AXIOMA ROOF™ SCORE HIGHLIGHTS

The United States went into the Iran war hoping to destabilize the leadership in Tehran and bring about regime change. Instead, the midterms delivered something rather closer to regime change at home. It is difficult to imagine a more spectacular own goal.

In the weeks leading up to the midterms, investor sentiment had been bracing for the worst across virtually every major market, with one notable exception: the United States, where sentiment remained neutral right up to the vote. The conventional wisdom is that a divided government – a White House controlled by one party and Congress by another – is generally good for markets, as it provides a degree of restraint on executive power and helps contain policy risk.

Popular memory may be short, but it is nothing compared with the amnesia of experts. Investors initially welcomed the prospect of a divided government, as they have historically tended to do, as the prospect of a Democratic Congress restraining the White House was initially seen as a positive for markets. But the enthusiasm proved short-lived and investors were quick to remember that not all divided governments are created equal, and that the historical reassurance of a divided government may not translate so neatly to a MAGA White House facing a Congress swept into office on a historic Blue wave.

But there is a difference between pricing the uncertainty of an election and pricing the uncertainty of what comes after it. The voting decision has been made; now comes the policy implementation. And here, the simple fact is that no one knows how a newly empowered Democratic Congress will work with a MAGA White House. What might ordinarily be regarded as a useful system of checks and balances could quickly turn into something closer to political paralysis. A divided government may neutralize policy risk; a dysfunctional one can amplify it (see scenarios 4a, 4b, and 4c in our “Stress Testing the Midterm Elections” piece here).

And if anyone was expecting Trump to read the election results as a signal to moderate, his response suggests otherwise. He has already announced his post-election transformation into "Mr Veto" – perhaps the next minor Marvel villain – and has apparently already recruited his faithful sidekick in Stephen Miller. The administration, it seems, is preparing for a political siege rather than for compromise.

That is particularly uncomfortable for investors given that the one trade on which they have placed their biggest bets – the AI build-out – is perhaps the one most dependent on a functioning government. Before AI can become a technology story, it first has to succeed as an infrastructure story. Land must be secured, permits granted, power sources developed, electricity grids expanded, and data centers built. None of this happens simply because Hyperscalers are willing to write cheques. It requires planning, approvals, and, crucially, cooperation between state and federal governments. And ultimately, it requires confidence that the money being committed today will generate returns tomorrow. 

From Taipei to Hong Kong, Shenzhen, Seoul and Tokyo, from Amsterdam to Toronto, investors across the global AI supply chain – a belt that circles the world, with New York as its buckle – were quick to reprice these assets, demanding a substantially higher risk premium for the uncertainty that came with the election results.

A month ago, investor sentiment was neutral in seven of the ten markets we track, negative in two and positive in only one: Australia. Today, investors are bearish in seven and negative in two, with Australian investors remaining the sole positive exception (see Regime Distribution chart below). 

For the past two years, investors have surfed the waves of the AI trade, from crest to trough and back again. But the funny thing is that, no matter how often they ride the wave, they never seem to notice that it's wet.

Aggregate ROOF Trend: The black line is the aggregate mean of ROOF scores across the ten markets; the shaded grey band shows the range from the most bearish to the most bullish market on each day, indicating the dispersion of sentiment across the universe. Reading it: a rising line indicates increasing risk tolerance; a declining line indicates increasing risk aversion. 

Bottom strip: cross-market dispersion percentile — the cross-sectional standard deviation of ROOF across the ten markets, percentile-ranked against its own full history. Shaded zones mark elevated (>80th percentile) and compressed (<20th) readings. Reading it: a spike into the top shaded zone is a material divergence episode (sentiment moving in different directions across markets), a slide into the bottom shaded zone is a material convergence episode on a common driver (sentiment moving in the same direction across markets).

Regime Distribution: Three horizontal stacked bars show how the ten markets are distributed across the five regimes — today, one week ago, and one month ago. Each bar is colored by regime: red (Bearish), yellow (Negative), grey (Neutral), blue (Positive), green (Bullish). The white vertical marker on each bar shows the aggregate ROOF score for that period. Tick marks below the bars align with the regime thresholds at ±0.20 and ±0.50. Reading it: a leftward shift over time indicates broadening deterioration; a rightward shift indicates broadening improvement. Widening tails signal rising dispersion.

Market Monitor: A table showing, for each market: current ROOF score, current regime, weekly and monthly changes, regime one month ago, and distance to the nearest extreme threshold. Color cues highlight regime deteriorations (red) and improvements (green). Reading it: scan the "1M Ago Regime" column for markets that have crossed regime bands over the past month; check the "Distance" column to find markets close to the ±0.50 extreme thresholds.

Correlation Matrix (Δ1M): A heatmap of correlations between monthly sentiment changes across all market pairs, over a rolling 60-day window. Green cells indicate that investor sentiment in the two markets changed in the same direction; red cells indicate opposite directions. The rightmost column shows each market's average correlation with the rest of the universe. Important: these are correlations of sentiment changes, not market returns or ROOF levels. High correlation means investor mood in the two markets moved in sync over the past 60 days.