What Our Entrepreneurial Experience Taught Us About Value Investing Through Market Cycles

By Euclidean Technologies

After building one of the first ever SaaS companies and successfully weathering the tech market crash of the late 90’s, Mike Seckler & John Alberg founded hedge fund Euclidean Technologies and employ value investing strategies strengthened by their entrepreneurial experience.

Are we in a bubble? No one can predict if we are or aren’t, but my founders argue that current market conditions hold similarities to the late 90’s. This post reflects on how this experience shaped their value investing fundamentals, and why current under-performance for many value investors is nothing to be surprised (or even necessarily alarmed) by.

Value Investing: A Formative Experience

Before we started Euclidean Technologies, we spent a decade building a software-as-a-service company named Employease. Our experience with that business informs how we invest, and also how we think about Euclidean’s recent results and future prospects.

When you think of Employease, think of but for the human resource (HR) applications that a company needs to manage its workforce. Employease was founded prior to the dot-com boom and acquired five years after the bust. Just as with most high-growth technology companies at the time, however, it was how we navigated that boom and bust cycle that determined our fate. These experiences cemented certain principles that we would apply years later to Euclidean.

During the boom years of 1998–1999, everyone seemed to be making a lot of money — at least on paper. There was plentiful access to large amounts of venture capital, which led to an abundance of unsustainable behavior. We had numerous competitors willing to burn millions each month doing uneconomic things in pursuit of growth. We felt a lot of pressure to follow that example.

At the time, there were also unusual developments in the public markets. The IPO environment was white hot. Public company valuations were at all-time highs in relation to earnings, driven in part by investor enthusiasm and soaring margin debt. And there was this pervasive sense that we had entered a new era with a new economy. It was fun to think that way.

Then, in late 1999, we saw the text of a speech Warren Buffett made at the Allen Conference in Sun Valley, Idaho. [1] The gist of his talk was that the stock market had become uncoupled from the economic foundation that determines companies’ long-term values. He provided a number of reasons for why he felt this was not sustainable, including that interest rates had been falling, corporate profits were high and unlikely to grow further as a percentage of GDP, and market valuations were unusually high both in relation to companies’ earnings and to GDP. In this context, Buffett believed that investors were unwisely projecting the then current bullish conditions into the future, and he anticipated that their high-expectations were unlikely to be realized. As recounted in Alice Snowden’s Snowball, Buffet’s “sermonizing on the stock market’s excesses at Sun Valley in 1999 was like preaching chastity in a house of ill repute.”

Soon enough, an unwanted reality began to emerge that those excesses were not sustainable. The public markets dropped and would take almost a decade to return to their prior peaks. From the perspective of young technology companies, access to capital evaporated.

Fortunately, our team was early to reluctantly, but successfully, embrace the idea that perhaps the good times might end. We remember tough meetings where we cancelled a planned, multi-million dollar marketing spend and the gut wrenching decision to reduce our team from 130 to 80 people. The process of executing those decisions was painful. It seared memories into our brains that forever colored how we think about business cycles.

The lasting lesson we took away from this experience is that a company’s worth and longevity is ultimately determined not by its market value, but by its ability to generate cash. Because we acted more aggressively and earlier than many of our peers in embracing this truth, we — unlike many of our competitors — survived and ultimately delivered a good outcome for our people and our investors.

Value Investing

Value Investing: What We Believe Is True

After that experience, we thought about how to apply those lessons toward managing the money we earned from selling our company. We wondered if there were timeless lessons regarding the qualities to seek when selecting potential long-term equity investments. Should those lessons exist, we felt that it would be wise to embed them into a process that would be protected from the very common human tendency to misinterpret market cycles and erroneously extrapolate recent events into the future.

We researched these topics for some time. In historical data on domestic public companies and in the writings of Graham, Buffett, and Shiller, among others, we saw that market prices in the short term are often far more volatile than companies’ financial results, reflecting perhaps the variability of investor sentiment. Conversely, we saw that companies’ long-term market values seemed to be determined by the consistency, growth, and magnitude of their ability to generate cash. This made sense to us as it resonated with our prior experience.

The question then was, Is there a way to systematically evaluate companies’ fundamentals in context of their market prices that yields good long-term investment results? The energy we devoted to answering this question drove us to launch Euclidean in the summer of 2008. Although there are many topics that we continue to explore and debate, there are two findings that we feel are so consistently validated by our research that we accept them as truth. They are:

We believe that systematically buying companies at low prices is a robust method for investing

Please review the simulated results below, which show the annualized performance by decade of four simple value-oriented approaches for selecting equity investments. [2]

Value Investing

The results are compelling. The difference between the best of these simulated portfolios and the S&P500 would have resulted in 14X more wealth creation over the study’s 40 years. Our takeaway is that a good route to realizing above-average returns would have been adhering to a process — however simplistic — for buying companies at prices that are low in relation to some intrinsic measure about those companies. Across these four decades, even as there would have been frequent temptations to deviate from these simple strategies, one could have done quite well by ignoring all external developments and sticking to them without modification.

