Euclidean Technologies letter to investors for the fourth quarter ended December 31, 2016; titled, – “How Does One Prepare For An Unknowable Future?”
We are pleased to write our ninth year-end letter to Euclidean’s limited partners. During the 12-month period ending December 31, 2016, Euclidean returned 19.5% after fees to investors. During this same period, the S&P 500’s Total Return (that is, the index return including dividends reinvested) was +12.0%.
During the past several years, the stock market’s rise was driven in part by investor enthusiasm for fast-growing companies with no, or marginal, profits. In this context, many value-oriented strategies — which seek to own profitable businesses when they are offered at low prices — did not participate in the market’s returns. Euclidean’s results were a case in point.
However, as we noted in last year’s letter, when these types of environments emerged in the past, they consistently ended with big rewards for value-oriented investors who maintained their discipline through the cycle. In 2016, we received some validation of this view. We are hopeful that the first stages of a supportive value environment are underway.
Yet, if that sounds like a prediction for the future, then you would have good reason to be skeptical. If you ever needed a year to demonstrate just how worthless it is to devote time to predicting the future, you received one in 2016. The experts failed to predict Brexit, the path of interest rates, the US election, and the stock market response to that election. They also counted out my (Mike’s) hometown Cubs when they were losing to the Indians in the World Series.
On all of these fronts, it has been interesting to watch so many experts tout their views with articulate confidence and yet be proven wrong.
It seems that while it is easy to make predictions, it is hard to predict the future with accuracy. This gets us to where we want to go with this letter. There is no question that so much beyond companies’ fundamentals impact share prices in the short term. This is a big reason why many investors devote attention to expert predictions regarding how political, industry, and macroeconomic dynamics will impact their portfolios. But to what end? Even prior to forecasters’ dismal record in 2016, expert forecasts have never been very reliable.
There are clearly great uncertainties that exist in our world today and how they play out will impact the share prices of what you own. However, perhaps the right takeaway is not to invest energy trying to know the unknowable. An alternative — the one we wholeheartedly embrace at Euclidean — is simply to prepare for an unknowable future by attempting to purchase sound companies at very low prices such that negative future scenarios are largely baked into their valuations.
Consider why this alternative can be fruitful. When companies are very inexpensive or expensive in relation to their fundamentals, they are priced in such a way for a reason. That reason is investors as a whole have established a consensus view on how the world is going to look going forward. That view embeds assumptions that prop up the prices of expensive companies and hold down the prices of inexpensive ones. But investors aren’t very good at accurately predicting the future. Thus, eventually, something surprising happens that challenges the consensus view and proves some of its embedded assumptions to be wrong. This erodes some of the lift — and alleviates some of the pressure — previously causing certain companies or industries to be priced, respectively, at premiums or discounts to their fundamentals.
So, although predicting the future is hard, you can prepare. And when you prepare by owning a collection of companies with good fundamentals and low prices, surprises can be very good things.
How Euclidean Is Different
We suspect that quantitatively oriented value investors, as a class, more or less subscribe to what we wrote above. So, it may be helpful to describe what is different about Euclidean.
To begin, if you want to do better than average, your portfolio has to look different than the market. The greater the difference, the greater potential you have for exceptional returns. Of course, this can work in either direction, with the potential for both exceptional over- and under-performance.
Therefore, good measures of an investment process are the magnitude and frequency that its recommendations outperform the median stock over some period of time. As others have extensively documented, sensible places to look for stocks with this kind of potential are companies that are inexpensive in relation to their fundamentals. Across long periods of time, it seems that owning a portfolio of companies that are inexpensive in relation to their earnings, sales, or book values would have yielded better results than owning the market as a whole.
The challenge, though, is that there are quite a few companies that prove to be rightfully cheap; these companies are sometimes referred to as “value traps.” Therefore, to achieve a reasonable probability of achieving good long-term results across a portfolio constructed using simple proxies for value, you need to maintain a very large number of positions. The catch, of course, is that as you own more positions, you also own a greater percentage of the market, and you progressively limit your potential performance.
