ETF Foundry
value factor

CashProd

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

What it measures

Calculate market value of equity (mve_c) as absolute price (prc) times number of shares outstanding (shrout). Cash productivity is equal to the difference between mve_c and total assets (at) divided by cash and short-term investments (che).

Why it should work

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

Full Sharpe
-0.19
Ann. Return (LS)
-2.9%
Ann. Volatility
15.6%
Max Drawdown
-81.5%

Growth of $1 — long-short

All stocks · cap-weighted · 331 months

All stocks
Where the edge comes from
Long leg Sharpe
0.45
top bucket, long-only
Long leg ann. return
7.1%
the buyable side
Bottom bucket Sharpe
0.60
the basket we short
Bottom bucket ann. return
9.9%
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–’120.37
Val ’13–’18-0.52
Test ’19–’26-0.62
Test FF5 α (ann.)
-9.4%
alpha vs Fama-French 5
Test FF5 α t-stat
-2.21
significant (|t| ≥ 2)
Monthly turnover
12%
of the long leg, per rebalance

Source study

Chandrashekar and Rao · 2009

WP

2 citations
View on Google Scholar

Worked example

Live inputs for a real holding

AAPL · July 2026
InputValue
Formula
Raw99.4180Signed −1)-99.4180

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 signalCashProd
Correlation — full sample0.83 strong match
Correlation — test window0.74 strong match
Published t-stat3.60

Correlation compares an equal-weighted rebuild of this signal against Open Source Asset Pricing’s published monthly long-short series. Above ~0.6 is a strong match; 0.35–0.6 is moderate, usually reflecting data-vintage and universe differences rather than a different signal.

Style tilt

Size × value map of the long leg

322 classified
Value
Blend
Growth
Large
Mid
Small
34%48
51%39
3%3
6%77
2%25
<1%2
1%77
<1%18
<1%6

Share of long-leg capital by market cap × book-to-market, using terciles of the 3,283-name universe at July 2026. Rows: Large ≥ $5.2B, Small < $819M. Columns: Value ≥ 0.62, Growth < 0.34 B/M. The dot marks the capital-weighted centroid of the book — 94% toward Large, 30% toward Growth. +2% unclassified (27 missing size/value). Hypothetical holdings — descriptive, not realized P&L.

Tilt over time
Size tilt94% → Large
SmallLarge
Value ↔ growth tilt30% → 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. 322 names now. Hypothetical holdings — descriptive, not P&L.

Since publication

Did the edge survive the paper coming out?

published 2009
Before publication (pre-2009)
0.18
Sharpe · 3.0% p.a.
January 1999December 2009 · 132 mo
Since publication
-0.47
Sharpe · -6.8% p.a.
January 2010July 2026 · 199 mo
Change in Sharpe−0.65the return reversed sign — the published edge now runs the other way

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.

Within the limit as implemented
Measured
1.2 (95% CI 0.9-1.5)
x reference VaR
Limit
2.00x
<= 2.00x reference VaR
Fund VaR
11.6%
99% / 20d
Reference
9.6%
FF5 market (mkt)

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

Same test, three estimators
historical
1.20x
within
parametric
1.08x
within
cornish fisher
1.20x
within

The estimators agree, which is mild evidence the number isn’t an artefact of one method.

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
46%
12 of 26 3-year windows made money
Worst window
-1.38
Sharpe, January 2017 – December 2019
January 1999July 2026
Median Sharpe
-0.19
Dispersion
0.66
Best window
1.32

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.-0.8%16.3%
3 yearsp.a.-7.9%13.8%
5 yearsp.a.-10.6%8.2%
10 yearsp.a.-11.6%7.8%
Since inceptionp.a.-4.0%6.0%
Calendar years
YearLong-shortLong leg
20267 mo6.6%13.2%
2025-11.4%8.0%
2024-17.1%16.1%
2023-33.1%2.8%
202221.2%-4.1%
2021-10.2%26.7%
2020-32.4%-8.1%
2019-7.0%25.6%
2018-10.8%-9.5%
2017-18.7%5.7%
201620.3%22.9%
2015-15.8%-11.2%
2014-1.7%10.6%
20130.3%30.4%
20121.0%14.0%
2011-0.8%0.4%
20104.1%22.1%
2009-1.7%24.4%
2008-2.1%-39.0%
2007-17.8%-6.0%
200614.2%20.8%
20050.6%6.7%
200413.1%16.9%
20035.9%24.1%
2002-5.0%-22.0%
20019.1%-4.2%
200051.0%20.9%
1999-30.2%-4.8%

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. Stocks sorted into deciles within a liquid common-stock universe (price > $5, market-cap floor). 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. OAP corr 0.83 compares an equal-weighted version to Open Source Asset Pricing’s published series.

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