This piece attempts to encapsulate my conclusions after several years of investigating stock-market conundrums. It is, in essence, a grand unified theory of stock market investing. It is in ten succinct points. After laying out each point, I will offer some further thoughts and elucidations, and link to my previous articles on the subject in question.

Tenet 1: The price of a stock is completely determined by investor expectations.

Because a stock’s price is determined entirely by the willingness of investors to buy or sell it, it is exactly equal to the aggregate of investors’ confidence that the price will rise or fall in the future plus the expectations of dividends to be received and of the price of a potential acquisition. This investor confidence can be influenced by any number of things, from a Twitter recommendation to a careful discounted-cash-flow analysis; these things are called “factors,” and they are almost infinite in number. Some of them are based on rigorous accounting principles, some are based on investor beliefs (many of them incorrect), and a few seem to have no basis whatsoever.

Because the price of a stock is completely a function of investor behavior, stocks cannot be said to be “mispriced,” and there is no such thing as “luck” or “randomness” in the stock market. Many stock-market theorists try to separate the price of a stock into two components: value and noise. Others hold to the Efficient Market Hypothesis, that the price of a stock fully reflects all available information about it. But, as George Soros puts it, “The prevailing wisdom is that markets are always right. I take the opposite position. I assume that markets are always wrong.” Or, as I wrote here, “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.”

Tenet 2: Stock prices have only a very tenuous relationship to a company’s intrinsic value (if such a thing even exists).

Because a stock’s price is determined by millions of different investors’ confidence levels, most of which are the result of an almost infinite number of different factors, the complexity of the system that sets stock prices is beyond rational calculation. It is therefore impossible to rationally assign a “value” or a “target price” to a stock. When people talk about the “intrinsic value” of a stock, they are looking at the “intrinsic value” of the company of which the stock is technically a portion, and base that value on the company’s earnings, free cash flow, dividend payout, book value, enterprise value, and/or similar numbers. But while this may make some sense for a privately held company, once a company goes public, the equity portion of it becomes more or less unmoored from its intrinsic value and its value instead becomes whatever investors as an aggregate think it should be.

The very fact that the S&P 500 can include two technology stocks like Citrix Systems (CTXS), with a P/E of 123 and a price-to-book ratio of 21, and Hewlett Packard (HPE), with a P/E of 7 and a price-to-book ratio under 1 (these figures are as of 11/25/18), gives the lie to conventional measures of value. In addition, as I have shown, you can invest very successfully without ever looking at the price of the stocks you’re buying, which is further proof that “value” is an overrated factor.

Tenet 3: Successful investing requires thinking in terms of probabilities.

Successful investing lies not in accurately predicting the future value or prices of stocks but in holding the stocks that have the highest probability of delivering strong returns. In other words, think in terms of odds rather than targets.

Because stocks are so unmoored from so-called value and prices are set so capriciously, it makes more sense to focus on the odds that a stock’s price and dividend payments will go up or down than on how much the stock is “really worth.”

Tenet 4: These probabilities are determined by two interrelated things: the likelihood of a company’s future success and the likelihood that investor expectations are mistaken.

The stock market is quite a bit like parimutuel betting (betting where the odds are determined by aggregate bet size rather than by the house). Just like at the race track, the payout is determined by two things: whether a company succeeds and how much investors have bet upon that company (the stock’s market cap). When we buy a stock, we are essentially making a bet that its price (or market cap) will increase and/or that its dividends will pay off and/or that it will be acquired at a premium. And our odds are dependent on other people’s bets.

In parimutuel betting, we must take into account not only the factors that will make a horse more likely to win but the factors that will make other bettors less likely to bet on it. An example of the first kind of factor might be the horse’s pedigree or its time in previous races; an example of the second might be if you think the jockey or trainer is underestimated.

In the stock market, the first kind of factor is the kind that directly drives investor interest and thus increases prices, such as an excellent earnings report or an upgrade in analyst estimates. The second is the kind that signifies that a company is likely to exceed investor expectations, such as a high ratio of unlevered free cash flow to enterprise value (a value measure that few people use).