So then, a reasonable objective is to craft an investment process that demonstrates better outcomes with individual investments than does a simple filter for screening for cheap stocks. If achieved, such a result would give you a sound basis for further concentrating your holdings and pursuing higher returns. The desired results would look something like this:
We believe that this objective can be achieved by taking a nuanced look at companies’ operating histories. Traditional value investors attempt to do this, to varying degrees, by conducting rigorous assessments of individual companies to understand the true character of their businesses. At Euclidean, we do this instead using the tools of machine learning to evaluate individual companies in the context of how similarly situated opportunities played out in the past.
In this context, you can visualize the difference between how Euclidean forms its portfolio and the way many mainstream quant funds form their Smart Beta, or Factor, funds. As they attempt to isolate one or a few statistical factors, you often see them employ a shotgun approach, where they invest in many names, often going long and short hundreds of positions. Euclidean, on the other hand, balances a variety of major concepts to examine a company’s operating history and evaluate it as a potential investment. As we do so, there are many inexpensive companies that our process excludes because of other qualities.
To use an analogy, consider this difference in the context of how you might go about building a winning basketball team. Index investors (Team A) are essentially making a statement that it is really hard to form a better-than-average team, so they do not evaluate individual players and simply let everyone play. Factor investors (Team B), on the other hand, home in on statistical anomalies that seem to persist across time and lead to better-than-average results. While in investing this anomaly might relate to a concept like value or momentum, in our analogy, imagine that they find that across large samples, basketball ability is correlated with a player’s height. So, the factor fund might form its team with the top 30% of players based on height. It seems reasonable to think that this team might do better than Team A over time.
However, we believe there is an opportunity to do better (Team C) by holding tryouts and judging players based on qualities that have persistently related to basketball success. In our experience, these qualities are not always as obvious as what has been accepted in common wisdom, and we believe they can be found quantitatively if you have the right discipline and the right tools.
At Euclidean, this is how we attempt to form a high-conviction, high-concentration portfolio. It is our expertise with machine learning that allows us to do complex analyses of companies’ operating histories and seek to understand the economic character of their businesses. In a way, our bottoms-up approach more closely resembles how traditional value managers select stocks than it does the practices at most quantitative asset managers. But, unlike a traditional value manager, Euclidean’s investment process is data- and process-driven, grounded in history, and protected from the behavioral biases that can lead investors astray.
How This Shows Up In Our Portfolio
At the end of this letter, we show how our comments about a high-conviction, high-concentration portfolio are reflected in our actual holdings. In that section, we plot the central tendencies of our portfolio as it looked in early December across a couple of meaningful dimensions, and compare them to the fundamental qualities of the S&P 500 (SPY), the Russell 2000 (RUT), and the Russell 2000 value (IWN) indices.
One point we hope to convey is that, when you look at fundamentals, the various indices aren’t all that different from each other. Another point, obviously, is that Euclidean’s portfolio is really different from these representations of “the market” and is concentrated in what our research suggests are sensible and high-potential qualities. Please take a look. We look forward to talking with you soon and discussing whatever comments and questions emerge from your review of these charts.
As Euclidean concentrates its portfolio in companies with better-than-average operating qualities and much lower-than-average prices, we believe we have the long-term odds on our side. But, as we have discussed and proven in years past, Euclidean’s investors have to be ready to endure tough periods along the way.
Tough periods are important. First of all, tough periods force a reexamination of every way in which we do business. Indeed, we have been driven to ask deeper questions and have incorporated what we believe are better risk controls, more extensive data, and more robust tools into how we form and oversee our investment process. Second, and as we documented a year ago, when value strategies endure a tough period of underperformance, they have subsequently delivered very strong absolute and relative returns. Thus, while we are pleased that we had a good year in 2016, we are excited about the years to come. We feel that we are in the early innings of a value recovery armed with hard-earned experience and an increasingly robust investment process.
