Magic Formula Investing: A Concise Guide

What it is

Magic Formula Investing is a rules-based value investing strategy developed by Joel Greenblatt. It ranks stocks using two simple quantitative metrics—earnings yield and return on capital—and aims to identify companies that are both cheap and efficient at generating profits. The approach is systematic, unemotional, and designed for long-term application.

Core principles

Focus on quality at a reasonable price: buy companies with high earnings yields and high returns on capital.
Use objective screens and a repeatable process to remove emotion from decisions.
Build a diversified basket of top-ranked stocks and rebalance regularly.

Key metrics and definitions

Earnings yield: EBIT ÷ Enterprise Value (EV). EV = market capitalization + debt − cash. This measures how much operating profit the company generates relative to its total valuation.
Return on capital: EBIT ÷ (Net Fixed Assets + Working Capital). This gauges how efficiently a company turns capital into operating profits.
Universe filters: typically exclude financials, utilities, and foreign ADRs; Greenblatt’s original implementation screened companies with market capitalizations above a minimum threshold (commonly cited as $50 million or higher).

How to implement the strategy

Define the investable universe
Apply market-cap and sector exclusions (no financials, utilities, or ADRs).
Calculate the two metrics for each company
Earnings yield = EBIT / Enterprise Value.
Return on capital = EBIT / (Net Fixed Assets + Working Capital).
Rank companies
Rank by earnings yield and by return on capital, then combine the ranks to form a final ranking.
Select stocks
Choose the top-ranked stocks (typical implementations pick 20–50 names).
Build the portfolio over time
Many investors dollar-cost into the selection over a year (e.g., buy a few top-ranked names each month) to reduce timing risk.
Rebalance annually
Common practice: rebalance once a year. Many practitioners sell losing positions shortly before one year for tax-loss harvesting and sell winners after one year to capture long-term capital gains treatment.
Hold long term
Apply the strategy for 5–10+ years to realize potential outperformance.

Historical performance and evidence

Greenblatt reported very high historical returns in his books, but independent analyses have found more modest outperformance.
Example backtest (2003–2015) showed annualized returns of about 11.4% for the Magic Formula versus 8.7% for the S&P 500—an outperformance, but smaller than early claims.
Results depend on implementation details, time period, and market conditions.

Advantages

Simple, transparent, and easy to follow for individual investors.
Removes much of the emotional bias from investing decisions.
Backtests show periods of outperformance versus broad market benchmarks.

Limitations and criticisms

Popularity and changing market conditions can erode excess returns over time.
The original formula omits potentially useful variables (e.g., leverage, dividend yield, industry adjustments); some investors modify the screen for improvement.
Excluding entire sectors (financials, utilities) limits the universe—and may miss attractive opportunities.
Short-term performance can be volatile; success generally requires a long time horizon and discipline.

Practical tips

Use equal-weighted positions to avoid concentration in a few stocks.
Be disciplined about rebalancing and tax-aware selling (loss harvesting vs. holding for long-term gains).
Consider starting with a larger market-cap threshold if you prefer fewer small-cap risks.
Monitor and, if desired, test modest variations (e.g., different rebalance frequency or additional screening criteria) before applying them broadly.

Bottom line

Magic Formula Investing is a pragmatic, rule-driven approach to value investing that helps ordinary investors systematically find companies that are both cheap and profitable. It’s not a guaranteed path to extraordinary returns, but when applied consistently over long periods it has historically delivered modest outperformance versus broad market benchmarks.