The Setup
On May 7, 2026, Rep. William R. Keating, a member of the House Armed Services Committee, bought positions in JPMorgan Chase, Northrop Grumman, Simon Property Group and VMware. The obvious headline is that an Armed Services member bought a defense company.
The more useful observation is that these four businesses have almost nothing in common by industry. One is a bank, one builds military hardware, one owns shopping centers and one sells enterprise software. What they share is a financial fingerprint: strong return on equity, durable operating margins, moderate debt, and cash generation that does not depend on favourable conditions.
That fingerprint, rather than the committee assignment, is the thing worth testing. If it works as a systematic screen, it works for anyone, with no disclosure filings required.
How to Think About This
The test compares two strategies built on the same screen. Both start from companies that clear four quality requirements drawn from the shared profile of those four holdings: strong return on equity, durable operating margins, debt kept within reasonable limits, and consistent free cash flow.
The thesis strategy ranks the qualifying companies with 60% weight on those fundamentals and the remainder on how their share prices have been behaving. The control strategy ranks exactly the same qualifying companies almost entirely on price behaviour.
That design isolates one question. Both strategies hold companies from the identical pool, so any difference in results comes from the ordering rather than the filtering. If the two finish close together, the filter did the work and the sort barely mattered.
| Strategy | Quality Filters | Ranking Method |
|---|---|---|
| Congressional Quality (Thesis) | ROE >= 15%, OPM >= 20%, D/E <= 2, FCF/sh >= $3 | 40% Momentum / 60% Fundamental |
| Momentum Control | ROE >= 15%, OPM >= 20%, D/E <= 2, FCF/sh >= $3 | 80% Momentum / 20% Fundamental |
What the Data Revealed
Both strategies ran from June 1, 2021 through May 25, 2026 starting with $100,000, holding 15 positions with equal weighting, monthly rebalancing, quarterly reconstitution and realistic trading friction of $0.005 per share commission and 0.1% slippage. Both included a 20% hard stop, a 15% trailing stop and a 35% maximum drawdown limit that halts the plan.
The Congressional Quality strategy screened 139 companies and made 180 trades over 1,370 trading days. It returned 37.4% in total, 6.6% a year, with a Sharpe ratio of 0.25 and a worst drop of 22.6%. It won on 52.8% of trades with a profit factor of 1.52. A Sharpe of 0.25 means you earned a modest premium for the volatility you sat through, which is livable rather than exceptional. The 22.6% drop means your $100,000 would have fallen to about $77,400 at the worst moment.
The Momentum control screened the same 139 companies and made 181 trades. It returned 40.9%, 7.1% a year, with a Sharpe ratio of 0.29 and a worst drop of 23.4%. It won on 53.0% of trades with a profit factor of 1.55.
The price-weighted approach won on total return by about 3.5 percentage points, and it sat through a slightly deeper trough to get there, 23.4% against 22.6%. The Sharpe ratios were close at 0.29 against 0.25, so both delivered similar efficiency for the risk taken. Where they differed was in what they held. The thesis strategy rotated toward the strongest balance sheets and cash flows. The control chased whatever was climbing. During the 2022 correction, when growth companies sold off hard, the fundamentally weighted portfolio recovered faster because it held companies whose cash flows did not depend on cheap borrowing.
Neither strategy clearly beat the other, and that is the finding. The filter set did most of the work. Both started from the same 139 qualifying companies, and whichever way you sorted them the results landed in the same neighbourhood, because the screen had already removed the fragile businesses. The edge was in the screen, not the sort.
| Strategy | Total Return | Sharpe | Max DD | Win Rate | Trades |
|---|---|---|---|---|---|
| Congressional Quality (Thesis) | +37.4% | 0.25 | 22.6% | 52.8% | 180 |
| Momentum Control | +40.9% | 0.29 | 23.4% | 53.0% | 181 |
What You Can Do With This
If you take one idea from this, take the finding that the screen mattered more than the ranking. It is worth far more of your attention to decide which companies are eligible than to adjust how you order the ones that qualify.
Build the filter from traits rather than from headlines. Strong return on equity, durable margins, debt kept in check, real cash generation. Those four requirements are describable in a sentence and testable across the entire market.
Then run the same screen with two different rankings, exactly as this test did. If the results land close together, you have learned that your filter is doing the work, which means your time is better spent improving it than adjusting the sort.
Run The Test
Both strategy JSON files are available in the Stax public strategies directory. Run them yourself to verify: