Practical analysis for investment professionals
27 August 2018

Franchise Quality Score: A Metric for Intangibles

The high valuations of Amazon, Facebook, Alphabet, Netflix, and other tech stocks can be puzzling — especially for value investors.

The prices of these stocks have skyrocketed despite valuations that are already exceptionally high based on traditional metrics like price-to-earnings (P/E) and price-to-book (P/B) ratios.

So what’s the explanation?

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One argument we’ve been making for a long time is that these companies have made substantial investments in valuable intangible assets, but accounting rules require that these investments be expensed rather than capitalized. This depresses current earnings and book value and thereby inflates P/E and P/B ratios.

As we observed back in 2002 in “Intangibles: The Next Frontier in Stock Valuation”:

“Current accounting standards were first developed during the industrial era and were designed for companies that were engaged primarily in manufacturing activities. These standards have not kept pace in an increasingly services-based economy characterized by rapid technological and financial innovation. . . . Even though it is impossible to measure the value of intangibles precisely, it is essential for investment professionals to come up with a logical approach to incorporate intangibles into their decision making; otherwise they risk being relics in the age of information.”

Feng Gu and Baruch Lev lend further credibility to this argument. They present evidence that ever-increasing investments in intangible assets by firms are rendering old stock valuation models obsolete and demonstrate the need for new valuation frameworks.

We designed such a framework that captures the value inherent in intangibles. We call this proprietary metric the Franchise Quality Score.

So what is it, what’s its logic, and how can it inform stock valuation?

Background on Intangible Assets

Intangible assets come in many forms, with patents and brands among the more obvious varieties.

Examples of Intangibles

Examples of Intangibles

As we pointed out in 2002, the increasing importance of intangibles is a function of the economy’s transition away from manufacturing to a more service-oriented focus. Service-oriented businesses require less investment in physical assets than their counterparts in manufacturing.

The US Economy’s Transition from the Industrial to the Information Era

The US Economy's Transition from the Industrial to the Information Era

Source: US Bureau of Economic Analysis

At a more granular level, Gu and Lev observe that corporate investment in intangible assets has increased from 9% of national gross value added (GVA) in 1977 to 14%  in 2014. Investment in tangible assets, by contrast, has declined from 15% to 9%. This trend has exacerbated the impact of the inconsistent accounting treatment that intangible and tangible investments receive.

This means that accounting data are accurately capturing increasingly irrelevant information while missing what’s important. So what is being captured by accounting data and what’s being missed?

What Accounting Data Show versus What Really Matters

Incorporating Intangible Assets into Stock Selection

Three factors make integrating intangible assets into a coherent stock-selection framework particularly difficult:

  • Disclosures about intangible assets are neither robust nor standardized.
  • Valuation techniques for intangibles are primitive.
  • Intangibles vary by industry, which makes it hard to compare two stocks with two different types of intangibles.

To overcome these obstacles, we focus on the “benefits” that intangibles provide rather than the intangibles themselves. For example, patents create high barriers to entry, and while they are not common across all industries, just how high barriers to entry are can be evaluated for all sectors. Likewise, valuable brands can confer pricing power on brand owners. But again, though brands are not critical across all sectors, we can measure the degree to which certain companies enjoy stronger pricing power because of their brands or other relevant factors.

We created the Franchise Quality Score based on our assessment of the most common benefits that intangibles offer. We define Franchise Quality as the ability of a firm to consistently and repeatedly earn excess return — i.e., return on capital in excess of its cost of capital — without inviting competition that would eliminate that excess return.

We calculate the score by assigning a value to eight component factors on a scale of 1 to 5. Of course, scoring the various factors on such a scale might seem arbitrary and subjective, we find applying specific criteria helps make the scores reasonably objective. These eight components are designed to answer two critical questions:

  • How attractive is the business?
  • How well is the business being managed for long-term success?

How Attractive Is the Business?

How Attractive Is the Business?

How Well Is It Being Managed for Long-Term Success?

How Well Is It Being Managed for Long-Term Success?

We derive the composite Franchise Quality Score from this framework and apply it as an independent variable in a regression model that uses valuation, quality and growth factors to identify undervalued stocks. Our approach bears some similarity to Michael Porter’s Five Forces framework for competition within an industry. Both attempt to distinguish the good businesses from the bad.

Evaluating the merits of a stock in light of its valuation, quality, and growth characteristics is not only logical but also mathematically consistent with the discounted cash flow (DCF) approach to stock valuation.

Reconciling the Franchise Quality Valuation Model with Traditional Models

Below is a simplifed example of a stock valuation model based on linear regression that includes the Franchise Quality Score.

P/E = α + β1 (Franchise Quality) + β2 (Growth Rate) + e

In its functional form, this model — Equation 1 — can be rewritten as:

P/E = fn(Franchise Quality, Growth Rate)

Based on this model, the P/E multiple that we should be willing to pay for a firm depends on two key considerations: Franchise Quality and Growth Rate. It’s worth comparing this model to the gold standard of valuation, the DCF model. One example of such a model is the dividend discount model.

Dividend Discount Model

P = D / (k- g)

By rewriting dividends as earnings multiplied by the payout ratio, we get:

P = (E * Payout Ratio) / (k – g)

Dividing both sides of the equation by E, we derive the following equation.

