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Deciphering Valuation

Valuation Myths & Market Conditions

2021 was an outstanding year at Applied Finance and our investment partners. For our investment partners, each of our strategies outperformed their benchmarks and peers. In addition, we

• Launched a new ETF that we believe will deliver consistent alpha with a low beta, broad market based alpha strategy

• Dan Obrycki, Derek Bergen, John Holt and I Introduced Quantitative Valuation® concepts and data to the academic community, through one of the most downloaded research working papers on SSRN in ’21 – Valuation Beta

• Doubled our AUM/AUA

• Added two new fun, all-round nice guys as team members

-John McErlean, 25-year institutional trader to head up our trading operations

Francesco Franzoni, PhD MIT and Professor at University of Lugano, Switzerland as an external research consultant

“The hardest thing to explain is the glaringly evident which everybody has decided not to see” Ayn Rand, The Fountainhead

Since DCF valuation and Applied Finance’s Economic Margin® Valuation Framework are often misunderstood, I thought I would address common errors and misunderstandings regarding how the investment community thinks about valuation. Having worked with hundreds of investment managers, analysts and advisors over the past 25 years, I know valuation is an interesting topic. Virtually every investment manager and analyst acknowledges its significance, but almost instantaneously begins justifying why they don’t give it much importance in their process. I’ll note that rarely do investment professionals offer as the reason an admission that they have not really devoted the immense time and study required to deeply understand valuation. I’ll provide my perspective on what I will call common myths/misunderstandings, then I’ll turn to a few insights from our Intrinsic Value Database™ and provide our perspective to current market conditions. Topics covered include:

1. DCF is too subjective

2. DCF valuation relies on inaccurate long-term forecasts

3. DCF valuation is not useful, as it requires a catalyst

4. Tech Crash Déjà vu, or the Bubble that Wasn’t

5. How inflation and rising rates will hurt equities

DCF is too subjective

We agree a highly subjective valuation process can be problematic as it applies to traditional DCFs, relying on individual analyst forecasts using Gordon Growth perpetuity assumptions or long-term explicit value driver modeling. As the behavioral economics literature has extensively documented, recency bias, overconfidence, anchoring, treating potential losses differently than gains all lead to poor decisions. All these apply to most DCF models and hinder their ability to identify attractive investment opportunities. But that is an implementation problem, not a valuation problem. Further I would add, the use of any analyst forecast data suffers from the same problems, whether in a DCF or in a price multiple. In 1995, Dan Obrycki and I began the research to develop Applied Finance’s Economic Margin® Valuation Framework that we have employed consistently since 1998 to develop monthly intrinsic value estimates on 20,000 companies globally. An overview of our model is available in Value-Based Metrics: Foundations and Practice by Frank Fabozzi and James L. Grant. In it, we describe our valuation approach that moves from raw accounting data to calculating a firm’s Economic Margin®, to estimating a firm’s intrinsic value. The entire process is systematic in nature. No Applied Finance employee forecasts a parameter used to value a company. We developed the research to power our systematic valuation process in 1995 and have applied it consistently since. The idea that DCF must be driven through subjective inputs, is summed up well by Mark Twain – “It’s not what you don’t know that gets you in trouble, it’s what you know for sure that just aint so.”

DCF relies on inaccurate long-term forecasts

This criticism centers around the idea that since a DCF valuation relies on long-term forecasts, and long-term forecasts are inaccurate, valuations must not be useful. Again, reflecting a lack of insight into valuation, this is an opinion, motivated by a seemingly serious point. Ultimately, it is an empirical question, rather than an assumed qualitative pronouncement.

Let’s first address the idea that DCF valuations require long-term forecasts. A realistic DCF valuation that properly incorporates economic profitability and the effects of competition, often does not require a long-term forecast. For example, if a firm only earns its cost of capital, assumptions regarding future growth are irrelevant, as the present value of such growth is zero. The relevant forecast for such a firm is simply understanding the wind down of cash from its existing assets. Harnessing this idea, Applied Finance’s Economic Margin® Valuation Framework, recognizes that once economic profitability is zero, no additional forecast years are required. This eliminates the absurd perpetuity assumptions that underpin common DCF approaches, as forecasting economic profitability is very different that forecasting specific company line items. Forecasting Economic Margins® benefits from the near universal principle that competition drives economic profitability to zero over time. Further as economic profits approach zero, each forecast year has a smaller impact on a firm’s overall valuation. We see this phenomenon over and over through the study of company life cycles. For example, as shown in Table 1 below, in 2009, ranking all firms on the spread between their ROI and cost of capital (Economic Margin®), the median spread for the top 10% of these firms was 14%. By 2019, the median spread for these firms declined to 4%. Within a span of 10 years, an emphasis on economic profitability, rendered forecasts increasingly irrelevant for the most profitable firms. The closer a firm’s Economic Margin® is to zero the less relevant a forecast becomes, as the present value of future investment is zero.

