to be exclusively the case.
Evaluated from the construct of opportunity costs, these results suggest that there is a significant cohort of stocks for which investors demand nothing at all in return for the risks to their committed capital. Indeed, investors in such securities are sending a message, intentionally or not, that they would rather put their principal at risk than hold cash. Effectively, this is an act of charity for which the company's management and employees are beneficiaries. If such decisions seem less than prudent, that's the whole point. It is quite likely that such explicit tradeoffs just did not "cross the mind" of these investors.
Other methods of determining expected returns are used in the process of investment decision making but often they are overly simplified in ways that undermine the usefulness of the exercise. For example, some practitioners observe the long term history of US stock returns in the 6-7% (real) range and therefore assign 6-7% as the level of "expected" returns.
Another simplification (that is commonly deployed by MBA types) involves deriving expected returns from a basic formula involving the risk free rate and the equity risk premium. While this approach comports conveniently with textbook theory, in practice it nearly always involves reducing the determination of the equity risk premium to a comparison of historical returns.
Both approaches make assumptions that put investors at risk. One is that the future will closely resemble the past, even though a great deal of evidence suggests otherwise. Another is that any given client's investment horizon is long enough for the historical returns to serve as a useful estimate of that client's expected returns. In practice, many investors have horizons that measure in decades, but are still short enough that they can experience results that vary substantially from the historical benchmarks.
So to wrap up, as Mr. Market has gotten moodier and investors have become more anxious, it's a good time to figure out what tools can help alleviate the anxiety. One of those tools is the concept of opportunity costs. While it is easy to justify stock performance with simple narratives like "things are getting better" or "earnings are jumping" or "stocks always do better over the long term", no such narrative describes concretely what level of return you can reasonably expect on your capital. As Harford describes, "Individuals neglect information that remains implicit ..."
What is needed is a way to make expected returns explicit. While many practitioners use very simplified expressions of expected returns, there is a way to calculate them directly that is robust in both a theoretical and a practical sense. This involves calculating economic cash flows and economic returns, and then deriving expected returns from current prices. The process is useful for analysts because it clearly provides direction for a productive course of research efforts. The process is also useful for strategists because it can be used to aggregate a large amount of micro data which can then be converted it into macro insights.
One thing the process of deriving expected returns clearly reveals is that investors have good reason to be anxious. For a large portion of stocks, current prices imply expected returns of less than zero. This means that owners of those stocks are not really investing at all, because they are not demanding anything in return for use of their capital. While there are plenty of good reasons to engage in philanthropy, such efforts should arise from a process of conscious decision making rather than as a function of an inadvertent investment mistake.