In October 1995, Dan Obrycki and I started Applied Finance. As we struggled to solve several valuation problems back then, we did not know that we would ultimately create and manage the Valuation 50, one of the best performing US Large Cap strategies since its inception in 2004. Then follow that up with a similarly successful US Small Cap Strategy. We recognized an opportunity to create asset management products centered around valuation and executed on that goal. Asset management was dominated by incomplete or unrealistic valuation approaches such as multiples and Gordon Growth oriented DCF models. We saw a great opportunity to trade against an industry that did not properly value companies, by creating a new valuation framework that consistently linked a firm’s economic performance to its intrinsic value. From that goal, we created the Economic Margin Valuation™ framework. We spent years working on the model, developing new techniques to measure company specific risk differentials, estimating the persistence of a firm’s economic profits, something we call Economic Profit Horizon™, and developing a systematic manner to estimate expected capital expenditures given a company’s likely capital structure. By 1998, we completed our model development and have since performed over 20 million live valuations, with the same framework we finalized in 1998 to estimate corporate performance, capital growth, company specific risk, and economic profit persistence. Our intrinsic value database sets us apart from every other investment manager. This wonderful asset we have built over the past 25 years allows us to implement our Valuation Driven® investment process, which considers the intrinsic value of every stock in an investable universe, not just “one or two buy ideas” at a given point in time. It has been a fantastic journey, as we made many great friends, continued expanding our knowledge, and built an amazing company with incredible partners. As it is our 25th anniversary month, I thought it fitting to provide examples of our research that bookend our 25 years history. The first example highlights a fundamental misunderstanding in the valuation community of applying our Economic Profit Horizon™ insights, and the second previews our current research into asset pricing, and why book to price is a poor choice to represent value. In both cases Applied Finance valuation research provides a very different perspective, and in our view more realistic, than the prevailing view. In both instances, I am constantly reminded of a wonderful quote from Stephen Hawking –
“The greatest enemy of knowledge is not ignorance; it is the illusion of knowledge.”
Economic Profit Horizon™
In 1956, Myron Gordon and Eli Shapiro published – “Capital Equipment Analysis: The Required Rate of Profit”. Through that work, they introduced the math behind capitalizing dividends into perpetuity as an approach to estimate the intrinsic value of a company. This technique is named the Gordon Growth Model, and has come to dominate the field of valuation, similarly to how the CAPM dominated investment finance. Mathematically, like the CAPM the Gordon Growth Model is very elegant. Empirically, it is bankrupt. To accept the Gordon Growth model requires a silly belief – that a firm’s point in time performance will persist into perpetuity. Prior to Applied Finance creating the Economic Margin Valuation™ model, virtually every valuation framework suffered from some form of perpetuity assumption, some proprietary approaches at the time claimed to address the problem but failed. While the Gordon Growth Model was first applied to value companies from a dividend perspective, the practice evolved to also consider free cash flows. However, the main insight from this model has not changed, mathematically capitalizing a normalized cash flow by the inverse of the cost of capital less an expected growth rate. Expressed in common words, this calculation assumes that a firm will never improve its operations or encounter competition causing its profits to decline after an explicit forecast period. From JC Penny to Blackberry, and Amazon to Apple, making such assumptions are not only unrealistic but very costly from the perspective of constructing alpha generating portfolios. Applied Finance significantly improved the construction of valuation from a projection of absolute, nonbenchmarkable series of cashflows to a stream of economic profits, easily compared to a company specific cost of capital to understand the assumptions driving an intrinsic value estimate. We developed the research and processes to estimate how quickly or slowly a firm’s economic profits are likely to persist above or below zero, something we call an Economic Profit Horizon™. The chart below depicts a common pattern found among countries globally. On the left, are the average Economic Margins™ for the top and bottom decile firms from the largest 1000 US companies in 2009. The chart on the right depicts the average EMs for those firms in 2019. While the exact magnitude of change varies year to year, the pattern is amazingly constant. The lesson – do not pay for perpetuities.
