Profitability

Gross profit ÷ total assets (Novy-Marx). Higher = more cash from each dollar of capital.

As of 2026-06-10 · 35 names held · backtest spans 232 months

Trailing returns

-1.14%

SPY -4.49%

—

SPY —

-5.09%

SPY -4.36%

-5.21%

SPY -4.30%

YTD

-4.11%

SPY -3.79%

+4.96%

SPY +9.73%

+42.49%

SPY +65.09%

10Y

+269.92%

SPY +266.59%

20Y

—

SPY —

Cumulative return vs SPY

Performance stats

Metric	Factor	SPY
Annualized return (1 + total) ^ (252/4847) − 1	+12.57%	+10.30%
Annualized volatility daily-return stdev × √252	+22.24%	+19.66%
Sharpe ratio ann return ÷ ann vol (rf = 0)	0.57	0.52
Max drawdown worst peak-to-trough on the cumulative series	-60.34%	—
Information ratio ann excess return ÷ tracking error (vs SPY)	0.26	—
Monthly hit rate share of months where factor return > SPY	55% (127/232)	—

How it's computed

What. At each month-end, take each ticker's most recently reported gross_profit (revenue − cost of goods sold) and divide by total_assets. This is gross profitability as defined by Novy-Marx (2013).

Why it has worked. Novy-Marx showed that *gross* profitability has roughly the same Sharpe as value, but is nearly uncorrelated with it — so combining the two materially improves a portfolio. Gross profit is harder to manipulate than bottom-line earnings (which can be inflated via one-time gains, accruals, etc.), so it's a cleaner read on what the business actually produces. Scaling by total assets puts firms of different sizes on the same footing.

Caveats. Sector-tilted: software and pharma will dominate the top quintile because of high gross margins, while capital-intensive sectors (utilities, materials) cluster at the bottom. The factor works partly *because* of and partly *despite* this sector tilt. A sector-neutral construction would mute the effect.

Current sector mix

Sector	Names	% of screen
Information Technology	11	31.4%
Consumer Discretionary	9	25.7%
Health Care	6	17.1%
Consumer Staples	5	14.3%
Communication Services	2	5.7%
Industrials	2	5.7%

Current top quintile (35 names)

Ticker	Name	Sector	Signal ↓	Z-score
DECK	Deckers Brands	Consumer Discretionary	85.6%	4.17
LULU	Lululemon Athletica	Consumer Discretionary	74.3%	4.17
NVDA	Nvidia	Information Technology	74.2%	4.17
RL	Ralph Lauren Corporation	Consumer Discretionary	73.3%	4.11
ULTA	Ulta Beauty	Consumer Discretionary	69.2%	3.83
BBY	Best Buy	Consumer Discretionary	63.9%	3.47
LOW	Lowe's	Consumer Discretionary	53.3%	2.76
ADSK	Autodesk	Information Technology	52.6%	2.71
DLTR	Dollar Tree	Consumer Staples	52.4%	2.69
HD	Home Depot (The)	Consumer Discretionary	52.2%	2.68
EA	Electronic Arts	Communication Services	45.3%	2.21
DG	Dollar General	Consumer Staples	42.3%	2.01
TTWO	Take-Two Interactive	Communication Services	40.6%	1.90
CRWD	CrowdStrike	Information Technology	32.4%	1.34
CRM	Salesforce	Information Technology	28.7%	1.09
SNDK	Sandisk	Information Technology	27.3%	0.99
VEEV	Veeva Systems	Health Care	26.9%	0.97
DPZ	Domino's	Consumer Discretionary	25.2%	0.85
STE	Steris	Health Care	24.5%	0.80
TPR	Tapestry, Inc.	Consumer Discretionary	22.8%	0.69
DELL	Dell Technologies	Information Technology	22.4%	0.66
STZ	Constellation Brands	Consumer Staples	21.5%	0.60
IDXX	Idexx Laboratories	Health Care	21.3%	0.59
GWW	W. W. Grainger	Industrials	20.0%	0.50
CL	Colgate-Palmolive	Consumer Staples	19.4%	0.46
ADBE	Adobe Inc.	Information Technology	19.3%	0.45
FAST	Fastenal	Industrials	18.9%	0.42
PODD	Insulet Corporation	Health Care	17.7%	0.35
MCK	McKesson Corporation	Health Care	17.7%	0.34
TER	Teradyne	Information Technology	17.6%	0.34
MU	Micron Technology	Information Technology	17.5%	0.33
MTD	Mettler Toledo	Health Care	15.1%	0.17
FTNT	Fortinet	Information Technology	15.0%	0.16
AAPL	Apple Inc.	Information Technology	14.8%	0.15
EL	Estée Lauder Companies (The)	Consumer Staples	14.4%	0.12