FACTOR -1 % wkDISPERSION 55 % >50-DMAGCC SPREAD 21 pptsOVX 58 indexDXY 100.53 index
equity signals · live registry
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Data through 2026-06-02 Next refresh per-section (daily / weekly / structural) Live as of checking… Read as LaymanAnalyst
Markets · Global Equities · State of the desk

First the channel.
Then the direction.

The call: a narrow, rich, defensively-led tape — mega-cap AI insulating the index while breadth thins and a live catalyst reprices the edges. Any new shock gets classified funding vs earnings before it gets traded. Medium confidence

Open the signal board →
Equity regime · live— from the registry
Active shock: Iran–Gulf — earnings channel classified · §2·Falsifiers tripped: 0 / 6 → §12

Index masks the split: mega-cap-AI insulation up top, importer and crowded-factor pain underneath. Each cell links to its section; the channel call is interpretation and carries its own chip.

The 30-second read
  • Classify the channel before the direction. A funding shock sells what is owned; an earnings shock sells what is exposed. The whole desk hangs on that split.
  • The index masks the damage: mega-cap AI insulation up top, thinning breadth underneath — watch the average stock, not the average of the index.
  • Prices move first, forecasts follow. Consensus EPS lags a real shock by weeks to a quarter — it confirms regimes, it never calls them.
  • Credit must agree. A vol spike without HY spreads widening is a positioning event, not a fundamental one. Two barometers, one rule.
  • A live Iran–Gulf catalyst is overlaid (§Catalysts) — an earnings-channel shock for energy and transports, a funding watch for everything else.
What would change this call
  • HY spreads break and STAY above ~600–700bp for 20+ sessions — credit calls the shock fundamental.
  • A crowded-factor dislocation keeps extending past a week with no Quant-Quake-style snap-back.
  • Sector EPS cut >5% inside the first earnings season — including in cost-insulated sectors.
  • %>200-DMA pinned under ~30% for 20+ sessions while the cap-weight index recovers without it.
  • Stock–bond correlation flips positive and stays there — the dash-for-cash signature.
Markets · Equities · In plain words
Detail

Is the rally as healthy as it looks?

This is the equities desk. The stock market’s headline number — the index — keeps setting records. But an index is an average, and right now a few giants are carrying it. Right now: strong on top, thin underneath.

  • How many stocks are actually participating in the rally
  • Who’s forced to sell when stress hits — and why that matters more than the news
  • Which warnings arrive early — and which only confirm what already happened
Narrow Broad Today — records on top, thin underneath
The index is at highs, but participation is narrow — fewer stocks are carrying more weight. medium confidence
The headline index
Near highs
carried by a few giants
How many stocks joining
55%
above their recent trend
Are stocks pricey?
Yes
thin reward over safe bonds
Is the bond market worried?
Not yet
the smoke detector is quiet
You’re reading the Skim — the 3-minute version. The Deep read adds seven full chapters (~25 minutes): timelines, decoders, and every claim’s source.
Today in 60 seconds

The call: a narrow, rich, defensively-led market — records on top, thin underneath. The Iran–Gulf conflict is repricing the edges, not the giants.

55%of stocks above their own trend — the rally’s thin base
0.3 corrstocks & safe bonds moving together — the watch item
35.3 indexemerging-market fear gauge — where stress shows first

Watch this week: if stocks and safe bonds keep falling together, everyone is raising cash at once — and this desk’s whole read changes (see “What would change our mind”).

I
Foundations

The dials, the units, and the ideas everything else builds on.

The six dials on this desk

Our analyst page tracks six live numbers. Here is what each one actually measures — and when it should worry you.

The tape · 55%Of the big US stocks, how many sit above their own 50-day trendline. A strong rally has most stocks marching; 55% means half the army is missing.Alarming: Under ~30% while the index sits at highs
The crowd · −1%/wkHow much the popular “style” trades lost this week. Sharp drops mean crowded funds are being squeezed out of the same doors at once.Alarming: Several negative weeks in a row
Tripwire · 0.3Do stocks and safe bonds seesaw (normal) or fall together (danger)? Falling together means everyone is raising cash at once.Alarming: Positive and holding for ~a month
Global risk · 35.3The price of insuring emerging-market stocks against swings — fear in the world’s riskier markets, where stress usually shows first.Alarming: Sustained climbs with no relief
Smoke detector · EMBIWhat lenders charge developing-country governments above the US rate. Credit stress surfaces here before it reaches US stocks.Alarming: Fast widening without a policy response
Dollar · 100.5The dollar’s strength against major currencies. A surging dollar tightens the screws on everyone worldwide who borrowed in dollars.Alarming: Rapid climbs — a global margin call

How to read market numbers

Six units that come up constantly — in our pages and everywhere else. Learn these once and most financial writing decodes itself.

Basis points (bp)1bp = one hundredth of a percentage point; 100bp = 1%. “Spreads widened 50bp” means risky borrowing got half a percentage point more expensive.
SessionOne trading day. 5 sessions ≈ a week; 20 sessions ≈ a month. “20+ sessions” means a condition persisted about a month — not a one-day scare.
Spread / OASThe extra interest a risky borrower pays over the US government rate. Junk-rated companies today: ~275bp (2.75%). Stress: 600–700bp. The 2008 panic: ~2,000bp.
Moving average (DMA)A stock’s average price over its last 50 or 200 trading days — its own trendline. “Above the 200-DMA” = above its long-term trend.
CorrelationRuns −1 to +1. Negative: two things seesaw (normal for stocks vs safe bonds). Positive and holding: they fall together — the danger pattern.
PercentileWhere today ranks against history. 90th percentile = higher than 90% of all past readings.

The five things to understand

  1. 1

    What the market is doing

    The headline index keeps making new highs — but most individual stocks aren’t joining in. A handful of giant AI-linked companies is doing nearly all the lifting; underneath, the average stock is treading water.

  2. 2

    Why it matters

    A rally carried by few names is fragile — if the leaders stumble, there’s little underneath to catch the fall. And because stocks are already expensive, the extra reward for owning them over safe bonds is unusually thin.

  3. 3

    The big idea on this desk

    Not all market drops are the same. A profit problem (companies will earn less) trends lower and keeps going. A plumbing problem (someone is forced to sell to raise cash) is violent but usually snaps back. Telling them apart is most of the game.

  4. 4

    What’s driving it now

    Four lasting forces and one live event: the AI investment boom, interest rates, company earnings, and how crowded the popular trades are — plus the Iran–Gulf conflict repricing energy and the Gulf. We name them all, including what we can’t explain.

  5. 5

    The bottom line

    Watch the average stock, not the index. Watch the bond market, which usually smells trouble first. And when a drop comes, ask who is selling and why — a forced seller and a frightened forecaster are very different animals.

How the stock market actually works

Four ideas that make the rest of this page click.

Two kinds of market shocks

Every selloff has a cause — and the cause decides what happens next.

  • A profit shock: news says companies will earn less. Sellers dump the exposed businesses. The fall grinds on as forecasts catch down.
  • A plumbing shock: a big borrowed-money investor gets a margin call and must sell whatever it owns — usually its best, most sellable stuff.
  • Plumbing shocks look terrifying but often snap back in days. Profit shocks look orderly but keep falling.

Why the index can lie

The S&P 500 isn’t 500 equal votes — the giants count for vastly more.

  • A few mega-companies can drag the index to records while most stocks sink.
  • So we track how many stocks are actually rising — the market’s participation.
  • A rally with shrinking participation is like applause from a thinning crowd.

The crowded-trade chain reaction

When everyone owns the same trade, the exit gets narrow.

  • Funds pile into the same popular positions, often with borrowed money.
  • One fund hits trouble and must sell; prices dip; the next fund’s risk limits force it to sell too.
  • The selling feeds itself — no bad news required. That’s why crowding is a risk we track on its own.

Prices move first, forecasts follow

Stock prices react to a shock in hours. Official profit forecasts take months.

  • Analysts wait for company calls before cutting numbers — the cuts arrive a quarter late.
  • By the time forecasts capitulate, the damage is usually already in the price.
  • So forecast cuts confirm a downturn; they never warn you of one.

What kind of market is this?

Before judging any stock or headline, professionals check the weather. These are the four gauges they use — all free, all daily.

The fear price (VIX)What investors pay to insure against market swings over the next month. Cheap insurance = calm; expensive insurance = fear. It’s the closest thing markets have to a mood ring — priced in real money.Calm ~12 · nervy 20+ · crisis 30+ · the 2020 record: 83
Distance from trendHow far the index sits above or below its own 200-day average price. Far above = stretched, like a runner sprinting ahead of their training pace. Far below = beaten down.Watch when far above trend while fewer stocks participate
Felt vs paid volatilityTwo numbers: how much the market has actually been swinging (realized), and how much swing the insurance market is pricing (implied). When insurance costs far more than recent reality, traders are braced for something.A wide gap in either direction marks a regime change brewing
Today’s fear vs next month’sNormally, insurance for further-out dates costs more than today’s (more time, more risk). When TODAY costs more than next month — “backwardation” — the market wants protection right now. That inversion is the stress signature.Inversion = the panic is now, not hypothetical

Where this comes from: the Cboe exchange publishes the fear gauge (VIX) free, daily; trend distance is simple arithmetic on any free chart. Our analyst page tracks all four in §1.

Three thermometers for the rally

One thermometer can lie. These three measure different things — when all three agree, believe them.

Count the soldiers

How many stocks are above their own long-term trend

A real advance has most of the army marching, not just the generals. When the index climbs while this count falls, the rally is hollowing out from underneath — historically the classic warning.

Free, daily: StockCharts $SPXA200R · Barchart $S5TH

Generals vs the army

The equal-weight index versus the famous one

The S&P you hear about gives giants more votes. Its equal-weight twin gives all 500 companies one vote each. When the famous index wins and the fair-vote one lags badly, a handful of giants are carrying everyone.

Free, daily: the RSP / SPY ratio on any charting site

Fresh peaks vs fresh wounds

Stocks hitting yearly highs minus those hitting yearly lows

Cuts through all the weighting math: is the typical stock having a good year or a bad one? An index at record highs while more stocks hit yearly LOWS than highs is the single most reliable free warning sign.

Free, daily: WSJ market data · StockCharts $NYHL

All three are deliberately free and public so you can check our work — and your own. The analyst page’s §3 runs them daily.

A margin call sells what it owns; a profit warning sells what it fears. Learn to tell the sellers apart.
II
How crises work

One true story, four flavours of trouble, and the scoreboard of every modern panic.

Watch it happen

August 2007: the cleanest plumbing shock on record — retold in six steps.

1
Dozens of big funds run the same computer-driven stock strategies, many with borrowed money. For years, it works.
2
Trouble hits elsewhere. One large fund loses money in mortgages — nothing to do with stocks — and gets a margin call.
3
It raises cash by selling what it can sell fastest: its stock portfolio. Those “reliable” strategy stocks dip.
4
Other funds running the same strategies see losses, and their risk rules force them to sell too. The dip becomes a rout.
5
For three days, the most consistently profitable strategies in the market lose 5–30% — while the overall index barely moves and the news wires stay quiet.
6
Then the forced selling exhausts itself — and prices snap back within days. Anyone who sold into the panic locked in the loss; the plumbing had failed, not the businesses.
August 2007 — anatomy of a quant quake
July 2007
The quiet bleed

Value strategies leak losses for weeks; nobody connects it to mortgages yet.

Aug 6–9
Forced selling

A margin call in mortgages forces stock sales; the most reliable strategies lose 5–30% in four days.

Aug 10
The snap-back

Forced selling exhausts; prices rebound within days. Whoever sold into the panic locked in the loss.

Feb–Mar 2020 — the two-phase panic
Late Feb
Flight to safety

Sell risky, buy safe — the ordinary scare. Treasuries rally as stocks fall.

Mid-March
Dash for cash

Even Treasuries get sold. $125bn flees prime money funds; the S&P drops 12% in a day; VIX hits 83.

Late March
The backstop

Central-bank liquidity opens. Only then does the spiral stop — valuation never got the chance.

2020 was the other kind of panic — the one where even the safest assets got sold. Comparing the two timelines is the whole lesson: one snapped back, one needed a rescue.

The four flavours of money trouble

“Funding shock” just means someone, somewhere, must raise cash NOW. It comes in four flavours — and knowing which one you’re watching tells you whether to expect a rebound or a grind.

The margin-call stampede 2007

One big borrower is forced to sell, dragging down everyone who owns the same trades. Violent, fast — and it usually snaps back within days once the forced seller is done. The 2007 quant quake above is the textbook case.

The pawn-shop rush 1998

When a giant fails, everyone suddenly pays up for things that are easy to sell and dumps anything obscure. Small and hard-to-trade holdings fall hardest — not because they’re bad, but because they’re illiquid.

The everything-must-go cash run 2020

Pure panic: even the safest assets get sold, because people don’t want safety — they want cash. The rarest and most serious flavour. It ends when a central bank opens the liquidity taps, not when prices get “cheap enough.”

The burst pipe in one room 2022

A funding crisis that stays trapped in one corner — UK pension funds and their bond collateral in 2022 — while the wider stock market barely notices. The lesson: always ask which room the pipe burst in before evacuating the building.

Where this comes from: each flavour is a studied historical episode — MIT’s study of 2007, the Federal Reserve’s histories of 1998 and 2008, the global regulators’ review of 2020, the Bank of England’s autopsy of 2022. The analyst page’s §2 carries the full case files.

Seven crises, one scoreboard

The same styles of stock were measured through every modern crisis, using free academic data anyone can download. Here’s what actually happened — including the one result that surprises professionals.

1998 · Russia/LTCM
A giant hedge fund failed; everyone rushed to easy-to-sell assets. Small companies fell hardest (−7% worse than big ones). Quality held up.
2008 · The financial crisis
Banks themselves were the problem; lending froze worldwide. The market lost ~42%; small and value stocks suffered most. Strong-balance-sheet companies beat weak ones by 13 points — the cleanest quality win on record.
2011 · Euro debt scare
Markets feared European governments would default. −18%, small caps again worst. Defensives beat economy-sensitive stocks by 16 points.
2020 · COVID cash run
The everything-must-go panic — even safe bonds were sold. −34% in five weeks; cheap “value” stocks crushed (−18). The shock: even quality LOST money — the one crisis where nothing defended.
2022 · UK pension scare
A burst pipe in one room — British bond collateral. UK bonds, badly. Stock styles barely moved. Proof that a funding crisis can stay contained.
2023 · Bank deposit runs
Regional US banks lost deposits overnight. Small and bank-heavy value stocks. Quality and necessities held — the system did not.

Where this comes from: the Kenneth French Data Library (Dartmouth) — free daily files used by academics worldwide. We recomputed every number; the analyst page’s §2 table shows the precise figures.

Every crisis arrives calling itself unprecedented. The scoreboard says they rhyme.
III
Prices & confessions

What you’re paying, what you’re paid for the risk — and how slowly the truth reaches the forecasts.

What are we paying for stocks?

Four ideas that turn “the market is expensive” from a vibe into something you can check yourself.

