I’m thinking of stocks like Consolidated Graphics (NYSE:CGX), General Dynamics (NYSE:GD), and Graco (NYSE:GGG). The quality of those businesses varies - I like Graco best - but they were all solid free cash flow generators that got really cheap during the 2008 crash.
They aren’t that cheap today. That doesn’t mean they’re bad investments. They could be worth a lot more than what they’re trading for now. It’s just that today’s prices better reflect those companies’ past performances. A year ago, the prices were low compared to the cash they pumped out each year. Today, you’re counting on at least a little growth to justify the price you‘re paying.
Last year, I had more ideas than cash. It was just a question of picking the best ideas. I didn’t always make the right decisions. But it worked out okay. Because stocks were cheap - and I stuck to buying good, predictable businesses.
That’s where we get to the idea of a value trap. Ben Graham wrote about value traps. This was before the Nifty Fifty and the Dot Com Bubble. So Graham didn’t have some of the experiences we’ve had with just how crazy stock prices can get.
Even though Graham was a value investor who bought a lot of cheap stocks - he didn’t think the big risk for investors way paying too much for a good company. He thought the big risk was buying a bad company during a stock market boom.
That’s really the problem you’re asking about here. How can you make sure you don’t buy a bad company?
There are a couple ways of preventing this. Some are qualitative approaches - things you can’t put into numbers. Others are quantitative approaches - things you can put into numbers.
Let’s start with the things you can put into numbers. Ben Graham was big on using averages. He never wanted to know just what a stock’s earnings were for the last year or two. He wanted to know what the stock’s average earnings were for 5 years or 7 years.
And he wanted to see the past year’s numbers - not just the average - so he could see how those numbers fell around the average. Graham’s textbook Security Analysis talks about this topic. He compares two different stocks and shows that in one case the average earnings look a lot like each year’s earnings. In the other case he shows that the average is an average in name only. Yes, it’s the mean number. But there’s no pattern to the way numbers fall around it. They don’t all land close to the average. Instead they’re spread far apart. Some years the earnings are positive. Other years they’re negative.
That’s not the kind of average Graham was looking for. He wanted a representative average. Something that gave you a real idea of a stock’s normal earnings.
Graham focused on earnings because there wasn’t enough information about cash flows back then. Investors couldn’t find those numbers the way we can today. But now cash flow data is as easy to find as earnings data.
So you can do the same thing with free cash flow that Graham did with earnings. You can look at the last 5 years or even the last 10 years.
Personally, I like to focus on the last 10 years. Today, you can use Microsoft Excel to calculate just how average a stock’s average free cash flow number is. There are a lot of different ways to measure how much a group of numbers are spread out around the average. For what we want to do using the standard deviation divided by the mean is fine.
Now you don’t have to do this. In most cases, it’s going to be very obvious just glancing at the last ten years of free cash flow data whether they are close together or spread far apart. It will also be obvious whether they’re going up, down, or sideways. But if you want an exact number that you can use to compare one stock to another - I’d suggest using Microsoft Excel.
You can set up a spreadsheet that will give you the minimum, maximum, median, mean, and standard deviation of the 10 free cash flow numbers you put in. Then you can type in those 10 numbers for as many stocks as you want. You can sort the list looking for the stocks that vary the least.
Again - you don’t have to do any of this. But if you’re worried about falling into a value trap this is a great step to add to your investment process.
It forces you to do something mechanically when you want to do it emotionally. As Kyle explained in his voice mail, the reason he’s afraid of falling into a value trap is that he can’t find as many good stocks to buy. So maybe he’s going to stretch a little. Maybe he’s going to give stocks the benefit of the doubt when he shouldn’t.
Adding a mechanical step like using Microsoft Excel helps stop you from doing something really stupid. Kyle mentioned NutriSysetm (NASDAQ:NTRI). You can ignore how uneven NutriSystem’s free cash flow has been if you don’t put it in actual numbers. But if instead of just looking at the last 3 years of free cash flow, you actually type all 10 years of free cash flow into Microsoft Excel and then compare how much Nutrisystem’s free cash flow has varied from year to year compared to how much Microsoft’s free cash flow has varied - well, then you’re less likely to make a mistake.
I’m not saying you should rely on a computer to make decisions for you. You don’t need to use Excel to be a good investor. Anything Excel can do precisely you can do approximately. I can look at Microsoft’s free cash flow numbers for the last 10 years and know they vary less than at least 9 out of 10 stocks. If you look at enough stocks, you start to see stuff like that automatically. You don’t need a computer to tell you.
