invest(igations)

Investing in Stinky Stocks

I use an evaluation system to rank stocks (I’ve written about it extensively here and here and here). But sometimes I get highly ranked stocks on my list that I really don’t want to buy. I won’t name any names here, but one company that was ranked number one or two on my list sells products that are complete crap, in my opinion, through agents whom they pay very little; in addition, their officers are, in my book at least, more or less crooks, with shady histories.

What I always like to do in these cases is to see if there are some factors that I’m overlooking, something in their financial statements that really damns this company. I like to learn from situations like this. But in this case, the financials looked superb, and the technicals were right too. So I just held my nose and bought a large number of shares, following my system. I actually put about 8.5% of my investments into this one company, or about 38% of my yearly salary.

That was in late May. Shares of the stock are now selling for more than double what I bought them for. I sold some of my shares at a profit of over 100% shortly before the earnings report, but the report was great, so I’m buying them back. This lousy, horrible, awful company has a way to go yet.

If I had exercised my discretion (i.e. trusted my gut) rather than blindly following my proven system, I wouldn’t have bought a single share in this company. That’s why it’s very important to be comfortable with your system. If it’s giving you a lot of stocks that you’re uncomfortable buying and it’s not making you rich, you need to do some more work on it. That’s a better approach than giving up on it and following your gut. Be discretionary about the process, not about the stocks that the process gives you.

But how do you trust the financial reports that unscrupulous companies issue? The key is to use a lot of metrics that ensure those reports are more or less honest—or at least of better quality than most companies. You don't just look at earnings: you look at sales and operating income and free cash flow and gross profit. You look at the stability of their operating margin, their accruals, their Altman Z-score, late reporting, quarterly sales stability, short interest, share turnover, and so on. If you evaluate companies carefully, it's like checking under the hood of a used car before you buy it.

When I set the amount I’m going to buy of a stock, I use an Excel spreadsheet that makes a few minor adjustments. Some of those adjustments depend on trading difficulties—if a stock has a big bid-ask spread or is very thinly traded, I’ll deduct a few points and buy fewer shares. But what I used to do is to award a company extra points or deduct points based on reviews on Glassdoor, which are written by companies' employees. It’s time-consuming to go through these, but Glassdoor does offer some interesting metrics, so long as enough people have written about the company (if it gets fewer than 25 reviews, it’s probably best not to look at them).

But I no longer consult Glassdoor. The reason for my investing success lies in my adherence to a carefully designed probability-based system which discovers things about companies that are not already reflected in their price. My edge lies in the numbers, not the looks. If I think a company’s products are lame or their management is crazy or they’re outdated or gimmicky, no doubt my opinion is shared by a large number of other investors, and that’s why the company’s price is low. The same is true if the common perception is that the management has no idea what they’re doing and it’s a terrible place to work.

If your system points to undervalued companies, it’s your job to ignore all the sentiment that justifies those prices, and to trust that you’ve found a diamond in the rough. Your biggest winners are always going to be the stocks that have been underestimated. Don’t underestimate them yourself. Instead, tweak your system so that you’re more comfortable buying them—perhaps in slightly smaller quantities.

Now there’s a behavioral issue involved as well. Take this scenario (which is mine):

You’ve lived all your life, over half a century, never getting paid more than $100K a year. You’ve saved diligently and you’ve invested wisely. You have $700K to invest in stocks. Your best model has you putting 6% to 8% into each position, and it’s a model that really works, that consistently beats the market big time in real time. So now you’re putting half a year’s salary into a hold-your-nose stock. You tell yourself it’s all about the process, and you’re doing fine.

And then someone asks you, “So, what companies are you investing in these days?”

You tell her.

“XXX is your #1 stock?” she says. “Are you kidding? Well, as long as it’s only a small position, I suppose it can’t hurt too bad.”

You tell her how much you own of this company.

“What?” she says. “You’ve put $45,000 into an unscrupulous company that rips off its franchises and sells snake oil? Are you nuts?”

“Well,” you say, “I also have a lot invested in YYY.”

“YYY bills their customers for thousands of dollars for a product that should cost $50 and then refuses to return their calls. And their CEO is a shady guy who once fired an employee because she was black. OK, that’s only two companies. What else do you own?”

You tell her. “There’s company ZZZ,” you explain, “which basically deals in stealth ads, the kind that get into your computer and pop up when you don’t want them to. And then there’s the mining company that mistreats its workers. And then, and then . . .”

I’m not about to stop putting huge sums of money into stinky stocks, but I have to have a very dark sense of humor about it.

CAGR since 1/1/16: 51%.