While assuming all DCF valuations require long-term forecasts is incorrect, it is a silly statement regardless. The proper question to ask, is given that DCF valuations require multiyear forecasts, are they useful relative to price multiples based on one- or two-year analysts forecasts to select stocks? In other words, empirically, is DCF Valuation more effective than price multiples? No one has ever addressed that question until this past year. There are many reasons why, but in a nutshell, no firm, except Applied Finance, has a 20,000+ firm multidecade long, live, out-of-sample intrinsic value database. Since 1995, Applied Finance has performed over 20,000,000 live, out-of-sample valuations using the same approach to measure corporate performance, estimate capital reinvestment, assign cost of capital, and determine an Economic Profit Horizon.

In a technique we created called Deconstructing Value™, there are three distinct scenarios to determine the efficacy of DCF valuation relative to price multiple based valuations – When the DCF and multiples give a similar signal; when the DCF is a buy, and the multiples are not; and when the multiples indicate a buy, but the DCF does not. Table 2 below displays the returns to those three portfolios from 10/18 to 6/20. It is clear attractively priced multiple stocks that are unsupported by intrinsic value, perform poorly. It is also clear, intrinsic value performs well regardless of whether a stock is attractive from a stock multiple perspective. It is obvious, criticisms centered around the idea that long-term forecasts render the Applied Finance valuation approach less useful than price multiples are baseless, reflecting a lack of understanding on the part of the critic.

Valuation is not very useful, as it requires a catalyst to unlock value

Most asset managers underperform. I suspect if they focused on understanding valuation rather than searching for catalysts, their performance might significantly improve. It amazes me that an asset manager can buy a stock, without understanding the stock’s worth. The problem for most asset managers is they have no idea as to the underlying intrinsic value or true worth of the stocks they own. Instead, asset managers tend to focus on a stock’s relative cheapness, which is the information provided by a price multiple. Like the question of whether a reliance on long-term forecasts prevents Applied Finance valuations from outperforming multiples, we can similarly study whether our valuations require a catalyst to outperform. Again, using live, out-of-sample data from 10/18 to 6/20, we form portfolios based on the top and bottom 30% of stocks sorted on the ratio of their intrinsic value divided by month end price, and rebalance these portfolios monthly. Table 3 below displays the results. With no catalyst, other than being over or undervalued, the DCF valuation identifies winning and losing stocks across 23+ years of comparisons. Many pundits and advisors will argue that the rise of passive investing makes understanding intrinsic value irrelevant and outperforming through stock picking is more difficult and less likely to reward investors than ever before. We disagree. The rise of passive investing creates an ever-growing opportunity for Applied Finance’s valuation expertise, as passive strategies consistently overinvest in overvalued stocks and underinvest in undervalued stocks. Consistently understanding the difference between over and undervalued stocks combined with the rise of passive investing creates a growing, repeatable, sustainable franchise to generate long-term outperformance. Ultimately, human nature and its propensity to over and under shoot is the catalyst required for valuation to work well.

It is clear, the investment industry has a very poor grasp on valuations from a theoretical and practical perspective. That will change in the future as research and track records continue to demonstrate how properly harnessed valuation is an insightful tool to evaluate companies.

The Growth/ “Value” Bubble – Long Hyperbole, Short Analytics

Are “value” stocks poised for a historic run similar to after the tech crash, or is all this growth/”value” bubble talk just hyperbolic marketing by “value” managers yearning for relevance after a decade of underperformance?

The evidence advanced by most “value” managers that the market is currently in a bubble relies on extreme difference in multiples between growth and “value” stocks. They argue that the spread today is at historic levels, exceeding those leading up to the Tech Crash of 2000. The potential problem with this analysis, is that price multiples do not reflect whether a stock is over or undervalued. As displayed in Table 1, when the signal for price multiples conflict with that of intrinsic value, price multiples have insignificant information regarding subsequent returns.