But if you’re afraid that you might be lowering your standards, and risk falling into a value trap, then adding an extra step of using a computer program to spit out real numbers at you is a good idea. It’s easy to lie to yourself when you don’t have exact numbers. It’s harder to do when you can actually compare ratios between stocks. And the variation in a bunch of numbers is something a computer can calculate very nicely. It’s something humans have a hard time eyeballing. The exact standard deviation isn’t important. But the idea that one stock’s free cash flow is bouncing around a lot more than another stock’s free cash flow is important. And most people won’t take the time to think that through.
They’ll be in a rush to go ahead with whatever great new stock idea they think they have and they won’t want to take the time to run some basic checks.
Now, Jackson Hewitt (JTX) is different. NutriSystem’s balance sheet is fine. Jackson Hewitt’s balance sheet is not. As I’m writing this, the company is in serious financial trouble. Again, this is obvious to anybody who looks at the stock.
But if you’re afraid you’ll miss something like that, I can suggest another mechanical check. You can use something called the F-Score. The F-Score was created by an accounting professor at the University of Chicago. He wanted to use a simple checklist to separate troubled companies from companies that were going to pull through.
Academics have long known that low price-to-book stocks outperform high price-to-book stocks. That has always been one of the biggest holes in the Efficient Market Hypothesis. It turns out you don’t need to use your brain to beat the market. Instead you can just buy the stocks that are cheapest in terms of price-to-book and you’ll do better than most investors.
There were a couple different arguments about why that was. Some people said it was mostly a size effect. Others said it had to do with risk. The market wasn’t really inefficient, it just priced low price-to-book stocks really low because a lot of them would go belly up. And that’s true. If you pick the very cheapest stocks in terms of price-to-book more than half of them do worse than the overall stock market. But the ones that do better than the market do so much better that your overall result is still really good.
Well this accounting professor figured he could take basic financial ratios that security analysts like Ben Graham had been using for decades and create a simple checklist that would fix the problem.
He was right. If instead of blindly buying low price-to-book stocks you only buy the ones that look good from an accounting perspective, you’ll do a lot better.
So that’s the F-Score. It’s a list of 9 different questions that can be answered yes or no. If you answer them yes it counts as a 1 and if you answer them no it counts as a 0. It’s basically an on/off switch. You tally up the score and see how the stock does. Most stocks score somewhere between 3 and 7. A few get very low scores like 0, 1, or 2. And a few get very high scores like 8 or 9.
The questions have to do with basic accounting ideas. There’s nothing innovative about the list. It wasn’t created by working backwards from statistics. That’s what most professors would do. They’d start with a regression analysis on a bunch of variables in a historical database.
This professor didn’t do that. Which is good, because that way of working is risky. You can end up with a very complicated formula that doesn’t look logical and isn’t going to work in the future.
Instead this accounting professor used basic ratios no one would argue with. The questions that make up the F-Score are pretty much the questions any stock analyst would ask.
So that’s another mechanical check you can do to avoid value traps.
If you really love mechanical checks, you can even figure the stock’s Z-Score. The Z-Score comes from another accounting professor who - back in 1968 – did his Ph.D. research on financial ratios used to predict bankruptcy.
The Z-score was created the opposite way from the F-score. And it’s not meant to pick good stocks. It’s just meant to warn you about a possible bankruptcy.
The Z-score was created by finding the variables that best fit some tiny slice of past history. Basically, this accounting professor used 60 or 70 companies and split them into two groups the way a clinical trial splits a bunch of people into a group that gets the drug and a group that gets the sugar pill. In this case, half the companies went bankrupt and half didn’t. But otherwise they looked the same a year or two before bankruptcy.
Then he found the variables that best fit each group. He came up with five different variables - some of which might sound weird to you since they aren’t as logical as the ones used in the F-Score. The Z-Score is tougher for the average investor to wrap his head around. It uses coefficients - which means it multiplies different variables by different numbers to get the total score.
The Z-score works well. It’s easy to plug numbers in. And, within a year or two of bankruptcy, the Z-Score does a good job of telling you which stocks will go bust and which won’t. Further out, the Z-Score is not accurate, but it’s better than nothing.
So, if you just want to talk numbers, there’s the F-Score and the Z-Score. Look them up online and you’ll find step by step directions on how to calculate them.
Both the F-Score and the Z-Score will steer you away from stocks headed toward bankruptcy.
Of course stocks headed toward bankruptcy aren’t the only value traps out there. But a weak financial position is one of the biggest risks with value traps. Another problem is a business that only looks good when you look at the last few years.
NutriSystem fits that description. But I think of it as a separate case. If you look at that NutriSystems’s history, it’s the story of a young business. The company has been around a while. But it completely changed its strategy a few years back. Since then it had unbelievable growth that leveled off. But NutriSystem hasn’t seen a steep drop - at least not compared to what a lot of companies have seen in this recession.
NutriSystem is what I would call an unproven stock. It isn’t a good business turning into a bad business. NutriSystem is young. We don’t have a good idea of what was a fad and what wasn’t. We don’t know how much of the past can be carried on year after year. We don’t know a lot of things. So I put NutriSystem in the unproven category.