My top ten holdings right now: AUDC, PERI, OSIR, PCOM, FNJN, INTT, PMD, LFVN, GVP, GRVY.

How to Obtain Leverage Without Margin or Loans

Tamara buys a stock market index (VTI) and reinvests her dividends. She doesn’t use leverage. She began investing exactly ten years ago, and has made 178% on her investments, for an annualized return of 10.76%. Her initial $100,000 investment is now worth $278,000.

Jessika buys the same stock market index and reinvests her dividends. But she does use leverage, at 1.5X, with a 10% margin carry cost and a minimum maintenance margin of 35%. You’d think she’d make quite a bit more than Tamara, right? But no. Starting at the same point in time as Tamara, she gets a margin call after seven months. And even if she had avoided that margin call in 2009, her total return is still only 172%, for an annualized return of 10.56%. Tamara still wins, because leverage is not cheap in this world.

What if Jessika had used 2X leverage? Her equity would have fallen below zero in March 2009. The only way Jessika could have made more money than Tamara is if there had been no margin call and her margin carry cost had been below 10%. But there’s a psychological cost to consider as well: the standard deviation of her returns would have been almost double that of Tamara’s.

If you make the right deal, leveraging your returns can be quite profitable. Let’s say that Jessika had found a broker that didn’t make margin calls, gave her 1.75X leverage, and charged only 2% interest. At the end of ten years, she would have made 259%, for an annualized return of 13.64%. Her initial $100,000 would be worth $359,000.

But finding a broker like that would have been very hard, if not impossible.

Jessika could, of course, have taken out a personal or home equity loan. The problem there is that she would have had to pay a portion of the total (loan plus interest) every month, and if her home equity loan had been big enough, she would have lost her house after seven months. If she had obtained a ten-year loan for $50,000 at 6%, putting the entire amount into VTI and paying $555 a month for the privilege, she would end up with $276,268 at the end of ten years, which is still lower than Tamara’s total.

What if Jessika had simply bought a 2X leveraged ETF like SSO instead? Well, she would have received a return of 323%, or 15.52% annualized, and her $100,000 would be worth $423,000. But she would have lagged Tamara for the first five years after her buy and suffered a drawdown of 77%. Using leverage is highly risky, and leveraged ETFs are not recommended for long-term holding.

I’m going to suggest a very different approach for Jessika. I’m going to suggest that she use leverage by investing in companies that are using their leverage wisely. To get leverage safely, invest in companies that use leverage, but make sure their earnings are high enough to cover their debts.

First, we need to define leverage. For investors, leverage is straightforward: it’s the sum of the amount you have and the amount you borrowed divided by the amount you have. If you have $100,000 and you’re borrowing $50,000, your leverage is 1.5X. Similarly, for a public company, leverage is total assets divided by total equity. But this isn’t nearly as straightforward, because there are plenty of companies with zero or negative equity. How do you measure their leverage?

Let’s look at it mathematically. Leverage = assets/equity, so 1/leverage = equity/assets. Since equity = assets – liabilities, equity/assets = (assets – liabilities)/assets = 1 – liabilities/assets. So leverage = 1/(1 – liabilities/assets).

Now liabilities divided by assets is what’s commonly known as the debt ratio. And it’s clear from the above formula that the higher the debt ratio, the higher the leverage. If the debt ratio is 0.5, leverage is 2X. If the debt ratio is 0.8, leverage is 5X. If the debt ratio is 0.95, leverage is 20X. And if the debt ratio is greater than 1, then leverage is off the charts.

Given this, I’ve designed an index for Jessica: the Leverage 100. These are the hundred stocks on the market with the highest debt ratios (and therefore the highest amount of leverage), so long as their price is over $1.00 per share, market cap is over $100 million, EBITDA is greater than zero, and debt-to-EBITDA is less than ten. (Just so that nobody accuses me of cherry-picking, these are nice round numbers and well-established criteria. And yes, I also wanted all the limits to be made up of 1’s and 0’s. Just for fun.)

(In case you’re unfamiliar with these terms, EBITDA stands for earnings before interest, taxes, depreciation, and amortization. Debt-to-EBITDA is the ratio that banks and credit agencies look at when deciding if a company is borrowing too much. Companies with debt-to-EBITDA ratios over five often get lower credit ratings. All of the companies I’ve looked at whose bonds have CCC ratings right now have debt-to-EBITDA ratios of five or higher.)

With quarterly equal-weight reconstitution and 0.25% slippage costs, the ten-year returns of the Leverage 100 are impressive: 384%, or 17.09% annualized. Jessika would have made more money investing in this index than with any of her other options: her $100,000 would have grown to $484,000, leaving Tamara in the dust.

