To Gain An Investing Edge Analyze the Data Devotees, Not the Data
How can you gain an investing edge? That timeless question has confounded investors almost forever. Many fixate on data, thinking quick data access mines magical statistical relationships. “Quantitative” fund managers run vast sums on this premise. It isn’t just them: Belief in data’s dominance abounds.
This approach suffers one huge flaw: Data has become a near commodity. Smartphones harness almost endless data. Professionals consider parallel stats. Anyone can crunch the numbers. And anything anyone can do holds no investing edge. Today’s investing requires analyzing the data devotees themselves, not the numbers alone—to seek truths they shun. Let me explain.
Decades ago, in pre-Internet days, information was scarce—hence, precious. Morning newspapers brought yesterday’s news. Magazines came weekly or monthly—even older news. Deeper analysis often required esoteric library records, microfiche and archives.
Using data was tough, too—no algorithms or spreadsheets to array data and quickly test hypotheses. My father, Philip Fisher, possessed such high-powered data-crunching tools as a hand-crank comptometer and a pencil. Yet it was enough then to become an investing legend. When I started, I had little more. Testing new theories required painstaking effort.
When I developed the price-to-sales ratio (PSR) four decades ago, it worked wonders. PSRs compared a firm’s market capitalization to its revenues, identifying temporarily troubled, profitless firms with oversold stocks. I gathered data from The Wall Street Journal’s then daily “Earnings Digest,” quarterly company reports and monthly brokerage “stock guides” to calculate PSRs. It was tediously time-consuming. Eventually I paid Goldman Sachs $25,000 for a one-time PSR screen of all NYSE listings. Valuable!
PSRs worked then precisely because data was scarce. Few conceived of comparing prices to sales, or had the time, tenacity or resources to deploy PSRs broadly. After my 1984 book, Super Stocks, their popularity slowly grew. Professors taught them. More demand made PSRs available. Stocks priced them in, sapping their power. They don’t work anymore.
The Internet’s abundant, accessible data accelerated this process. Any widely known metric—from price-to-earnings and price-to-book ratios to now-coveted high-frequency metrics tallying COVID cases and restaurant reservations—is yours instantly. And if anyone can do it, it holds little stock market power—always.
Instead of accepting this, pundits, quantitative analysis firms and others double down, seeking ever-more data and deeper statistical complexities. Their exertion makes truly unique findings near impossible. Any data edge is fleeting. Big institutions get illiquid fast trading on it. All their data hasn’t helped quants navigate 2020.
Don’t get caught in their wake. Instead, see what the data-devoted dismiss as wrong or too simple because of biases. Humans are wired to seek data supporting pre-existing beliefs and dismiss contradictory information. Psychologists call this “confirmation bias.” It was hugely helpful for our pre-industrial ancestors, building the confidence needed to face daunting tasks with high failure rates. In markets, it’s a hindrance. But you can harness others’ susceptibility to bias as your edge.
Presently, confirmation bias thwarts the data devoted. Consider: Ever since this new bull market’s March birth, most observers have expected small-cap value stocks to soar. Why? Historical data says so! Bear markets usually pound small, low-quality firms most—priming them to surge off the bottom. Small value’s early bull market outperformance has a long, long data history—global small-cap value stocks surged 99.6% from March 2009’s low through that year end, trouncing world stocks’ 73.0%. But not this time! Too many expected it. When many believe something and everyone can do it, it is pre-priced. This is Markets 101.
Data devotion blinds adherents to contradictions in the current scenario, too. The ultra-swift contraction that hit when governments issued COVID-19 lockdowns didn’t give small value time to grind lower, reach capitulation and get primed to bounce. Global small-cap value stocks’ plunged -43.6% in about a month!
This unusual downturn’s specifics also present fresh headwinds for many small value stocks—like airlines. Yes, airlines are small cap. The entire global industry’s total market cap is $35.4 billion—smaller than 253 individual companies globally. Apple alone is nearly 50 times as big. Devotees ignore airlines’ huge headwinds because “the data” say small value leads early.
Another example: Most growth stock investors have net profit margins burned into their brains. But gross profit margins are a much better gauge of today’s future growth potential, measuring discretionary cash to plow back into the business—the only way to internally fund material growth. Yet few notice. Habitual bias toward net profit margins obscures simple truth.
Remember: While data are cold and unfeeling, everyone interpreting them is biased and emotional—human. Investing successfully now isn’t about extra data but about recognizing others’ blinding biases.