Ah, but there is the catch — sticking to these strategies without modification. The temptation to deviate would surely have become intense during intermediate periods when these approaches yielded below market results. For example, the best performing of the simulated portfolios shows annualized returns of 7.6% in excess of the S&P500, across 40 years. However, you would have had to endure a six-year period, from April 1994 to February 2000, when the simulated portfolio’s results fell behind the S&P500’s return by almost 50%.

Buying companies at low prices certainly appears to a robust method for investing, but it requires conviction to stick to the process.

We believe that buying companies at low prices does best when valuation multiples compress

Given that strategies for buying companies at low prices can underperform for periods, even as these approaches seem to do well over the long-term, it is useful to consider the types of environments in which systematic value strategies are likely to do best.

We most recently examined this topic in Euclidean’s 2013’s second quarter letter to investors. In that letter, we presented a study showing the simulated performance of value portfolios during periods of optimism and pessimism. The results showed a big advantage to investing in the least-expensive companies (i.e., those with the highest earnings yields) across pessimistic periods when price-to-earnings multiples compress. This study also showed that this advantage diminishes during periods of optimism when valuation multiples expand.

Euclidean’s investment process is very sensitive to price. We evaluate the “goodness” of a company by looking at its balance sheet and long-term operating characteristics, and we view these qualities in relation to the company’s earning power normalized over several years. Given this, we believe that Euclidean’s results are likely to follow a similar general pattern. We expect to do better in pessimistic periods and less well during times of optimism. Importantly, however, we expect to deliver good results
when viewed across a complete market cycle.

Euclidean’s Process And Performance In Today’s Environment

At the end of 2014, it is relevant to reflect on the wisdom of grounding a process in lessons that we believe would have served investors well across previous market cycles. This is so because there are elements of today’s environment that are unusual but, in some ways, resemble the boom times of the late 1990s.

Specifically, like that period, valuation multiples are again considerably above historical averages, [3] and they have swelled at the same time that corporate profit margins have expanded toward record highs. [4]

Investor enthusiasm for this high-valuation-on-high-margin environment is reflected in investors owning near record amounts of stock on margin. [5] Another similarity is that the IPO market is open for speculative [6] companies and valuations for certain high-growth technology firms resemble the dot-com heights of the late 1990s. [7] This has all occurred in the context of interest rates being at historic lows. So, what happens next? Do these factors continue to move away from their long-term averages and justify an ever-higher stock market? Or, does some combination of these factors eventually move back towards their long-term averages and create market headwinds?

Predicting the future is not our game. The current conditions may persist for some time, and, should they do so, our portfolio’s performance may continue to be challenged. Nevertheless, our review of history and our muscle-memory from navigating prior downturns informs our belief that cycles persist. We reference Howard Marks:

“I think it’s essential to remember that just about everything is cyclical. There’s little I’m certain of, but these things are true: Cycles always prevail eventually. Nothing goes in one direction forever. Trees don’t grow to the sky. Few things go to zero. And there’s little that’s as dangerous for investor health as insistence on extrapolating today’s events into the future.” Oaktree Capital Memo, 2002

These words make sense to us as they align with our prior experience. We remain focused on what we believe would have done well across past market cycles and anticipate that, soon enough, the benefits to adhering to our systematic value strategy will once again be on display.

[1] Mr. Buffett on the stock market. Fortune Magazine. November 1999.

[2] In the simulations, Standard & Poor’s COMPUSTAT database was used as a source for all information about companies and securities for the entire simulated time period. The S&P 500 return is the total return of the S&P 500, which refers to the Standard & Poor’s 500 Index with dividends reinvested. Simulated returns also include the reinvestment of all income. In each simulation, NYSE, AMEX, and NASDAQ companies were ranked according the stated criteria such as Market Value to Book Value. Non-US-based companies, companies in the financials sector, and companies with a market capitalization that, when adjusted by the S&P500 Index Price to January 2010, is less than $400M were excluded from the ranking.

The simulation results reflect assets-under-management (AUM) at the start of each month that, when adjusted by the S&P500 Index Price to January 2010, is equal to $100M. Portfolios were constructed by investing equal amounts of capital in the top decile of companies represented by each value factor and then rebalancing monthly to equally weight the evolving constituents of the top decile. The amount of shares of a security bought or sold in a month was limited to no more than 10% of the monthly volume for a security.

During the period 1983 to present, the purchase and sale price of a security was based on volume weighted daily closing price of the security during the first ten trading days of each month. Prior to 1983, when daily pricing is not available for all securities, the purchase and sale price of a security was based on the monthly closing price of the security.

Transaction costs are factored as $0.02 per share plus an additional slippage factor that increases as a square of the simulation’s volume participation in a security. Specifically, if participating at the maximum 10% of monthly volume, the simulation buys at 1% more than the average market price or, conversely, sells at 1% less than the average market price. Other than these transaction costs, the simulated results do not reflect the deduction of any management fees or expenses. Historical simulated results presented herein are for illustrative purposes only and are not based on actual performance results. Historical simulated results are not indicative of future performance.

[3] Shiller PE Ratio for the S&P 500 (current & historical)

[4] FRED Graph, 2015 Research – Federal Reserve Bank of St. Louis

[5] Historical Securities Market Credit – NYSE Data

[6] By speculative, we mean companies that have yet to demonstrate a track-record of earnings and, given this, their valuations are not justified by prior earning power.