The price of $1 of profit (P/E)If a company earns $1 per share each year and the share costs $20, you’re paying 20× earnings. The higher the multiple, the more future you’re paying for in advance — and the less room for disappointment.US large stocks have historically averaged ~16–17×; well above that means optimism is already in the price
The smoothed version (CAPE)One great or terrible year can distort the picture, so this stretches profits over ten inflation-adjusted years. It’s useless for timing next month — but historically meaningful for what the NEXT DECADE of returns looks like from a given starting price.Track it free: Professor Shiller’s data, Yale (updated monthly)
The danger pay (equity risk premium)Stocks should pay more than safe government bonds — that extra is your compensation for the rollercoaster. Around 3.2% today, it’s historically thin: you’re taking stock-market risk for not much more than bond-market reward. Thin pay doesn’t predict a crash; it means little cushion if one comes.Thin ~3% · typical ~4–5% · generous 6%+ (free: Damodaran, NYU, monthly)
Where returns actually come fromOver any stretch, a stock market’s return ≈ profit growth + change in the mood multiple + cash paid out (dividends and buybacks). When profits stall, only mood and payouts are left — and mood is the part that vanishes fastest.The analyst page’s “return bridge” chart is exactly this, drawn

Where this comes from: Professor Shiller’s public dataset (Yale), Professor Damodaran’s monthly risk-premium estimates (NYU), and the Fed’s FRED database for bond yields — all free. Labeled as long-run context on our analyst page (§4), never as a timing signal.

The smoke detector next door

The bond market is the stock market’s smoke detector. Lenders only care about being repaid, so they smell trouble before stock investors do — when the extra interest charged to risky companies jumps, stocks usually feel it later.

  • Credit confirms or deniesA stock-market panic that the bond market ignores is usually just positioning — it tends to blow over.
  • Both alarms togetherWhen stocks fall and risky-company borrowing costs jump, the trouble is real. That combination is our regime-change signal.
  • The strangest tell of allWhen stocks and safe government bonds fall together, everyone is selling everything for cash — rare, serious, and the one pattern that says “this is systemic.”
How long the truth takes — from shock to forecasts
Hours
Price reacts

Markets reprice the shock immediately — before anyone updates a spreadsheet.

1–6 weeks
Consensus stirs

Analysts begin trimming nearest-quarter numbers, gated by the calendar.

~3 months
Sectors confess

The first earnings season shows real damage (an oil shock: ~−1.9% aggregate profits).

After guidance
Annual resets

Full-year forecasts finally move — long after prices already did.

This is why waiting for official forecasts means reacting to old news — the market repriced months before the spreadsheets did.

Who confesses first

When a shock hits, industries admit the damage in their profit forecasts at very different speeds. The order is surprisingly reliable.

Oil producersThe shock IS their product’s price — analysts just read it off the screen.Days to weeks
Airlines & shippersThey sold tickets and contracts before fuel spiked and can’t reprice them — the squeeze shows up a quarter later.1–3 months
InsurersStorm claims hit fast; long-tail claims (injuries, lawsuits) settle over years as the real costs surface.Months, then years
Defense contractorsTheir stocks jump on headlines, but revenue moves through multi-year government contracts — the slowest confession on the street.Quarters to years
Retailers & brandsAnalysts wait to see whether shoppers absorb higher prices or walk away before cutting numbers.3–6 months

Where this comes from: decades of academic work on analyst behaviour (Ball & Brown 1968 onward) plus the European Central Bank’s and Federal Reserve’s studies of forecast lags — the analyst page’s §5 carries the citations and exact figures.

IV
The map of the market

Eleven neighborhoods, four seasons, six teams — the geography money moves across.

The eleven neighborhoods

Every stock market is a city of eleven neighborhoods, each with its own weather. Most “market” stories are really just money moving between them. Each has a ticker you can chart for free.

TechnologyThe growth engine — software, chips, cloud. Loves falling interest rates (its profits live far in the future), suffers when rates rise.Track it: XLK
CommunicationsTwo families in one house: ad-driven internet giants (economy-sensitive) and boring telecoms (defensive).Track it: XLC
Consumer discretionaryThe wants, not the needs — cars, travel, fashion. First to feel it when households tighten belts.Track it: XLY
Consumer staplesThe needs — food, soap, toothpaste. People buy them in any economy, which is why this neighborhood shines in downturns.Track it: XLP
Health careDemand barely follows the economy — illness doesn’t check the business cycle. Policy headlines are its real weather.Track it: XLV
FinancialsBanks and insurers. Unusual: often HELPED by rising rates (wider lending margins) — but punished hard when borrowers start defaulting.Track it: XLF
IndustrialsMachines, freight, aerospace. The economy’s muscle — orders boom mid-cycle, roll over before recessions.Track it: XLI
MaterialsChemicals, metals, mining. Rides global construction and China’s appetite; an inflation-era favourite.Track it: XLB
EnergyOil and gas. Marches to crude’s drum, not the stock market’s — which makes it the classic geopolitical-shock hedge.Track it: XLE
UtilitiesPower and water — steady dividends, heavy debts. Behaves like a bond: when rates rise, it falls, defensive label or not.Track it: XLU
Real estateProperty trusts. Income-driven and borrowing-heavy — rate moves matter more than the economy. Offices and warehouses now live opposite lives.Track it: XLRE

Where this comes from: the standard industry classification (S&P/MSCI) that the whole industry uses; the tickers are the free-to-chart sector funds. The analyst page’s §6 carries the full sensitivity table — sortable.

The market’s seasons

Leadership among those neighborhoods rotates with the economy in a rough, repeating order — seasons, not clockwork.

Early cycle — spring

Rates falling, recovery starting. Banks, small companies and consumer-wants lead the thaw.

Mid cycle — summer

Steady growth, calm inflation. Technology and industrials do the compounding.

Late cycle — autumn

Inflation warm, capacity tight. Energy and materials harvest; the clock above sits roughly here.

Recession — winter

Demand contracts. Necessities — food, power, medicine — and cash are the only warm rooms.

A historical tendency, not a promise — the analyst page labels it a framework prior, and the cycle clock there shows where we judge today to sit.

The six teams

Big money doesn’t just buy companies — it buys styles of company, wholesale. Six teams dominate the league, and the crisis scoreboard above showed something important about each.

Value

The bargain bin — cheap relative to profits. Wins recoveries; but in a margin-call stampede it’s often the first thing dumped.

Growth

The expensive promises — paying up for future profits. Thrives when rates fall; gets repriced hard when they rise.

Quality

Fortress balance sheets, fat margins. The usual crisis shelter — except in a true cash run: in March 2020 even quality lost money.

Momentum

Whatever has been winning lately. Keeps winning — until the turn, where it crashes hardest. In 2007 it rose INTO the quake.

Low volatility

The calm stocks — utilities, staples. Defensive, except when rising rates ARE the problem: then the “calm” bond-like names fall with bonds.

Size (small caps)

The little guys. More room to grow, less cushion in stress — small lost worse in five of the six crises on the scoreboard above.

Where this comes from: the factor data is the same free Kenneth French library as the scoreboard; the crisis findings are computed from it. Analyst §7 carries the playbook with exact percentages.

The index is one number. The market is eleven neighborhoods having different weather.
V
The crowd & the bond market

Who’s already leaning which way — and the neighbor whose alarm rings first.

How crowded is the boat?

Markets are most fragile when everyone already agrees. Three free gauges measure the crowd — one of feelings, two of actual positions.

The amateurs’ mood pollEvery week, ordinary investors are simply asked: bullish or bearish? It’s a feelings survey — and most useful in reverse: extreme optimism means most buyers have already bought.AAII survey · free · every Thursday
The professionals’ actual betsActive money managers report how invested they actually ARE, from all-cash to leveraged-long. Actions, not feelings.NAAIM index · free · Wednesdays, published Thursday
The regulator’s X-rayBig funds must file their futures positions with the US regulator. The catch built into the data: Friday’s report shows TUESDAY’s positions — a three-day-old photograph, useful for the trend, not the moment.CFTC report · free · Fridays 3:30pm ET

The reading rule: extremes matter, and in reverse — when nearly everyone is bullish and fully invested, there’s no one left to buy. We treat all three as caution lights, never trade signals (analyst §9).

The most dangerous thing in a market is unanimous agreement.

Three handshakes with the bond market

The smoke detector above is actually three distinct signals. Each one is checkable, free, daily.

The early-warning handshake

When risky companies’ borrowing costs jump while the stock market stays cheerful, someone is wrong — and history says it’s usually the stock market. We never treat it as a same-week timer; it’s a divergence that demands an explanation.

Junk-bond spread: FRED series BAMLH0A0HYM2, free, daily

The two-alarms rule

A stock-market fear spike plus rising credit stress = real trouble. A fear spike the bond market ignores = usually a positioning squall that passes. One alarm is noise; two alarms is a fire.

Fear gauge: Cboe VIX, free · credit: the spread above

The systemic stamp

When even the strongest companies’ borrowing costs start jumping too, the problem has graduated from “weak companies” to “the system.” That’s the difference between a storm in one neighborhood and a citywide blackout.

Top-grade spread: FRED BAMLC0A0CM, free, daily · full diagnosis: our credit desk

Watch what the average stock does, not what the index says.
VI
The conflict

How the Iran–Gulf shock actually reaches stocks — pipes, scenarios, and the world map of winners and losers.

The Gulf angle, in plain words

The Iran–Gulf conflict reaches stocks through a few clear pipes — follow the chain:

1
The conflict threatens oil supply, so oil prices and shipping costs jump.
2
Energy producers earn more — their product just got pricier. Defense contractors get a demand story too.
3
Fuel burners get squeezed — airlines and shippers sold tickets before the spike and can’t reprice them for months.
4
The Gulf markets split: oil revenue helps Saudi; security risk and shipping exposure weigh on the UAE and Qatar.
5
The giant US tech companies that dominate the index barely notice — which is exactly why the index hides the damage.

So one event produces winners and losers at the same time — and the index, dominated by insulated giants, shows almost none of it. The real action is in the spread between sectors, not the headline number.

The Iran–Gulf shock — what happened when
Mar 2
Freight panic peak

Tanker rates hit a record $736k/day-equivalent; war-risk insurance ~2.5% of hull value per week.

March
Hormuz closure window

Transit blocked or uninsurable. UAE output forced down toward ~1.9M bpd; Qatar declares force majeure at Ras Laffan.

Apr 9
Petroline strike

Drone strike cuts the Saudi east–west bypass by 700k bpd — the workaround itself gets hit.

By late Apr
Bypass restored

Petroline back to 7.0M bpd; Saudi exports ~3–4M bpd around Hormuz.

Today
Partial normalization

War-risk premia ~1% (from 2.5%); §scenarios above tracks the next branch.

What to watch

The signals that the picture is changing — all free, all checkable.

  • More stocks joining the rally — or not — the share of stocks above their long-term trend is the market’s health meter
  • Junk-bond borrowing costs — the smoke detector — if they jump and stay up, the bond market has changed its mind
  • Stocks and safe bonds falling together — the rare “everyone needs cash now” pattern — the most serious tell there is
  • Company forecast cuts spreading — late but decisive confirmation that a downturn is profit-driven, not just nerves
  • The gap between the big index and the average stock — when the equal-weighted market lags badly, leadership is narrowing
  • A fear spike the bond market ignores — usually a positioning squall, not a regime change — often a recovery setup

If this happens, then…

Four “what-ifs” and what each would mean.

The conflict escalates
Oil spikes. Energy stocks win, airlines and importers lose, and the Gulf markets reprice hardest. If shipping or money flows seize up, it can morph into a plumbing problem — that’s the escalation we watch for.
A ceasefire lands
The roles flip fast: energy gives back its war premium, airlines and Gulf “losers” snap back. The biggest moves often come from relief, not damage.
Interest rates jump
Expensive growth stocks and bond-like sectors (utilities, property) get hit hardest — the price of future profits just went up. Banks can actually benefit.
The economy re-accelerates
The rally finally broadens: factories, banks and smaller companies join in. Ironically, the index giants may lag while the average stock catches up.

The four conflict scenarios, precisely

“Escalation” is too vague to trade or track. These are the four specific branches we monitor — one already happened.

Hormuz closure✓ realized

Transit through the Strait blocked or priced as un-insurable — a transport blockage of intact supply. Barrels still exist; they cannot move. First-order repricing: freight, war-risk insurance and regional spreads (the March record: VLCC $736k/day-equivalent, AWRP ~2.5% of hull per 7 days), then importers’ input costs.

Oil-infrastructure strike◇ escalation path

Strikes that destroy processing or export capacity at the source — the Abqaiq–Khurais 2019 analog: stabilization plants, export terminals, pumping stations. Distinct from Hormuz: this removes supply outright rather than blocking its movement, so it reprices the whole crude curve and persists until capacity is repaired, not until a lane reopens.

Cable severance◇ escalation path

Cutting subsea data/telecom cables in the Gulf / Red Sea corridors — a connectivity and financial-plumbing shock, not a barrels shock. Hits exchange access, settlement, cloud and comms first; equity expression runs through regional financials and any business dependent on Gulf connectivity.

Ceasefire◇ de-escalation path

The roles flip fast: war premia unwind — energy gives back the conflict premium, transports/insurers and Gulf “losers” snap back, and the biggest single-day moves often come from relief, not damage. The desk treats this as a scenario with the same discipline as the escalations.

A transport blockage, a capacity destruction, a connectivity cut and a de-escalation are four different shocks with four different repricing paths — which is why we never say just “escalation.”

Around the world in one shock

The same event lands very differently depending on where you stand. The board’s clearest reads, in one breath each:

  • Energy importers pay the bill: Japan and South Korea were the most exposed on the board (−20 to −30% in a full closure scenario), with Europe, India and China close behind.
  • Energy exporters catch the windfall: Brazil was the board’s clearest winner (+5 to +15%) — the same barrel price that hurts Tokyo helps São Paulo.
  • The US sits in the middle: hurt, but cushioned — it produces much of its own energy, and its index giants barely touch the Gulf.
  • The Gulf itself splits: oil revenue cushions Saudi while security risk hits the UAE hardest — neighbours, opposite trades.
  • A ceasefire flips nearly every sign on the board — yesterday’s losers bounce hardest, and the windfall winners give theirs back.

Where this comes from: scenario ranges drawn from historical analogues, measured against pre-conflict levels — provisional by nature. The analyst page carries the full country × scenario table, sortable by outcome.

How to read any “winners and losers” table

When we call a sector a winner or loser, it means something narrow and honest: compared to where it stood before the event, relative to its peers, in the scenario that actually happened — not a forecast, not a recommendation. The same sector can flip from loser to winner the day a ceasefire lands. That’s not the table being wrong; that’s what the table measures.

The live table runs on the analyst page under §Catalysts, with a confidence chip on every row.

VII
Our discipline

The misconceptions we guard against, the tripwires that would change our mind, and how to check our work.

Three things people get wrong

“The index is up, so the market is healthy”
The index is a weighted average, and right now the weights belong to a few giants. A market where five stocks carry everything is more dangerous at its highs, not less — participation, not the headline level, tells you how solid the ground is.
“Good companies always hold up in a crash”
Usually — but not in the worst kind. In March 2020, even the highest-quality businesses fell, because panicked investors sell whatever they can, not whatever deserves it. When everyone needs cash at once, quality is just another thing to sell.
“Wait for the forecasts before worrying”
Profit forecasts are rear-view mirrors. Analysts cut numbers a quarter after the shock, once companies confirm the damage on earnings calls. If you wait for the forecasts, you’re reacting to old news the market priced months ago.