Do you want more than ten-year returns? Well, I can only backtest back to 1999, but the Leverage 100 has annualized returns of 14.03% since then, compared to VTI’s 7.04% (or the equal-weight S&P 500’s 9.02%). And if we reduce the number of stocks in the Debt 100 to the Debt 50 or the Debt 20 or the Debt 10, choosing the stocks with the very highest debt ratios, the ten-year returns go up: to 20.90%, 26.29%, and 30.45% annualized, respectively. (If you’d like to play around with this and you subscribe to Portfolio123, here’s the screen and here’s the simulation.)

What were these miracle stocks Jessika would have invested in? Seven stocks have been in the index for ten years running: Cincinnati Bell (CBB), Choice Hotels (CHH), Dennys (DENN), Dun & Bradstreet (DNB), Domino’s Pizza (DPZ), National CineMedia (NCMI), and Sally Beauty (SBH); AutoZone (AZO), Unisys (UIS), and Vector Group (VGR) have been in it almost as long. The current top ten are Domino’s (DPZ), Yum Brands (YUM), Wingstop (WING), Aspen Technology (AZPN), Nathan’s Famous (NATH), MSG Networks (MSGN), Weight Watchers (WTW), Mechel (MTL), Northern Oil and Gas (NOG), and Verisign (VRSN).

These high-debt-ratio companies are getting tremendous leverage. At the moment, every single stock in the Leverage 100 has a debt ratio greater than one, which means a practically infinite amount of leverage. Back in 2008, when Jessika was first investing, the Leverage 100 included 46 stocks with debt ratios less than one, so that you could quantify their leverage, which ranged from 16X to 2300X. But now, negative equity companies rule.

I should say a word or two about the negative equity phenomenon, which Travis Fairchild at O’Shaughnessy Asset Management has written about at length here. (I’ve also written about it at length here; this article explains why you should favor companies with high debt over companies with high equity.) Fairchild points out that negative equity companies have outperformed the market in 57% of rolling three-year periods over the last twenty-five years (unlike me, he includes companies with extremely low or negative EBITDA, which worsens his results). He rightly points out that some of the reasons these companies have negative equity are that their balance sheets understate the value of their intangible assets, that their long-term assets are depreciated too fast, and that their use of buybacks and dividends create a decrease in equity that can “accelerate distortions.” But what Fairchild doesn’t look at is these companies’ use of debt (and certain non-debt liabilities) as leverage to power their growth. In fact, the word “debt” appears nowhere in his paper.

Since negative equity companies have low total assets to begin with, it’s begging the question to use assets or equity in a measure of these companies’ debt. So let’s compare their debt load to their market cap instead. The median debt-to-market-cap ratio of the 126 negative-equity companies that currently have $100 million market caps and debt-to-EBITDA ratios under ten is 0.70; the median debt-to-market-cap ratio of the S&P 500 is 0.24, and the median ratio of the Russell 3000 is 0.25. By absolutely any measure, negative equity companies are awash in debt. And that’s why they thrive—not because their assets are understated.

As long as the debt-to-EBITDA ratio of these companies is reasonable, banks and bondholders are not going to be knocking on their doors for repayment. These companies have interest expenses, of course, but those expenses are usually pretty modest. The median trailing twelve-month interest expense of the Leverage 100 right now, expressed as a percentage of each company’s total debt, is 5.37%, and though that number was somewhat higher ten years ago (7.34%), interest expenses for public companies are in general a lot lower than what your broker charges.

Now some would argue that the reason these companies are getting such high returns is that they’re undervalued. In other words, the returns aren’t driven by leverage, they’re driven by investor mispricing. But I’m afraid that argument doesn’t hold water. The median EV/EBITDA of the Leverage 100 is 10.43; the median of the S&P 500 is 10.65. The difference is negligible, as is the difference in their median P/E ratios. It would indeed be hard to argue that Domino’s, Wingstop, Aspen Technologies, Weight Watchers, or Verisign are value stocks: by any conventional measure, they’re certainly not. Rather, they are companies that have figured out how to use massive amounts of leverage to their advantage.

John Rekenthaler, the vice president of research at Morningstar, has written that “purchasing securities on margin, at retail interest rates . . . is wiser than renting furniture with monthly payments—but only barely.” Instead, he recommends “investing in securities [that] put more than 100% of their assets to work.” That’s indeed the best way to get leverage to work for you.

CAGR since 1/1/16: 52%.

My top ten holdings right now: AUDC, FNJN, PCOM, GRVY, INTT, IRMD, MSON, ZYXI, KEQU, PMD.

When Is Investing Like Gambling?

