The universe is 39 liquid names — 38 large-caps plus SMH — but you never start with all 39. The Screener opens on a single screen, Oversold (14 names), because the 30-second promise only works one screen at a time. Every figure is computed from Yahoo Finance daily closes, Friday, Nov 6, 2026 (same dated snapshot as the Brief, not a live feed). Counts sit on every screen button. Each row says why it's here — which screens it hits — and whether it loads in the simulator: only 12 names are in the one-stock simulator; the other 27 are marked “Detail only” and open their full detail view instead. SMH is an ETF basket, not a company — it overlaps NVDA, AVGO and AMD, which are also listed individually. In the full-universe view, the five names that hit no screen on Nov 6 — AMZN, JPM, GS, CVX, UNH — are badged “No screen hit”: they are market context, not setups, on this date. RSI = 14-day Wilder; relative volume = Friday vs its 20-day average. Second-source check (completed Nov 7, 2026): all 39 of the 39 names were cross-checked against Finnhub — every name matched on close and day change, and every name matched on week, 1-month and YTD changes too (16 in the first pass, the remaining 23 in the completion pass); third-vendor outlier prints (MarketBeat on JPM, LLY, MA, BAC, CAT, UNP, DIS) are flagged in the ledger, where Finnhub agrees with Capmark on each. No name in this universe is single-source.

Credibility · High All figures calculated by formula from dated daily closes (formulas stated above and in the ledger). Snapshot, not live — prices move on; these don't. ✓ Verified by 2 sources · Yahoo + Finnhub · all 39 names, every field · checked Nov 7, 2026

A screen is a filter, not a verdict: “oversold” names include both washed-out leaders (NVDA, RSI 31) and falling knives (CAT, RSI 21 after a −29.8% month) — the columns beside the RSI are how you tell them apart. Nothing here is a recommendation to buy, sell or hold any security.

Testing the gridlock hypothesis: pick a Washington, an amount and a horizon — see the range of outcomes its history implies, not one smooth line. The sector panel below moves with the same pick.

Credibility · Medium Base path uses the sourced RBC averages (Medium, above). The ±6-point downside/upside band is an illustrative estimate, not a statistic — flagged wherever it appears. The stock simulator's prices are real (Yahoo adjusted closes) but per-setup samples run just 2–8 years.

Sectors under this Washington

For the combination selected above: the sectors history and policy exposure have favored, and the ones they have pressured. Read these as tilts, not measured per-combination returns — no major study publishes a clean sector-return table sliced by all six combinations (see the honesty note under the leaderboard). Where a hard number exists, it is shown with its source and window.

Real years arrive with five forces at once. Stack stances below — the Lab finds the historical years (1973–2024, hand-tagged) where all of them were in play, and shows those years' S&P 500 returns. The sample size is the headline: most mixes have happened only a handful of times, and the Lab says so.

Credibility · Medium S&P 500 returns are sourced (Slickcharts / S&P DJI series), but the force tags are hand-assigned editorial labels and the dataset is 30 selected years out of 52 — matches of 1–6 years are stories, and the Lab labels them so. ✓ Return series spot-checked vs a second table · checked Nov 7, 2026 Force tags: editorial — not second-sourced

Your questions 1–4, taken one chamber at a time first, then together. One dataset — Mike Patton's Dow Jones analysis of 1946–2020 — breaks returns down by each lever separately. Read the single-chamber numbers with care: they overlap heavily (a Democratic Senate usually coincided with a Democratic House), and a 2025 American Economic Association paper covering 94 years found no statistically reliable premium for either chamber alone once combinations are accounted for.

Credibility · Medium Single-analyst compilation (Patton, Dow 1946–2020, via Forbes) — a long 75-year sample and transparent method, but not peer-reviewed, and a 2025 AEA paper disputes single-chamber premiums outright.

Questions 5 and 6, name by name: S&P 500 annualized price return since Reagan (totals are price-only, dividends excluded). Notice what the ranking is really measuring — starting point luck. Obama began at a crisis bottom; George W. Bush began at a bubble top and ended in a financial crisis. Clinton rode the internet boom; Trump and Biden both rode recoveries and the AI build-out.

