What Four Stock Picking Formulas Reveal About Beating The Market

F-Score

Joseph Piotroski developed the F-Score, which combines 9 criteria to measure a company’s financial strength across three major themes: profitability, leverage, and operating efficiency. The F-Score is then combined with a valuation metric, the book-to-market ratio (B/M), to rank each stock’s attractiveness.

Magic Formula

The Magic Formula was developed by Joel Greenblatt and popularized in his book, The Little Book That Beats The Market. The Magic Formula uses the combination of 2 metrics to rank stocks: earnings yield (EY) and return on capital (ROC). Earnings yield measures relative valuation, while return on capital measures profitability and operational efficiency.

Acquirer’s Multiple

Tobias Carlisle’s Acquirer’s Multiple was popularized by his book of the same name. The Acquirer’s Multiple uses only one valuation metric to rank stocks. This valuation multiple is calculated by dividing a company’s enterprise value (EV) by its operating earnings. Enterprise value is the sum of a firm’s equity market capitalization and its debt.

Conservative Formula

Pim van Vliet and David Blitz authored the Conservative Formula, which combined three market anomalies into one stock rank. The three underlying components, which are equally weighted, are: volatility, net payout yield (NPY), and price momentum. The volatility component seeks stocks with a lower 36-month historical return volatility. The net payout yield measures the company’s capital return to shareholders by combining the dividend yield with the net share buyback yield. Lastly, the price momentum piece favors stocks with the highest cumulative total return for an 11-month period ending one month before the ranking.

Formula Investing Results

This analysis used the US stock market as defined by the CRSP/Compustat universe, but excluded microcaps, very small companies. The performance period was 1963 to 2022. Each stock is divided into a quintile based on its investment formula rank to aid analysis.

Notably, all four investment formulas showed increasing returns when stocks were sorted into deciles, with the top-ranked decile outperforming the bottom by a meaningful amount. The top portfolios also outperformed the market.

Formula Investing Portfolio Performance

Using a methodology more likely to be implemented by an investor, the top 40-ranked, equally weighted stocks for each investing formula were analyzed from 2000 to 2022.

Three out of four formulas showed sizable annualized outperformance versus the market, but all three long-term outperformers had higher volatility of returns and a larger maximum drawdown than the market as a whole. While the Conservative Formula had slightly lower annualized returns than the index, it did so with a smoother ride, thanks to lower price volatility and a lower maximum drawdown. This outcome makes sense, since the Conservative Formula assigns one-third of its ranking to low price volatility. The low volatility anomaly can yield better volatility-adjusted returns, but it does not necessarily lead to absolute outperformance.

Implications For Investors

As seen in a recent analysis of top-performing stocks, the major drivers of outperformance in these investing formulas were valuation and profitability, often referred to as quality. One investing formula adds price momentum as another driver. Despite not being a fundamental measure, price momentum has a long history of performance enhancement for investment strategies.

Beyond adding to the evidence of value and quality being durable drivers of investment performance, these relatively simple investing formulas bring home Warren Buffett’s famous words: “Investing is simple, but not easy.” While these investment formulas delivered impressive long-term results, the average investor would have difficulty using them in their portfolio construction. Investors would have needed to stomach significant periods of underperformance in order to realize the long-term rewards of these strategies.

The F-Score, Magic Formula, and Acquirer’s Multiple had significantly higher price volatility than the market and a deeper maximum drawdown. Further, the portfolios would have acted significantly differently from the market. For example, the best-performing, the Acquirer’s Multiple, outperformed the benchmark by 2.2% annualized, with a tracking error of 12.4%. This means that in the normal year, the strategy could be expected to outperform or underperform the market by 24.8 percentage points! To put the magnitude into context, a typical professionally managed active investment portfolio has a tracking error of about 2-5%.

While a higher tracker error is not bad in and of itself, most investors become uncomfortable when their portfolio acts so differently from the index. Obviously, this isn’t a problem when it significantly outperforms, but it is human nature for doubt to creep in about the formula’s future effectiveness when there is severe underperformance. For example, the Acquirer’s Multiple portfolio would have fallen by 15.2% in 2015 while the market rose by 1.4%. Would investors have stuck around for 2016 to collect some significant outperformance again, 35.3% versus the market’s 12.1%? Interestingly, the strategy then underperformed for the next three years, 2017 to 2019.

The final point is that markets often deviate from rewarding the long-term drivers of stock performance, like valuation and quality, which makes sticking with a winning formula very difficult. Currently, small-cap investors have been experiencing this phenomenon since early 2025, with companies in the Russell 2000 index with negative earnings outperforming those with positive earnings. While one can be very confident that this situation will eventually revert to the opposite, which is consistent with historical behavior, the recent outperformance of money-losers has raised doubts about small-cap investment strategies that focus on profitable companies.