What would change our mind

Before a crisis, we write down exactly what evidence would prove our reading wrong — with the numbers anchored so you can judge them too, and the free data source so you can track each one yourself.

1
If junk-bond stress stays high for a month
high

Companies with shaky finances pay extra interest to borrow — today about 2.75 percentage points over the US government rate. A scary headline can spike that premium for a day or two and mean nothing. But if it jumps past 6–7 percentage points and stays there for about a month of trading days, the bond market is declaring the damage real, not mechanical — and we abandon the “this will snap back” read.

~275bptoday — calm
600–700bpthe trigger
~2,000bp2008 panic
Proof — track it yourself
Free dataFRED BAMLH0A0HYM2 · daily
2
If a crowded-trade crash doesn’t bounce within a week
high

When selling is forced — funds hit margin calls and must dump positions — it exhausts itself fast: 2007’s “quant quake” rebounded within four days. So we give any crowded-trade crash about a week. If it keeps falling past that window, the seller isn’t a margin call anymore; it’s conviction. The “mechanical, will-bounce” story dies on schedule.

Days 1–4forced selling typical
~Day 5snap-back due
Past a weekconviction — read falsified
Proof — track it yourself
Free dataKenneth French dailies · IWM/SPY · RSP/SPY
3
If profit forecasts get slashed fast and everywhere
medium

Analysts cut profit forecasts slowly and reluctantly — usually a quarter late. So speed itself is a signal: if forecasts get slashed by more than 5% within a single earnings season, and the cuts hit even companies with no direct cost exposure to the shock, then demand itself is breaking — not just margins being squeezed. That’s recession behaviour, not plumbing.

Slow trims, exposed sectorsnormal lag
>5% in one seasonthe trigger
Cuts in insulated sectors toodemand breaking
Proof — track it yourself
Free dataConsensus EPS calendars · revision breadth
4
If the rally’s ground doesn’t heal underneath
high

After a genuine plumbing shock, the rebound should be broad — most stocks recovering together. If fewer than about 3 in 10 stocks sit above their own long-term trendline for a month while the headline index “recovers,” the recovery is a handful of giants carrying a sick market on their shoulders. The ground hasn’t healed; the durability read is falsified.

~55%today — narrow but standing
Below ~30% for a monththe trigger
~70%+healthy broad rally
Proof — track it yourself
Free dataBarchart $S5TH · StockCharts $SPXA200R · RSP/SPY
5
If stocks and safe bonds keep falling together
high

Stocks and safe government bonds normally seesaw — when one falls, money hides in the other. The rare and serious exception is when both fall together, day after day: it means everyone is selling everything to raise cash, the March-2020 signature. A one-day flip means little. Holding positive for about a month of trading days means the system itself is under stress — the “contained event” read is dead.

−0.3normal seesaw
+0.3 brieflyuneasy — current zone
Positive ~a monthsystemic — the trigger
Proof — track it yourself
Free data20-day rolling corr · FRED/Yahoo dailies
6
If banks stop trusting each other
high

Banks lend to each other constantly — it’s the financial system’s bloodstream, and this spread is its blood pressure. It measures how much extra banks charge each other versus the risk-free rate. Calm readings sit near 0.1–0.2 percentage points. Past ~0.4 points (40bp), banks are pricing real distrust of each other — and every “markets are functioning smoothly” assumption on this page is void, instantly.

~10–20bpcalm
~40bpthe trigger
100bp+2008-grade seizure
Proof — track it yourself
Free dataFRA-OIS / SOFR spread · daily

The week-by-week checklist

When a fresh shock hits, here is the actual schedule we run — each step a question with a date attached. Anyone can run it.

1
Within a week: have risky companies’ borrowing costs actually jumped? Has the fear gauge actually spiked? If not — this probably isn’t a money-plumbing event at all.
2
By two weeks: are small stocks still falling harder than big ones? If small caps are WINNING, the forced-selling story is wrong for this episode.
3
By three weeks: have the boring necessities started beating the economy-sensitive stocks? If not, the market isn’t actually bracing for damage.
4
First Friday report: did the big funds really cut their positions, per the regulator’s filings? If not, drop the “machines are deleveraging” line.
5
First earnings season: did profit forecasts move the way the story predicted? If not, the whole event was noise in prices, not damage to businesses.

Each checkpoint maps to a free data source — junk-bond spreads and the fear gauge (FRED/Cboe), small-vs-large and defensive-vs-cyclical funds (any free chart), the regulator’s Friday filings (CFTC), and consensus forecasts each earnings season. The analyst page runs this as the “confirmation clock.”

The market’s hidden machinery

Three forces move prices every day without any news at all. Knowing they exist is half the defense against misreading a quiet move as a meaningful one.

BuybacksCompanies are often their own biggest customers, steadily buying their own shares. Before earnings they must step away from the register — the “blackout.” A steady daily buyer disappears for weeks.Earnings calendars + NASPP window norms · §8 table row 1
CTAs / vol-controlAutopilot funds that buy when markets are calm and trending, and sell when volatility jumps — all watching the same triggers. They don’t read news; they read the speedometer.CFTC TFF (weekly) + OFR monitor · §8 table row 2
0DTE optionsBets on where the market closes today — same-day lottery tickets that now make up roughly half of all S&P option volume. Their hedging can amplify intraday swings.Cboe/OCC volume data · §8 table row 3
Dealer gammaThe firms selling those options must constantly buy and sell stock to stay balanced — sometimes leaning against the wind (calming), sometimes with it (amplifying). Which mode we’re in is an estimate, never a fact.Cboe open interest (inputs free; the “level” is a vendor model) · §8 table row 4
One quarter in the life of the buyback bid
Weeks 1–8
Window open

Companies repurchase their own shares — a steady daily buyer in the market.

~5 weeks out
Blackout begins

Discretionary buying pauses before earnings (pre-set 10b5-1 autopilot plans may continue).

Earnings day
The report

Results released; the quiet period peaks.

+48 hours
Window reopens

The corporate bid returns to the market.

Plain glossary

Breadth — how many stocks are actually participating in a rally — many means sturdy, few means fragile.
Margin call — a demand to repay borrowed money immediately — what forces funds to sell good assets fast.
Spread — the extra interest a risky borrower pays over the government rate. Wider = lenders more scared.
Defensive stocks — businesses people pay for in any economy — food, power, medicine. They fall less in downturns, usually.
Crowded trade — a position so popular that everyone’s in it — fine on the way up, a stampede risk at the exit.
Equity risk premium — the extra return stocks should offer over safe bonds to be worth the risk. Thin premium = little cushion.
Factor — a repeatable style of stock — cheap ones, fast-growing ones, high-quality ones. Big money trades these styles wholesale.
Dash for cash — the panic mode where investors sell even the safest assets to raise cash — the 2020 signature.

How we know — and what we don’t

Two kinds of confidence

We keep two questions separate — and never dress an opinion up as a fact.

  • Is the number reliable? — data quality.
  • Do we believe the story behind it? — interpretation.
  • A figure can be rock-solid while its explanation is still a judgement call.

Where the numbers come from

Free, public, reproducible sources — any reader can check our work.

  • Fama-French factor data from the Kenneth French library.
  • The Fed’s FRED database for spreads and yields.
  • Cboe, the CFTC and the OFR for volatility and positioning.

What we don’t do

We don’t predict prices or hand out advice.

  • We show what’s moving, the range of what could happen, and how sure we are.
  • We tell you in advance what would prove us wrong.
  • The decision stays yours.

If you remember three things

  • Watch the average stock, not the index — participation is the rally’s health meter.
  • Ask who is selling and why — a margin call snaps back; a profit problem grinds on.
  • Let the bond market confirm — one alarm is noise, two alarms is a fire.

The Deep read is seven chapters, about 25 minutes — every claim sourced, every number anchored.

Same desk, two reading levels — switch Skim / Deep up top for less or more. Research and analysis, not investment advice.

What's moving equities

Many drivers, named — never one.

Causal map →

Attribution shown as buckets, not invented weights, with an explicit residual.

AI / mega-cap capex cycleprimaryInsulates the index; widens the breadth gap
Rates & liquiditymaterialDiscount-rate pressure on long-duration growth
Earnings & revisionsmaterialRevision momentum leads price — with a documented lag
Positioning / crowdingmaterialCrowded books reprice first in any funding shock
Active catalyst (Iran–Gulf)secondaryOverlay — see §Catalysts
Residual / unexplaineduncertainExplicitly named; never assumed zero
§1 · What environment are we in?

Market Regime.

daily

The lens for everything below: trend, volatility and the macro backdrop set the prior for how to read every other module. We treat the regime label as a prior, not a forecast.

VIX (implied vol)
feed pending
% from 200-DMA
feed pending
Realized vs implied (20d)
feed pending
Vol term structure
feed pending
Regime — index vs MA band, catalyst markedillustrative
Iran–Gulf shockIndex + MA band
Observed

The index has printed new highs, yet only about 55% of constituents sit above their 50-DMA. current

Interpretation

The advance is mega-cap-led; breadth this narrow has historically preceded corrections — a prior, not a forecast. attribution: medium

What we track
  • MIndex vs 50/200-day MA
  • MVIX level + vol term structure
  • MRealized vs implied vol (20d)
  • MStock–bond correlation regime
  • NMacro nowcast backdrop
  • NRegime-switching model
Leading-indicator value
Medium-high

VIX and vol-term-structure inversion often precede drawdowns; trend breaks are coincident-to-lagging.

Sources T1 Cboe VIX (daily/intraday) · FRED macro series · index MAs
Market Regime — live numbers, feed pending
VIX + term structureCboe — wire in
% from 200-DMAindex feed — wire in
Sources named above; wires in with the data layer.
§2 · Which kind of shock is this?

The shock channel.

Episode library →

Classify the channel before the direction. Every shock is sorted — funding or earnings — before it is traded, because the two run opposite playbooks. Mistake one for the other and you trade the second-round move with the first-round rules.

1 · Channel before direction

Funding shocks reprice crowded/levered books via margin mechanics; earnings shocks reprice cash-flow exposure via forecasts. Classify first — the playbooks are opposites.

2 · Observable vs inferred, labeled

HY OAS, breadth and VIX term structure are free and reproducible — quantitative. CTA positioning, dealer gamma and blackout impact are vendor estimates — qualitative, assumption-flagged.

3 · Pre-committed falsifiers

A regime read that cannot be proven wrong is a narrative, not a framework. Every central claim carries a dated, observable, free-data condition for abandoning it (§12).

Funding / liquidity channelsell what is owned

The seller is a margin call, not a revised forecast. Crowded and levered books reprice first through collateral mechanics; the move is violent, factor-shaped and historically mean-reverting once forced selling exhausts.

Tell: dislocation in crowded factors with no news; Treasuries wobble; credit may lag.
Earnings / demand channelsell what is exposed

The seller is a revised cash-flow view. Cyclical earnings exposure reprices first on the fundamental axis, then consensus EPS confirms with its documented lag. The move trends rather than snaps back.

Tell: sector-shaped selling that follows the input-cost map; credit widens with it.
One shock, two channels — the fork that sets the playbookillustrative
shockfunding — snaps backearnings — trends
Funding shocks are not monolithic — four sub-types, by collateral chain

The ordering of what reprices first depends on which collateral chain is impaired. Ask “which chain?” before assuming a funding shock generalises — the 2022 LDI episode barely touched equity factors. classification: contested

Quant-Quake unwindAug 2007
First to repriceValue & crowded long/short books reprice first; momentum actually rises into the event
SignatureMean-reverts within days (the Aug-10 snap-back) — losses of −5% to −30% on the most consistent books, then partial reversal
well-established
LTCM flight-to-liquidityAug–Sep 1998
First to repriceLiquid-over-illiquid and large-over-small; SMB −7.14% in the window
SignatureThe liquid/illiquid spread is itself the priced factor; 14-firm recapitalisation marks the bottom
well-established
Dash-for-cashFeb–Mar 2020
First to repriceEverything correlates to one — even quality drew down (RMW −2.90%) while defensives only won relatively (+14.33pts)
SignatureTreasuries and equities fall together; MMF flows invert; resolves only on a liquidity backstop
well-established
Localised collateral chainUK LDI · Sep–Oct 2022
First to repriceEquity factors barely move (SMB +1.17%, HML +5.20%); the shock stays in the impaired chain (gilts/repo)
SignatureThe boundary case: a funding shock in one collateral chain need not generalise — ask “which chain?” first
contested
The empirical anchor — six funding-stress windows, Fama-French dailies computed from public data
EpisodeMarketSMBHMLRMWDef−CycRead
LTCM / Russia · Aug–Sep 1998−10.86%−7.14%+0.51%+2.28%n/aLiquidity shock punished small/illiquid; modestly rewarded profitability
GFC funding panic · Sep–Nov 2008−42.05%−9.18%−7.47%+13.18%+21.25ptsQuality and defensives were the cleanest equity expressions of funding stress
Euro sovereign · Jul–Oct 2011−17.84%−9.29%−5.36%+9.19%+16.14ptsTraded like a funding/sovereign shock, not an earnings slowdown
COVID dash-for-cash · Feb–Mar 2020−33.98%−7.53%−17.92%−2.90%+14.33ptsBroad liquidation overwhelmed quality in absolute terms — the exception that disciplines the rule
UK LDI / gilt crisis · Sep–Oct 2022−5.54%+1.17%+5.20%+4.19%−4.27ptsA rates/collateral shock localised in gilts; equity factors barely moved
SVB deposit flight · Mar 2023−1.32%−5.54%−7.68%+3.56%+7.00ptsDeposit stress punished small/financial/value; rewarded quality and defensives

SMB = size · HML = value · RMW = quality/profitability · Def−Cyc = defensive-vs-cyclical sector ETFs. Computed from the public Kenneth French daily five-factor file and Yahoo ETF histories. baseline T3/T4

The single most important number in that table

RMW −2.90% in February–March 2020. Quality did not defend in absolute terms during the acute dash-for-cash.

  • It falsifies the practitioner rule that “quality always defends in a crisis.”
  • Defensives still won relatively (+14.33pts vs cyclicals) — the relative-vs-absolute reconciliation matters because either framing alone misleads.
  • This is why funding shocks must be sub-classified, never treated monolithically.
Diagnostic tells, in order
  • Stock–bond correlation flips positive — Treasuries and equities falling together marks the crossing from ordinary risk-off into dash-for-cash (the FSB’s March-2020 signature).
  • Crowded-factor dislocation with momentum rising — the Quant-Quake unwind signature: value and fundamental long/short books bleed first, and the move mean-reverted on 10 Aug 2007.
  • Equity factors barely moving while one asset class convulses — a localised collateral-chain event: LDI 2022, where forced selling explained roughly half the gilt fall and equities shrugged.

Energy and geopolitical shocks behave differently again — they hit sector earnings directly and run the earnings-channel playbook first: producers reprice on the revenue line, fuel-burners on the cost line (§5), with the funding watch as the escalation path. The Iran–Gulf overlay in §Catalysts is read exactly this way.

