What it measures

ib / lag(market value of equity, 6 months). NYSE stocks only. Exclude if EP < 0. Lag simulates the Dec 31 market equity used in original paper

Why it should work

Valuation: stocks that look cheap relative to fundamentals (earnings, book value, sales, cash flow) have historically out-earned expensive ones.

Full Sharpe
-0.07
Ann. Return (LS)
-1.7%
Ann. Volatility
25.5%
Max Drawdown
-90.0%

Growth of $1 — long-short

Technology only · cap-weighted · 331 months

Technology only
Where the edge comes from
Long leg Sharpe
0.58
top bucket, long-only
Long leg ann. return
13.8%
the buyable side
Bottom bucket Sharpe
0.47
the basket we short
Bottom bucket ann. return
15.5%
lower ⇒ wider spread

The bottom-bucket figures are that basket’s ownreturn (a long position in what the strategy shorts) — not the short side’s P&L. Long-short return = long leg − bottom bucket, so a falling bottom bucket widens the spread.

Performance by period
train
val
test
Sharpe by split
Train ’00–’120.50
Val ’13–’180.15
Test ’19–’26-0.69
Test FF5 α (ann.)
-23.2%
alpha vs Fama-French 5
Test FF5 α t-stat
-2.64
significant (|t| ≥ 2)
Monthly turnover
15%
of the long leg, per rebalance

Source study

Basu · 1977

Journal of Finance

5,357 citationsPublished +0.58%/mo
View on Google Scholar

Worked example

Live inputs for a real holding

AAPL · July 2026
InputValue
netinc122,575,000,000$
Market cap4,901,758$M
Formula
netinc / marketcap (drop if < 0)
Raw25006.3334Signed (×+1)25006.3334

signed_value is the internal ranking value; only its cross-sectional rank matters. $-vs-$M unit mix means ratio magnitudes carry a constant offset and are not comparable to textbook levels.

Replication

How closely this rebuild tracks the published research

Replicable
Open Source Asset Pricing signalEP
Correlation — full sample—
Correlation — test window—
Published monthly return0.58%

The OSAP comparison is only computed for the all-stocks variant — switch to “All stocks” above to see how the rebuild tracks the published series.

Style tilt

Size × value map of the long leg

56 classified
Value
Blend
Growth
Large
Mid
Small
65%16
17%1
·
12%15
3%4
·
3%20
·
·

Share of long-leg capital by market cap × book-to-market, using terciles of the 421-name universe at July 2026. Rows: Large ≥ $8.9B, Small < $1.9B. Columns: Value ≥ 0.63, Growth < 0.38 B/M. The dot marks the capital-weighted centroid of the book — 89% toward Large, 10% toward Growth. Hypothetical holdings — descriptive, not realized P&L.

Tilt over time
Size tilt89% → Large
SmallLarge
Value ↔ growth tilt10% → Growth
ValueGrowth

Capital-weighted centroid of the long leg, December 1998 → July 2026; the right-hand end is the same value as the box’s dot. 56 names now. Hypothetical holdings — descriptive, not P&L.

Since publication

Did the edge survive the paper coming out?

published 1977
Entirely since publication
All 331 months of our record post-date the 1977 paper.
Sharpe -0.07-1.7% p.a.January 1999 – July 2026

There is no “before” to compare against — the predictor was already public when our data begins, so every month shown is out-of-sample relative to the original study.

Split at January of the year after the factor was published. The post-publication stretch IS genuinely out-of-sample relative to the original study -- the predictor was public by then -- so it speaks to whether the effect survived being known. Nothing is fitted here, so this is performance SINCE PUBLICATION, not validation of a model. Note the 'pre' side is our data before publication (our panel starts ~1999), NOT the study's original in-sample period, which usually ran decades earlier; a decay figure compares before-vs-after within our sample and is not a comparison against the published result.

Derivatives risk (Rule 18f-4)

Relative VaR against the designated reference portfolio — as implemented here

long-short

This assessment describes the research long-short construction — long the top bucket, short the bottom.

Governing rule
Rule 18f-4(c)(2)(i) relative VaR (exception unavailable)

This fund does NOT qualify for the limited-derivatives-user exception (100% of net assets vs <= 10% of net assets), so the relative VaR test governs. Note the inversion: a dollar-neutral long-short book suppresses the market risk the VaR ratio measures and so tends to pass it, while being barred from the exception by construction — what disqualifies the strategy is the exposure threshold, not the risk limit.

