You need to find companies with a moat that the market is pricing like companies without a moat.
A deeper, qualitative inspection is usually how you find such opportunities. If a company looks like it has a moat, is highly predictable and is growing at a nice clip year after year, it will tend to trade at 25 to 30 times earnings. If a company is doing all those things “under the hood” but does not appear to have a moat when you do a surface scan of the corporate financial data – then that same business will trade around 12 to 15 times earnings. As an investor, you get rich by buying wide moat businesses at 12 to 15 times earnings, holding them for a long time and then finally selling them at 25 to 30 times earnings.
Anyone can screen for a good, long-term, quantitative record. In fact, GuruFocus has 30-year financial data. It also has a predictability score. I like both of those. I encourage you to use them, but only as a first step.
I own two companies, Cullen/Frost Bankers Inc. (CFR, Financial) and BWX Technologies Inc. (BWXT, Financial), that I think have moats. GuruFocus gives Frost a predictability score of one-star – meaning it is not predictable. GuruFocus does not rate BWX’s predictability. I think they are both predictable. And I think the reason I was able to get the opportunity to buy those stocks – in both cases at much lower prices than they now trade at – is precisely because GuruFocus (and others) could not recognize their predictability using a surface scan. A computer would not know they were predictable. At least, not when I bought them.
Frost in 2015 – federal funds rate near zero for years
Frost is sensitive to interest rates, but the cost of its deposits and the losses on its loans are predictable. The one unpredictable element is the yield on its bonds and its loans. When I looked at the stock in 2015, the record over the past six years reflected the lowest sustained federal funds rate in history. In fact, interest rates from 2009 to 2015 were as low as they had ever been. In a sense, I was looking at Frost because the commodity called “loanable funds” was in a cyclical bust. This would be the same as me looking at a high-quality oil producer after oil had traded at $30 a barrel for six years. That last part – for six years – is important. Investors are very aware of short cycles. But when a cycle goes on long enough, they confuse cyclical and secular. So they either start to believe interest rates will now always be lower than in the past or they just get fed up waiting for a catalyst and start actively ignoring stocks that depend on that catalyst to outperform.
The yield on Frost’s loans and securities is an uncontrollable cyclical element that will even out over time. But it pollutes the recent record. For example, the company’s 10-year revenue per share growth rate is just 3%. In 2007, however, the weighted average yield of Frost’s securities portfolio – mostly government bonds – was 5.3%. Today, the weighted average yield of Frost’s securities portfolio is 3.3%. The decline in yield there has been mitigated by taking more risk in terms of going further out in the maturity date of what the bank buys. In fact, the best gauge of the kind of bond buying and lending Frost does – in terms of time until maturity – would be something more like the five-year U.S. Treasury bond. Ten years ago, that yielded a little over 5%. Today, it yields a little under 2%. So Frost is like a commodity producer that has managed to grow the top line 3% a year while the price it receives on the commodity it sells has fallen 60% over 10 years.
As a result, I believe Frost looks – on a surface scan by a human or computer looking at the last 10 years of data – like it is consistently growing around 3% a year. On a deep dive inspection of the company, I believe Frost is growing more than 8% a year. That is just the compound annual growth in deposits per share over the last 10 years. Anyone can look at that number if they want to. But it is just far enough under the surface that they do not. If Frost had been compounding EPS at 8% to 9% a year over the last 10 years, it would have traded at 25 to 30 times earnings instead of 12 to 15 times earnings. Instead, it compounded deposits per share – which I consider to be a long-term proxy for normal earning power per share – at 8% to 9% a year. Since that is not a headline number, the stock traded at half of the valuation a well-liked wide moat stock would.
BWX Technologies in 2015 – mishmash of two businesses
This one is the result of several factors working in unison. I got really, really lucky having a chance to buy BWX Technologies at an average stock-type valuation through purchasing ahead of a spinoff.
I bought stock in a company called Babcock & Wilcox. Most of the value in that company came from being the monopoly provider of nuclear reactors and related components on all U.S. Navy submarines and aircraft carriers. A business like this would normally trade at 25 to 30 times earnings.
Four things worked in my favor:
- Babcock & Wilcox had itself only been an independent public company for less than five years. Even in its pre-spinoff state of being a mishmash of a great business and a business now facing challenges, it did not have a long history. Stocks that have only five years of clean financial data do not get picked up on by people who use GuruFocus screens or read Value Line looking for amazing long-term compounders. If Babcock had been both independent and public for its entire corporate history – I never would have gotten the chance to buy it so cheap. The company’s past was obscured by its own spinoff from McDermott (MDR, Financial) five years earlier.