The case files — full episode anatomy
August 2007 — the Quant Quakecleanest pure-funding factor event
well-established
  • Quantitative equity market-neutral funds lost −5% to −30% month-to-date over 6–9 August — among the most consistently profitable books in the market (Khandani & Lo, MIT).
  • The factors that broke: value and the classic fundamental long/short factors (book-to-market, earnings-to-price, cash-flow-to-market) — quietly bleeding since July.
  • Price and earnings momentum actually rose into the event — the tell that this was positioning, not fundamentals.
  • Sharp partial reversal on 10 August — the signature snap-back once forced liquidation exhausted.
  • The “Unwind Hypothesis”: a multi-strategy desk liquidated stocks to meet margin calls from a deteriorating subprime book — the canonical model of credit stress invading equity factor space with equity fundamentals unchanged.
Aug–Sep 1998 — Russia / LTCMliquidity as a priced factor
well-established
  • Russia’s devaluation/default triggered flight-to-liquidity; LTCM lost 44% in August — $4.6bn in under four months.
  • A 14-firm, $3.625bn recapitalisation on 23 September 1998 marked the systemic moment — and the bottom.
  • Factor prints for the window: market −10.86%, SMB −7.14%, RMW +2.28%, CMA +3.82% — liquid-over-illiquid, large-over-small.
  • The spread between liquid and illiquid securities was itself the priced risk factor that gapped.
Feb–Mar 2020 — the dash-for-cashtwo phases, one lesson
well-established
  • Phase 1, “flight to safety” (late Feb): sell risky, buy safe — the ordinary risk-off response.
  • Phase 2, “dash for cash” (mid-March): investors sold even Treasuries to raise cash — the stock–bond correlation broke positive (FSB).
  • The plumbing record: prime MMF outflows $125bn · government MMF inflows >$800bn · record bond-fund outflows $109bn · S&P −12% on 16 March · VIX peak 83.
  • Factor prints: market −33.98%, HML −17.92%, RMW −2.90% — quality failed absolutely while defensives won relatively (+14.33pts).
  • Resolution came only on the liquidity backstop — not on valuation.
Sep–Oct 2022 — UK LDI / giltsthe negative case that disciplines the rule
contested
  • After the 23 September mini-budget, 30-year gilt yields rose >100bp in four days; pension LDI leverage spiked from <2.0× to 2.7×.
  • The Bank of England attributes roughly half the gilt-price decline to LDI forced selling — a textbook collateral-chain funding shock.
  • Yet equity factors barely moved: SMB +1.17%, HML +5.20%, RMW +4.19%; defensives underperformed (−4.27pts). State Street’s fragility metrics put the systemic risk in gilts, corporate bonds and property — not equity.
  • Falsifier-grade lesson: a funding shock localised in one collateral chain need not produce a global equity-factor rotation. Ask “which chain?” first.
August 2007 — anatomy of a quant quake
July 2007
The quiet bleed

Value strategies leak losses for weeks; nobody connects it to mortgages yet.

Aug 6–9
Forced selling

A margin call in mortgages forces stock sales; the most reliable strategies lose 5–30% in four days.

Aug 10
The snap-back

Forced selling exhausts; prices rebound within days. Whoever sold into the panic locked in the loss.

Feb–Mar 2020 — the two-phase panic
Late Feb
Flight to safety

Sell risky, buy safe — the ordinary scare. Treasuries rally as stocks fall.

Mid-March
Dash for cash

Even Treasuries get sold. $125bn flees prime money funds; the S&P drops 12% in a day; VIX hits 83.

Late March
The backstop

Central-bank liquidity opens. Only then does the spiral stop — valuation never got the chance.

Where the research disagreed — and what we adopted

On these questions the research supports more than one defensible reading. Disagreement is evidence about uncertainty — we publish the competing reasoning and the factor each reading weights, rather than smoothing it over.

What reprices first in a funding shock?
PositionsThree defensible readings, each weighting a different mechanism. Weighting crowding: momentum and levered value carry the heaviest positioning, so they break first and quality wins immediately. Weighting liquidity: forced sellers sell what they can sell, so small/illiquid (SMB) is the most repeatable first casualty. Weighting collateral mechanics: the crowded long/short book goes first, and the ordering depends on which collateral chain is impaired.
AdoptedThe collateral-chain framing — funding shocks are not monolithic; hence the four-way sub-taxonomy above.
Does quality always defend?
PositionsOne reading generalises from the typical episode and states it as a clean practitioner rule. The other tests the rule against the public daily factor file and finds the exception: RMW −2.90% across the March-2020 window — quality failed in absolute terms during the acute dash-for-cash.
AdoptedSettled by the data — quality defends except in a true dash-for-cash. The exception is on the page.
Does the 2022 LDI episode generalise?
PositionsJudged by mechanism similarity — leverage, collateral calls, forced selling — it reads as a generic funding analogue. Judged by the factor prints, it reads as a localised boundary case: the stress stayed inside the gilt/repo chain and equity factors shrugged (SMB +1.17%, HML +5.20%).
AdoptedThe boundary-case reading — it is the discipline on the whole taxonomy.
Does HY OAS lead equities by days?
PositionsThe pattern-weighted reading: widening past 400–500bp has preceded drawdowns by days-to-weeks often enough to trade on. The evidence-weighted reading: the academic lead/lag literature runs both directions (Acharya-Johnson find credit leading equities; Norden-Weber find the reverse), so no short-horizon lead can be relied on.
AdoptedThe conservative reading — HY OAS is a state variable and divergence detector, not a point-forecast input.
§3 · Is the move real or narrow?

Breadth & Internals.

daily

Three free, daily, orthogonal gauges — participation, concentration, thrust — chosen so any reader can reproduce them. One alone is noise; all three agreeing is signal; conflict between them is itself informative (broad participation with narrowing leadership marks a transitional regime).

% > 50-DMA
55%
currentmedium
% > 200-DMA
feed pending
RSP/SPY ratio
feed pending
Net new highs − lows
feed pending
Breadth divergence — index vs participationillustrative
Index ↑% > 200-DMA ↓
The trio, in detail — three orthogonal axes
Participation
% of S&P 500 above its 200-DMA

A tape rising on falling participation is narrowing leadership — the classic late-regime tell. Index higher-highs on lower breadth highs is the textbook divergence.

Free: StockCharts $SPXA200R · Barchart $S5TH · daily · EOD
Concentration
Equal-weight vs cap-weight (RSP/SPY)

Whether average constituents confirm index leadership. Top-10 names drove >70% of H1-2024 return at a 28% cap-weight P/E premium — concentration this extreme has historically mean-reverted.

Free: RSP:SPY ratio · S&P EW methodology · daily · intraday via ETFs
Thrust
Net new 52-week highs − lows

Cuts through weighting to the median stock. New index highs with expanding new lows is the single most reliable free divergence warning; a thrust off a low confirms.

Free: WSJ market data · Barchart · $NYHL · daily · EOD

Deliberately free and end-of-day so any reader can reproduce them — reproducibility is itself a durability property. Variants for cross-checks: $S5FI (50-day participation, faster), $SUPA200R (S&P 1500 — adds mid/small breadth). divergence: well-established timing: contested

What we track
  • M% of constituents > 200-DMA ($S5TH / $SPXA200R)
  • MEqual-weight vs cap-weight (RSP/SPY)
  • MNet new 52-week highs − lows ($NYHL)
  • NAdvance / decline line
  • NMcClellan oscillator
Leading-indicator value
High (divergence) · contested (timing)

Well-established for divergence detection; nobody times precisely with breadth alone.

Sources T1/T4 StockCharts · Barchart · WSJ market data — all free, daily EOD
Breadth & Internals — live numbers, feed pending
% > 200-DMA$S5TH / $SPXA200R
RSP/SPYETF feed
Net new highs − lows$NYHL / WSJ
Sources named above; wires in with the data layer.
§4 · What are we paying, and what return is embedded?

Valuation & Return Engine.

monthly · daily ERP

Decomposes return into earnings growth + multiple change + dividend/buyback yield. CAPE and ERP are weak short-horizon timing tools but meaningful 7–10yr signals — labeled baseline/context, never nowcasts.

Forward P/E
feed pending
Shiller CAPE
feed pending
Equity risk premium
≈3.2%
baselinemedium
Div + buyback yield
feed pending
Valuation — ERP vs its normal rangeillustrative
normal ERP rangeERP ≈3.2% — thin
Return bridge — ΔPrice ≈ Δearnings + ΔP/E + yieldillustrative
Div + b/backEPS growthΔP/ETotal
What we track
  • MTrailing & forward P/E vs history
  • MShiller CAPE
  • MEquity risk premium (earnings yield − real yield)
  • MReturn bridge: ΔPrice ≈ ΔEPS + ΔMultiple + Yield
  • NRegression-implied fair value
Leading-indicator value
Low for timing, high for 7–10yr return

CAPE/ERP have weak short-horizon power but meaningful long-horizon signal.

Sources T3 Shiller CAPE (monthly) · Damodaran implied ERP (monthly) · FRED real yields (daily) · forward multiples (T2)
Valuation & Return Engine — live numbers, feed pending
Forward P/Eestimate feed
Shiller CAPEShiller ie_data (monthly)
Implied ERP≈3.2% (Q1’26 ref) — Damodaran / earnings-yield − 10Y
Sources named above; wires in with the data layer.
§5 · Is the fundamental engine accelerating or stalling?

Earnings & Revisions.

continuous · season

The desk’s rule: consensus EPS is a lagging confirmation, never a leading signal. Prices react within hours; revisions wait for the earnings calendar. Lead on price, positioning and credit — expect the first real EPS evidence ~3 months after a cost-channel shock.

Fwd EPS growth
feed pending
Revision breadth
feed pending
Beat rate
feed pending
Net margin trend
feed pending
The lag asymmetry — price now, revisions laterillustrative
shockprice — hoursEPS revisions — ~3 months
The revision-lag map — how long each sector takes to confess

The desk convention for the clock: prices within hours-to-days · consensus within 1–6 weeks · annual EPS only after guidance. The map below is the sector-by-sector version of that rule.

How long the truth takes — from shock to forecasts
Hours
Price reacts

Markets reprice the shock immediately — before anyone updates a spreadsheet.

1–6 weeks
Consensus stirs

Analysts begin trimming nearest-quarter numbers, gated by the calendar.

~3 months
Sectors confess

The first earnings season shows real damage (an oil shock: ~−1.9% aggregate profits).

After guidance
Annual resets

Full-year forecasts finally move — long after prices already did.

SectorEPS-revision lagWhyConf
Energy producers1–4 weeksThe catalyst is the revenue line; spot/futures flow into decks within days, consensus follows hedging and capex commentaryhigh
Transports / airlines4–12 weeksFuel surcharges lag a week; near-term tickets were sold before the shock and cannot be repriced — a 30–90-day earnings-risk windowmedium
Insurers (P&C)4–12 wks → 1–3 yrsTwo-stage: short-tail catastrophe and auto/property hit current quarters; long-tail claims settle over years as reserve models resethigh
Defense primesQuarters → yearsStock moves fast, EPS slow — revenue flows through multi-year procurement and ASC 606 backlog conversion; news first compresses forecast dispersion, not estimateslow
Consumer discretionary3–6 monthsGasoline pass-through hits real income within a week, but analysts smooth and wait for the print before cutting marginsmedium
Calibration — what an oil shock does to earnings
  • A supply-driven oil shock cuts aggregate profits ~−1.9% at three months, persisting near −1.6% at a year (Lombard Odier decomposition — single-house, mechanism-consistent). contested
  • A 50% oil-price rise maps to roughly a 15% earnings decline over a year — the direct cost/margin channel (≈−2.1pts) dwarfs the rate channel (≈−0.2pts).
  • The ECB’s real-time model: oil passes into gasoline one-for-one within a week; airline stocks respond −0.45% on impact — substantially stronger than aggregate indices. well-established
The academic bedrock — why the lag is structural, not laziness
  • Ball & Brown (1968) → PEAD: abnormal returns drift for weeks-to-months after earnings news — the market underreacts; incorporation is slow, not instant.
  • Chan, Jegadeesh & Lakonishok: analyst forecasts “respond sluggishly to past news, especially for the worst past performers”; past surprises predict large drifts.
  • Federal Reserve (FEDS 2024): bottom-up analyst forecasts are largely uncorrelated with macro-based growth forecasts; the macro–analyst gap predicts ~50% of current-quarter and ~40% of quarter-ahead forecast errors.
  • Agarwal & Hess: analysts lean on macro news hardest for cyclical industries, and more in medium-term than current-year forecasts.
  • Chen, Narayanamoorthy, Sougiannis & Zhou: revisions themselves display momentum and underreaction — post-revision drift tracks serial correlation in individual analysts’ revisions.
  • Desk corollary: the price trough usually precedes the revision trough by months — by the time consensus capitulates, the multiple has already absorbed the damage.
Airline jet fuel

Jet fuel is 25–30% of airline opex (IATA 2026); global average $159.85/bbl vs $86 expected for 2025 (~+86% YoY at peak). 2008 analog: jet fuel $127/bbl took industry operating margins from ~4% to ~0%. "Sudden change is more challenging than high fuel prices" (IATA). Most carriers hedged <30% of 2026 fuel.

Petrochemicals / chemicals

Naphtha/ethane feedstock tied to crude; both input-cost and demand-destruction hits. EIA distillate crack spreads $1.42/gal in March 2026 — highest monthly since 2022. Refiners benefit temporarily; pure (non-integrated) chemical producers take the full feedstock shock.

Auto / manufacturing

OEM margins already 3.6% in Q4'25 — down >60% from the 2021 peak (Bain); full-year 2025 average 2.7%. ICE faces fuel-cost demand destruction; energy is embedded in steel/aluminum/plastics, compounding supply-chain pressure at razor-thin margins.

Insurance / war-risk premium

AWRP reached ~2.5% of hull value per 7-day period (March peak; ~1% now). VLCC rates hit a record $736k/day-equivalent (+94% vs prior Friday) on Mar 2. Major war-risk insurers (American Club, Gard, Skuld, Standard, London P&I) withdrew Gulf cover in early March; maritime premiums surged >1,000% for some categories; MR-tanker AWRP ~$40k/7 days (4× pre-war).

Freight / shipping pass-through

2024 Red Sea precedent: Suez-region shipping costs +180% peak; global freight indices +120%; container-shipping equity index −8.5% on one ceasefire rumor. 2026 analog: war-risk withdrawal + longer routing = capacity reduction; surcharges filter to CPI with a 1–3 month lag.

Aggregate S&P 500 EPS

Lombard Odier: a 10% global oil-supply disruption (≈Hormuz) → +50% oil → −15 to −20% US EPS over 12 months. US CPI 3.8% in April 2026 (energy-driven); core 2.8%.

What we track
  • MNTM/forward EPS growth (consensus)
  • MRevision breadth (up vs down)
  • MEPS surprise % / beat rate
  • NRevision diffusion by sector
  • NMargin decomposition
Leading-indicator value
High — as confirmation

Revision momentum leads price more consistently than valuation levels, but lags the catalyst itself by weeks to a quarter.

Sources T1/T2 Estimate vendor (T2) · SEC EDGAR XBRL company-facts for filed actuals (T1, real-time)
Earnings & Revisions — live numbers, feed pending
Fwd EPS growthestimate feed
Revision breadth (4-wk)estimate feed
Beat rateEDGAR + estimates
Sources named above; wires in with the data layer.
§6 · Where is leadership, and does it fit the cycle?