Credibility · Medium Compiled from TD Economics / Bloomberg figures via secondary summaries; the two compilations on this page differ by a few points on the same presidents (window and dividend conventions) — disclosed in the note under the ranking. Six presidents only: starting-point luck dominates.

Longer view: TD Economics/Bloomberg data through 2024 puts the average annual S&P 500 return since 1946 at just over 10% under Democratic presidents vs just over 6% under Republicans — a gap researchers attribute substantially to which crises and booms happened to land in which terms, not to party policy alone. Total gain by term tells the same timing story in the longer compilations too — Eisenhower +129% and Truman +87% (TD Economics/Bloomberg via Cabot). Note the two compilations on this page differ by a few points on the same presidents (e.g. Obama +182% price-only in the cards above vs +189% in Cabot's) because of window and dividend conventions; treat any single figure as approximate.

Question 7 and 8, era by era. Pick a period to see who held each lever, what the Dow and S&P 500 did, what was happening in the world — wars, oil shocks, pandemics — and the socioeconomic forces (inflation, jobs, wages, debt) that usually mattered more than the politics.

Credibility · Medium Narrative compiled from multiple secondary sources; era market totals are approximate and convention-dependent. The in-progress Trump II era is explicitly provisional. Best used as context, not as a return dataset.

Markets don't float above the economy. The most-cited academic comparison — Blinder & Watson, Princeton, published in the American Economic Review — covers Truman's elected term through Obama's first term. An Economic Policy Institute update through the Biden era points the same direction. Both carry the authors' own warning: the gap is real in the data, and roughly half of it looks like luck.

Credibility · High The strongest sourcing on the page: a peer-reviewed American Economic Review paper (Blinder & Watson, Princeton) plus an EPI update, over 1949–2023, with official NBER recession dates. The caveat is interpretive — the authors attribute roughly half the gap to luck.

Party control moves sectors more reliably than it moves the whole market, because platforms translate into regulation, spending and tax policy. These are historical tendencies in sentiment and policy exposure — not return guarantees. In the 12 months after midterms, across recent cycles, technology led, then consumer discretionary and communication services, while defensives and financials trailed (Bloomberg/Ameriprise, midterm cycles 2002–2022).

Credibility · Medium Measured windows rest on as few as six ETF-era midterm cycles (sector ETFs exist only from 1998), and the winner flips with the window — both disclosed in the leaderboard. The per-party tilts are qualitative policy exposure, not measured per-combination returns; no such dataset exists.

Under split control, history favors the incumbents of the moment: gridlock freezes the regulatory status quo, which is why post-midterm leadership has usually come from growth sectors already working — technology above all in the AI era — plus industrials carried by bipartisan defense and infrastructure money.

Kept separate from every stock figure on this page — and the sample is the story: Bitcoin has priced history only from ~2010, Ethereum from 2015. That's parts of four presidencies and three midterm cycles, against 125 years of stocks. Where the Washington lens applies honestly, it's applied; where it can't, this section says so.

Credibility · Medium Calendar-year returns cross-checked across two exchange-close series (they differ by a few points in early years — immature data, disclosed). Term figures are calculated from year-end prices, as labeled. Sample is four presidencies and three midterms: too short for the averages the stock sections use, and none are claimed.

If party control were the main driver, the studies above would agree. They don't — because these four forces swamp the partisan signal.

Credibility · Medium Interpretive synthesis of the sections above — each underlying claim traces to a sourced dataset on this page, but the “swamps the partisan signal” framing is this page's editorial conclusion, stated as such.

The full map: 31 drivers across social, geopolitical and core economic forces, each with real example years and a strength-of-evidence label — including the ones that are mostly narrative. Drivers marked ▸ IN THE SCENARIO LAB mix directly into the Lab above.

Credibility · Medium The historical episodes in each card are sourced, but the strength-of-evidence grades are this page's editorial judgment — criteria are stated in the ledger. Drivers graded “weak” or “mostly narrative” are presented as unverified patterns, not facts.

Evidence labels are this page's editorial grading of the historical record behind each driver — how consistently the force has coincided with measurable market effects, across how many episodes. “Strong” still does not mean predictable: public health is graded strong because 2020 happened, not because anyone can time the next one. Sources are named inside each card; the master list is in Section 10.