Here's Why Markets Are Wary of a Democratic Midterm Win

NextFin News - The S&P 500 has spent recent months grinding toward record highs on the back of an AI investment boom so large it is now priced into earnings forecasts, equity valuations and the American power grid itself. Yet as November's midterm elections approach, the scenario that once looked like the cleanest path to deregulation and deficit relief - a Republican sweep - is no longer the market's base case, and the alternative is giving portfolio managers a reason to pause. A Democratic takeover of Congress would not merely add oversight hearings and appropriations fights. It would put a political brake on the data-center build-out that has been the single largest growth engine of this market cycle.

That is the tension at the heart of the current market mood. Investors are being asked to believe two things at once: that AI capital spending can keep compounding for another year, and that a Washington likely to shift left can be trusted not to interrupt it. History says the party in power matters less than the earnings trend. The AI cycle says the earnings trend is already mature. Put them together and the risk is not a crash - it is a slower, more drawn-out de-rating of the stocks that have carried the index.

The Setup: Records, Yields, and a Maturing AI Cycle

The backdrop is unusually strong. The S&P 500 has topped 7,500, powered by a hyperscaler capital-spending wave that shows no sign of exhausting itself in the near term. Consensus estimates for the five largest AI infrastructure investors now sit above $527 billion for 2026, up from $465 billion at the start of the third-quarter earnings season. Third-quarter spending alone reached $106 billion, a 75 percent year-over-year increase, and analysts expect the growth rate to slow to 49 percent in the fourth quarter and to roughly 25 percent by the end of next year. Even that deceleration leaves an enormous absolute spend - and some strategists see as much as $200 billion of upside to current estimates if balance-sheet strength keeps the spending race going.

Yet the market is not celebrating early-cycle euphoria. Tatiana Darie, macro strategist for Markets Live, has been explicit that the AI trade is in its mature phase, not its infancy. "We're definitely not early," she said in a mid-October interview, pointing to analyst expectations that AI capital expenditure will peak this year and to AI investment as a share of GDP tracking its dot-com-era analog - a pattern that points to roughly one more year of capex growth before the curve bends. In her own words, investors can call her "tactically bullish, long term, a bit cautious."

Valuation support has improved even as yields have not. The S&P 500's price-to-earnings multiple has compressed to what Darie described as a "19 handle," the lowest since late 2023 with brief exceptions such as the March sell-off. In her reading, that compression means a modest Federal Reserve hiking cycle is already priced in, because earnings held up while multiples gave ground.

The bond market, meanwhile, has stopped being the villain - or at least become a more predictable one. The 10-year Treasury yield has sat above 5 percent, and equities have absorbed it.

Rate volatility upsets stocks, not the yields itself.

Why a Democratic Congress Changes the AI Calculus

The political risk is specific rather than diffuse. Progressive lawmakers have already put data-center restraint on the legislative agenda. In March, Senator Bernie Sanders and Representative Alexandria Ocasio-Cortez introduced the AI Data Center Moratorium Act, which would impose an immediate federal pause on new AI data centers until national safeguards are in place. "We cannot sit back and allow a handful of billionaire Big Tech oligarchs to make decisions that will reshape our economy, our democracy and the future of humanity," Sanders said at the announcement.

The bill is a progressive proposal, not leadership policy, and it is not law. But a Democratic majority in one or both chambers would give the party a platform it currently lacks, and the sentiment has already spread beyond the left flank. In Ohio, Democratic gubernatorial candidate Amy Acton has proposed a "conditional moratorium" on data centers. In Wisconsin, Democratic gubernatorial candidate Francesca Hong has called for a "full moratorium until we have the new regulations." At the federal level, Representative Jared Moran and Democrat Ted Lieu have introduced an AI Kill Switch Act that would require developers of the most powerful frontier models to be able to throttle, suspend, or shut down systems that threaten $100 million in economic damage or 10 deaths.

Public opinion gives these proposals room to move. A national poll of 1,000 registered voters conducted in late February and early March found that 57 percent agreed that "the risks outweigh the benefits of AI," while 33 percent said they trusted neither party to handle the technology. Only 19 percent favored Democrats and 20 percent favored Republicans. When more than half the electorate believes the risks outweigh the benefits, even modest regulatory proposals acquire political cover they would not otherwise have.

The transmission mechanism from politics to portfolios runs through capex, not ideology. Hyperscalers are expected to spend more than $1 trillion on AI-related capital expenditure from 2025 through 2026, according to the Bank for International Settlements, and a meaningful share of that spending is already outpacing earnings and free cash flow, forcing some companies to issue debt. The BIS flagged exactly this dynamic: investment commitments running ahead of the cash that funds them. That is the seam where politics can pry.

If a Democratic Congress slows permitting, tightens energy siting rules, or raises the political cost of new data-center construction, the first-order effect lands on the companies that have been selling the picks and shovels: chipmakers, data-center real estate investment trusts, power-equipment suppliers, and the utilities that priced in a decade of rising electricity demand. The second-order effect is more important for the index. AI-linked earnings deceleration would hit at the same time that valuation multiples have only just begun to recover, meaning the market could face a double squeeze - lower growth and a lower multiple - rather than the clean "earnings carry us higher" path it has enjoyed since the March lows.

There is also a power-grid dimension that makes the brake more binding than a simple sentiment story. Data centers are no longer just tenants; they are becoming the largest marginal source of electricity demand in several regions, and utilities have begun underwriting generation and transmission build-outs on the assumption that hyperscaler load keeps arriving. A permitting slowdown does not just defer a server hall - it strands the capacity built to serve it, turning an AI story into a utility-credit story. That channel is why the market's wariness is about duration, not direction.