US – Top & Bottom Decile Economic Margin Levels
Data Universe: Applied Finance Global Database
To this day, Economic Profit Horizon™ is still a poorly understood concept. We have performed over 20 million live, out of sample valuations globally since we launched our company in 1995, each week adding an additional 20,000 valuations to our database. However, in 2008 our intrinsic value database was much smaller and our track record as a money manager was yet undefined. The concept of systematically estimating a firm’s Economic Margin™ decay rate at the time was foreign to most academics and industry professionals. Interestingly it is typically investment analysts and academics, rather than investment advisors, that have the most difficulty accepting this concept as they struggle with a need to get a precisely right answer, rather than understanding it is much more important to avoid the unrealistic perpetuity assumptions underpinning most models. In 2008, Forbes learned of our approach from a client and wanted to explore it in depth. As part of their research they sought input from various academics. One comment perfectly captured the dynamic we often witnessed at the time that if our estimated Economic Profit Horizon™ estimate was wrong, then our insights were obviously suspect. Aswath Damodaran, a valuation expert and professor from New York University stated in the article:
“Anybody who says they can predict the decay rate … I won’t say they’re lying, but it’s impossible to do it accurately”
It was unfortunate Professor Damodaran did not understand incorporating an Economic Profit Horizon™ that is 100% accuracy is not required to perform more accurate valuations. We feel he missed a great opportunity to advance valuation knowledge by highlighting the need to avoid perpetuities – as obviously every perpetuity assumption is also wrong. Over time the empirical evidence continues to grow that our Economic Margin Valuation™ is not only a theoretically superior approach to organize corporate information to perform valuations, but empirically very robust as well. Common sense and economic theory suggest that assuming a firm’s economic performance stays constant forever is a sucker bet. Interestingly, the same article referenced work by Dennis Capozza a finance professor from The University of Michigan who studied Applied Finance’s Intrinsic Value Factor™. His research showed that after controlling for various factors, traded prices converged to Applied Finance intrinsic values on average by 15% to 30% per year.
The Forbes article concluded by asking whether we created a better mousetrap and intimated that with our limited track record we likely had not. While Forbes aims to sell magazines, such conclusions illustrate the problems focusing on short term performance, rather than insights, edge, and process. We launched our Valuation 50 strategy in 2004, and its performance has been extraordinary against the world’s pre-eminent strategies as identified by Morningstar analyst Gold, Silver, and Bronze rated funds. The charts below compare the performance of The Valuation50 over the past 15- and 10-year periods against the group of large cap value funds that Morningstar has identified as Gold, Silver, and Bronze rated funds. Measured over the past 15 years, only 4 out 40 funds on the list outperform the Valuation50. Measured over the past 10 years, the Valuation 50 outperforms every Morningstar rated Gold, Silver, and Bronze fund. That is quite impressive for a sector neutral, equal weighted within sector strategy over these periods. This reflects the superior ability of our Economic Margin Valuation™ approach to identify over and under- valued companies. In addition to the Valuation 50, our other three strategies in the dividend, small cap, and Core-Growth space have all beat their categories and benchmarks since inception, highlighting the consistency of our process.
Valuation 50 – 10 & 15 Year Annualized Returns
Source: Morningstar, Zephyr, Applied Finance
Intrinsic Value and Asset Pricing
We believe the reason so little academic research exists with respect to estimating and understanding the properties of intrinsic value is that outside of Applied Finance’s database, there is no intrinsic value database with enough history to study. We decided to enter the asset pricing debate, as we have an extraordinary common sense yet ignored perspective to add to the field – understanding asset prices requires understanding valuation. Our data set begins in 1998, providing over 22 years of live out of sample data from which to draw insightful conclusions. While many insist on the importance of having data back to the 1960’s, it is clear as a result of regulatory changes (accounting disclosures), legal changes (share repurchase safe harbor), and technological changes (shifting corporate expenditures between tangible and intellectual capital investments), somewhere between 1988 and 1995 is a likely reasonable period to begin serious modern equity pricing. As a result, data prior to this period is much less relevant to understanding the behavior of security prices today.
In their initial asset pricing research, Fama and French identified a firm’s Book to Price ratio as a critical variable to explain cross-sectional, time series stock returns. Since the publication of their model, Book to Price has developed a cult like following as the “value factor.” Unfortunately for their research agenda, since 1991 when book to price went “live” it has performed very poorly, causing a panic among “value” managers that have built their businesses arguing, and often screeching incessantly, that book to price is a fundamental causal factor to explain stock returns.
Fama French in 2015, expanded their three-factor asset pricing model to a five-factor model that included profitability and growth metrics in addition to their original three factors. In that work they note that though book to price seems statistically insignificant in the presence of profitability and investment growth factors, they kept book to price in the model. It is interesting to note that to motivate their five-factor model, Fama French led the reader through a theoretical dividend discount valuation exercise examining how a firm’s value changes, with changes in profitability and investment growth. As with most prior academic studies involving value and valuation, they never actually valued a company, or the tens of thousands required to have actual valuation data. We find this curious, and an area where the extant asset pricing research has failed miserably, as avoiding a direct estimate of intrinsic value and whether a stock if over or under valued invites correlation rather than causality into any conclusions as to whether there exists a “value” factor. Rather than directly estimating the intrinsic value of the companies they studied, Fama French identified the following two algebraic relationships from the structure of their dividend discount model which they subsequently tested and found supporting empirical evidence.