P/E = Payout Ratio / (k – g)

By making the simplifying assumption that the payout ratio is constant, the above equation can be written in its functional form, which we’ll call Equation 2:

P/E = fn(Discount Rate, Growth Rate)

Compare Equation 1 and Equation 2. Both models demonstrate that the P/E ratio of a stock should depend on two factors, one of which is the growth rate. Where the two models differ is on the second factor. Should it be the discount rate or the Franchise Quality Score?

Think about it: Both the discount rate factor and the Franchise Quality Score attempt to capture the risk dimension. The discount rate is an estimate of risk. The Franchise Quality Score measures risk with intuitive factors derived from the fundamental building blocks of businesses.

Firms with high Franchise Quality Scores are less risky than their low-scoring counterparts because they are more likely to maintain and grow their earnings regardless of the economic environment.


Capturing intangible assets in stock valuations is a difficult task. Absolute precision is impossible. But the perfect should not be the enemy of the good. These intangible assets cannot be excluded from valuations. Even a basic, logical attempt to incorporate intangible assets is better than none at all.

It is the only way we can hope to see the complete mosaic of stock valuation.

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All posts are the opinion of the author. As such, they should not be construed as investment advice, nor do the opinions expressed necessarily reflect the views of CFA Institute or the author’s employer.

Image credit: ©Getty Images/FrankRamspott

About the Author(s)
Gautam Dhingra, PhD, CFA

Gautam Dhingra, PhD, CFA, is the founder and CEO of High Pointe Capital Management, LLC. He developed the firm's pioneering investment approach based on the concept of Franchise Quality, and under his leadership, High Pointe has built an enviable investment performance record. Dhingra served on the faculty member at Northwestern University’s Kellogg School of Management for two years. In this role, he designed and taught The Business of Investing course in the school’s MBA curriculum. His research interests include ESG investing and valuation of intangible assets. He holds a PhD in finance, with specialization in investments and econometrics, from the University of Florida’s Warrington College of Business. At Warrington, he taught two courses in securities analysis and derivatives.

Christopher J. Olson, CFA

Christopher J. Olson, CFA, is a principal and portfolio manager at High Pointe Capital Management. Prior to High Pointe, he was a portfolio manager at Columbia Wanger Asset Management in Chicago for 15 years where he managed both equity and balanced mutual funds. He began his investment management career at Yasuda Kasai Brinson in Tokyo in 1991, and later joined the parent company, Brinson Partners, to help start the firm’s emerging markets investment strategy. He has lived and worked in Sweden, Japan, and Taiwan. He is proficient in Mandarin Chinese and has studied five other foreign languages. Olson received an MBA from the Wharton School of Business with distinction and an MA in international studies from the School of Arts and Sciences, both at the University of Pennsylvania. He graduated from Middlebury College with a BA in political science, summa cum laude. He earned his CFA charter in 1998 and is a member of CFA Chicago. His civic responsibilities include his role as chair of the board at Swedish Covenant Hospital in Chicago and as trustee at Lincoln Academy in Maine.

3 thoughts on “Franchise Quality Score: A Metric for Intangibles”

  1. Let me start off by saying that I agree, in principle, with about 90% of this article. Since that makes for a boring read, I’m going to focus on the 10% I disagree with.

    There is nothing wrong with conventional valuation methods, nor are they incompatible with the valuation principles outlined in this article.

    A robust valuation is one that reconciles the differences between a conventional economic valuation approach, like Discounted Cash Flow (DCF), and other approaches that may be more industry-specific, whether based on Comparables (Comps), Key Valuation Indicators (KVIs) or Qualitative Assessment (QA).

    Determining fair value is an iterative process that requires triangulating and corroborating the valuation conclusion with primary and alternative valuation techniques that are sufficiently different in their approach to provide reasonable assurance that all relevant and material factors have been considered.

    To state that conventional valuation techniques are antiquated is inconsistent with good valuation principles or practice. On the contrary, this type of logic is fully consistent with professor Shiller’s paradigm of the “thought virus” that gives rise to speculative bubbles.

  2. Peter

    Thanks for your comments. I actually agree with you assessment that combining the old with the new is the best way to triangulate. However, there is one aspect of the “implementation of the old” that I think should be questioned more that it has been. Investors keep using risk metrics like beta to estimate discount rate for DCF valuations when empirical work has shown that high beta companies have not produced the higher returns that was expected from them. To that extent investors keep implementing the “old” incorrectly, the “new” method outlined here can help overcome that empirical inconsistency.

  3. Steve Houseworth says:

    I disagree with both the premise and the conclusions. Just look at the Share of GDP chart comparing services, manufacturing and government. Services has been a larger part of the US economy since the late 40’s, so ‘intangibles’ have already been included in valuations, rather than just manufacturing output. Second, if ‘intangibles’ can’t be defined precisely, they can’t be measured precisely. If they can’t be measured precisely then no basis exists to develop mathematical models that include them. This is hocus-pocus on the hunt for legitimacy. Third, and an extension of my preceding points, intangibles MUST have some real material value which are inherent in products or services, otherwise an Enron methodology exists, which may seem reasonable, but has no basis in the real world, real accounting and real company valuations.

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