Sector rotation & the business cycle.

structural + daily RS

The durable sensitivity map — what each sector is structurally driven by. Click a column to sort. Live relative-strength and the cycle clock are feed-pending; the conflict winner/loser is the overlay in §Catalysts.

SectorCycleRatesOilETF
EnergyCyclicalLowHigh +XLK
MaterialsCyclicalModerateInputXLC
IndustrialsCyclicalModerate− inputXLY
Cons. DiscretionaryMost cyclical− High− inputXLP
FinancialsCyclical+ BenefitLowXLV
Info. TechnologyGrowth− DurationLowXLF
Comm. ServicesMixed− DurationLowXLI
Cons. StaplesDefensive− Mild− inputXLB
Health CareDefensiveLowLowXLE
UtilitiesDefensive−− HighLowXLU
Real EstateBond-proxy−− HighLowXLRE
Business-cycle clock — where leadership sitsillustrative
Early — Cyclicals Late — Energy/Mat Recession — Defensives Mid — Tech/Inds
Sector desk profiles — the 11 GICS sectors
Information TechnologyXLK
Secular digitization, cloud/AI capex, R&D intensity, long-duration cash flows
Rates High(−) · Cycle High · Oil Low · USD Med(−) · Infl Med(−)
KPIsRevenue growth · operating margin · R&D/sales · cloud growth · forward P/E
Leading indicatorsEnterprise capex intent · semi billings/bookings · cloud backlog · ISM new orders
Classic risksMultiple compression from real yields · mega-cap concentration · capex pullbacks
Lead / lagLeads early-cycle on falling rates; vulnerable late-cycle as rates/valuations bite
Communication ServicesXLC
Digital advertising, streaming/subscriptions, telecom infra; bifurcated (growth internet + defensive telecom)
Rates Med(−) · Cycle Med · Oil Low · USD Med(−) · Infl Low–Med
KPIsAd revenue growth · ARPU · subscriber net adds · EBITDA margin · churn
Leading indicatorsAd-spend surveys · ISM · consumer confidence · device/data trends
Classic risksAd-budget cyclicality · antitrust · content-cost inflation · cord-cutting
Lead / lagInternet/ad names track the cycle; telecom subset defensive and rate-sensitive
Consumer DiscretionaryXLY
Household non-essential spend, autos, e-commerce, travel/leisure; high beta to consumer health
Rates High(−) · Cycle High · Oil Med(−) · USD Med · Infl High(−)
KPIsComp sales · traffic · gross margin · inventory/sales · discretionary spend share
Leading indicatorsConsumer confidence · real wages · retail sales · credit availability · auto/mortgage rates
Classic risksRecession demand shock · margin squeeze · inventory gluts
Lead / lagClassic early-cycle leader; early to roll over late-cycle
Consumer StaplesXLP
Inelastic food/beverage/household demand; pricing power, brand moats; defensive
Rates Med(− bond-proxy) · Cycle Low (defensive) · Oil Low–Med · USD Med(−) · Infl Med (pass-through)
KPIsOrganic sales · volume vs price · gross margin · FCF · dividend coverage
Leading indicatorsCommodity input costs · FX · private-label share · real income
Classic risksInput inflation outpacing pricing · FX translation · volume loss to private label
Lead / lagOutperforms late-cycle/recession; lags in early-cycle risk-on
Health CareXLV
Aging demographics, pharma/biotech innovation, managed care, devices; mixed defensive/growth
Rates Med · Cycle Low–Med (defensive) · Oil Low · USD Med(−) · Infl Low–Med
KPIsPipeline/R&D productivity · patent cliffs · medical-loss ratio · drug volume/pricing · FCF
Leading indicatorsFDA approvals · utilization trends · policy/reimbursement · demographics
Classic risksDrug-pricing/policy reform · patent expiries · trial failures · litigation
Lead / lagDefensive ballast late-cycle; policy headlines can override the cycle
FinancialsXLF
Banks (NIM, credit), insurers, capital markets, asset managers; geared to rates and the credit cycle
Rates High(+ steeper curve) · Cycle High · Oil Low · USD Low–Med · Infl Med
KPIsNet interest margin · loan growth · credit-loss provisions/NPLs · ROE/ROTCE · trading/IB revenue
Leading indicators2s10s slope · credit spreads · loan-officer survey · deposit trends
Classic risksCredit losses in downturns · inversion compressing NIM · regulatory capital · deposit flight
Lead / lagEarly-cycle leader (steepening curve); vulnerable to inversion and recession credit losses
IndustrialsXLI
Capital goods, machinery, aerospace/defense, transports, construction; geared to global capex/trade
Rates Med(−) · Cycle High · Oil Med (transports −) · USD Med(− exporters) · Infl Med
KPIsOrder backlog / book-to-bill · capacity utilization · PMI exposure · operating leverage · freight volumes
Leading indicatorsISM/PMI new orders · durable-goods orders · capex intentions · global trade volumes
Classic risksCapex downturn · trade/tariff shocks · input inflation · defense-budget shifts
Lead / lagEarly/mid-cycle leader on rising PMIs; rolls over late-cycle as orders peak
MaterialsXLB
Chemicals, metals/mining, construction materials, packaging; commodity-price and global-demand driven
Rates Med · Cycle High · Oil Med (input) · USD High(− commodities in USD) · Infl High(+ real-asset)
KPIsCommodity prices · capacity utilization · spreads/margins · volume growth · China-demand exposure
Leading indicatorsChina PMI/credit impulse · copper/industrial metals · global PMIs · USD trend
Classic risksCommodity-price collapse · China-demand shock · strong-USD headwind · overcapacity
Lead / lagEarly-cycle/reflation leader; inflation-hedge tilt; lags in disinflation
EnergyXLE
Oil & gas E&P, integrated majors, refiners, services; crude/gas prices and supply discipline
Rates Low–Med · Cycle High · Oil High(+) · USD High(− inverse) · Infl High(+ hedge)
KPIsRealized oil/gas price · production volumes · FCF/breakeven · capital discipline/buybacks · reserve replacement
Leading indicatorsCrude inventories/EIA · OPEC+ supply decisions · rig counts · global demand/PMIs
Classic risksOil-price crashes · demand destruction · capital-discipline lapses · energy-transition/stranded-asset risk
Lead / lagLate-cycle/inflationary leader; strong geopolitical-shock hedge; lags in disinflation
UtilitiesXLU
Regulated electric/gas/water, rate-base growth, electrification/data-center demand; bond-proxy defensive
Rates High(− bond-proxy) · Cycle Low (defensive) · Oil Low · USD Low · Infl Med(−)
KPIsRate-base growth · allowed ROE · load/demand growth · dividend yield/coverage · capex plan
Leading indicatorsLong real yields · regulatory rate-case outcomes · electricity-demand/load forecasts
Classic risksRising long rates compressing the bond-proxy premium · adverse rate cases · high leverage
Lead / lagOutperforms in slowdowns and falling-rate regimes; lags in risk-on/rising-rate phases — and can fail as a defensive when the shock is rate duration itself
Real EstateXLRE
REITs (residential, industrial/logistics, data centers, retail, office), towers; rate- & credit-sensitive, income-oriented
Rates High(−) · Cycle Med (by subsector) · Oil Low · USD Low · Infl Med (rent escalators hedge)
KPIsFunds from operations (FFO) · occupancy · same-store NOI · cap rates · leverage/debt maturities
Leading indicatorsLong rates/financing costs · credit spreads · leasing/absorption · construction starts
Classic risksRising rates raising cap rates and refi costs · office secular pressure · oversupply
Lead / lagLeads when rates fall; office vs industrial/data-center dispersion is large; lags in rising-rate regimes

Sensitivity ratings are framework priors for IA defaults, not forecasts. Sector definitions per GICS (S&P / MSCI); liquid proxies are the SPDR Select Sector ETFs.

§7 · What style is being rewarded — and what breaks first?

Equity factors.

Factor lab →

Value/size/momentum/quality/low-vol explain the dispersion the sector lens misses — and under a funding catalyst they are the transmission itself (§2): the crowded book reprices before the exposed business. The 2007 Quant Quake is the canonical case — value and fundamental long/short factors broke while momentum rose into the event, then partially reversed within days.

Value
cyclical
Discount to fundamentals; leads in reflation — but the first casualty in a Quant-Quake-style unwind
Growth
long-duration
Future earnings growth; rate-sensitive
Quality
defensive
Strong balance sheets; defends in funding stress — except in a true dash-for-cash (Mar 2020: RMW −2.9%)
Momentum
pro-cyclical
Recent winners; rose INTO the 2007 quake, crash-prone at turns
Low / Min-vol
defensive
Lower fluctuation; fails when the shock is rate duration (levered utilities/REITs sold for cash)
Size
cyclical
Small-caps; SMB −5% to −9% in every major funding-stress window
The funding-stress factor playbook (episode-tested, §2 table)
  • Size: SMB was negative in five of six funding-stress windows (−5% to −9%) — small/illiquid is the most repeatable first casualty.
  • Quality: RMW defended in 2008 (+13.18%), 2011 (+9.19%) and SVB (+3.56%) — but failed in the 2020 dash-for-cash (−2.90%).
  • Value: HML’s crisis sign is unstable (−17.92% in 2020, +5.20% in the LDI window) — it depends on whether financials/energy are the epicenter or the beneficiary.
  • Low-vol: fails precisely when the shock is rate duration. SPLV vs SPY: +10.07pts in 2011, −2.11pts in the 2020 window, −1.84pts in the LDI window, ~flat through SVB — levered utilities and REITs get sold for cash.
  • Momentum: rose into the 2007 Quant Quake while value broke — crowding, not direction, is its crisis risk.

orderings: contested case-to-case

Factor returns — feed pending
Trailing factor returns (1m/3m/12m)Kenneth French Data Library
Value−growth spread · factor momentumFrench / MSCI / AQR proxies
FF 3/5-factor + momentum, free daily/monthly files; investable proxies via MSCI/AQR.
§8 · What moves the tape that isn’t fundamentals?

Index plumbing — free vs vendor.

Plumbing monitor →

The mechanical flows — buybacks, systematic strategies, options hedging. The most heavily marketed signals in markets, and the least verifiable.

  • Anything a reader can reconstruct from free public data is published quantitatively.
  • Anything that is a vendor estimate stays qualitative, with its modelling assumption flagged inline.
  • We do not publish point estimates we cannot source — false precision is the failure mode this section exists to prevent.
One quarter in the life of the buyback bid
Weeks 1–8
Window open

Companies repurchase their own shares — a steady daily buyer in the market.

~5 weeks out
Blackout begins

Discretionary buying pauses before earnings (pre-set 10b5-1 autopilot plans may continue).

Earnings day
The report

Results released; the quiet period peaks.

+48 hours
Window reopens

The corporate bid returns to the market.

SignalFree / reconstructableVendor-onlyDesk treatment
Buyback blackout calendarYes — derive from earnings dates: ~75% of firms close windows ≥11 days pre-quarter-end; “5 weeks before, 48h after” is the standard overlayBlackout-adjusted live corporate demand by constituentPublish the calendar quantitatively. The return effect is contested — State Street finds no significant blackout-period degradation — so the direction stays a qualitative overlay. medium
CTA / vol-control positioningMechanism fully public (trend signals + vol targeting). Weekly proxies: CFTC TFF (Fri for Tue) and the OFR Hedge Fund Monitor’s leveraged-fund futures exposureReal-time AUM, rebalancing thresholds, “$30bn if SPX breaks X” de-grossing estimatesDescribe the trigger logic quantitatively; never publish point-estimate flows we cannot source. Magnitudes are proprietary sell-side models. high
0DTE activityYes — Cboe/OCC volume and share data. 0DTE reached >40% of SPX volume by mid-2023, ~56% by Feb 2025, from <17% in 2020Customer-type decomposition, intraday hedging pressureQuantitative — the growth and share are documented from primary sources. high
Dealer gamma (GEX) & the “flip”Inputs only (Cboe open interest, strikes) — enough to approximateThe headline GEX level and flip line — they embed a dealer-positioning assumption (“short puts, long calls”) that is a simplificationCite qualitatively, always flag the positioning assumption, never treat the flip level as a hard line. medium
VIX term structureYes — Cboe, daily. Backwardation is the stress signature; an academic contrarian signal for forward returnsQuantitative, with the caveat that the timing signal is noisy and regime-dependent. medium
Why the GEX caveat matters

The dealer-hedging mechanism is public and real: positive gamma exposure dampens moves (“pinning”); negative amplifies them.

  • Every published GEX level embeds a dealer-positioning assumption — typically “dealers short puts, long calls” — which is a simplification.
  • The “flip” line is a model output: it varies by provider and moves intraday.
  • Desk treatment: cite the regime qualitatively; never treat the flip as a hard line. level: contested
The free positioning stack
  • Weekly: CFTC TFF — Friday 3:30pm ET for Tuesday’s book, split Dealer / Asset-Manager / Leveraged-Fund / Other — plus the OFR Hedge Fund Monitor’s leveraged-fund net notional in index futures.
  • Daily: Cboe 0DTE share and OCC volume / open-interest / put-call resources.
  • Calendar: the buyback blackout map, derived from public earnings dates — ~75% of firms close windows ≥11 days before quarter-end (32% at 11–15 days, 23% at >25); EU MAR mandates a 30-day closed period.
  • The 10b5-1 nuance: pre-established repurchase plans can keep buying through a blackout — so the calendar bounds the discretionary bid, never the total bid.
  • All T1, all free — the desk’s plumbing read is built only on these.

The vendor tier — named so readers know what we are not using: real-time CTA de-grossing estimates and vol-control AUM are proprietary models at Nomura, Goldman QIS, Deutsche Bank, UBS and J.P. Morgan. Their trigger logic is public; their point estimates are not reproducible and therefore not published here.

§9 · Is the trade crowded?

Positioning & Sentiment.

weekly

How much is already priced — and in a funding shock, §2 says the crowded book is the first casualty. Extremes are most informative; sentiment is a conditioning variable, not a trigger — NAAIM itself states its index is not predictive.

AAII bull−bear
feed pending
NAAIM exposure
feed pending
CFTC net (lev. funds)
feed pending
Fund flows
feed pending
Sentiment — composite dialillustrative
FearNeutralGreed
What we track
  • MAAII bull/bear
  • MNAAIM Exposure Index
  • MCFTC TFF leveraged-fund positioning
  • MOFR Hedge Fund Monitor — lev-fund index-futures exposure
  • MICI fund flows / ETF net issuance
  • NPut/call ratios
  • NPositioning composite z-score
Leading-indicator value
Medium, contrarian

Extremes mark turns; treat as conditioning, not a trigger.

Sources T1/T2 AAII (Thu) · NAAIM (Wed→Thu) · CFTC TFF (Tue data, Fri 3:30pm ET) · OFR HFM · ICI flows
Positioning — feed pending
AAII bull−bearAAII (public)
NAAIM exposureNAAIM (public)
TFF lev-fund netCFTC (3-day lag)
Weekly flowsICI (estimate)
§10 · Does the rest of the macro complex confirm equities?

