ETF Foundry
value factor

Price

Long low Price · rebalanced monthly · cap-weighted long-short

What it measures

Log of absolute value of price (prc).

Why it should work

A value signal from the cross-sectional asset-pricing literature (Open Source Asset Pricing).

Full Sharpe
-0.05
Ann. Return (LS)
-0.9%
Ann. Volatility
17.2%
Max Drawdown
-61.3%

Growth of $1 — long-short

Financial Services only · cap-weighted · 331 months

Financial Services only
Where the edge comes from
Long leg Sharpe
0.29
top bucket, long-only
Long leg ann. return
7.8%
the buyable side
Bottom bucket Sharpe
0.49
the basket we short
Bottom bucket ann. return
8.7%
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
’00–’12 · ’13–’18 · ’19–’26windows
Evaluation windows
StartEnd
train
val
test

Recomputes the split Sharpes and test alpha. Full Sharpe, ann. return, max drawdown and OAP correlation span the whole sample and don’t change.

Sharpe by split
Train ’00–’12-0.03
Val ’13–’18-0.33
Test ’19–’260.04
Test FF5 α (ann.)
3.2%
alpha vs Fama-French 5
Test FF5 α t-stat
0.67
not significant
Monthly turnover
11%
of the long leg, per rebalance

Source study

Blume and Husic · 1973

Journal of Finance

187 citations
View on Google Scholar

Worked example

Live inputs for a real holding

AAPL · July 2026
InputValue
closeunadj333.74
Formula
log(closeunadj)
Raw5.8104Signed −1)-5.8104

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 signalPrice
Correlation — full sample
Correlation — test window
Published t-stat2.90

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

111 classified
Value
Blend
Growth
Large
Mid
Small
12%4
·
53%7
8%12
6%8
9%10
5%41
2%22
<1%3

Share of long-leg capital by market cap × book-to-market, using terciles of the 554-name universe at July 2026. Rows: Large ≥ $4.3B, Small < $753M. Columns: Value ≥ 0.61, Growth < 0.39 B/M. The dot marks the capital-weighted centroid of the book — 80% toward Large, 70% toward Growth. +4% unclassified (4 missing size/value). Hypothetical holdings — descriptive, not realized P&L.

Tilt over time
Size tilt80% → Large
SmallLarge
Value ↔ growth tilt70% → Growth
ValueGrowth

Capital-weighted centroid of the long leg, December 1998July 2026; the right-hand end is the same value as the box’s dot. 111 names now. Hypothetical holdings — descriptive, not P&L.

Since publication

Did the edge survive the paper coming out?

published 1973
Entirely since publication
All 331 months of our record post-date the 1973 paper.
Sharpe -0.05-0.9% p.a.January 1999July 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
1.4 (95% CI 0.9-2.1)
x reference VaR
Limit
2.00x
<= 2.00x reference VaR
Fund VaR
13.4%
99% / 20d
Reference
9.6%
FF5 market (mkt)

The interval spans the limit. The point estimate is 1.39x but the 95% interval runs 0.872.12x, 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
1.39x
within
parametric
1.18x
within
cornish fisher
1.31x
within

The estimators differ materially in value but agree on the verdict. Historical and Gaussian fund VaR differ by 18%; both still land on the same side of the 2x limit.

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
42%
11 of 26 3-year windows made money
Worst window
-0.88
Sharpe, January 2017 – December 2019
January 1999July 2026
Median Sharpe
-0.11
Dispersion
0.45
Best window
0.90

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.14.5%22.5%
3 yearsp.a.4.0%21.7%
5 yearsp.a.0.2%9.7%
10 yearsp.a.-1.3%12.1%
Since inceptionp.a.-2.3%4.1%
Calendar years
YearLong-shortLong leg
20267 mo3.7%5.8%
202513.0%29.0%
2024-10.7%15.6%
202323.8%42.7%
2022-18.0%-27.9%
2021-2.3%21.2%
2020-5.6%1.0%
2019-3.4%27.8%
2018-7.8%-15.3%
2017-11.6%9.3%
20169.5%25.9%
2015-7.0%-7.2%
2014-4.3%7.2%
20135.5%49.8%
201238.2%64.9%
2011-23.7%-32.7%
201029.4%39.7%
2009-29.4%-25.6%
2008-21.0%-58.9%
2007-11.8%-21.8%
20061.1%21.6%
20053.8%11.9%
20044.3%14.4%
200317.1%49.5%
2002-18.8%-32.8%
200130.9%14.0%
2000-22.4%-0.5%
1999-7.4%3.3%

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 Financial Services 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.