High52
Long high High52 · rebalanced monthly · cap-weighted long-short
Price (prc/cfacshr) divided by the maximum price over the previous 12 months.
Momentum: recent winners have historically kept outperforming recent losers over the following months.
Growth of $1 — long-short
Technology only · cap-weighted · 331 months
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.
Source study
George and Hwang · 2004
Journal of Finance
Worked example
Live inputs for a real holding
| Input | Value |
|---|---|
| Adj. close | 333.74 |
| Adj. close max12 | 333.74 |
closeadj / trailing-12m-highsigned_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
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
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 — 99% toward Large, 95% toward Growth. +1% unclassified (9 missing size/value). Hypothetical holdings — descriptive, not realized P&L.
Capital-weighted centroid of the long leg, December 1998 → July 2026; the right-hand end is the same value as the box’s dot. 83 names now. Hypothetical holdings — descriptive, not P&L.
Since publication
Did the edge survive the paper coming out?
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
This assessment describes the research long-short construction — long the top bucket, short the bottom.
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.
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.
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 dataThe interval spans the limit. The point estimate is 2.15x but the 95% interval runs 1.28–3.06x, 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
The estimators disagree about the verdict, not just the value — the choice of method decides the answer here. Historical VaR gives ratio 2.15 (fail) but Gaussian VaR gives 1.82 (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?
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
| Period | Long-short | Long leg |
|---|---|---|
| 1 yearcum. | 89.3% | 64.8% |
| 3 yearsp.a. | 39.3% | 49.0% |
| 5 yearsp.a. | 26.6% | 27.5% |
| 10 yearsp.a. | 9.4% | 28.6% |
| Since inceptionp.a. | 3.2% | 13.9% |
| Year | Long-short | Long leg |
|---|---|---|
| 20267 mo | 67.3% | 61.3% |
| 2025 | 0.7% | 16.0% |
| 2024 | 71.3% | 70.9% |
| 2023 | -17.9% | 38.3% |
| 2022 | 9.5% | -31.9% |
| 2021 | 28.5% | 31.3% |
| 2020 | -8.5% | 52.3% |
| 2019 | -5.0% | 43.0% |
| 2018 | 3.6% | -3.3% |
| 2017 | -13.3% | 33.0% |
| 2016 | -14.7% | 14.1% |
| 2015 | 15.4% | 3.3% |
| 2014 | 24.3% | 25.6% |
| 2013 | -10.0% | 36.9% |
| 2012 | 34.3% | 26.5% |
| 2011 | 26.8% | 7.0% |
| 2010 | -18.7% | 13.1% |
| 2009 | -49.1% | 14.7% |
| 2008 | 18.2% | -40.5% |
| 2007 | 18.8% | 14.9% |
| 2006 | 14.6% | 20.1% |
| 2005 | -19.3% | -6.3% |
| 2004 | 3.2% | 8.6% |
| 2003 | -40.3% | 34.9% |
| 2002 | -8.7% | -37.0% |
| 2001 | 9.9% | -13.3% |
| 2000 | 8.8% | -29.4% |
| 1999 | 36.7% | 113.7% |
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.