That’s why I like to use 10 year free cash flow numbers. Now, obviously, you’re not going to get many stocks where the 10-year average free cash flow divided by the current stock price is more than 10 percent. That’s not going to happen, because that would be an absurdly low price. Also, most businesses are growing, so their 3-year average free cash flow is higher than their 10-year average free cash flow. That means the free cash flow yield, when you use 10 years of data is going to be lower.
Fine. But I still like to look at the last 10 years. I want 10 straight years of free cash flow. And I want the average to be high compared to the price I’m paying. I also want the yield to be as much as triple A corporate bonds.
Let me say that again: I want the 10-year average free cash flow divided by the current stock price to be more than the yield on triple A corporate bonds. Right now, triple A corporate bonds yield 5.34%. So the stock price has to be less than 20 times the stock’s 10-year average free cash flow or I’m not interested.
Being picky limits your choices. Most stocks don’t have 10 straight years of free cash flow for a couple reasons. Some companies haven’t been public for 10 years. To have free cash flow data going back 10 years, the company needs to have been public for 8 or 9 years.
Then there’s the issue of consistent free cash flow with no negative numbers thrown in. Retailers have a hard time making the cut. Most growing retailers don’t throw off free cash flow every year. And those that do are slowing down and getting old. Sometimes they’re losing sales to new competitors.
It’s hard to find retailers with this approach. You can’t find financial companies with it either. Cash flow data for financial companies is not as important as cash flow data for other businesses. It doesn’t mean the same thing. If you want to know how to value a financial company, listen to the two episodes I did about banks and insurance companies.
And finally, it’s hard to value utilities on 10-year free cash flow. Utilities tend to be inconsistent free cash flow generators because of their capital spending. Most utilities are good on the operating cash flow line but bad on the free cash flow line. I have mixed feelings about this. On the one hand, I admit that demanding utilities to have some free cash flow every year is a bit harsh. But, on the other hand, I think too many investors are too easy on utilities when it comes to free cash flow. The best utilities still throw off a lot of cash. And the worst utilities often look fine on the operating line, but dump too much cash back into the business.
It’s not the end of the world if you miss out on retailers, financial companies, and utilities. First of all: some retailers will qualify. They throw off cash every year. And while electric utilities almost always fail the 10 year free cash flow test, there are plenty of telecom companies that don’t. Pipelines can pass the 10-year test too. So it’s not like you’re throwing out all utilities.
Still, I have to admit that it’s a hard test to pass. You might only find 5 to 10 stocks for every hundred you look at. But demanding 10 straight years of positive free cash flow and a reasonable yield on the average free cash flow for those 10 years is a good way to avoid value traps.
One of my favorite ways to avoid value traps is a thought exercise. When you research any stock, promise yourself you won’t sell it for at least 5 years. Then, whenever you figure what kind of returns you can get in that stock, limit yourself to only looking at possible 5 and 10 year annual returns.
This is a great way to avoid value traps. Bad businesses can only give you good returns over 5 or 10 years if you buy them super cheap. Most bad businesses won’t give you good returns unless you manage to flip them in 1, 2, or maybe 3 years. Good businesses can work out well if you own them for the long haul. Making yourself act like selling isn’t an option for at least 5 years is a good way of keeping yourself far away from any value traps.
Another way to steer clear of value traps is simply to keep a list of companies you love. Instead of always searching for cheap stocks, start by finding good businesses. Don’t look at the stock price. Just find the best businesses you can think of. Put their names on a list. You can even create a database on your computer if you want to. Then follow those businesses over time. I bet a couple of them will get cheap in a year or two.
Doing something like that takes patience. But it pays off. Some of the best investments I ever made were possible only because I had been following the business for years and then it suddenly got cheap.
For example, in the last couple months, I bought a stock I’d been following since 2005. The company was hit by a scandal and its stock got cheap. I didn’t buy it then. The stock got cheaper and cheaper over the years and they just put the last of the scandal behind them. If you hadn’t been following the stock for years, you wouldn’t realize what a big deal this was. The last five years clouded the picture. But if you know the business well, like I do, you can see the stock’s inner beauty waiting to be unwrapped.
I could have bought that stock at the worst of the scandal. I thought it was cheap. But there were some problems I couldn’t figure out well enough to make sure I had a margin of safety.
It’s an insurance company. So I needed to know how fast they could get out of the bad lines they were writing. More importantly, I needed to know when they would get a better rating from A.M. Best. That’s the company that rates insurers for their ability to pay policyholders. A big downgrade, like the one this stock got, can ruin an insurer if it stays in effect.
So I decided against buying the stock in 2005. But I kept watching it. And 5 years later, when the market recovered from the 2008 crash, and stocks were starting to look pricey, this stock was still cheap. The company put the scandal behind it. So I bought the stock after waiting 5 years.
Sometimes that’s how long it takes to get the right business at the right price. You have to be patient. And opportunistic. If you don’t know the company ahead of time, it’s harder. And it’s always riskier to start reading about a company when the stock price is low. We’re value investors. We want to find bargains. That can color our judgment. It can make us think the business isn’t as bad as it looks because we really want to buy the stock when it’s cheap.
It’s hard to be honest with yourself. But you have to. Separating the business from the stock price is a good first step. Is this a good business? Or just a good stock? Sometimes bad businesses make good stocks. But they have to be cheap enough and safe enough. Be careful. Bad businesses are often dangerous stocks. Even at low prices.
That’s especially true when you give them the benefit of the doubt. Instead: always expect the worst.
One way to always expect the worst is to keep an investment journal. Every time you buy or sell a stock, you write something about that stock in your journal. Explain why you’re buying it. And be honest. Don’t write the journal for anyone else. Write the real reasons for your trade. Talk about your expectations. What do you think will happen in the next couple quarters and the next couple years.
Whenever an investment goes badly, go back and read your original idea. See why you bought the stock. And read how wrong you were.
Keeping an investment journal reminds you how bad you are at predicting the future. That’s something most investors forget.
Another thought experiment to keep you from falling into a value trap is to pretend you’re buying the whole business, not just shares of stock.
Imagine you run a family business. It’s a holding company that’s branched out into a few different industries. You’ve got some extra cash lying around. And the CEO of the company you’re looking at comes to you and offer you the whole business for the stock’s current market cap.
Imagine buying the business will eat up 25 percent of your family’s wealth. You can’t count on selling the business. If it loses money, you’ll be stuck with it. It’s harder to shut a business down than most people think. There’s always someone saying they can turn it around. And most owners are too stubborn to know when they’re beat. A bad business is worth a lot less than zero. It’s a cash drain.
Okay. Put yourself in that mindset. Would you buy the business? And Ii not, why are you thinking about buying the stock?
That’s an extreme example of how thinking differently about an investment decision can keep you from making a dumb mistake. In either case you could be wrong. People do buy whole businesses and lose their money. Just like people buy stocks and lose everything. But you set the bar higher when you think about buying a business you’ll never sell.
The last two suggestions I’ll make are to be honest with yourself and don’t be a contrarian.
In other words: be rational. Look at the stock for what it is. Don’t try to go against the crowd. Instead, try to look at the stock like there’s no crowd at all. Too many value investors think being contrary means being right.
No. The market is right most of the time. It’s not hard being right. What’s hard is being right when the market is wrong. You don’t want to be so humble that you trust the market. But you don’t want to be so proud that you automatically think the opposite.
You need an independent mind. You need to be rational. And you need to be honest with yourself.
One more thing. Don’t look for catalysts. Looking for events that will drive up a stock’s price is a dangerous game. It makes you overconfident. You think you know something other people don’t. You think you know a stock will get bought out. Or you know natural gas prices have nowhere to go but up. Investors loves catalysts, because they don’t just tell you how much money you’ll make, they tell you when you’ll make it and why you’ll make it.
Value is its own catalyst. Cheap stocks go up because they’re cheap. You don’t need another reason. Looking for one is dangerous. More investors fall into value traps looking for catalysts than doing anything else.
Kyle asked for some recommendations. I don’t know if I can give you any of those. But I can tell you about a couple stocks I own.
These two stocks make up 40% of my portfolio. So I believe in them. On the other hand, I bought them at lower prices, so they’re not as cheap as they once were.
The two stocks are Omnicom (NYSE:OMC) and Birner Dental Management (NASDAQ:BDMS). Omnicom is a collection of advertising agencies and agencies in related fields like public relations. It’s a $12 billion company by market cap. The stock trades around $40. I bought it at $27.82 a share.
Birner Dental Management is a bunch of dentist offices in Colorado, New Mexico, and Arizona. It’s a much smaller business. The market cap is $30 million. It’s an illiquid stock. That means it doesn’t trade much. The family owns a lot of the shares. And the company has a long history of buying back stock. That combination doesn’t many shares for the public to buy and sell. It took me months to buy all the shares of Birner I wanted. The cost was spread out. But I did all my buying under $15 a share.
So, be warned, the stock is more expensive today than when I bought it.
I still like both stocks. They don’t have a lot in common other than some of the things we talked about today. They both have good free cash flow numbers going back 10 years. The amount of free cash flow hasn’t varied much compared to most stocks. And they’re both cheaper than most stocks.
Well that’s all for today’s show. If you have an investing question you want answered call 1-800-604-1929 and leave us a voicemail. That’s 1-800-604-1929. Thanks for listening.