About

We are a small investment firm trying to enrich the lives of others

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Tobias Carlisle

Managing Director

Eyquem Investment Management

Tobias Carlisle is the founder and managing director of Eyquem Investment Management LLC, and serves as portfolio manager of the Eyquem Fund LP and the separately managed accounts.
He is best known as the author of the well regarded website Greenbackd, the book Deep Value: Why Activists Investors and Other Contrarians Battle for Control of Losing Corporations (2014, Wiley Finance), and Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (2012, Wiley Finance). He has extensive experience in investment management, business valuation, public company corporate governance, and corporate law.
Prior to founding Eyquem in 2010, Tobias was an analyst at an activist hedge fund, general counsel of a company listed on the Australian Stock Exchange, and a corporate advisory lawyer. As a lawyer specializing in mergers and acquisitions he has advised on transactions across a variety of industries in the United States, the United Kingdom, China, Australia, Singapore, Bermuda, Papua New Guinea, New Zealand, and Guam. He is a graduate of the University of Queensland in Australia with degrees in Law (2001) and Business (Management) (1999).

Investment Strategy

An overview of our investment philosophy

Eyquem is a deep value investment management firm.

We employ an evidence-based, research-intensive method of valuation, and a consistent, disciplined approach to portfolio management. We publish our research here.

We offer our deep value strategies in low fee-only, separately managed accounts.

We Are Value Investors

Investors, including professional investors, often believe that investing is about making great market calls, predicting which product will win, or outguessing everybody else about the next quarterly results.
That’s simply not a reliable approach.
The truth is that investing is not about picking winners: It’s about finding mispricings. And value investing is a very effective method of identifying mispriced securities.
 What is value investment?
Value investment is a method of security analysis pioneered by Benjamin Graham, and popularized by his former student, some-time employee, and life-long friend, Warren Buffett.
Graham’s foundational insight was that the market price of a stock was distinct from its “intrinsic value,” which could be calculated by carefully analyzing a company’s financial statements, and business prospects. If the stock traded at a sufficient discount from its intrinsic value to provide a margin of safety it could be purchased. Given time, the market price would revert towards the intrinsic value, at which time the stock should be sold.
To illustrate his idea, Graham asked that we imagine stocks as dollar coins available for 50 cents. The problem, he cautioned, is that in the stock market the dollar coins have strings attached. Our task as value investors is to find those dollar coins trading at a discount to a conservative estimate of intrinsic value, one that takes into account all the “strings.”
 Why is valuation so important to returns?
Chart 1 below shows the five-year rolling average returns to five portfolios sorted on the basis of valuation. The “value” portfolio contains the cheapest stocks, those with the lowest average of price-to-book value, price-to-earnings and price-to-cash flow, all simple price ratios familiar to many value investors. The “glamour” portfolio contains the most expensive stocks measured on the same basis.

Chart 1. Five-Year Rolling Average Returns By Valuation (1980 to 2013)

Glamour
49.7%
Quintile 2
63.3%
Market
68.5%
Quintile 4
80.2%
Value
94.3%

Source: Carlisle, “Deep Value” (Due August 2014)

Chart 2. Returns to $10,000 in the Glamour, Market, and Value Portfolios (1980 to 2013)

The impact of rolling average return figures can be hard to visualize. Here’s the value in 2013 of $10,000 invested in each of the glamour, market and value portfolios in 1980.
Excluding the impact of costs and taxes, $10,000 invested for thirty-three years in the value portfolio at what appears to be only a slightly higher rate of return becomes $801,503almost three times the $313,011 in the market portfolio, and more than five times the $143,372 in the glamour portfolio. An intrinsic value-based approach provides a significant advantage over the market.
This advantage is not confined to the US. We can observe this phenomenon all over the world–the results in chart 1 are an average of 23 developed nations–through market capitalizations large and small, and over different periods of time. Value doesn’t beat out the market every year, or even in every decade, but in most years, and decades. Statistically, a value approach gives good odds of beating the market over the long run.
Investors who pay attention to intrinsic value know that, though they might not catch any fish, they are at least fishing in the right spot. Investors who ignore intrinsic value are adrift, doomed to buy overvalued stocks, and avoid undervalued stocks.
Though the research is clear that undervalued stocks outperform over the long runfewer than 1 percent of professional investors identify as value investors.