The Counter-Argument: Midterms Are Usually Noise, Not Regime Change

The strongest case against reading too much into November is history itself. Since 1874, the S&P 500 has risen in 32 of the 38 years following midterm elections, gaining an average of 14 percent, according to an analysis of election-year stock market history. Data from a major US brokerage puts the 12-month post-midterm average return at 16.3 percent. The pattern holds regardless of which party won, how many seats changed hands, or who ended up in charge of Washington afterward.

Institutional research is similarly skeptical of election-driven regime shifts. A 2026 midterm note from Morgan Stanley Research argued that the final balance of power in Congress is likely to produce little change to the policies that matter most for markets. A divided government limits major legislation; it does not reverse established industrial trajectories. BlackRock reached a related conclusion from a different angle: scenarios in which one party lost control of the political trifecta saw material underperformance in the six months after midterms - 10.4 percent - compared with 16.1 percent when control was gained or Congress remained divided. The market rallies either way; it just rallies slower when the expected ability to pass legislation gets repriced.

There is also a meaningful gap between the progressive wing and the Democratic leadership. House Minority Leader Hakeem Jeffries, in creating the House Democratic Commission on AI and the Innovation Economy, called for a balance between allowing AI companies to "continue to thrive" while preventing "bad actors from exploiting this transformative technology and inflicting harm." That is the language of oversight and guardrails, not of a construction freeze. The party that would hold gavels has signaled regulation, not prohibition.

Prediction markets, for what they are worth, have moved sharply toward Democrats. Polymarket has priced a Democratic sweep of both chambers at roughly 62 percent, with the party favored at about 91 percent to win the House. If the market truly feared a Democratic victory, that fear should already be visible in the odds and in equity positioning. To a degree, it is not - which is precisely why the wariness shows up as caution rather than capitulation.

The Verdict: A Cyclical Peak, Not a Structural Break

The right way to frame this is not as a structural break in the AI revolution but as a cyclical peak arriving on schedule - with politics potentially pulling it forward. Darie's own framework supports this. She has said AI capital expenditure is expected to peak this year, that the cycle has roughly one year of growth left, and that her red flag would be a hyperscaler such as Meta or Oracle guiding spending below expectations.

Earnings is your North Star.

A Democratic brake on data centers would not end AI investment. It would compress the window in which that investment can grow at the rates the market has underwritten. The asymmetry is clear: the upside case - capex continuing to compound at 25 percent or more through 2026 - is already priced in. The downside case - permitting delays, state-level moratoria, and a political narrative that makes data centers toxic - requires only a slowdown to disappoint. In a mature cycle, disappointment is priced faster than surprise.

The bond market adds a twist. If slower growth is read as disinflationary, Treasury yields could fall and give multiples room to expand. If it is read as a growth shock, credit spreads would widen first. Darie has already flagged the tripwire: CCC-rated bonds and leveraged loans are at distress levels typically seen in recessions or slowdowns, even as the economy continues to expand.

It quickly morphs from a rate risk into a growth risk.

Who benefits and who is exposed follows from the mechanism. The exposed are the AI supply chain and the capital-intensive names that priced in uninterrupted load growth: semiconductors, data-center REITs, electrical-equipment makers, and merchant generators. The potential beneficiaries are the laggards that a slower AI cycle would make relatively more attractive - healthcare, which Darie sees as a diversifier with earnings trends improving into 2027, and energy, which has posted more than 100 percent earnings growth and trades at roughly 13 times earnings, the lowest multiple in the S&P 500. Technology itself, despite its run, trades at a discount to the broader market on a forward basis, with consumer staples at 21 times forward earnings - a valuation gap that only makes sense if investors still expect AI earnings to deliver.

What to Watch

The falsifying signal is concrete. If the five largest hyperscalers guide 2027 capital expenditure to grow less than 5 percent year over year while a Democratic Congress is seated, the policy-brake thesis is confirmed. If combined capex keeps growing above 20 percent year over year under Democratic control, the thesis is wrong - the build-out is too profitable and too entrenched for politics to slow it. Either way, the number is observable, and it will arrive with fourth-quarter earnings.

Near-term, the October Federal Open Market Committee meeting matters for the rate-volatility channel. Darie does not expect a full tightening cycle and has noted that Fed speakers have pushed back on back-to-back hikes. A steady 10-year yield around 5 percent is survivable for equities; a volatile one is not. The election and the Fed are separate stories, but they converge on the same question: how much uncertainty can a mature valuation tolerate?

Outlook: Three Scenarios for the Post-Midterm Market

Base case - divided or narrow Democratic control, capex slows but does not stall. The S&P 500 grinds higher on earnings but with narrower leadership and lower multiples for AI-exposed names. Post-midterm seasonality - historically strong - does part of the work, and the index sets a new high on thinner breadth.

Upside case - gridlock prevails. No major AI legislation passes, hyperscaler spending stays on track, and the market rallies into year-end on the combination of falling rate volatility and resilient earnings. This is the scenario in which the "noise, not change" view is vindicated and the AI complex reclaims its leadership.

Downside case - a Democratic sweep plus a capex miss. Permitting fights slow the build-out at the same time that Meta or Oracle guides spending lower. Earnings revisions turn negative, credit spreads widen, and the index gives back a meaningful portion of its record-setting gains. This is the scenario the current positioning is not underwriting.

The short-term read is sentiment-driven and vulnerable to headlines. The medium-term read depends on whether earnings can grow into the valuations that a mature cycle has already been handed. The long-term read is structural and largely unchanged: AI remains a transformative technology, and regulatory friction is a tax on its diffusion, not a repeal of it.

The market is not pricing a Democratic apocalypse. It is pricing something subtler and more plausible: a slower AI cycle, arriving right on schedule, with Washington holding the brake.

Explore more exclusive insights at nextfin.ai.