With that in mind, let us examine the Intrinsic Value Gap™ between growth and “value” portfolios through time to contrast 2000 with today. Chart 1 displays the Intrinsic Value Gap™ between growth and “value” portfolios from 1998 to 2021. A few observations-

1. In 2000, the Intrinsic Value Gap™ between growth and “value” stocks exceeded 100%, identifying the extraordinary opportunities “value” presented relative to growth stocks.

2. From 2010 to 2019, growth stocks offered upside relative to “value” stocks. This is the fundamental reason growth stocks significantly outperformed “value” stocks during the period.

3. Since late 2020, “value” stocks have become more attractive than growth stocks. While “value” stocks offer 30% greater upside than growth stocks, that is a far cry from the 100%+ of 2000.

A price multiple centric investment view begins with a faulty foundation that cheap and expensive corresponds to undervalued and overvalued. That is the classic correlation versus causality blunder. In comparing market conditions today relative to 2000, there are many fundamental reasons why growth stocks today should trade at much higher multiples than “value” stocks relative to the past decades. For example, the cost of capital for companies is much lower today than it was in 1980, 1990, 2000, and 2010. As a result, companies with higher profitability and higher growth will have higher market prices relative to fixed accounting variables such as book value, sales, or earnings.

Cheapness investing is nothing more than a sophisticated cyclical play, wrapped around extensive data collation. While “value” stocks are more attractive than growth stocks today, it is not a historic opportunity to buy “value” stocks.

Rising Rates, and Equity Sensitivity

While the 2021 market buzz was centered around economic growth, 2022 market sentiment is dominated by rising rates. With rates dominating market sentiment, a natural question to ask is how valuation and price multiples explain stock returns for High and Low interest rate sensitive companies. We developed a simple proxy for this by segmenting a company’s value into the cash from existing investments and future growth. All things equal, the more future cash flow a company needs to justify its value, the more sensitive its value is to changes in interest rates.

Table 4a displays the returns to high and low interest rate sensitive stock portfolios, segmented into overvalued and undervalued portfolios. Table 4b displays the returns to high and low interest rate sensitive portfolios segmented into growth and “value” portfolios (low and high book to price ratios).

A few interesting observations:

1. Regardless of whether stocks have high or low sensitivity to interest rate changes, undervalued companies outperform, while overvalued companies underperform.

2. Book to Price provides inconsistent buy / sell signals for companies with a high sensitivity to interest rates.

As we have seen from many different perspectives, Book to Price is a poor tool to manage portfolio interest rate sensitivity. Alternatively, intrinsic value provides consistent signals about future returns regardless of a stock’s sensitivity to interest rates. No one really knows when or how much interest rates will change in the coming years, but a complete approach to handling corporate value that incorporates interest rate levels and changes is required to identify how those rate changes affect a firm’s intrinsic value and subsequently its investment attractiveness.

Market Value and Interest Rate Changes

I’ll end my discussion with a couple scenarios to help frame alternative market value changes as interest rate sentiments change. For bonds, this is easy, simply calculate the bond’s duration. For equities, this first requires a DCF Valuation, and for it to be useful the model needs to have live and out-of-sample results that consistently explain valuations through time. I’ll use Applied Finance’s Intrinsic Value Database to address the following questions:

  • How much should the S&P 500 decline, if cost of capital increases by 50 basis points?
  • How much should the highest 50% duration companies value decline with such a change?
  • How much should the lowest 50% duration companies value decline with such a change?
  • How much should company values change if discount rates reverted to 1980 levels, when we last saw inflation similar to the quarterly measurement?

Table 5 lays out the answers to these questions.

Through Jan 24, 2022, the SPY is down approximately 8.5% YTD. This seems to be consistent with the expected drop to higher duration stocks for a 50-bps increase in the cost of capital. If markets expect a full 100 bps increase, then we are about half of the way towards a normalized adjustment. However, given that the equity risk premium is quite high, I would not expect market implied rates to reflect a one-to-one increase in rate increases. While I have no claim to market timing skills, I believe the rising rate phenomena from a fundamental perspective has mostly played out for now. Markets always over and undershoot, so the exact reaction won’t be tidy, but fundamentally an additional downward move by more than high single digit from these levels becomes harder to justify without a strong belief that rate increases beyond 100 bps are likely soon.

Lastly, not to be too negative, but should market feel inflation is permanent, and the cost of capital reverts to the early 80’s levels, approximately 400 bps higher based on Applied Finance cost of capital calculation, we can expect an additional 20% downside from existing levels for fundamental reasons, plus an additional downward response from an emotional multiplier.

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