invest(igations)

The Abominable Anomalousness of the Anomaly Analogy

The other night I asked my son, a high school student who knows next to nothing about economics or the stock market, “Which is more likely to grow faster, a small company or a large company?” He answered, “A small company.” Then I asked him, “Which will rise in price faster, a company whose price is cheap compared to what it earns, or a company whose price is expensive?” He answered, “The cheap one.”

An anomaly is a strange or unusual occurrence, a deviation from the rule. Academics talk of the fact that small firms grow faster than large firms as a “size anomaly.” The fact that cheap stocks usually rise in price faster than expensive stocks is a “value anomaly.” But are these really “anomalies”? Or, like my high-school student suggested, are they in the very nature of firms?

I don’t want to go into the whole history of the efficient market hypothesis (EMH), the capital asset pricing model, and the application of Thomas Kuhn’s paradigm-shift theory to them, which is why these things are called “anomalies.” Instead I want to look at the big metaphor (the analogy) behind the term.

Back in 1972, Eugene Fama proposed that we could work with a model of “a capital market that is efficient in the sense that prices at every point in time fully reflect available information.” He has stuck with his theory of an efficient market, and even won the Nobel prize for it in 2013. Basically, the EMH views the stock market as a rather well-oiled machine. An anomaly, then, is analogous to a gear that’s gone slightly out of place.

I’d like to propose a different metaphor. The stock market is a badly oiled contraption, stuck together with cellophane tape and staples, and full of rust spots and leaks and broken parts. Its pricing mechanism is terrible and inefficient, and it runs a crazy, circuitous, and illogical course. Why? Because many of the price movements in stocks are based on the quirks of human behavior rather than on sound financial sense.

In this model, what the academics call an “anomaly” is really a thing in the machine that actually works the way it’s supposed to.

The reason movements in stock prices are so confoundedly difficult to predict is not because they’re efficient and reflect all known information, but because they are the products of thousands of small overreactions, unfulfilled expectations, and misguided second guesses. Rather than cancelling each other out, as Fama suggests, these behavioral quirks make stock prices far more volatile than they should be, and make them move in entirely unexpected directions.

This is where the savvy investor gets an advantage. By looking at the general principles behind this machine, she can see through all the smoke, hear through all the noise, and figure out approximately what certain stocks are doing and what they’re likely to do in the future.

Fama’s view of the stock market is Orwellian. In 1984, war is peace, freedom is slavery, and ignorance is strength. For Fama, a common-sense principle is an anomaly. So let me list, in alphabetical order, four of the many “anomalies,” or common-sense principles, that really govern the stock market:

1. The accruals anomaly. Companies with low accruals—whose earnings are backed by real cash transactions in the present—are more likely to do well than companies whose earnings are all predicated on future cash flows.
2. The size anomaly. Small companies generally grow faster than large companies.
3. The stability anomaly. Companies whose sales and earnings grow at a modest but steady rate are more likely to keep growing at a modest but steady rate than companies that are growing or shrinking extremely fast. Similarly, companies with big changes in margin—in other words, that are increasing their sales while decreasing their earnings, or increasing their earnings while decreasing their sales—are more likely to fall in price than companies that keep their margins steady by increasing both their sales and their earnings.
4. The value anomaly. Stocks whose price is low compared to similar companies with similar sales, earnings, and free cash flow are more likely to increase in price than stocks whose price is high.

All of these principles should either be immediately apparent after a few moments’ thought or can be easily explained in a paragraph or two. One doesn’t need elaborate models of stock behavior or decades worth of backtests to come to these conclusions.

Now these are not precisely the same anomalies that Fama and his accomplice Kenneth R. French talk about. Their “value anomaly” is based on book value alone, which even Benjamin Graham thought was a silly idea. Their “momentum anomaly” makes even less sense. But the size and accruals “anomalies” are very similar to theirs.

So if these are general principles rather than anomalies, what are the real anomalies in stock market behavior? Or are there any?

Let’s go back to my model of the stock market as a huge but terribly inefficient machine held together with matchsticks and glue. What would qualify as a “strange or unusual occurrence” for such a machine? Even a total breakdown, as happened in 1929 and 2008, wouldn’t be an anomaly. Nor would various other inefficiencies, like the overvaluation of “momentum” stocks, the huge jumps in price after earnings reports that showcase unsustainable growth, the huge drops in price when a firm decides to issue a few extra shares, and so on.

No, the only real “anomaly” in today’s stock market is the dominance in popular opinion of the academic view that the stock market is a well-oiled machine, that stock prices just reflect all available information, and that inefficiently priced stocks simply don’t exist.

My top ten holdings right now: SMMT, CVV, HDNG, ALSK, LXFR, VHI, QNST, ACNB, ELMD, GSL.

CAGR since 1/1/2016: 44%.