Cross-Asset Linkages.

daily

Rates, credit, FX, commodities and vol often lead equities — and the credit desk owns the credit diagnosis; this desk translates it. Caveat: correlations are regime-dependent and spike toward 1.0 in stress — exactly when diversification fails. The three credit→equities hooks below are the desk’s standing cross-desk contract.

The three credit→equities hooks cross-desk contract
1
HY OAS — the fundamental confirmer well-established

The strongest single hook, used as a state variable, not a point forecast.

  • Spread-to-forward-return correlations: 69% at 1yr, 87% at 2yrs, 88% at 3yrs, 86% at 4yrs (LSEG/FTSE Russell) — a valuation relationship, strongest at 2–4yr horizons.
  • HY and Russell-1000 monthly returns correlated 84% over five years to Feb-2023, 92% in the final year of that sample.
  • The short-horizon “credit leads by days” rule is contested — Acharya-Johnson find CDS→stock information flow; Norden-Weber and Hilscher et al. find the reverse.

Desk rule: HY widening without breadth damage = early-warning divergence. HY re-tightening after a shock = necessary condition for durable re-risking.

FRED BAMLH0A0HYM2 · credit desk §1
2
VIX × CDX / Credit VIX — two barometers must agree well-established

A VIX spike without HY OAS or CDX widening is more likely a positioning/gamma event than a fundamental repricing — §2’s channel split, made operational.

  • VIX and CDS/iTraxx are cointegrated with predominant VIX price leadership; both rose ~400% through 2008 (Figuerola-Ferretti & Paraskevopoulos).
  • Cboe/S&P launched VIXHY and VIXIG (Oct 2023) precisely to give credit its own fear gauge — most academic lead/lag work predates them; the desk monitors them going forward.
  • VIX tends to lead credit-vol in broad risk shocks; CDS can lead in firm-specific credit events — divergence is a cross-check, never a single trigger.

Desk rule: only call a fundamental risk-off regime when credit and equity vol move together; otherwise label it a positioning event.

Cboe VIX (free) · Credit VIX (partly gated) · CDX via credit desk
3
IG OAS — the systemic validator well-established

HY moves early; IG moves when stress goes systemic.

  • HY wide with IG tight (<~150bp) = stress contained to low-quality credit.
  • IG widening fast alongside HY validates a macro/systemic equity selloff.
  • Price-discovery evidence (OFR): single-name CDS led cash bonds ~0.20% next-day pre-UMR, weakening to ~0.11% after; CDX index price discovery stayed stable throughout.

Desk rule: equities translate the credit desk’s spread-quality diagnosis into beta, sector and factor exposure — never re-derive it.

FRED BAMLC0A0CM · OFR WP 24-04 · credit desk §2
The one rule that uses all three
  • Credit (HY/IG OAS) is the fundamental confirmer; vol term structure / Credit VIX is the stress-state confirmer.
  • Call a fundamental risk-off regime only when both move with equities — otherwise label it a positioning event.
  • This single rule is what keeps a Quant-Quake from being traded like a GFC. Full credit diagnosis lives on the credit desk →
Live cross-asset tiles
US Dollar (DXY)
100.53 index
reserve-currency bid
EM credit (EMBI) spread
35 bps
sovereign risk premium
Oil vol (OVX)
58 index
energy-shock gauge
EM equity vol (VXEEM)
35.3 index
EM risk appetite
Stock–bond correlation
0.3 corr
the dash-for-cash tell
USD/JPY carry
159 USD/JPY
carry-unwind tripwire
Gold spot
4099 $/oz
real-asset / haven bid
BTC-ETF flow
-733 $m/day
downstream risk node
10Y Treasury yield
discount-rate anchor · feed pending
2s10s curve
recession lead · feed pending
HY credit OAS
credit-stress lead · feed pending
FRA-OIS / SOFR spread
interbank tripwire (~40bp) · feed pending

Live tiles read from the watch registry (data through 2026-06-02); greyed tiles await the FRED rates/credit feed. Caveat: these correlations are regime-dependent — they converge toward 1.0 in stress, exactly when diversification is needed most.

What we track
  • M10y yield & 2s10s curve
  • MHY & IG OAS (credit desk)
  • MVIX vs Credit VIX
  • MUSD (DXY)
  • MOil / copper
  • MStock–bond correlation regime
  • NGold · MOVE/VIX ratio
Leading-indicator value
Medium-high

Credit spreads and the curve are well-established macro leads; the lead is regime-dependent and often coincident — treated as confirmation, not prophecy.

Sources T1 FRED (daily) · Cboe (vol) · OFR · credit desk hooks · live registry tiles below
Where equities sits in the causal chain

Equities is the first-order financial layer in the causal chain: physical shock (Sections 1–7) → equity sector/factor rotation (here) → cross-asset correlation breaks & volatility regimes (Cross-Asset) → crypto beta/reflexivity (/markets/crypto). The sector winners deep-dive on /markets/energy, /markets/defense, /markets/insurance; the EM/credit stress on /markets/credit; the full correlation/vol synthesis on /markets/cross-asset.

§11 · What changes the view, and when?

Catalysts & scenarios.

3× daily

Catalysts annotate the framework above — they don't rewrite it. Each is read through §2 first: which channel is this shock arriving through? Scenario tilts are scenario framework priors, never recommendations.

Forward catalyst calendar
EventDriverImpact tierSections it touchesDate
FOMC decisionratesHighRegime · Valuation · Financials / Utilities / REITsfeed pending
CPI releaseinflationHighRegime · rate-sensitive sectorsfeed pending
Jobs reportgrowthMed-HighCyclicals vs defensivesfeed pending
Earnings-season peakfundamentalsHighEarnings · Sectors · Breadth · the blackout calendarfeed pending
OPEC+ meetingenergyMedEnergy · Cross-asset (oil)feed pending
CFTC TFF release (Fri)positioningMedPositioning · Plumbingfeed pending

Dates wire in with the calendar feed; events shown are the standing high-impact set the desk always tracks.

Scenario-conditional tilts durable framework
ScenarioTriggerLikely equity readSector / factor tilt (prior)
Hawkish surpriseRates / real yields ↑Long-duration & rate-sensitive pressuredTech / Utilities / REITs (−); Financials (+ NIM/curve)
Dovish surpriseRates ↓, easingRisk-on, multiple expansionDiscretionary / Tech (+); defensives lag
Growth re-accelPMIs / orders ↑Cyclicals leadIndustrials / Materials / Financials (+)
Growth scarePMIs / credit ↓Defensive rotationStaples / Health Care / Utilities (+)
Funding shockMargin/collateral stressCrowded & levered books reprice first; mean-reverts if containedLarge/liquid over small/illiquid; quality — unless dash-for-cash
Active catalysts affecting equities
ActiveIran–Gulf Conflict 2026earnings-channel shock · sector rotation · GCC
Channel read (§2):
  • An earnings-channel shock for energy, transports and defense — repricing on the input-cost map, EPS confessions due on the §5 lag schedule.
  • The funding watch (dollar plumbing, Gulf recycling) is the escalation path.
  • If the stock–bond correlation flips and holds, the classification changes — and so does the playbook.
The bifurcation
IndexRegionPeak decline realizedRecoveryConf
S&P 500US~−8% (trough ~6,316, Mar 30)Full recovery; ~7,400+ new ATH MayHIGH
Nasdaq 100US~−9% (Composite; tech led recovery)New highs on AI; Mag-7 +17%+ from Mar lowHIGH
Russell 2000US Small Cap−2.7% single-day Mar 4 (vs S&P −1.3%); deeper troughLagged; credit/fuel-cost pressureHIGH
STOXX Europe 600Europe>10% in onset weeks; persistent energy burdenPartial; 4 weeks of gains by Apr 17HIGH
DAXGermanyFell sharply; energy-intensive industrial baseBelow pre-conflict by late AprilMEDIUM
CAC 40FranceFell with STOXX; TotalEnergies partial offsetMixed; energy majors bufferLOW (proxy)
FTSE 100UKSlight decline; BP/Shell/commodity hedgeBetter than STOXX; commodity tiltMEDIUM
Nikkei 225Japan~−3% single session Mar 9; sustained pressurePartial; oil-import dragHIGH
TOPIXJapanParallel to Nikkei; banks/industrials dragSimilar to NikkeiMEDIUM (proxy)
KOSPISouth Korea~−3% single session Mar 9; refining/semis stressPartial on de-escalationHIGH
Hang SengHK/ChinaFell; EM oil-importer pressureEM recovery in AprilMEDIUM
CSI 300ChinaFell; China imports 5.4M bpd via HormuzPartialMEDIUM (proxy)
Nifty 50IndiaFell; Sensex −999.79 pts on shock days; Nifty ~22,000–23,900Volatile; domestic buying supported floorHIGH
MSCI EMGlobal EM−11% in March alone; then +14.7% in AprilRecovered most March losses by April endHIGH
Tadawul (TASI)Saudi Arabia+5% in March (!) to ~11,250; +1.7% above pre-war mid-MarchOutperformed all major marketsHIGH
DFMUAE/Dubai−16% since onset; −4.71% first post-halt day (Mar 5)Deep drawdown; partial recoveryHIGH
ADXUAE/Abu Dhabi−9% since onset; −1.93% Day 1Partial recoveryHIGH
Qatar ExchangeQatar~−4%; Ras Laffan strike forced QatarEnergy force majeureHeavy; LNG-revenue disruptionHIGH
IbovespaBrazilOutperformed; near 177,000+; BRL +10% vs USDRecord highs by late AprilHIGH
Reading the bifurcation

Total UAE market-cap loss ~$120bn (Al Jazeera). The defining 2026 feature is index/stock divergence: the S&P closed >7% above its 50-day MA for the first time in three decades, yet <55% of components were above their own 50-day MA — the AI/Mag-7 complex masking broad weakness. [PROVISIONAL-2026] for all conflict-window levels; regional exchanges without major-newswire close data are LOW/proxy.

Winners & losers under this catalyst

Definition: winners/losers of this catalyst's repricing — vs the pre-catalyst baseline, sector-relative, over the repricing window, in the currently realized scenario. Sectors flip across scenarios — switch below.

SectorStatus (realized)MechanismETFConf
Energy (E&P, integrated majors)WINNERBrent $72→$120; direct price-to-revenueXOP, XLE, BNO (+84% Q1)HIGH
Oilfield ServicesWINNERCapex surge; repair contractsOIHMEDIUM
Defense / AerospaceWINNERSpending surge; weapons demandITA (+18% YTD by Mar); DFEN +14% YTDHIGH
Tanker / Shipping OwnersWINNERVLCC rates +94% Day 1; longer routesFRO +62.6%, NAT +63.2%, DHT +59.1% YTDHIGH
CybersecurityWINNERDigital-warfare premiumCIBR +7.5% wk1, ISPY +8% wk1, HACKHIGH
Gold MinersWINNER (volatile)Initial 10% 2-day drop then sharp recoveryGDX +95% 12-mo to Apr, GDXJHIGH
LNG Exporters (non-Gulf)WINNERRas Laffan force majeure; US/Australian premiumLNG, GLNG (names)MEDIUM
AirlinesLOSERJet fuel 25–30% of opex; +40% spikeJETSHIGH
Chemicals / PetrochemicalsLOSERFeedstock (naphtha/ethane) surgeIYM, CHEMHIGH
Consumer DiscretionaryLOSER (mixed)Gasoline +51%; household squeezeXLY (lagged)HIGH
Auto OEMsLOSEROEM margins already 3.6% Q4'25 (−60% from 2021); EV write-offsCARZHIGH
Travel / Tourism / Hotels / AirportsLOSERGCC tourism at standstill; ME routing suspendedAWAY, JETSHIGH
Import-Heavy EM EquitiesLOSERIndia/Korea/Thailand; current-account drainEEM, INDAHIGH
EM BanksMIXED–LOSERCredit risk on energy importers; GCC NFI exposureNamesMEDIUM
Insurers / ReinsurersMIXEDAWRP 2.5% hull/7-day (Mar peak) vs ~1% nowSpecialty reinsurersMEDIUM
Semiconductors / AI InfrastructureMIXED (cable_severance: LOSER)Cable latency; AI-capex funding; data-center energySMH, SOXXMEDIUM
UtilitiesMIXEDFuel-clause pass-through lag; US natgas −51.7% in March (offset)XLUMEDIUM
The four scenarios, defined precisely

One of these is not a hypothetical. Each scenario below carries its status — the winners/losers table above is shown in the realized one. Definitions are physical, not vibes: a transport blockage, a capacity destruction, a connectivity cut and a de-escalation are four different shocks with four different repricing paths.

Hormuz closure✓ realized

Transit through the Strait blocked or priced as un-insurable — a transport blockage of intact supply. Barrels still exist; they cannot move. First-order repricing: freight, war-risk insurance and regional spreads (the March record: VLCC $736k/day-equivalent, AWRP ~2.5% of hull per 7 days), then importers’ input costs.

Oil-infrastructure strike◇ escalation path

Strikes that destroy processing or export capacity at the source — the Abqaiq–Khurais 2019 analog: stabilization plants, export terminals, pumping stations. Distinct from Hormuz: this removes supply outright rather than blocking its movement, so it reprices the whole crude curve and persists until capacity is repaired, not until a lane reopens.

Cable severance◇ escalation path

Cutting subsea data/telecom cables in the Gulf / Red Sea corridors — a connectivity and financial-plumbing shock, not a barrels shock. Hits exchange access, settlement, cloud and comms first; equity expression runs through regional financials and any business dependent on Gulf connectivity.

Ceasefire◇ de-escalation path

The roles flip fast: war premia unwind — energy gives back the conflict premium, transports/insurers and Gulf “losers” snap back, and the biggest single-day moves often come from relief, not damage. The desk treats this as a scenario with the same discipline as the escalations.

The Iran–Gulf shock — what happened when
Mar 2
Freight panic peak

Tanker rates hit a record $736k/day-equivalent; war-risk insurance ~2.5% of hull value per week.

March
Hormuz closure window

Transit blocked or uninsurable. UAE output forced down toward ~1.9M bpd; Qatar declares force majeure at Ras Laffan.

Apr 9
Petroline strike

Drone strike cuts the Saudi east–west bypass by 700k bpd — the workaround itself gets hit.

By late Apr
Bypass restored

Petroline back to 7.0M bpd; Saudi exports ~3–4M bpd around Hormuz.

Today
Partial normalization

War-risk premia ~1% (from 2.5%); §scenarios above tracks the next branch.

All dated facts above are sourced in the GCC cards below and the insurance/freight records in §Catalysts. realized

Sector impact by scenario

Energy, defense, tankers, cyber, gold miners maximally bullish. Airlines, autos, petrochem, consumer discretionary, EM importers −20–40%. GCC non-oil (retail, real estate, hospitality) bear-market.

Similar but shorter duration; extremes less pronounced. Energy +15–30%, airlines −15–25%.

Cybersecurity surges additively. Semis volatile. Financials face settlement risk. Online retail/e-commerce disrupted. Physical-world sectors less impacted.

Violent rotation: energy sold off sharply (oil −10–20%, as Apr 17 when Brent dropped >10%); airlines, autos, consumer discretionary recover; EM importers bounce.

Precedent: 2022 Russia-Ukraine: energy and basic resources were the only two STOXX Global 1800 sectors positive YTD through Feb 24 (Brent >$100). 2024 Red Sea: the Drewry Container Equity Index fell 8.5% on ceasefire rumors in a single week.