The opinions expressed herein are those of Euclidean Technologies Management, LLC (“Euclidean”) and are subject to change without notice. The information provided in this report should not be considered financial advice or a recommendation to purchase or sell any particular security. Euclidean Technologies Management, LLC is an independent investment adviser registered under the Investment Advisers Act of 1940, as amended. Registration does not imply a certain level of skill or training. More information about Euclidean including our investment strategies, fees and objectives can be found in our ADV Part 2, which is available upon request. ETM-17-01
Below, we plot the central tendencies of our portfolio as it looked in early December across a couple of meaningful dimensions, and compare them to the fundamental qualities of the S&P 500 (SPY), the Russell 2000 (RUT), and the Russell 2000 value (IWN) indices.
In each of the charts, the plotted ellipses represent the minimum-sized ellipses that enclose 50% of the various portfolios’ holdings. Also, the universe that defines the percentile ranks are all NYSE and NASDAQ stocks with market capitalizations greater than $120M as of December 6, 2016.
Chart 1: Long-Term & Near-Term Price
As Euclidean evaluates companies’ operating histories over the long term, our process has learned to care not only about how inexpensive a company is on recent earnings, but also how inexpensive it is in relation to its long-term earning power. This first chart reflects how this focus is reflected in our holdings. It shows Euclidean’s portfolio in the context of three market indices on axes representing, respectively, the percentile rank of trailing twelve-month earnings yield and trailing four-year earnings yield. Earnings yield here is defined as a company’s operating income over the period after depreciation and amortization, divided by total enterprise value.
Chart 2: Return on Capital & Price
Euclidean’s models are sensitive to how much a company earns in relation to the amount of capital invested in its business. Return on capital measures this quality. All else being equal, companies that overpay for acquisitions, or retain more capital than they can productively deploy, will show lower returns on capital than businesses that do the opposite. This chart shows Euclidean’s portfolio in the context of the three market indices on axes representing the percentile rank of trailing twelve-month earnings yield and return on capital. Return on capital here is defined as operating income after depreciation and amortization (EBIT) divided by the company’s shareholders’ equity plus its long-term debt.
Chart 3: Firm Maturity & Price
Within this concept of “firm maturity” are two elements. The first is a company’s market capitalization, and the second is a company’s number of years of public operating history. As Euclidean evaluates long-term operating histories, our process discounts companies with short track records and favors companies with more operating history. But, when it comes to a company’s market capitalization, our process is agnostic, as it seeks to maintain as large an investment universe as possible. Thus, Euclidean invests in companies that range from being too small to be included in the Russell 2000 (small cap) index, all the way up to some of the world’s largest enterprises. This chart shows Euclidean’s portfolio in the context of three market indices on axes representing the percentile rank of firm maturity and trailing twelve-month earnings yield.
Chart 4: Operating Consistency & Price
As our models evaluate whether a company may be mispriced, we have found that we can make stronger statements if their operating characteristics are long-standing and consistent. Moreover, given that margins and returns on capital tend to compress over time due to scale challenges and competitive pressures, there is information reflected in a company’s ability to consistently operate at a high level. This chart shows Euclidean’s portfolio in the context of the three market indices on axes representing the percentile rank of trailing twelve-month earnings yield and the long-term consistency of return on capital. Here, long-term consistency of return on capital measures a company’s volatility of return on capital over the past ten years.
Chart 5: Firm Leverage & Price
Over time, our models have developed a more nuanced view of leverage, and we operate today with less sensitivity to debt on a company’s balance sheet than we did in our early years. This said, the more indebted a company is, the better the price our process demands. And our portfolio consists of companies that, on average, have less leverage than the median company and less leverage than the market indices presented here. Leverage in this chart is defined as a firm’s shareholders’ equity divided by its total assets.