The Perils of High Growth

Operating margin is very simply defined: operating income divided by sales.

If a company’s operating margin is growing, then either its income is rising, its sales are slowing, or both. If its operating margin is shrinking, then either its income is falling, its sales are rising, or both. This isn’t much of a problem if the margin is shrinking or growing by a few percentage points. But a ten percent rise or fall in operating margin can indicate some serious problems. Because what you’d really like to see is a company whose sales are rising and whose income is rising too. In other words, you don’t really want to see operating margin grow or shrink very much. I’d much rather invest in a company with a stable operating margin than a rapidly growing one.

The stability of operating margin is just one of many metrics that are usually overlooked by investors, metrics that I have found extraordinarily useful in my investing.

Take a look at the following three quantile charts, which I created on Portfolio123. The first measures the performance of the Russell 3000 since 1999 if you group stocks into deciles by operating margin growth, trailing twelve months minus previous twelve months, rebalancing monthly with no transaction costs. The second does the same except for asset growth: the ratio of the TTM total assets to that of the previous twelve months. The third does exactly the same but for sales rather than assets.

In each case, you see a parabolic graph; in each case the highest performance was in a middle decile, and the highest and lowest deciles performed worst. This is especially true for sales--notice how the decile with the highest sales growth not only performed worst of all deciles, but actually lost a considerable amount of money, and the fifth decile beat the market by an annualized seven percent. The reason is simple: extremely high growth is usually unsustainable.

You’ll get similar parabolic graphs if you measure year-on-year ROE growth, profit margin growth, book value growth, employee growth, income growth, and change in the cash conversion cycle. The only year-on-year growths I’ve found that look more like an upward slope are in dividends and free cash flow. Only in those cases is higher growth really better.

So don’t invest in companies that boast an operating margin twenty percent higher than last year’s, or sales fifty percent higher than last year’s, or that have doubled their assets through acquisitions. Companies with middling growth rates are the best investments.

My ten largest holdings right now: SMMT, CVV, ALSK, HDNG, SONS, ELMD, LXFR, PRTS, ACNB, KMDA.

CAGR since 1/1/2016: 44%.

How Long Should You Hold a Microcap?

Value investing is probably at least a hundred years old: it was already a long-established practice by the time Benjamin Graham and David Dodd published the first edition of Security Analysis in 1934. And one of its central tenets is patience. One buys a stock that appears cheap and one waits patiently for it to rise in price to a level that approximates its intrinsic value. This could take years, and often does.

Let’s say you bought all the stocks in the S&P 500 and held them for four years. When would be the optimal time to sell each one? When their price is the highest, of course. The chart below plots the number of bars that it takes S&P 500 stocks to reach their four-year peak. (I obtained this data, and the data in the rest of the article, from Portfolio123 by screening every two years since 1999 for stocks that were in the S&P 500 or microcap universe four years earlier, so it therefore does not include stocks that no longer existed after four years). The bar on the right shows the most recent five months; that’s when 38% of the stocks reached their highest points. And no doubt most of those went (or will go) still higher.

Now the chart below repeats the same experiment with microcaps. The result is markedly different. 25% of the microcaps reached their peaks within five months of purchase, and another 25% reached their peaks within the last five months. Not only that, but the four-year survivorship rate for microcaps is only 74%—compared to 90% for the S&P 500—due to a higher level of mergers, acquisitions, and bankruptcies; if one were to take that into account, the percentage that reach their peaks four years after purchase would be markedly smaller.

And what kinds of peaks are they? Well, the average peak among that 25% that achieved their high within five months was an increase of 52% over the purchase price. Of course, one would have to be superhuman to sell at exactly the right point, but considering that peak was achieved an average of 43 bars (two months) after purchase, your superhuman stock seller would achieve a CAGR of over 1,000%. By contrast, the average high among the microcaps that lasted close to four years was an increase of 212% over the purchase price, which makes for a CAGR of 34%. There’s a huge survivorship issue here too, which I wasn’t able to take into account—a lot more microcaps are going to survive for 43 bars than for four years.

All this suggests that the optimal holding period for microcaps is significantly shorter than that for large caps—in fact, it’s only about two or three months.

Microcap investors have a host of advantages over other investors, which I’ve detailed here and Jim O’Shaughnessy has detailed here. But to reap the maximum profit from those advantages, it’s best not to play the buy-and-hold game. Over the last two years I’ve doubled my money by investing in microcaps. I would not have done half as well if I hadn’t sold most of my holdings within a few months. Patience is indeed essential to successful value investing, but with microcaps impatience may be more profitable.

My ten largest holdings right now: VHI, AVDL, ALSK, CVV, CRNT, ELMD, SMMT, GSL, CTG, KMDA.

CAGR since 1/1/2016: 47%.