GCC repricing GCC asymmetry · live 21 ppts

The GCC shows the most dramatic internal divergence of any region. Saudi Arabia is an oil-revenue equity winner; UAE is a geographic/security-risk loser short-term despite strong oil-bypass infrastructure; Qatar is a casualty of Iranian strikes on Ras Laffan. GCC sovereigns benefit from high oil at the macro-fiscal level, but GCC domestic equity sectors (banks, real estate, tourism, logistics, construction) reprice security and funding risk rapidly when conflict is geographically proximate.

Saudi — oil-revenue winner
  • Petroline (East-West) restored to 7.0M bpd by April 2026 after an Apr 9 drone strike cut throughput 700k bpd;
  • Yanbu loading ~4.0–4.5M bpd is the operational proxy constraint — so Saudi can export ~3–4M bpd bypassing Hormuz.
  • With Brent >$100, Aramco (16% TASI weight) surges → TASI +5% in March alone, +1.7% above pre-war by mid-March, one of the few major indices positive globally.
  • Saudi domestic banks are net beneficiaries of oil-driven public spending, unlike UAE banks facing expat-outflow risk.
UAE — security loser
  • ADCOP (Abu Dhabi→Fujairah) at 1.7–1.8M bpd (May 2026), ramping toward ~3.6M bpd by 2027.
  • UAE crude output fell to 2.02M bpd (April) / 1.9M (March) from ~3.4M pre-conflict as Hormuz closure forced shut-ins.
  • DFM −16% since onset (−4.71% Day 1), ADX −9%, ~$120bn market-cap loss.
  • Day-1 sector hits: real estate −4.92% (Emaar/majors at 5% circuit breaker), financials −4.38% (Emirates NBD, FAB); materials +2.38% (National Cement, sole positive on defense/infrastructure).
Qatar — LNG casualty
  • Iranian strikes on Ras Laffan forced QatarEnergy's first force majeure in three decades.
  • Global LNG supply fell ~8% YoY in March (Qatar+UAE loadings −9.5 bcm annually); reportedly −20% globally.
  • Qatar Exchange fell ~4% while TASI rose — a direct LNG-revenue-casualty vs oil-revenue-insulation expression.
  • Cumulative 2026–2030 LNG loss estimated at 120 bcm (~15% of expected global supply).
Factor rotation under this catalyst
Factorvs marketMechanismConf
Minimum VolatilityOutperformed in all 3 regions (US, World ex-US, EM)Flight to safety; defensive sectorsHIGH
QualityOutperformed ex-US & EM; underperformed US (captured in AI/tech)Earnings stability; pricing powerHIGH
Energy (sector tilt)Outperformed; highest positive active return across all 3 regionsDirect oil-price benefitHIGH
ValueMixed; negative in initial shock, partial recoveryCyclical value (banks/industrials) sold first; energy value recoveredMEDIUM
MomentumWorst performer — "unwinding of crowded trades"EM tech/AI momentum unwound; EM crowding factor −1% in first 2 weeks of March (4-sigma)HIGH
Growth (ex-AI)UnderperformedMultiple compression as rates rose on inflationMEDIUM
AI/Tech (Large Cap)Anomalous outperformer; oil-cost insulationMag-7 +17%+ from Mar trough; AI capex maintainedHIGH (novel)
High BetaUnderperformedDeleveraging; risk-offHIGH
Dividend YieldOutperformed ex-US & EMDefensive income allocationMEDIUM
Small CapUnderperformed significantlyRussell 2000 −2.7% Mar 4 vs S&P −1.3%; credit costs; no fuel hedgingHIGH
EM Exporter basket (Brazil, Colombia, Saudi producers)OutperformedOil-revenue windfall; FX strengthHIGH
EM Importer basket (India, Korea, Thailand, Philippines)UnderperformedCurrent-account drain; currency weakness; fiscal pressureHIGH
1

AI insulation override: the large-cap tech/AI factor acted as a circuit-breaker on the traditional oil-shock bear market. Micron +140% from the March trough by mid-May. The S&P closed >7% above its 50-day MA for the first time in three decades, yet <55% of components were above their own — extreme index/stock divergence.

2

Volatility-control / risk-parity deleveraging: VIX surged +57% in one week; vol-targeting strategies mechanically cut equity exposure as realized vol rises, amplifying the initial sell-off. ECB research confirms this feedback loop is structural.

3

Asymmetric volatility: since the war began, SPX realized vol was higher on up days (16.9%) than down days (14.6%) — highly unusual; investors were well-hedged for downside and the upside rally surprised positioning (Cboe).

4

Options skew inversion: oil 1M implied vol jumped 7 points; crude upside-call skew stayed extremely inverted (upside bid), extending to 6M options — not seen since 2022 Russia/Ukraine (Cboe).

Country × scenario matrixexpand

Click a scenario column to rank countries by outcome — best-to-worst or worst-to-best. Colours parse the generated outcome text: winner · mixed/neutral · loser.

CountryHormuz closure ✓Oil-infra strikeCable severanceCeasefire
USMixed-Loser (−8 to −15% S&P)Mixed (−5 to −8%)Mixed-Loser (−3 to −6% Nasdaq)Winner (+8–12%)
EULoser (−15 to −25%)Loser (−10 to −15%)Mixed (−3 to −5%)Winner (+10–15%)
JapanLoser (−20 to −30%)Loser (−12 to −18%)Mixed (−5 to −8%)Winner (+12–18%)
IndiaLoser (−15 to −25%)Loser (−10 to −15%)MixedWinner (+10–15%)
SaudiMixed/Winner (+5 to −5%)Winner (+3 to +8%)NeutralLoser (−5 to −10%)
UAELoser (−15 to −25%)Loser (−8 to −15%)Loser (−5 to −10%)Winner (+15–20%)
BrazilWinner (+5 to +15%)Winner (+3 to +10%)NeutralLoser (Petrobras −5 to −10%)
ChinaLoser (−10 to −20%)Loser (−8 to −12%)Loser (−5 to −8%)Winner (+8–12%)
S. KoreaLoser (−20 to −30%)Loser (−12 to −18%)Mixed (−5 to −8%)Winner (+12–18%)
Risk-parity / vol-control deleveraging

Risk-parity/vol-control strategies mechanically de-risk as realized vol rises — with VIX +57% week 1, typical vol-targeting funds cut equity allocation 30–50%. ECB research confirms this feedback loop amplifies sell-offs. The EM crowding factor fell >1% in the first two weeks of March — a 4-sigma event. Margin calls in energy futures likely triggered correlated equity selling in commodity-focused funds.

Crypto spillover → the terminal node

VIX spikes correlate with crypto drawdowns via risk-parity deleveraging (crypto increasingly a risk asset), leveraged-ETF unwinding, and institutional risk-limit triggers. In the March shock, crypto's correlation with equity risk-off was elevated: BTC/ETH fell alongside equities in week 1 and recovered as the SPX recovered in April. Full crypto analysis is in Crypto (Section 10).

MonitoringOPEC+ Supply PolicySpare capacity · Quota compliance

Spare-capacity buffer and quota discipline — the biggest swing factor sitting behind every oil-price scenario. — Tracked as a standing driver; promoted to a dossier when a decision materially shifts the supply balance.

MonitoringGlobal Tariff EscalationInput costs · Supply-chain reroute

Announced-vs-delivered tariff measures and the supply-chain reroute they trigger. — Monitored via the announced-vs-delivered gap; promoted when measures take effect at scale.

MonitoringTreasury-Issuance ShiftAuction quality · Real yields

Refunding size/mix and auction quality — the plumbing behind real yields and the dollar. — Tracked through refunding announcements and auction tails.

Simultaneous catalysts: when events cluster, we group them into one high-density window, name competing drivers + a residual when they conflict, and widen the affected sections' confidence rather than forcing one story. Charts anchor to multi-cycle history to fight recency bias.

§12 · What would prove us wrong?

Pre-committed falsifiers.

standing · free data

A regime read that cannot be proven wrong is a narrative, not a framework. We publish, in advance, the dated, observable, free-data conditions under which we abandon the central read.

  • The central read under test: “shocks here are funding-mechanical and mean-reverting unless the evidence says otherwise.”
  • Each falsifier names exactly which clause it kills — no vague “risks remain” hedging.
  • Every input is free and checkable by any reader: FRED, the Kenneth French library, Barchart/StockCharts, CFTC, OFR, FSB.
1
Sustained HY OAS regime break
high

HY OAS breaks and stays above ~600–700bp for 20+ consecutive sessions (vs the benign ~275bp mid-2026 regime). Spike-and-revert is mechanical; sustained is fundamental.

Free dataFRED BAMLH0A0HYM2 · daily
FalsifiesThe “credit confirms benign fundamentals” clause
2
No Quant-Quake reversal
high

Within ~5 sessions of a crowded-factor dislocation, the Aug-2007-style partial snap-back fails to appear; value/momentum or large/small keeps extending past a week.

Free dataKenneth French dailies · IWM/SPY · RSP/SPY
FalsifiesThe Unwind Hypothesis — the “mechanical, mean-reverting” read
3
Fast, broad, cost-insulated EPS cuts
medium

Consensus sector EPS revised down >5% within the first earnings season (~3 months), including sectors with no direct input-cost exposure — demand destruction, not margin compression.

Free dataConsensus EPS calendars · revision breadth
FalsifiesThe “contained funding event” read
4
Breadth fails to recover
high

%>200-DMA stays below ~30% for 20+ sessions while the cap-weight index recovers, or RSP/SPY breaks a 40-week low and holds it. Mean-reverting shocks broaden on the rebound.

Free dataBarchart $S5TH · StockCharts $SPXA200R · RSP/SPY
FalsifiesThe durability / mean-reversion read
5
Persistent positive stock–bond correlation
high

SPX/UST return correlation flips positive and stays there ≥20 sessions — Treasuries and equities falling together is the FSB’s dash-for-cash signature crossing into systemic.

Free data20-day rolling corr · FRED/Yahoo dailies
FalsifiesThe “contained, mean-reverting funding event” thesis
6
Interbank funding tripwire
high

FRA-OIS / SOFR spread blows past ~40bp — money-market plumbing stress that bypasses every equity-side falsifier and goes straight to the funding system.

Free dataFRA-OIS / SOFR spread · daily
FalsifiesAny “smooth liquidity” regime, instantly
The confirmation clock — the staged downgrade schedule

The falsifiers above kill the central read; this clock grades a live shock against it in real time. From catalyst date T, each checkpoint that fails removes one leg of the funding-shock narrative — a schedule, not a vibe.

ByIf we do NOT see…Then…Free dataConf
T+5HY OAS not +50bp · VIX not above 25 (or +8pts) · %>200-DMA not −5ptsDowngrade “funding shock” to an earnings or idiosyncratic readFRED HY OAS · VIXCLS · $S5THmedium
T+10Small beating large · equal-weight beating cap-weight · SMB positive while HY stays wideThe liquidity-preference assumption is wrong for this episodeIWM/SPY · RSP/SPY · French dailiesmedium
T+15Defensives not outperforming cyclicals · new lows not expandingThe shock is not transmitting through macro risk aversion at allXLP/XLU/XLV vs XLY/XLI/XLF/XLE · $NYHLmedium
First TFF after T+7Leveraged-fund index-futures exposure has not fallen; OFR proxies show no de-riskingRemove the CTA/vol-control deleveraging leg from the narrativeCFTC TFF · OFR HFMhigh
First revision cycle (~4 weekly snapshots / next season)Exposed-sector EPS revisions not moving in the predicted directionThe catalyst is price-only, not earnings-transmissiveConsensus snapshots · revision breadthhigh
Falsification cuts both ways — every read has a kill-switch

Symmetric discipline: the desk pre-commits against its bearish and bullish narratives as readily as its benign ones.

  • Kills the bearish read: the 3-month moving average of EPS estimate upgrades outnumbers downgrades across cyclical sectors (transports, industrials) while macro-fear headlines persist.
  • Kills the soft-landing read: the index prints a new all-time high while HY OAS widens >50bp over two weeks — credit refusing to confirm the high is the classic divergence.
  • Kills the cyclical-expansion read: quality and low-vol outperform value and small caps for 4 consecutive weeks while indices rise — the market rotating to safety under the hood of a rally.

Thresholds are judgement calls and labeled as such; the discipline is the pre-commitment, not the precision. scenario

§13 · Why should I believe this?

Evidence & methodology.

Two confidences, kept distinct — and neither ever borrows the other’s credibility.

  • Data confidence — are the numbers sound? Observed facts render in neutral type.
  • Attribution confidence — did the driver cause the move? Interpretation is labeled and carries its own chip; it never inherits the data’s confidence.
  • Research claims arrive tagged well-established / contested / anecdotal and keep those tags on the page.
Value types
Baselinelong-run norm / historical reference
Currentlatest observed print
Nowcastmodel estimate of the present from incomplete data
Forecastforward model / consensus estimate
Scenarioconditional “if-then” path
Source tiers
T1Primary / official — SEC EDGAR · CFTC · Cboe · FRED · OFR · FSB · S&P/MSCI GICS
T2Reputable institutional — State Street SPDR · ICI · AAII · NAAIM · LSEG/FTSE Russell
T3Academic / research — Kenneth French · Khandani & Lo · Damodaran · Shiller · ECB WP
T4Estimated / in-house — breadth composites · episode tables computed from public dailies · regime label
Numbers upgraded to HIGH confidence (23)expand
  1. S&P 500 trough ~6,316 on Mar 30; ~−8% from Feb 28 pre-conflict (CNBC).
  2. Brent $72.48 (Feb 27) → $119.46 peak early March; +55% in <2 weeks (CNBC) [PROVISIONAL-2026, pending primary recheck].
  3. TASI +5% in March; +1.7% above pre-war mid-March (Arab News).
  4. DFM −4.71% Day 1 (Mar 5); ADX −1.93% Day 1; total UAE market-cap loss ~$120bn (Al Jazeera).
  5. MSCI EM −11% in March; +14.7% in April (MSCI).
  6. Nikkei/KOSPI ~−3% single session Mar 9 (CNBC).
  7. VLCC rates +94% in first days; FRO +62.6%, NAT +63.2%, DHT +59.1% YTD to Mar 9 (247 Wall St).
  8. GDX (gold miners) +95% over 12 months to April (247 Wall St).
  9. VIX +57% in one week (Mar 2–9) (Forbes).
  10. Petroline restored to 7.0M bpd by April (Energy Connects).
  11. ADCOP Fujairah at 1.7–1.8M bpd by May (Argus).
  12. War-risk premiums >1,000% surge for some Gulf cover; AWRP 2.5% hull/7-day peak (Reuters; S&P Global).
  13. Jet fuel 25–30% of airline opex (2026); global average $159.85/bbl (IATA).
  14. QatarEnergy force majeure on Ras Laffan; global LNG reportedly −20% in April (Bloomberg; The National citing IEA).
  15. Lombard Odier: 5% oil rise → −2.2% US EPS over 12 months; 50% spike → −15% EPS (Lombard Odier).
  16. 1990 Gulf War: WTI +90.2% Aug 2–Oct 11; S&P −16.9% same period (DataTrek).
  17. 2022 Russia-Ukraine: STOXX Europe 600 −3.2% Feb 24; Brent +30%+ YTD (STOXX).
  18. 2024 Red Sea: Suez shipping +180%; global freight +120% (St. Louis Fed).
  19. Brazil Ibovespa near 177,000+; BRL +10% vs USD (Latin Finance).
  20. Brent +16% drop on initial ceasefire then recovery to −13.5% at $94.36 (Morgan Stanley).
  21. EIA distillate crack spreads $1.42/gal March 2026, highest since 2022 (EIA).
  22. Auto OEM margins 3.6% Q4'25, down >60% from the 2021 peak (Bain).
  23. Micron +140% from the March trough by mid-May; S&P >7% above 50-day MA (first in 3 decades) with <55% of components above their own.
Could not verify / proxy only (15)expand
  1. Exact close levels for CAC 40, TOPIX, CSI 300 during the window — directional press only [PROXY via STOXX/MSCI correlated moves].
  2. Full-timeline DFM/ADX levels — Day-1 verified, full series not in open sources.
  3. Qatar Exchange daily levels — only aggregate % changes (−4% from Al Jazeera).
  4. Specific GCC ETF inflow/outflow — proprietary (Bloomberg/EPFR) [PROXY: premium/discount to NAV].
  5. Daily ETF flow breakdown (energy/defense/EM) — aggregate only [PROXY: weekly AUM changes].
  6. Name-level short-interest changes (airlines/autos) — subscription-only [PROXY: Cboe put/call ratios].
  7. Aramco intraday and DFM/ADX single-stock intraday — not public at required granularity.
  8. Q1 2026 OEM margins — Bain data through Q4'25 [PROXY: extrapolated with energy uplift].
  9. Pakistan KSE-100 window performance — contextual only [PROXY: EM-importer analog, −10–20% in hormuz_closure].
  10. Nifty 50 exact peak-to-trough — Sensex −999.79 one session confirmed; full trough not pinpointed [PROXY: 22,000–24,000].
  11. Drewry/Clarksons 2026 freight rates — paywalled; 2024 Red Sea used as analog.
  12. TeleGeography 2026 cable-traffic diversion — 2024–2025 data used.
  13. EM bank NPL data for GCC-exposed portfolios — not in open sources; directional inference.
  14. Vol-control fund deleveraging magnitude — no public AUM data; ECB 2020 paper as framework.
  15. Russia equity performance — sanctioned/inaccessible for the 2026 window.
Scenario trade expressions
Analyst desk · trade expressions Analyst tier