1. All else equal, increasing profits lead to increasing corporate value.
2. All else equal, increasing investment growth leads to decreasing corporate value
However, what Fama French missed in their analysis, is that with respect to wealth creation, all else is not equal. If firms make investments at rates of returns above their cost of capital, their value increases. Any examination of investment growth in the context of a valuation framework that ignores this property is poorly specified. As a result, it is not enough to evaluate a firm’s investment growth independent of its Economic Margin®. For all the amazing contributions to finance individually and together Fama French have made through time, they missed an opportunity to expand valuation knowledge in this instance. Further we would argue they set the field back, through an over-reliance on book to price. In addition, they obviously missed an opportunity to create a more robust asset pricing model. Ignoring or missing the interaction of profitability and growth is the basis of criticism of the Fama French model by a competing framework called the Q Model put forward by Hou-Xue-Zhang. Unfortunately for the Q Model, it excludes the financial sector, making it an incomplete approach to explain stock returns in cross-section and through time, though the intuition behind this model is much better aligned with the wealth creation process that drives valuation.
In response to Fama French claiming book to price was no longer a significant factor, AQR, set about “reviving” book to price as a relevant factor by changing the timeliness of the data used to measure book to price and adding a price momentum factor to their model. More recently, Research Affiliates, among others, has argued that adding some period expenses, such as R&D back to book value improves its ability to explain subsequent stock returns. It is quite exhausting to follow all the arguments and ad hoc adjustments made to book value in the hope of making a backward-looking, static variable better able to explain the forward-looking dynamic nature of company valuations.
Instead of expending such energy to justify/revive book to price as value indicator, why not just directly build a valuation framework to estimate intrinsic value directly? As we suggested earlier, it is critical to understand whether book to price is a causal indicator of future returns, or if it is simply a variable correlated to a much more important factor that better explains future returns. For example, it is possible the past research discovering the alpha properties of book to price is correct, but book to price is merely correlated with a more fundamental value indicator and in the instances when that value indicator is not present, it loses its ability to explain subsequent stock returns. If so:
1. Should the investment community continue expending such resources defending the efficacy of book to price?
2. Do book to price strategies warrant the trillions of dollars invested around book to price strategies?
Like the controversy we encountered introducing Economic Profit Horizon™, I suspect we will encounter a similarly frigid reception to our conclusions regarding book to price’s proper role in portfolio construction. Soon Applied Finance will release our perspective on asset pricing, and introduce what we believe is a much more complete framework to explain stock returns. I will provide an initial introduction to our work by evaluating the interaction between book to price and Applied Finance’s Intrinsic Value Factor™ to better understand the source of book to price’s alpha generating capabilities. The table below displays the intersection of quintile portfolios of Russell 3000 stocks from 2/98 through 12/19 (formed on book to price, and Applied Finance’s Intrinsic Value Factor™ rankings. Book to price quintiles are the ranking of companies each month based on their measured book to price ratio, using their last fiscal year’s book value and the current month price. Intrinsic Value Factor™ quintiles are the monthly ranking of company’s estimated intrinsic value relative to its month end traded price. For purposes of our comparison, we are interested in examining the cheapest stocks against those that are the most undervalued.
There are three sets of returns required to begin answering whether book to price and Intrinsic Value Factor® are causal or correlated factors to explain stock returns. This data is displayed in the chart below, the return sets are:
1. When price to book and intrinsic value give comparable signals, “Cheap and Undervalued”
2. When price to book indicates a stock is cheap, but intrinsic value does not support the conclusion, “Cheap but Not Undervalued”
3. When intrinsic value indicates a stock is cheap, but price to book does not support the conclusion, “Undervalued but Not Cheap”
Factor Quintile of Applied Finance vs. Book to Price
- Cheap (CHP) = Most attractive Price Multiple Composite companies Expensive
- (EXP) = Least attractive Price Multiple Composite companies Undervalued
- (UV) = Most attractive Intrinsic Value companies Overvalued
- (OV) = Least attractive Intrinsic Value companies
While our study confirms the classic “value factor” ability of book to price to generate alpha over the period 2/98 to 12/19, such conclusions are quite deceiving. Absent a confirming signal that a stock is also undervalued, price to book effectively provides no alpha when constructing a portfolio. Conversely, all undervalued stocks, as identified by Applied Finance’s Intrinsic Value Factor™ generate significant alpha regardless of whether they are cheap or expensive from a book to price perspective. We explore this in much greater detail in a soon to be released asset pricing research report.
Given that book to price’s ability to explain stock returns results from its correlation to the Applied Finance Intrinsic Value Factor™, rather than being an independent causal factor it is reasonable to conclude that book to price portfolios are over-invested. Further, each advisor needs to seriously consider if a portion of their client’s portfolio should have exposure in some form to Applied Finance’s Intrinsic Value Factor™.
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Rafael Resendes, Co-Founder