Limited derivatives user exceptionby construction

Rule 18f-4(c)(4): a fund whose derivatives exposure (gross notional, including the value of assets sold short) is <= 10% of net assets is excepted from the VaR tests and the full derivatives risk management program.

Does not qualify
Required
<= 10% of net assets
Exposure
100% of net assets
Margin
−90pp

No confidence interval: this follows from portfolio construction, not from an estimate.

Rule 18f-4(c)(2)(i): fund VaR at 99% over 20 trading days must not exceed 200% of the designated reference portfolio's VaR on the same basis.

Not settled by the data
Measured
2.0 (95% CI 1.3-2.6)
x reference VaR
Limit
2.00x
<= 2.00x reference VaR
Fund VaR
19.4%
99% / 20d
Reference
9.6%
FF5 market (mkt)

The interval spans the limit. The point estimate is 2.01x but the 95% interval runs 1.32–2.59x, which includes 2.00x. This test does not settle which side of the line the fund is on.

historical method · 331 monthly observations · about 3.3 in the 99% tail · paired percentile bootstrap over months

Same test, three estimators
historical
2.01x
over
parametric
1.74x
within
cornish fisher
1.88x
within

The estimators disagree about the verdict, not just the value — the choice of method decides the answer here. Historical VaR gives ratio 2.01 (fail) but Gaussian VaR gives 1.74 (pass). The pass/fail conclusion is an artefact of estimator choice, not a property of the strategy.

Engineering approximation of SEC Rule 18f-4 for research display. Not a compliance opinion and not a determination that any fund is compliant. Hypothetical model portfolio, not a registered fund.

Consistency across eras

Is this record broadly durable, or one regime?

26 windows
Positive windows
50%
13 of 26 3-year windows made money
Worst window
-1.34
Sharpe, January 2023 – December 2025
January 1999July 2026
Median Sharpe
-0.00
Dispersion
0.66
Best window
1.41

3-year rolling windows, stepping 1 year (26 windows). Dispersion is the spread of window Sharpes — higher means the record depends more on which era you look at.

Rules-based factors fit no parameters, so these windows are not out-of-sample tests and do not validate a fitted model. They show whether the factor's record is consistent across eras or driven by one regime.

Returns

Long-short is the research line; the long leg is what a long-only fund could hold

since January 1999
Trailing
PeriodLong-shortLong leg
1 yearcum.-38.8%-6.3%
3 yearsp.a.-31.4%7.3%
5 yearsp.a.-25.0%6.4%
10 yearsp.a.-15.3%15.1%
Since inceptionp.a.-4.8%11.6%
Calendar years
YearLong-shortLong leg
20267 mo-32.1%-7.4%
2025-21.5%12.9%
2024-38.8%10.9%
2023-33.6%46.2%
20224.8%-31.6%
202119.6%46.1%
2020-34.0%9.5%
20190.2%38.1%
2018-6.1%4.9%
20176.2%40.5%
20165.4%15.6%
2015-16.5%-6.4%
201423.0%33.2%
2013-1.3%31.0%
2012-15.0%1.6%
201113.2%-2.2%
2010-28.9%1.0%
20095.2%66.1%
200830.6%-43.1%
200711.3%8.8%
20064.1%9.9%
2005-8.0%1.7%
2004-5.2%21.1%
2003-13.8%42.5%
200246.8%1.6%
2001164.6%24.1%
20004.4%-9.5%
1999-59.8%28.3%

Long-short is the research line (long the top bucket, short the bottom); the long leg alone is what a long-only fund could actually hold. Trailing figures run through July 2026: 1 year is a plain cumulative 12-month return (cum.), 3 years and longer are annualised (p.a.). Years marked with a month count are partial. These match the fact sheet’s tables by construction. Hypothetical backtest, gross of the placeholder expense ratio and trading costs — not investor results.

Methodology

Signal computed monthly from Sharadar point-in-time data, signed so higher = higher expected return. Restricted to the Technology sector, then sorted into quintiles within that sector. The virtual ETF is long the top bucket, short the bottom, cap-weighted, rebalanced monthly. FF5 alpha regresses the long-short on the Fama-French 5 factors.

Hypothetical research backtest. Not an offer, recommendation, or investment advice.