Scenario implications, not individualized advice. No price targets or buy/sell calls. Directional and instrument-level expressions are for the analyst audience only.

hormuz_closure — Sustained Closure >60 Days

Stagflation bear. S&P −15–25%; STOXX −20–30%; Nikkei −25–35%; MSCI EM −15–25%; TASI initially positive then falls on recession risk.

Dir.TradeInstrumentRationale
LongUS energy E&P (non-Gulf)XOP, XLEBrent $120–$150; domestic revenue
LongDefense / AerospaceITA, DFENSpending surge; weapons backlog
LongTanker equitiesFRO, NAT, DHTRoute length maximized; rates at records
LongCybersecurityCIBR, ISPYDigital-conflict premium
LongGold minersGDXInflation + geopolitical + gold-price hedge
LongNon-Gulf LNG exportersLNG, GLNGQatar force majeure → US/Aus premium
ShortAirlines (non-hedged)JETSJet-fuel shock destroys margin; >30% cost base
ShortEuropean industrialsEXV1Energy-import shock + margin crush
ShortJapan/Korea equityEWJ, EWY100% oil importers; currency drag
ShortEM importer basketINDAFiscal + currency + earnings triple hit
ShortConsumer discretionaryXLYGasoline/energy squeeze on disposable income
ShortAuto OEMsCARZThin margins + EV write-offs + demand fall
Long-ShortTASI energy vs TASI real estate/banksTASI namesOil income vs security risk bifurcation
Crypto spilloverShort BTC/ETHPerpetualsRisk-off; correlation with equity drawdown elevated
oil_strike — Infrastructure Damage, Partial Output, 3–6 Months

Energy-infrastructure shock; shorter duration. S&P −8–12%; Europe −12–15%; Asia −10–18%.

Dir.TradeInstrumentRationale
LongOilfield services / repairOIH, SLBInfrastructure-repair surge
LongEnergy majors w/ Gulf bypassAramco, BPOil-price benefit + bypass capacity
LongDefense (missile defense, drone)ITA, L3HarrisAttack/defense spending spike
ShortGulf-region airlines(no pure ETF)Gulf routing disrupted; jet fuel at peak
ShortEM banks w/ GCC exposureEM bank namesNPL risk from GCC disruption
Crypto spilloverModerate short BTCPerpetualsRisk-off; less severe than hormuz_closure
cable_severance — Internet / Telecom Infrastructure Cut

Cyber/AI volatility; settlement risk; EM fintech/e-commerce disruption. Broad-market impact more contained vs oil.

Dir.TradeInstrumentRationale
LongCybersecurityCIBR, ISPY, HACKDigital-infrastructure protection demand
LongSatellite internetASTS, STRL, VSATRedundancy demand if subsea cables impaired
LongDomestic cloud (US/EU)CLOUTraffic rerouting to domestic infrastructure
ShortEM e-commerce / fintechEM namesTransaction latency; consumer impact
ShortAI infrastructure (short-term)SMH, SOXXData-center connectivity impairment
ShortCross-border payments/clearingEM-specialist namesSettlement latency risk
Crypto spilloverShort crypto exchanges w/ Asian routingExchange-specificWithdrawal/deposit latency; DeFi settlement risk
ceasefire — Hormuz Reopens, Brent Falls $15–20 Day 1

Rapid risk-on; violent sector reversal; growth/AI rotation resumes; EM importers recover.

Dir.TradeInstrumentRationale
LongAirlines (pre-position)JETSJet-fuel cost reversal; demand recovery
LongEM importer basketINDA, EWY, EWJOil shock reverses; currencies strengthen
LongConsumer discretionaryXLYGasoline falls; budget relief
LongAutos (EV particularly)CARZ, DRIVDemand recovery; EV substitution less needed
LongEM banksBroad EM financialsCredit risk recedes; GCC revenue recovers
LongDFM/ADX (UAE)UAE namesSecurity premium reverses; expat flows return
LongQatar ExchangeQatarEnergy-relatedLNG-revenue restart
ShortEnergy E&PXOPBrent falls $10–20; Morgan Stanley sees ~$94 near-term
ShortDefenseITA, DFENSpending urgency fades
ShortGold minersGDXSafe-haven premium reverses
ShortTanker equitiesFRO, NATVLCC rates normalize; longer routes unwind
Crypto spilloverLong BTC/ETHSpot/PerpetualsRisk-on; BTC +20–35% projected on ceasefire
Detail files
Global Equity Index Shock MapEquities
The defining bifurcation: macro-vulnerable indices fell while AI/tech insulated the US. S&P −8%→new ATH; STOXX/DAX energy-importer pain; Nikkei/KOSPI −3% sessions; MSCI EM −11%→+14.7%; TASI +5% vs DFM −16%; Ibovespa records.
high
Sp500
−8% (trough ~6,316 Mar 30) → >7,400 ATH
Msci em
−11% March → +14.7% April
Tasi
+5% March
Dfm
−16%
Ibovespa
record highs; BRL +10%
Equity Sector Winner/Loser MapSector Rotation
Clearest sector bifurcation since 2022. WINNERS: energy, defense/aerospace, tankers (FRO +62.6%), cybersecurity, gold miners (GDX +95%/12mo), non-Gulf LNG. LOSERS: airlines, petrochemicals, autos, consumer discretionary, EM importers. Energy/defense move in hours; airlines/petrochem lag by weeks.
high
Energy etf
BNO +84% Q1
Defense
ITA +18% YTD
Tankers
FRO +62.6%, NAT +63.2%
Gold miners
GDX +95% 12-mo
Airlines
jet fuel 25–30% opex
Earnings & Margin TransmissionEarnings
Oil shocks hit equities through margin compression, not re-rating. Lombard Odier: +5% oil → −2.2% US EPS over 12 months (−2.1% direct, −0.2% rates); +50% oil → ~−15% EPS. Jet fuel 25–30% of airline opex at $159.85/bbl; EIA distillate cracks $1.42/gal (highest since 2022); auto OEM margins 3.6%.
high
Lombard 5pct
−2.2% US EPS / 12mo
Lombard 50pct
~−15% S&P EPS
Jet fuel
$159.85/bbl (25–30% opex)
Crack spread
$1.42/gal
Oem margin
3.6% Q4'25
Equity Factor RotationFactors
Min-vol, quality and energy outperformed across regions; momentum, small-cap and high-beta were worst — the EM crowding factor fell >1% in two weeks (4-sigma) as crowded EM tech/AI unwound. The novel 2026 feature: an AI-insulation override (Mag-7 +17%, Micron +140%) acting as a circuit-breaker on the oil-shock bear.
high
Winners
min-vol, quality, energy (+2.98%/mo analog)
Losers
momentum, small-cap, high-beta
Em crowding
−1% in 2 weeks (4-sigma)
Ai override
Mag-7 +17%; Micron +140%
Country Equity Impact MapCountry
Outcomes set by oil position, Gulf exposure and index composition. Winners: Brazil, Saudi Arabia (oil exporters). Losers: India, Japan, S. Korea, Egypt, Pakistan (importers; rupee 94+). US mixed-positive on AI insulation; China/EU complex middle ground.
high
Winners
Brazil, Saudi
Losers
India, Japan, S.Korea, Egypt, Pakistan
Us
mixed-positive (AI buffer)
China
loser (5.4M bpd via Hormuz)
GCC Equity AsymmetryGCC
The sharpest internal divergence of any region: TASI +5% (Aramco 16% weight, 7M bpd Petroline bypass) vs DFM −16% (security/expat risk; ~$120bn cap loss) vs Qatar ~−4% (Ras Laffan force majeure, LNG −20%). Sovereigns win on oil fiscally; domestic equity sectors reprice security risk fast.
high
Tasi
+5% March
Dfm
−16% (~$120bn loss)
Qatar
~−4% (FM)
Petroline
7.0M bpd
Adcop
1.7–1.8M bpd
LNG loss
~120 bcm 2026–2030
Equity Market Plumbing & FlowsMarket Structure
Energy ETFs took >$2bn YTD, defense ~$467m, BNO +84% Q1; EM ETFs bled then recovered. VIX +57% in a week triggered risk-parity/vol-control deleveraging (−30–50% equity allocation), amplifying the sell-off. SPX skew inverted (upside bid); dollar–VIX flipped back positive. Crypto fell with equities then recovered (bridge to §10).
medium
Energy etf
>$2bn YTD
Defense etf
~$467m YTD
Vix
+57% in one week
Em crowding
4-sigma unwind
Uae domestic buy
AED 2.2bn floor
Equity Scenario Trade MapStrategy
Actionable long/short constructs per scenario. hormuz_closure: long energy/defense/tankers/cyber/gold-miners, short airlines/EM-importers/autos. oil_strike: long oilfield-services/repair. cable_severance: long cyber/satellite, short semis/EM-fintech. ceasefire: fade the conflict trade — long airlines/EM/autos, short energy/defense/gold/tankers.
medium
Hormuz
long energy/defense/tankers/cyber/gold
Oil strike
long oilfield services/repair
Cable
long cyber/satellite; short semis
Ceasefire
long airlines/EM; short energy/defense
Data quality

HIGH — Vol indices and S&P/MSCI EM levels (CNBC/MSCI/Forbes/Cboe); Lombard Odier earnings model; IATA jet-fuel; EIA crack spreads; Petroline/ADCOP capacity (Energy Connects/Argus); the historical precedent compendium (RBC/DataTrek/STOXX/St. Louis Fed). See the 23-item HIGH-confidence register.

MODERATE — Brent absolute prices [PROVISIONAL-2026, pending primary recheck]; Qatar/UAE LNG-loss figures (T2 citing T1-underlying); ETF flow magnitudes (Trackinsight/press-derived); regional-exchange levels without major-newswire close data.

Quarantined — CAC/TOPIX/CSI 300 exact levels, Pakistan KSE-100, Nifty trough, GCC daily ETF flows, OEM Q1'26 margins, vol-control AUM, Russia equity — all proxy/unavailable. See the 15-item Could-Not-Verify register.

Cadence discipline

Each module shows its own update clock — daily breadth, weekly positioning and structural episode tables are never visually equated. A weekly TFF print next to a daily VIX without cadence labels is a false-precision trap.

Glossary
ERP — Equity Risk Premium — equities’ excess return over the real risk-free yield; here earnings yield minus real yield.
CAPE — Cyclically-Adjusted P/E — price ÷ the 10-year average of inflation-adjusted earnings; smooths the cycle.
Breadth — How many stocks participate in a move — broad vs mega-cap-narrow.
Dispersion — How widely individual stock or sector returns scatter around the index.
Factor unwind — A crowded style factor (e.g. momentum) reversing as positioning is cut.
SMB — Small-minus-big — the Fama-French size factor; deeply negative in funding shocks as liquidity gets sold.
HML — High-minus-low — the Fama-French value factor; its crisis sign depends on whether financials/energy are the epicenter.
RMW — Robust-minus-weak — the Fama-French profitability (quality) factor; usually defends in funding stress, but went negative in March 2020.
GEX — Gamma exposure — an estimate of dealers’ option-hedging pressure; positive dampens moves, negative amplifies them. The level is model-dependent.
0DTE — Zero-days-to-expiry options — same-day expiry contracts, now roughly half of SPX options volume.
COT/TFF — CFTC’s weekly positioning reports — Dealer, Asset-Manager, Leveraged-Fund and Other categories, Friday for Tuesday’s book.
FRA-OIS — The spread between forward interbank lending and the risk-free overnight rate — the classic interbank funding-stress gauge.
Dash-for-cash — The March-2020 signature: investors sell even Treasuries to raise cash, and the stock-bond correlation flips positive.
PEAD — Post-earnings-announcement drift — returns keep drifting for weeks after earnings news; the market underreacts.
2s10s — The 10-year minus 2-year Treasury yield; negative = inverted curve, a classic recession lead.
OAS — Option-Adjusted Spread — a bond’s yield premium over Treasuries; wider = more credit stress.
NTM — Next-Twelve-Months — forward-looking consensus estimates for the coming year.
OVX — Cboe Crude Oil Volatility Index — the “oil VIX”; option-implied crude volatility.
VXEEM — Cboe Emerging-Markets ETF Volatility Index — EM equity implied volatility.
EMBI — Emerging Markets Bond Index spread — EM sovereign risk premium over Treasuries.
McClellan — A breadth oscillator built from the difference between advancing and declining issues.
Vol-control — Risk-parity / vol-control strategies cut exposure mechanically when volatility rises.
Credit VIX — Cboe/S&P’s VIXHY and VIXIG (Oct 2023) — implied volatility of credit-index spreads, the credit market’s own fear gauge.
Primary sources

Research and analysis only — no investment recommendations, price targets, or personalized advice. Scenario tilts are conditional framework priors. NAAIM states its index is not predictive; episode tables are computed from public Fama-French dailies and labeled by confidence; the business-cycle framework is a historical tendency, not a guarantee.

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