Q4 2025 Convergence Report

Our convergence detector flagged 100 tickers where at least 2 independent data sources pointed in the same direction during Q4 2025. Of these, 17 crossed the high-conviction threshold of 5+ independent sources — the level where our backtested methodology shows statistically meaningful alpha over single-source trades.

Convergences mapped to our 7 tracked investment themes. A single ticker can appear in multiple themes (e.g., nuclear fuel names appear in both AI and Energy).

How often each data source appeared in a convergence. Congressional trades dominated — appearing in 72% of all convergences — but this partly reflects the breadth of congressional trading activity. The more useful metric is source independence: when sources with no structural relationship align, the convergence carries more weight.

6 additional sources (lobbying lead indicators, hyperscaler contracts, gov contract trends, prediction markets, job postings, Form 4 insider filings) each appeared in <5% of convergences. Low frequency doesn't mean low value — when these rare sources appear, they add meaningful independent confirmation.

Bullish/bearish/mixed breakdown by theme. Direction is determined by the consensus of individual data points within each convergence.

Convergence scores combine source count, source independence, and directional alignment into a single composite. Higher scores mean more sources agreeing with less structural overlap between them.

Most convergences are noise. The 55 tickers scoring 20–39 have only 2–3 sources and meaningful directional disagreement — they're where the system is watching, not where it's convinced. The 12 convergences scoring 60+ are where the data is speaking clearly: 5+ independent sources, strong directional consensus, and the kind of source independence that our backtested methodology shows produces measurable alpha over single-source trades.

A convergence is detected when multiple structurally independent data sources align on the same ticker, in the same direction, within a defined time window. The system is fully automated — no human curation or cherry-picking.

The convergence framework is fully documented with a backtested track record. The key insight: any single data source can mislead. When structurally unrelated sources independently point the same direction, the probability of noise drops materially.

Future reports will track: total convergences vs. prior quarter, theme rotation (which themes gained or lost convergence density), source composition shifts (are new sources emerging?), and high-conviction migration (which tickers crossed the 5-source threshold since last quarter).

Defense density is unprecedented. Twelve convergences across the defense theme, six at high conviction, and zero bearish. That's not one senator buying Lockheed — it's congressional trades, lobbying spend, federal job postings, options flow, and policy catalysts all pointing the same way across half a dozen defense contractors simultaneously. When the data is this uniform, the question isn't whether the thesis is right but how much the market has already priced in.

Energy convergence is splitting. Nuclear fuel chain names (uranium miners, enrichment, conversion) are clustering strongly bullish with high source counts, while broader clean energy names show mixed indicators. The market narrative treats "energy" as monolithic, but our data shows two distinct conviction profiles within the same theme. The nuclear fuel chain names are converging with the kind of source independence typically reserved for defense primes.

AI convergence is broadening beyond compute. Q4 2025 shows convergence spreading into infrastructure adjacencies: power (NEE, VST), networking, and the semicap stack. The most unexpected: INTC generated a 5-source, high-conviction convergence from 13F filings, congressional trades, government equity stakes, policy catalysts, and technical alignment — despite the stock being widely written off. When that many independent sources align on a consensus "loser," it's worth asking what the data sees that the narrative doesn't.

The 17 high-conviction convergences ranked by composite score. Each drew from 5–8 independent sources — the level where our backtested methodology shows the strongest historical alpha generation.

For each high-conviction ticker, which of our data sources confirmed the convergence — and which didn't. This matrix is the core analytical layer: it shows where each name's edge comes from and where the data gaps remain.

10 tickers sitting at exactly 4 sources — one data point away from triggering high-conviction convergence. These are the names most likely to cross the threshold in Q1 2026 as new 13F filings, congressional trade disclosures, and policy catalysts arrive.