We Are Deep Value Investors

Eyquem conducts groundbreaking research into methods of security valuation and portfolio management, and invests on the basis of those findingsnot on conventional or received wisdom.
This philosophy leads us to demonstrate some seemingly odd investment preferences. For example, we often hold apparently  “losing” stocks—those with failing businesses, cash flow problems, plummeting revenues, and red ink-spattered income statements. We do so because–under the right conditions–they offer unusually favorable investment prospects, with limited downside, and enormous upside.
This is a counterintuitive philosophy. Many investors believe that a good business and a good investment are the same thing. Many value investors believe that a good, undervalued business is the best investment. The research offers a contradictory view. The problem is not that we don’t want to own “good” businesses. The problem is that, when we test this proposition empirically, we find that “goodness,” or “quality” is an elusive property.
Quality is often defined as a persistent high return on invested capital. The research shows that businesses earning persistently high returns do exist, but they are a very small minority, and we don’t well understand the causes of persistence. This is to say that we can’t reliably predict which will persist, and which will mean revert. Hence, what appears to investors as an unusually high quality business tends to be a business enjoying unusually favorable conditions. And those conditions tend not to persist.
Investing assuming that they do leads to reduced returns. In 2006 Joel Greenblatt wrote a book called The Little Book That Beats The Market. The book described a “Magic Formula” that identified portfolios of stocks that, in aggregate, and on average, beat the market. (We tested the strategy. It works!). The Magic Formula examines stocks for value and quality, and buys those with the best combination of both. It defines quality as a high return on invested capital. Intuitively, it’s a great idea. But when we test the components of the strategy independently we find something unexpected. Chart 3 shows the returns to the Magic Formula and its value and quality components.

Chart 3. Three-Year Rolling Average Returns to Magic Formula, Deep Value Stocks, High Quality Stocks, and the Market (1974 to 2013)

Market
34.8%
Magic Formula (Value + Quality)
47.9%
High Quality Stocks
34.4%
Deep Value Stocks
68.5%

Source: Carlisle, “Deep Value” (Due August 2014)

Chart 3 demonstrates that, on average, the Deep Value portfolio outperforms the Magic Formula–a combination of value and quality–and the Market. Here’s the value in 2013 of $10,000 invested in each of the Magic Formula, Deep Value and High Quality portfolios in 1974.

Chart 4. Returns to $10,000 Invested in Magic Formula, Market, High Quality and Deep Value Portfolios (1974 to 2013)

Magic Formula

$1,849,476

Market

$536,041

High Quality

$517,657

Deep Value

$3,722,460

Excluding the impact of costs and taxes, $10,000 invested for forty years in the Magic Formula portfolio becomes $1,849,476, more than three-and-a-half times the $536,041 in the Market portfolio. Strikingly, $10,000 invested in the High Quality portfolio grows to just $517,657, underperforming even the Market portfolio. The returns to the Deep Value portfolio stand out. $10,000 becomes $3,722,460, more than double the Magic Formula, and seven times the sum in the High Quality portfolio.
Why are these results important?
They are important because they demonstrate that the quality metric actually reduces returns, and probably for the reasons we identified above–what looks like an unusually high quality business is simply a business enjoying unusually favorable business conditions, and those conditions don’t persist. The business is more likely to enter a period of “mean reversion.”
Mean reversion is the observation that high-growth stocks tend to return to earth, and exceptional returns on investment become ordinary. The micro-economic theory of mean reversion is well understood. High growth, and high returns invite new entrants who compete away profitability, leading to stagnation, while losses and poor returns cause competitors to exit, leading to better returns for those industry participants able to survive. Hence the best returns are found in apparently poor businesses available at steep discounts.
The evidence is that investors become overly pessimistic about a “bad” business, and sell down its stock, creating the conditions for high returns even assuming the low profitability persists. This creates an opportunity for so-called “contrarian” investors to take the other side of this trade, seeking out the undervalued, apparently “bad” business, and waiting for mean reversion.
Though it is as pervasive as it is, we don’t intuitively recognize the conditions for mean reversion. Time and again investors, including value investors, ignore likely mean reversion and consequently reduce returns. Our instinct is to naïvely extrapolate out a trend—whether it be in fundamentals like revenues, earnings or cash flows, or in stock prices. Thus the intrinsic value in these stocks is uncertain because its assessment requires the anticipation of mean reversion, which is not obvious in the historical financial data. Rather we must rely on the statistical base case for undervalued, money-losing securities—that they will spontaneously mean revert toward a state of earning power commensurate with their assets. We actually prefer high-growth value stocks when the research is clear that high-growth value stocks underperform their low- or no-growth brethren. The better bet is the counterintuitive one: deep undervaluation with no consideration given to that elusive quality.
We know that a portfolio of deeply undervalued stocks will, on average, generate better returns, and suffer fewer down years, than the market, but investors fixate on the fact that any individual stock appears more likely to suffer a permanent loss of capital. The reason is that even those of us who identify as value investors suffer from cognitive biases, and make behavioral errors. This bias—ignorance of the base case, and, by extension, mean reversion—is a key contributor to the ongoing returns to deep value investment. Im the next section we tackle one means of eliminating behavioral errors.
We are dedicated deep value investors. It’s an unusual approach. But we believe in it so much that we’ve written a book about it called Deep Value: Why Activist Investors and Other Contrarians Battle for Control of Losing Corporations, due from Wiley Finance August 2014.

