Narrator: Imagine a team of stock-picking experts who have access to a powerful, data-driven system with a remarkable track record of identifying winning stocks. This system, the Value Line Investment Survey, consistently produced research that, if followed, would have generated cumulative gains of nearly 76 percent over a five-year period. Yet, the mutual fund run by these very same experts, the Value Line fund, lost a cumulative 19 percent over that same period. How could this happen? The fund managers, believing they could improve upon the system, ignored their own data and let their intuition and biases guide their decisions. They fell victim to the very human tendencies that sabotage investment success. This paradox is at the heart of James P. O’Shaughnessy’s landmark book, What Works on Wall Street. It’s a comprehensive, data-rich investigation that systematically tests decades of investment strategies to uncover what truly leads to long-term market-beating returns, and more importantly, why the biggest obstacle to achieving them is often ourselves.

Narrator: A core argument of the book is that human judgment, especially in complex and uncertain fields like investing, is deeply flawed and consistently outperformed by simple, data-driven models. We believe in the power of expert intuition, but the evidence tells a different story. O'Shaughnessy points to numerous studies outside of finance that reveal this limitation.

Consider a psychological study where seasoned experts were tasked with distinguishing between neurotic and psychotic patients using a standardized personality test. A simple model, using a few key data points from the test, achieved a 70 percent success rate. The human experts, despite their training and experience, couldn't match it; the best among them only reached 67 percent accuracy. Even after receiving extensive training and feedback, the human judges still failed to outperform the simple, unwavering model. The model won because it applied the same criteria consistently, every single time, without being swayed by fatigue, emotion, or a compelling but irrelevant detail in a patient's file. This illustrates a fundamental truth: models beat humans because they are not human. They are never inconsistent. This same principle applies directly to Wall Street, where "expert" fund managers, like those at the Value Line fund, let their flawed judgment override proven quantitative strategies, leading to underperformance.

Narrator: The reason models consistently beat experts is rooted in a deep-seated human bias: we are wired to prefer compelling stories over cold, hard statistics. O’Shaughnessy explains that we are far more persuaded by vivid, descriptive information than by abstract base rates, even when the base rates are overwhelmingly more predictive.

A classic experiment illustrates this perfectly. Participants were told they were analyzing a sample of 100 people, composed of 70 lawyers and 30 engineers. When asked to guess the profession of a randomly selected individual with no other information, they correctly used the base rate, guessing lawyer. But when given a worthless but descriptive detail, such as “Dick is a 30-year-old man who is well liked by his colleagues,” they abandoned the 70 percent probability and started guessing based on their "feel" for the person. When the description included stereotypes, like a love for mathematical puzzles, they almost universally ignored the base rate and bet on engineer. This preference for narrative over numbers explains why investors chase hot tech stocks with great stories but no profits, or why they get swept up in market manias. They are betting on the story, not the statistics, a tendency that systematic strategies are designed to prevent.

Narrator: After establishing the need for a systematic approach, O’Shaughnessy tests a battery of value factors over 52 years of market data to see which ones are most effective. While low price-to-earnings, price-to-book, and price-to-cashflow ratios all proved to be winning strategies, one metric stood out as the most consistent and powerful: the Price-to-Sales Ratio (PSR). The PSR compares a company's stock price to its revenues. O'Shaughnessy crowns it the "king of the value factors" because sales are much more difficult to manipulate than earnings, making it a more stable and reliable indicator of a company's underlying business.

The data is unequivocal. From 1951 to 2003, a strategy of annually buying the 50 stocks with the lowest PSRs turned a $10,000 investment into an astonishing $22 million. For comparison, investing in the 50 stocks with the highest PSRs—the most expensive stocks relative to their sales—turned that same $10,000 into just $19,118. The decile analysis is even more stark, showing a nearly perfect inverse relationship: as the PSR decile increases, the long-term compound return steadily decreases. This demonstrates that paying less for a dollar of a company's sales is one of the most reliable paths to outperformance.

Narrator: One of the book's most counterintuitive findings is that buying stocks based on high earnings growth is a surprisingly poor strategy. Common sense suggests that companies with rapidly growing profits should be great investments. The data, however, reveals the opposite. A strategy of buying the 50 stocks with the highest one-year earnings gains from 1952 to 2003 significantly underperformed the market. A $10,000 investment in this strategy grew to just under $3 million, while a simple investment in the All Stocks universe grew to over $5.3 million.

The reason for this failure is human psychology. When a company reports stellar earnings, investors get excited and project that extraordinary growth far into the future. This optimism gets baked into the stock price, often pushing it to unsustainable levels. The company is now priced for perfection. When it inevitably fails to maintain that breakneck growth, disenchanted investors sell, and the stock tumbles. The market consistently overpays for good news, making high-growth stocks a systematically risky bet.

Narrator: While growth factors like earnings are unreliable, O'Shaughnessy finds that another type of growth—price momentum—is an incredibly powerful predictor of future returns. The concept, known as relative price strength, is simple: stocks that have performed well over the past year tend to continue performing well. This is not just a statistical anomaly; it reflects the "wise crowds" theory, where a stock's price aggregates the collective judgment of millions of investors. A rising price signals that the crowd is becoming increasingly optimistic about a company's prospects.

From 1951 to 2003, buying the 50 large-cap stocks with the best one-year price performance turned a $10,000 investment into over $12.6 million, crushing the $3.1 million return of the Large Stocks universe. Conversely, buying the 50 worst-performing stocks was a recipe for disaster. This shows that while the market may overpay for past earnings growth, it is surprisingly efficient at pricing in future prospects through momentum. Winners tend to keep winning, and losers tend to keep losing.

Narrator: The book's ultimate conclusion is that the most powerful investment strategies are not based on a single factor, but on a combination of them. The best results come from uniting the discipline of value investing with the power of momentum. O’Shaughnessy demonstrates this with his "Cornerstone Growth" strategy. This multifactor model first screens for value by looking for stocks with a low Price-to-Sales Ratio (less than 1.5). From that pool of reasonably priced stocks, it then selects the 50 with the best one-year relative price strength.

The results are spectacular. This blended strategy, which buys cheap stocks that are starting to attract investor attention, produced a compound annual return of 18.31% from 1952 to 2003. It beat the All Stocks universe 100% of the time over all rolling 10-year periods. By combining value and momentum, the strategy ensures an investor is not overpaying for a stock (the value screen) while also confirming that the market is beginning to recognize its potential (the momentum screen). This synthesis of seemingly opposite approaches creates a robust, risk-adjusted model that consistently beats the market.

Narrator: The single most important takeaway from What Works on Wall Street is that successful investing is not a game of intelligence, but a game of discipline. The market is not a random walk; it is driven by timeless patterns of human behavior. The data proves that simple, logical strategies based on value and momentum consistently outperform both the market and the discretionary decisions of so-called experts. The greatest challenge, therefore, is not in finding a winning strategy, but in finding the emotional fortitude to stick with it through good times and bad.

The book leaves us with a profound and practical challenge: can you trust a simple, data-driven model over your own gut feelings? In a world that celebrates complex narratives and heroic predictions, the idea of succeeding by mechanically following a set of rules feels almost too simple. Yet, as O'Shaughnessy's exhaustive research shows, it is this very simplicity and discipline that separates the winners from the losers on Wall Street.