- Babcock & Wilcox combined a completely noncyclical business tied to the U.S. Navy with a completely cyclical business tied to coal power plants. In my view, the future of U.S. Navy orders for submarines and aircraft carriers was certain looking out 10 to 30 years. Meanwhile, the future of coal power plant capital expenditure was totally unclear looking out 10 to 30 years. Also, defense spending is noncyclical. Coal power plant capital expenditure is cyclical. By combining these two companies in one summary financial statement, it looked like you were seeing a fairly normal, average business. In reality, you were seeing an extremely predictable company blended with an unpredictable company.
- Babcock had operated a money losing division for the last couple years. The company had something called mPower that was a development stage attempt to produce modular nuclear reactors. Think reactors small enough to be transported by train and set up at a job site. Money-losing divisions often disguise great businesses because the market tends to inadvertently capitalize both the profitable and unprofitable profit and loss streams at the company. Between 2011 and 2013, mPower had lost an average of about $100 million a year while the Navy business made about $220 million in operating profit. To find the value of the parts, you should assume the Navy business is perpetual and capitalize it at something like 15 times pretax profits (a price-earnings (P/E) of about 23 after taxes). Watch what happens if you do that. You put a valuation of 15 times EBIT on the Navy business alone and you get an appraisal of $3.3 billion.
Now what if you put a valuation of 15 times pretax profits on the money-losing mPower division? You get a $100 million loss times 15 equals negative $1.5 billion. That is absurd – and you would not do it. But actually, a lot of people do that by using the summary financial data. They take all the divisions together and then apply a multiple – something more like 10 times EBIT – to the whole company. But that is wrong. The Navy business will be around in 15 years – in fact, it will be earning a lot more money – mPower will either get profitable or get shut down. In this case, it got shut down. The correct thing to say to yourself is “they might run this for three more years before shutting it down for good. So it is worth something between zero dollars and negative $300 million.” Note, this can change your valuation by $1 billion if you do not break the company down into money-making and money-losing divisions and value them separately. The previous statement sounds arbitrary and flippant, but it saves you from precisely measuring a very stupid figure like negative $1 billion or more. Computers do not do arbitrary and flippant. They precisely measure the nonsense number instead. Again, this kind of thing blends stuff in a way that disguises reality. The stock is cheap based on the money-making parts, but looks normally priced if you blend the money-making and money-losing parts. So a surface level scan would say Babcock was a fairly normal business trading at a fairly normal price. In reality, included in the mix was a great business trading at a low price, but you had to break apart the financial data to see it. - I bought my shares of Babcock & Wilcox when the spinoff had been discussed but had not been announced with an actual date. The logical thing to do – since what I wanted was the BWX part – would be to wait for the spinoff and then start buying stock in the remaining business I liked. I knew the company would be getting its story out to investors ahead of any spinoff, however. There would be presentations showing what just the Navy business would look like and what the two businesses would look like once mPower no longer existed and so on. What had been an obscure wide moat business would be trotted out into public view for investors. Once the spinoff was certain, people would dig into it. As long as the spinoff was uncertain, the stock would still look a little messy like you had to do your own work. So I bought my shares while I thought it was still somewhat obscure.
BWX Technologies now trades at a P/E ratio of 26. And for good reason. The company recently announced:
“Beyond 2017, we continue to anticipate an EPS CAGR in the low double digits over the next three to five years based upon our robust organic growth strategy and remaining balance sheet capacity.”
When a company is announcing 10% or better EPS growth over the next three to five years as some sort of long-term “guidance” – you are too late. You need to find companies that can do that – but cannot yet cleanly show they are capable of it.
Breeze-Eastern – before Transdigm bought it
Breeze-Eastern Corp. (BZC, Financial) was a duopoly provider of search and rescue hoists for helicopters. The company had market share of 50% or more. Another competitor – part of United Technologies (UTX, Financial) – had market share of maybe 25%. There are no reliable figures for market share in such a niche business, but no one making purchasing decisions I talked to was even aware they could order from someone other than those two companies. In addition to that, customers reported that although it was neither difficult nor especially expensive to engineer a solution that allowed you to switch your copter fleet from one search and rescue hoist maker to another – no one did or was likely to ever do that.