The ideal factor, then, is one which reverses conventional wisdom. For example, conventional wisdom says that a strong company has a high return on assets, exceptional revenue growth, a low debt ratio, a healthy ratio of net operating assets to total assets, a high beta, a high dividend yield, and a low price-to-book ratio. But a low return on assets is a strong predictor of future earnings growth, low but sustainable revenue growth is less likely to lead to investor disappointment, a high debt ratio enables a company to more efficiently use its capital resources, a low ratio of net operating assets to total assets signifies low accruals and a high proportion of cash on hand, low-beta stocks are more likely to have high alpha, a stock with a low dividend yield is less likely to have an unsustainable payout ratio, and stocks with very low or negative book values have an edge over those with high book values because equity financing is so much more expensive than debt financing.

An investor’s edge may lie in her ability to find advantageous factors like these and to leverage them efficiently.

Tenet 5: Low-volume stocks present the most opportunities.

The more people investing in a stock, the more complex the system of factors that sets its price; the fewer people investing in it, the more likely one can find some reason and rhyme to the stock’s price, and the easier it is to estimate the odds of its success or failure.

I use the word easier in a purely relative way: estimating the odds on a stock, no matter its size, is almost infinitely complex. But low-volume stocks, while expensive and difficult to buy and sell, are less complicated to evaluate. Jim O’Shaughnessy wrote a terrific article on this, which I recommend.

Tenet 6: In the stock market, risk and reward are related but not correlated.

Whether risk is measured as price variability, the likelihood of bankruptcy, or the likelihood of a steep loss in value, the relationship of risk and reward follows a curve that looks a bit like this. 

In other words, the highest reward is achieved by taking some risk, but not too much, and the worst losses result from taking too much risk.

How does this relate to investor expectations, probabilities, and factors? Well, according to the conventional idea that the higher the risk, the greater the reward, a factor that lowers risk shouldn’t work. However many of the best factors are precisely those that lower risk. For example, investing in stocks with low share turnover lowers risk while increasing returns precisely because it goes contrary to investor expectations about the market as a whole. Looking at a company’s quality by measuring its accrual ratios, the stability of its cash conversion cycle, the stability of its quarterly sales figures, and so on are wise things to do not only because one lowers risk but also because most investors don’t bother to look at these important indicators of a company’s potential.

Tenet 7: Consider as many factors as possible (within reason) when examining a stock.

This is advantageous for a number of reasons:

• you’re lowering your risk by “checking under the hood,” looking at everything that could go wrong;
• you’re maximizing the chance of using both types of factors: those that drive investor interest and those that confound expectations;
• while you may be introducing type 1 errors (relying on a factor that doesn’t really work), you’ll be avoiding type 2 errors (ignoring a factor that does work), which tend to have greater consequences;
• you’re mirroring, to some degree, the complexity of how stock prices are actually set.

Tenet 8: Mechanical judgments are more likely to succeed than discretionary ones.

In order to consider all these factors, the investor can either use her own discretion or can employ computer-based tools. Discretionary judgments are more fallible than those made by an objective calculation and are more likely to conform to the judgments of the majority of investors, thus denying the investor an edge. For example, in evaluating the management of a company, the investor would be better off relying on a deep, intelligent, careful, and original analysis of the company’s earnings statements and analyst estimates than on employee assessments or Internet scuttlebutt, since the latter are more likely to be already reflected in the stock’s price.

Tenet 9: It’s better to rank than to screen.

When employing computer-based tools to pick stocks to invest in, ranking systems offer more flexibility than screening systems. A screening system excludes a wide range of stocks that fail on a single measure, while a ranking system keeps more possibilities in play.

Tenet 10: Factors are best chosen by backtests.

Backtesting is a useful tool to test a stock-picking strategy, but it must be robust. A backtested strategy that is too closely aligned with historical data may have little predictive power. Moreover, every factor used in a backtest must have a logical explanation. Backtesting can too easily become data-mining, which is useless for out-of-sample success. But simply using a factor without backtesting it can lead to unintended results, and backtesting is an invaluable tool for looking at how a factor has worked in the past, and for refining factors to best reflect the disparities between investor confidence levels and likely future company performance. And finding those disparities is the key to successful stock picking.

CAGR since 1/1/2016: 41%.