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Euclidean Q2 – Using Simulations to Compare Valuation Measures for Selecting Inexpensive Companies

By VW Staff. Originally published at ValueWalk.

Always a good read – Euclidean 2Q17 Letter to investors can be found below.

Euclidean uses machine learning to find persistent relationships between company fundamentals and investment outcomes. Through this effort, we have become convinced of the merits of maintaining a long-term commitment to buying good companies at low prices. Indeed, there is abundant evidence from a variety of sources indicating that a fruitful, long-term strategy would be to buy companies that were priced very low in relation to their fundamental qualities, such as their earnings or book values. Moreover, our own research suggests that this has particularly been the case for companies that also have a combination of consistent operations, good returns on capital, and balance sheet strength.

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However, the discipline of owning inexpensive companies has delivered muted performance during recent years. Indeed, despite some reversion in 2016, the first half of 2017 has extended the longest period of expensive-stock dominance since World War II. In the past, investor enthusiasm for expensive companies generally has proven to be both cyclical and not a fruitful basis for long-term investing. As we review in this letter, after periods when expensive companies led the market, value investors historically have achieved strong returns.

In the pages that follow, we:

1. Revisit perspectives we shared 18 months ago regarding the history of value and growth cycles.

2. Provide simulations of different value factors’ relative merits in evaluating public companies and constructing portfolios of inexpensive stocks.

Update on the Current Growth vs. Value Market Cycle

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In this section, we update an analysis that we first shared 18 months ago that reflects one of the most widely researched approaches to value investing, in which a value stock is defined as having high book equity to market equity.

In this analysis, it should be no surprise to see that the first half of 2017 has extended the current period of expensive-stock dominance. Investors have great enthusiasm for fast-growing FANG stocks and heightened awareness of incredible changes they are thrusting upon the distribution, retail, and media industries (among others).

Amid this enthusiasm, it is crucial to remember that in the past, investors have frequently taken even the best ideas to extremes, operating as though no price is too high for innovative companies driving the future. Likewise, investors often have extrapolated that new advances will make currently profitable and established companies irrelevant, as though there is no price low enough to consider owning shares in such legacy companies.

“Among large-cap stocks, the spread between value and growth is now larger than at any point over the past six decades, with one exception—the top of the dot-com bubble.”  Barrons, June 28, 2017

Repeatedly, this dynamic has ended with investors reminded that even the best companies can become bad investments when priced too high, and that valuable opportunities to buy cash-generating companies at very low prices often emerge when outside catalysts spark the flames of fear. These reminders – lurking now, and perhaps ready to ambush investors once again – characterize what repeatedly has occurred across market cycles. You can see this in the graph below.

Euclidean 2Q17 Letter

This graph [1] shows the cycles involved in buying out-of-favor, inexpensive (VALUE) companies vs. expensive (GROWTH) companies. In this graph, the blue line falls below the dotted line when the trailing five-year annualized return has been higher for expensive stocks than inexpensive ones, and goes above the dotted line when value stocks have outperformed. So, to glimpse the long-term advantage that value stocks have held, note that returns spend most of their time above the line.  Value has outperformed growth across a significant majority of rolling five-year periods.

However, since 1945, there have been six distinct times when expensive stocks outperformed, based on trailing five-year compounded returns. The beginning of each of these periods is reflected by the green dots on the chart above. We are currently in one of these periods, with the prior one occurring during the dot-com era. This next chart provides a perspective on what has occurred following prior periods when expensive companies led the market.

Euclidean 2Q17 Letter

After the previous five periods when growth outperformed value, value delivered very strong results over the subsequent five-plus years. In the current cycle, despite some head fakes in 2013 and 2016, the value rebound consistently observed in the past has not yet occurred.

Using Simulations to Compare Valuation Measures for Selecting Inexpensive Companies

The analysis above uses the valuation metric of book-to-market to classify companies into growth and value categories. This metric was popularized by Eugene Fama and Kenneth French in their paper, “The Cross-Section of Expected Stock Returns,” published in the Journal of Finance in 1992. While this use of book-to-market as a value factor permeates academic literature and is also at the core of how many value-oriented indexes are constructed, many value investors embrace different concepts when valuing companies.

For example, it is common practice to look at a business’s value from the perspective of a whole owner, for whom a company’s market capitalization provides an incomplete starting point. The concept of enterprise value is more encompassing, as it quantifies what it would take to purchase a company outright. It does this by reflecting not only the company’s market capitalization, but also the company’s cash that could be used to offset the purchase and the company’s debts, pension liabilities, and other interests that would need to be settled to wholly own the business.

Another difference is that value investors seek to understand the intrinsic value of a business, which is generally viewed as the discounted future cash flows that the business will provide to its owners. The challenge, of course, is that these future cash flows are unknown and can only be estimated. Well, a company’s book value provides very little information that can help us estimate a company’s future cash flows.  Book value makes no distinction between a pile of cash and a company with productive assets, great products, and loyal customers. Many investors, therefore, look at other fundamental qualities to better approximate a company’s future ability to distribute cash to its owners.

Given all of this, we thought we would share some simple simulations that look at which valuation metrics worked best for ranking investment opportunities during the period from January 1970 through March 2017.  The results, shown below, reflect the average return from 300 simulations, each constructed with random starting conditions. The simulations use a consistent set of assumptions that, while more fully listed in the appendix, reflect:

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