Once you bought the original equipment, you would order the replacement parts from your original provider forever. In addition to this, customers told us they always initiated calls to the product manufacturer – sales representatives did not call them. The manufacturers did not keep spare parts in stock and sometimes made customers wait up to 90 days. The business was a duopoly in terms of winning the design for a new aircraft (to be the original manufacturer of the part for Boeing (BA, Financial), Airbus (XPAR:AIR, Financial), etc.), but then a monopoly once you were supplying parts for a specific model and a specific customer. About two-thirds of gross profit came from after-market sales. This is a razor and blade business.
The competitive position was strong and clear. The company’s history and some present day actions were obscuring the earnings power, however:
- Breeze-Eastern was the rump remnant of an overleveraged and diversified business that sold itself down to just this core, high-quality business. So the long-term financial data at the corporate level was meaningless. There was no 10-year record that mattered because Breeze had sold all that stuff.
- Breeze-Eastern had recently been spending more on research and development than it normally would. Normal engineering expense was probably 7% of sales. In the last three years it had spent 15%, 12% and then 9% of sales on engineering.
- Breeze-Eastern had invested in new products that require upfront engineering costs. This added operating expenses without any revenue to show for it. Once revenue was going to flow in, it would still be a couple years of no-profit original equipment sales (low gross margins) and only then a regular stream of high gross margin after-market sales.
Here you have to look into the business model to understand future earnings power. Breeze needs to partner with an aircraft manufacturer. So while a new aircraft is being developed – which can take years – there is engineering expense with no additional revenue at all for Breeze. This period is followed by original equipment sales. Original equipment is sold at a 30% gross margin, which – let’s face it – is incrementally pretty much zero profit for shareholders. But once there is an installed base, the spare parts are sold for many years thereafter at a 60% gross margin. The company’s highest gross margins are then earned when operating expenses are lowest. On a given project, there is first a loss period then a roughly breakeven period and then many years of milking a cash cow. If you misinterpret the data – for example, you just look at the summary financial data without reading the 10-K – you would confuse investment in new projects with a deteriorating business.
We did some scuttlebutt on the industry and knew there was no way gross margins could contract for competitive reasons. It was also very clear from reading the earnings call transcripts and annual filings that the company had been investing a lot in new projects. In fact, that was a point of contention between a major shareholder and the former CEO. The shareholder thought management was spending too much on new projects. That is a sure sign the business is under-earning today.
As it worked out, a company in this space – TransDigm (TDG, Financial) – probably thought so because it paid a higher price for Breeze than where the stock had traded when I wrote about it for my newsletter. Then a major shareholder or Breeze obviously also thought so because they opposed the sale to Transdigm even at that price.
These may seem like random anecdotes about wide moat businesses I have found in recent years, but there is a practical point to all this. What I am talking about here is what real wide moat investing is like. It is finding companies with market power – companies that should have easily predictable futures but are not priced that way. That is key.
You do not want to pay 30 times earnings for Coca-Cola (KO, Financial). That is not what Buffett did. He bought it at a much lower price.
In the first 10 years Buffett held Coke, it returned about 30% a year. It did that by not only being the wide moat, growth company he thought it was, but also by going from a P/E of about 15 in 1989 to a P/E of about 60 in 1999. In other words, the market’s assessment of Coke’s moat quadrupled from 1989 to 1999. Without that P/E expansion, you would get more like a 14% annual return over those 10 years. If you think about Coke today – what if it goes from a P/E of 30 back down to that P/E of 15 it had in 1989? Then – even if it is as wide moat and as high growth as you could possibly hope – it will be very hard to make more than about 6% a year in the stock over the next 10 years. A contraction in the P/E from 30 to 15 is very costly even in a great company.
So practical wide moat hunting – as opposed to identifying moats in theory – is really about finding businesses with a moat that is momentarily obscured enough to avoid detection in the kind of surface scans for quality that most computers and investors do.
The best opportunities are in stocks where you would have to read the 10-K to know it is a good opportunity. They are rarely identifiable on the basis of just top-level, quantitative data alone. If a business looks great just from a surface scan – it will trade at a P/E of 25 to 30 instead of a P/E of 12 to 15. You want to pay 12 to 15. So you need to do more than a surface scan.
Check Out Geoff’s New Website: Focused Compounding
Disclosure: Long CFR, BWXT
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