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L.26 · BEGINNER · 4 MIN

Rank-Screening on ROIC and Earnings Yield

Joel Greenblatt popularized a deceptively simple quantitative value strategy: rank the investable universe on two factors only — return on invested capital and earnings yield — then buy a basket of the highest-combined-rank names. The strategy combines a quality factor with a price factor in the most parsimonious way possible. It has a genuine long-run edge in the published evidence. It also has structural features that make it operationally difficult to run, and understanding both halves is part of the canon every serious quantitative-value student should absorb.

Quiz · 5 questions ↓
§ 01

Return on invested capital, often abbreviated ROIC, measures how productively a company converts each dollar of operating capital into operating profit. High ROIC is the quantitative fingerprint of business quality — a company that earns 25 cents of operating profit on each dollar of invested capital is structurally different from a company that earns 6 cents. Earnings yield is the inverse of the price-to-earnings multiple — a stock with a 10 multiple has a 10 percent earnings yield, and earnings yield is the parsimonious quantitative fingerprint of price-cheapness.

§ 02
Factor combinationWhat the strategy targetsWhy the combination matters
High ROIC aloneQuality businesses regardless of priceTends to identify durable franchises but does not protect against paying any price for quality
High earnings yield aloneStatistically cheap stocks regardless of business qualityTends to identify Graham-style cheapness but does not protect against value traps where the business is genuinely deteriorating
Combined two-factor rankQuality businesses available at a reasonable priceThe combination protects against both ends — paying any price for quality and buying cheapness without quality — and is the structural source of the strategy's long-run edge
§ 03

The mechanical implementation is unusually simple. Rank every investable stock in the chosen universe on each factor independently, sum the two ranks, buy a basket of the top names — typically 20 to 30 holdings — hold each name for roughly a year, then refresh the ranking and rebalance. Greenblatt's preferred implementation excludes financials and utilities and applies a minimum market-cap floor; small variations in the construction rules do not materially change the long-run results.

§ 04
Combined Rank Score = Rank On Earnings Yield + Rank On Return On Invested Capital
§ 05

The well-known underperformance windows. The strategy's long-run edge is not a steady year-over-year drip; it shows up as a cycle of strong years interrupted by multi-year stretches of underperformance. The 2010 to 2014 period is the most-documented modern example — the strategy lagged the broad market by several percentage points per year for several consecutive years, primarily because the post-crisis bull market was led by quality growth names whose multiples were already high enough to keep them out of the high-earnings-yield half of the rank. Earlier multi-year underperformance windows show up in the late 1990s late-cycle technology run and in shorter stretches throughout the 1980s. The frequency of multi-year underperformance is structurally embedded in the strategy and is not a sign that the strategy is broken when it occurs.

§ 06

What the underperformance windows do to professional implementations. Professional managers running the strategy inside an institutional vehicle face quarterly or annual performance evaluations from clients who often cannot tolerate three to four consecutive years of lagging the broad market, regardless of the strategy's long-run record. The structural mismatch between the strategy's cycle and the typical professional evaluation cycle is the load-bearing reason so few professional managers run the strategy in its pure form, even though the long-run evidence base is real. The strategy works most cleanly for investors with the structural ability to commit to a full cycle — individuals investing their own capital, family offices, or explicitly long-term institutional vehicles.

§ 07
Pull up the most recent quarterly financials for any one company you own or are studying. Compute ROIC as operating profit divided by the sum of debt and equity. Compute earnings yield as earnings per share divided by current price. Imagine ranking this company within a universe of roughly 1,500 stocks. Where do you think it would fall on each factor? Then ask the harder question: would you actually be willing to hold a basket of the top 25 combined-rank names for the full cycle through the next multi-year underperformance window, without intervention?
§ 08
An individual investor with patient capital and no external client base implements the two-factor rank-screen, holds a 25-name basket through the strategy's typical one-year rebalance cycle, and at the end of year three finds that the portfolio has lagged the broad market by roughly 14 percentage points cumulatively. The investor is considering whether to abandon the strategy. Which framing is most consistent with the structural evidence on the strategy?
§ 09

A strategy with a real long-run edge is not the same thing as a strategy that is easy to run. The two-factor rank-screen is a particularly clean illustration: the edge is genuine, the implementation is mechanically simple, and the underperformance windows are structurally embedded enough that the strategy has historically been most workable for investors whose evaluation horizons match the strategy's cycle rather than the typical professional review cycle.

Five questions · AI feedback

Sit with the ideas.

A reader is told that a two-factor rank-screen combining return on invested capital and earnings yield generated meaningful long-run excess returns in the academic literature and the practitioner record. The reader plans to implement the screen and asks why so few professional managers actually run the strategy in its pure form. Which response best captures the practitioner consensus on the strategy?

Why:
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