We share these numbers because they are easy-to-communicate measures that show the results of our systematic process for buying shares in historically sound companies when their earnings are on sale.  
It is important to note that Euclidean uses similar concepts but different measures to assess individual companies as potential investments. Our models look at certain metrics over longer periods and seek to understand their volatility and rate of growth. Our process also makes a series of adjustments to company financial statements that our research has found to more accurately assess results, makes complex trade-offs between measures, and so on. These numbers should, however, give you a sense of what you own as a Euclidean Investor. In general, higher numbers for these measures are more attractive. The key measures are:
- Earnings Yield – This measures how inexpensive a company is in relation to its demonstrated ability to generate cash for its owners. A company with twice the earnings yield as another is half as expensive; therefore, all else being equal, we seek companies with very high Earnings Yields. Earnings Yield reflects a company’s past four-year average earnings before interest and tax, divided by its current enterprise value (enterprise value = market value + debt – cash).
- Return on Capital – This measures how well a company has historically generated cash for its owners in relation to how much capital has been invested (equity and long-term debt) in the business. At its highest level, this measure reflects two important things. First, it is an indicator of whether a company’s business is efficient at deploying capital in a way that generates additional income for its shareholders. Second, it indicates whether management has good discipline in deciding what to do with the cash it generates. For example, all else being equal, companies that overpay for acquisitions, or retain more capital than they can productively deploy, will show lower returns on capital than businesses that do the opposite. Return on Capital reflects a company’s four-year average earnings before interest and tax, divided by its current equity + long-term debt.
- Equity / Assets – This measures how much of a company’s assets can be claimed by its common shareholders versus being claimed by others. High numbers here imply that the company owns a large portion of its figurative “house” and, all else being equal, indicates a better readiness to weather tough times.
- Revenue Growth Rate – This is the annualized rate a company has grown over the past four years.
 All Euclidean measures are formed by summing the values of Euclidean’s pro-rata share of each portfolio company’s financials. That is, if Euclidean owns 1% of a company’s shares, it first calculates 1% of that company’s market value, revenue, debt, assets, earnings, and so on. Then, it sums those numbers with its pro-rata share of all other portfolio companies. This provides the total revenue, assets, earnings, etc. across the portfolio that are used to calculate the portfolio’s aggregate measures presented here.
 The S&P 500 measures are calculated in a similar way as described above. The market values, revenue, debt, assets, earnings, etc., for each company in the S&P 500 are added together. Those aggregate numbers are then used to calculate the metrics above. For example, the earnings yield of the S&P 500 is calculated as the total average four-year earnings before interest and taxes across all 500 companies divided by those companies’ collective enterprise values (all 500 companies’ market values + cash – debt).
Euclidean’s Ten Largest Holdings as of December 31, 2016
We provide this information because many of you have expressed an interest in talking through individual positions as a means of better understanding how our investment process seeks value.
We are available to discuss these holdings with you at your convenience. We are happy to explain both why our models have found these companies to be attractive as well as our sense of why the market has been pessimistic about their future prospects.
Euclidean’s ten largest positions as of December 31, 2016 (in alphabetical order)
- ACCO Brands – ACCO
- Anixter International – AXE
- Best Buy – BBY
- Brocade Communications – BRC
- Capella Education – CPLA
- CRA International – CRAI
- DeVry – DV
- Iconix Brand Group – ICON
- Trinity Industries – TRN
- Western Digital – WDC
 There is no assurance that any securities discussed herein will remain in the Fund at the time you receive this report or that securities sold have not been repurchased. It should not be assumed that any of the securities transactions, holdings or sectors discussed were or will be profitable, or that the investment recommendations or decisions Euclidean makes in the future will be profitable or equal the performance of the securities discussed herein. There is no assurance that any securities, sectors or industries discussed herein will be included in or excluded from the Fund’s holdings.