We Use a Highly Consistent Investment Process

haphazard approach to investment reduces returns because it opens the door to behavioral errors. How damaging to returns are behavioral errors?
Remember Joel Greenblatt’s Magic Formula? Greenblatt gave the clients in his investment firm two choices:
1. Have Greenblatt apply the Magic Formula to automatically pick stocks, and manage the portfolio, or
2. Receive stock picks generated by the Magic Formula and cherry pick the best ideas.
Greenblatt tracked the performance of the two groups of investors for two years from May 2009 to April 2011. The results, shown in chart 5, are striking.
Chart 5. Two-Year Cumulative Returns to Magic Formula, Automatic Accounts and Cherry Picker Accounts (May 2009 to April 2011)
S&P 500 TR
63%
Automatic Magic Formula
84%
Cherry Pickers
59%

Source: Joel Greenblatt (“Adding Your Two Cents May Cost a Lot Over the Long Term”).

The reason these results are so striking is that the cherry pickers took a strategy that handily beat the market–21 percent outperformance over two years is nothing to sneeze at–and cherry-picked out the best ideas, leading it to underperform the automatic strategy and the market.
Why did the cherry pickers underperform? As unbelievable as these results are, they form a part of a much larger area of study into the abilities of human experts and statistical prediction rules to make predictions under conditions of uncertainty. In study after study, researchers have found that statistical prediction rules based on historical data make more accurate predictions than human experts using experience and intuition.
A well-known study, often used to illustrate the findings of the field, examined the ability of psychologists, experienced, and inexperienced, and statistical prediction rules to identify intellectual deterioration. The results–shown in chart 6 below–are humbling.
Chart 6. Predictive Accuracy of Experts and Statistical Prediction Rules
Experienced
58.3%
Inexperienced
62.5%
Statistical Prediction Rule
83.3%
Experienced + Statistical Prediction Rule
75.0%
Inexperienced + Statistical Prediction Rule
66.5%

Source: Leli and Filskov (“Clinical Detection of Intellectual Deterioration Associated with Brain Damage”).

We might expect that an expert using a statistical prediction rule would combine the best of both worldsdata-driven analysis and experience and intuition–leading to an optimal outcome. It’s not the case. What study after study has found is that the statistical prediction rule is the ceiling on performance from which the experts detract, rather than a floor on performance to which the experts add.
The reason that the cherry pickers and the psychologists underperform is a symptom of what is known in the literature as the “broken leg problem.” Suppose we know that Jack goes to the movies every Friday. Our statistical prediction rule might guess that he goes to the movies this Friday. Now suppose that we know that Jack has a broken leg. Surely we should be allowed to use our discretion to guess that Jack’s broken leg will affect his regular Friday movie attendance? The answer is that we do better limiting our discretion because we find more broken legs than there really areWe exercise our discretion too frequently, and that leads us to underperform the statistical prediction rule.
In fields as diverse as detection of brain damage, the interview process to admit students to university, the likelihood of a criminal to re-offend, the selection of “good” and “bad” vintages of Bordeaux wine, and the buying decisions of purchasing managers statistical prediction rule reliably beats out the expertseven when the experts had access to the statistical prediction rule.
Researchers Bishop and Trout describe this as “The Golden Rule of Predictive Modeling:”
When based on the same evidence, the predictions of [statistical prediction rules] are at least as reliable, and are typically more reliable, than the predictions of human experts. Even when experts are given the results of the actuarial formulas, they still do not outperform [statistical prediction rules].
Making an investment process consistent leads to improved investment performance because it eliminates the many small behavioral errors that humans make. We further discuss the impact of these two investment methods in our free white paper, Simple But Not Easy: The Case for Quantitative Value Investment, and in our book, Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors (Wiley Finance, 2012).

 Let us do it for you

Value investing is simple, but it’s not easy. Deep value investing is behaviorally harder again, which is one of the reasons it works so well.
And that’s often why it’s better to have someone else do it for you. That’s where we come in.
We are always researching the most deeply undervalued stocks. For a low fee, we can make sure you’re always invested in the best opportunities the market has to offer.
Click the button below to make an appointment to speak to us.

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  • A wonderful company will earn a market rate of return if the stock price fairly reflects its intrinsic value. You don’t get paid for picking winners; you get paid for identifying mispricings.

    - Tobias Carlisle -

Research

Our books, academic research, white papers, presentations, and media appearances

  • Successful investing is about having people agree with you…later.

    - Jim Grant -

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Eyquem Office

2800 Neilson Way, Suite 1411
Santa Monica, CA 90405
(646) 535 8629
info@eyquem.net