We scan congressional trades, institutional filings, options flow, defense contracts, and 30 other data sources. When multiple unrelated sources point to the same stock, we score it. The more sources agree, and the more critical that company is in its supply chain, the higher the score. Higher scores win more often — at every single level.
Win Rate by Quality Score Threshold
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Each bar shows: of all picks scoring at least X, what percentage made money? The bars go down in a perfect staircase — zero exceptions. The odds of this pattern happening randomly: about 1 in 5,000.
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Top vs. Bottom
Return gap between best and worst scores
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Supply Chain Boost
Extra return from mapped companies
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Gain / Loss Ratio
Dollars won per dollar lost, top tier
How Each Tier Performed vs. the Market
Average return since February 12, 2026. The S&P 500 returned — over the same window.
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Full Score Breakdown
Detailed stats at every score threshold. Higher scores consistently produce better results.
Threshold
Picks
Win Rate
Avg Return
With Stops
$1K Becomes
How the Tiers Work
The score ranks picks into four tiers, each with different confidence levels and risk limits.
Runner (Score 7+)
Highest confidence. Multiple sources agree AND the company sits at a critical supply chain position. Stop-loss at –12%.
Core (Score 4–6)
Decent scores but missing something — fewer sources or a less critical supply chain role. Lower confidence than Runner. Stop-loss at –10%.
Tactical (Score 1–3)
Weak scores. The data flagged something, but not enough to be confident. Tracked for learning purposes. Stop-loss at –8%.
Avoid (Score 0 or below)
The system flags these as low quality. We track them to prove the scoring works — and they consistently lose money.
Why the raw losses look scary: The worst raw loss on the page is –82%. But that stock (Fujikura) was a Core pick with a –10% stop-loss — the managed loss caps at –10%, not –82%. The Avoid tier stocks that fell 30–55%? The system flagged them as low quality. The "With Stops" column in the score table above shows returns with risk limits applied.
Best and Worst Picks
Biggest wins and biggest losses since February 2026. Raw returns shown — see tier and stop-loss for what the managed loss would be.
Best Picks
Worst Picks (Raw — Stops Would Cap These)
Runner Tier Performance
Highest-conviction picks identified by the V4 quality model
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PICKS
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WIN RATE
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AVG RETURN
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W/L RATIO
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BEST PICK
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WORST LOSS
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Past performance does not guarantee future results. All investments involve risk including loss of principal. Returns shown are from detection date to current price and do not represent actual trades. This is not financial advice.
When Multiple Sources Agree
We monitor 34 independent data feeds — what Congress is buying, where hedge funds are moving, unusual options activity, defense contracts, lobbying spend, and more. When several of these unrelated sources independently point to the same stock, that's a convergence. The more sources agree, the stronger the signal. Updated daily.
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Stocks Tracked
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Days Live
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Supply Chain Boost
More Agreement = Better Returns
Every convergence gets a score from 0 to 100 based on how many sources agree, how recent they are, and whether they're telling a consistent story. Higher scores produce better returns — consistently, with no exceptions.
Supply Chain Mapping Adds an Edge
We built a map of 2,000+ companies and the materials they depend on. Stocks that show up in both the data feeds AND our supply chain map perform significantly better than those found by data alone.
IN SUPPLY CHAIN MAP
-- stocks
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avg return · -- win rate
DATA ONLY (NO MAP)
-- stocks
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avg return · -- win rate
Stocks in our supply chain map returned -- more on average, with -- higher win rate.
Score Tiers
Stocks in the supply chain map are grouped into four tiers by their overall score. The top tier (Runner) wins more often and returns more. Each step down performs worse. No exceptions.
Sample growing daily. We've been tracking live picks since February 2026. As more data comes in, the results become more statistically meaningful. We show everything — the system learns from real outcomes and gets better over time.
How It Works
What we scan: 34 independent data sources — congressional trades, hedge fund filings (13F), options flow, short interest, defense contracts, lobbying spend, prediction markets, technical analysis, and more. Each source is checked daily.
What triggers a pick: When two or more unrelated sources independently flag the same stock within a rolling window, the system scores it. More sources agreeing = higher score.
The supply chain layer: We built a map of 2,000+ companies and the materials they depend on. If a flagged stock also sits at a critical point in this map (e.g., it makes something that can't be easily replaced), the score goes up further.
Quality Score (0–10): Combines source count, how critical the company is in the supply chain, how big the opportunity is relative to company size, and sector relevance. Stocks are grouped into tiers: Runner (score 7+), Core (4–6), Tactical (1–3), and Avoid (0 or below).
Entry price: Closing price on the day the system first flags the stock. No backdating.
Returns: Measured from entry price to current price. Updated daily. Open positions shown as-is — nothing is cherry-picked or removed.
Risk management: Each tier has an automatic stop-loss: Runner –12%, Core –10%, Tactical –8%. The "With Stops" column shows what returns look like with these floors applied.
Deduplication: One pick per stock per 30-day window, so the same stock can't inflate the numbers by being counted multiple times.
No trading costs modeled: Returns don't include commissions or slippage. Real-world returns would be somewhat lower.
What We Show Honestly
Small sample: The live system has been running since February 2026 — less than two months. 270 picks and 751 flagged stocks is a real start, but not yet statistically bulletproof. We show everything so you can watch the track record build.
One market regime: This period has been mostly sideways-to-down (S&P 500 fell ~4%). We haven't yet seen how the system performs in a strong bull market or a crash. That data will come with time.
Survivorship bias: We only track currently listed stocks. Companies that got delisted or acquired aren't in the dataset, which may slightly inflate results.
Disclosure delays: Some data sources (like congressional trade disclosures) can be filed weeks after the actual trade. We measure from disclosure date, not trade date — so some of the move may have already happened before we see it.
The system learns: The scoring model adjusts its weights based on real outcomes. As more data comes in, the scores get more accurate — but it also means performance characteristics may shift over time.
What Would Change Our Mind
We believe the approach works. Here's what would make us reconsider:
If the top-scored picks (Runner tier) drop below a 50% win rate over any 3-month period, the scoring model may need rethinking.
If the staircase pattern breaks — meaning lower-scored picks start outperforming higher-scored ones — the quality score isn't working.
If stocks in our supply chain map stop outperforming those found by data alone, the map isn't adding value.
If the results only hold in one sector (e.g., it's really just a semiconductor momentum play), then the edge is narrower than we think.
Every pick is timestamped and tracked from the day it's flagged. If the pattern breaks down, the data on this page will show it — we can't hide it. See our full methodology page for deeper detail on how the system works.
See What the System Finds Next
The supply chain map tracks 2,000+ companies across semiconductors, defense, energy, and robotics. When a small company controls something critical and demand is growing, the system flags it.