Last May, Kit Chellel wrote a very interesting article for Bloomberg News about Bill Benter, who won $900 million betting on horse races. The races he bet on were run on a parimutuel system, where odds are updated in proportion to how bettors bet, with the house simply skimming a commission off the top.

One passage in the article leaped out at me:

Buried in stacks of periodicals and manuscripts, [Benter] found what he was looking for—an academic paper titled “Searching for Positive Returns at the Track: A Multinomial Logit Model for Handicapping Horse Races.” Benter sat down to read it, and when he was done he read it again.

The paper argued that a horse’s success or failure was the result of factors that could be quantified probabilistically. Take variables—straight-line speed, size, winning record, the skill of the jockey—weight them, and presto! Out comes a prediction of the horse’s chances. More variables, better variables, and finer weightings improve the predictions.

It struck me that that’s exactly what I’m doing when I trade.

The stock market is a bit like a parimutuel system. In parimutuel betting, all bets are placed in a pool, taxes and the house take are skimmed off the top, and the pool is shared by the winning bettors.

Let me give an example. Let’s say five horses are racing, and right before the race is run, all bets have been placed. $100 has been placed on horse #1, $200 has been placed on horse #2, $300 on horse #3, and so on. Altogether, $1500 has been bet. Let’s say the taxes and the take amount to 10%, leaving $1350 in the pool. If horse #5 wins, then those who bet on that horse will take home $1350 divided by $500, or a payout ratio of 2.7 to 1. If horse #1 wins, on the other hand, those who bet on that horse will take home $1350 divided by $100, or 13.5 to 1.

How is this like the stock market? Because in both cases, prices are set purely by the bidders, the traders, the buyers and sellers. The key to winning in a parimutuel betting system—just like the key to winning in the stock market—is to wield an advantage over other bettors/investors through better information/data and/or a better strategy.

Just like Bill Benter did, a wise investor can take factors that can be quantified, weight them, and come up with a prediction of a stock’s chances. The more and better variables, the better the predictions.

This has been my practice: to use as many and as good variables as possible, to weight them well, and to look at every decision I make in probabilistic terms. I’m betting on twenty-seven stocks right now, stocks that I think will be winners not only because they’re primed to beat other stocks, but because I’m using formulae that few other investors use. I’m interested not only in the future performance of the companies I invest in but in the behaviors of other investors in those companies, just as Benter was interested not only in the performance of the horse he bet on, but in the betting behavior of his competitors.

The relationship between gambling and investing is made explicit in the abstract to the 1986 paper that Bill Benter read: “This paper investigates fundamental investment strategies to detect and exploit the public’s systematic errors in horse race wager markets” (emphases added).

At some point, gambling and investing can become interchangeable. Bill Benter was a gambler. But what about Edward O. Thorp, one of the greatest investors in history? Fundamentally, he was a gambler too.

Thorp started out playing blackjack. He proved, mathematically, that the odds could be in his favor if he counted cards, and in his 1966 book Beat the Dealer he was the first to show exactly how it could be done. When Thorp placed his bets at a blackjack table using his method, was he gambling or investing?

“The overlap of interest between gambling and the stock market is very high,” Thorp once said. “It’s an amazing phenomenon. But there are so many similarities and so much one can teach you about the other. Actually, gambling can teach you more about the stock market than the other way around. Gambling provides an analytically simpler world, and you can see principles and test theories.”

Thorp went on to derive the Black-and-Scholes options pricing model a few years before Black and Scholes (he decided to keep it secret in order to make money on it). Between 1969 and 1988 his Princeton Newton Partners firm made 19.1% annually, with a positive performance in 227 out of 230 months. Frederik Vanhaverbeke, in his book Excess Returns, points out that the probability of getting this kind of performance by pure chance is smaller than the probability that one would find a specific atom by looking in a random place on earth. Over twenty-nine years, Thorp’s compound annual return was almost 20%.

Now a lot of gambling has nothing to do with investing, and a lot of investing has nothing to do with gambling. Gambling based on odds set by a money maker rather than by other gamblers (as in most sports betting these days), gambling on slot machines, gambling on lottery tickets—these have little in common with investing. Dividend investing and fixed-income investing have little in common with gambling.

But I would argue that the point when successful gambling and successful investing become interchangeable comes when your aim is to beat the market, you take a purely systematic approach, you never let your emotions get in the way, and you let the data do the work.

If you take a rigorous probabilistic approach and put in lots of practice and hard work, it’s not that difficult to beat the house.

CAGR since 1/1/16: 52%.

Top ten holdings right now: LFVN, FNJN, IRMD, PCOM, AUDC, MGIC, PERI, MSON, ZYXI, MNDO.