By Jack Forehand, CFA, CFP® (@practicalquant) —
I started out my career as a Price/Book guy. It certainly wasn’t the only value factor I used, but I would defend it when it came under fire and I thought it deserved a significant role in constructing value portfolios.
I have since come to recognize that my defense of the Price/Book wasn’t as grounded in facts as I once thought it was. Although there are several reasons for that, the major one is that our economy has changed significantly over time, and the Price/Book just hasn’t kept up. While the economy was once dominated by tangible things like property, machines and equipment, it is now dominated by intangible ones like patents, brands and software code. Since the former items end up on a firm’s balance sheet and the latter ones do not, that poses significant issues for investors using the Price/Book ratio.
The chart below shows just how much has changed over the past 45 years. In 1975, intangibles assets were only 17% of the assets of S&P 500 companies. Today, intangibles assets make up 90% of the total S&P 500 assets.
Accounting vs. Reality
To understand why this situation better, it is first important to understand how both tangible and intangibles assets are handled on financial statements. When a tangible asset is purchased, it is not expensed right away. Instead, its value is depreciated over time. The period used varies with each asset, but the idea is that if an asset will produce value over time, then it should be expensed over time as well.
Intangible assets are handled differently. Intangible assets are typically created via things like research and development and advertising. According to accounting standards, they are expensed right away and do not end up on a firm’s balance sheet.
The problem all of this poses for investors is that both tangible and intangible assets produce value over time. But only tangible assets are counted in book value. This results in a situation where the Price/Book is either less valuable than it used to be in the best case or useless in the worst one.
A Real World Example
Before we get into how to handle this problem, let’s look at an example of why it is important. This idea really clicked with me when I was able to apply it to our own business. At Validea, we sell subscription services for an annual fee. Let’s say that we wanted to start a significant advertising program to grow our business. And let’s also assume that we charge $100 per year for our service. If we were able to acquire customers for $200, would that be profitable? To answer that, we need another data point. We need to know how long the average customer will stay with us. By multiplying that customer life by our annual charge, we can come up with the lifetime value of a customer to us. For this example, let’s say the average customer stays with us 10 years, resulting in a lifetime value of $1000.
Now that we have the numbers, let’s look at this situation from both an accounting and an economic standpoint. From an economic standpoint, we are acquiring a customer for $200 and we expect to receive $1000 from that customer over their lifetime. That is a very profitable situation. But from an accounting standpoint, it won’t look that way. That is because in year 1, we would be putting out $200 and getting back $100. It would look like we are losing money, even though we expect to return five times our investment. Our marketing spending would effectively be creating an intangible asset that our financial statements would not be accounting for.
To look at another example, let’s say we initiated a major research and development project and developed an algorithm that would consistently beat the market every day. And let’s also say that there was no way anyone could ever copy it and it would never stop working. That obviously isn’t going to happen, but if it did, we would have an asset worth billions of dollars. But that asset wouldn’t exist on our balance sheet. In fact, it would only show up as a research and development expense on our income statement. Eventually the value of that asset would result in much higher profits, but an investor analyzing our company using the Price/Book would completely miss its value.
Searching for a Solution
So how do we fix this problem? The answer is complicated.
The first option is to use the information that companies already report and to make adjustments. Using my example above, the money we spent on our advertising program could be treated as an asset and amortized over time. If we used a ten-year period to match our customer lifetime, instead of having a $200 expense in year one, we would have a $20 expense. By making that adjustment, our year one profit transitions from a $100 loss to an $80 gain, better reflecting the economic reality.
But there are still significant limitations to this approach. To understand why, consider the R&D example above. If we truly developed a model that would outperform the stock market every day, it would likely be worth many multiples of what we spent in R&D to create it. Although turning that R&D expense into an asset would better reflect reality, it would still fall well short of reflecting the true economic situation. To use a public company example, think about what Google’s search algorithm is worth. Or its brand for that matter. Both are worth many multiples of the expenses that helped to create them.
This is where more advanced approaches come in. For example, Kai Wu at Sparkline Capital has developed systems using machine learning to analyze things like patent filings or the number of PhDs at a company to estimate the value of its intangible assets. We talked about his approach, in our podcast interview with Kai.
These more advanced methods can get closer to reality, but they will never get all the way there. This is because valuing intangible assets is an inexact science. Even the most advanced methods will have a hard time getting close to the true value of a brand or an algorithm because their nature makes them extremely difficult to value.
The Intangible Spectrum
It is also important to keep in mind that the impact of intangibles varies a lot for different types of companies. Trying to value Google with a standard Price/Book is a waste of time. Trying to value a steel company in the same way may still have issues, but it gets much closer to reality. What this means is that investors looking for the absolute cheapest stocks with the Price/Book will likely have more success than those trying to figure out the most expensive ones.
To illustrate this idea, we ran a test where we looked at the cheapest 5% of stocks in our database using the standard Price/Book. We then reran the same test with an adjusted Price/Book that treated R&D and a portion of sales, general and administrative expense (SG&A) as assets and amortized them over time. The resulting portfolios were about 80% the same. While this does not validate Price/Book as a metric, it does show that intangibles are less of an issue with the cheapest stocks.
Is the Price/Book Dead?
In the end, the most important takeaway here is that our economy has changed. And the way we value companies has to change with it. This means that standard accounting metrics need to be looked at more carefully and adjustments often need to be made. In the same way, we can’t use computers from twenty years ago to run today’s software programs, we also can’t value today’s companies with the same approaches we used then.
Jack Forehand is Co-Founder and President at Validea Capital. He is also a partner at Validea.com and co-authored “The Guru Investor: How to Beat the Market Using History’s Best Investment Strategies”. Jack holds the Chartered Financial Analyst designation from the CFA Institute. Follow him on Twitter at @practicalquant.
