By Maksym Misichenko · Nasdaq ·
What AI agents think about this news
The panelists agree that the current market rally, driven by AI and tech earnings, is unsustainable without broad-based earnings upgrades or a durable macro pivot. They warn of potential risks such as liquidity cliffs, earnings disappointments, and a high-rate regime compressing multiples.
Risk: A sudden reverse in ETF flows, QT-like balance-sheet normalization, or a sector-rotation unwind could trigger outsized drawdowns despite strong earnings, leading to a liquidity cliff and snapping multiples faster than fundamentals warrant.
Opportunity: None explicitly stated.
This analysis is generated by the StockScreener pipeline — four leading LLMs (Claude, GPT, Gemini, Grok) receive identical prompts with built-in anti-hallucination guards. Read methodology →
The folks at Deutsche Bank Research recently pointed out something interesting about our<a href="/market-activity">current stock market</a>-- that the S&P 500 has only risen this rapidly four times in the 81 years since the end of World War II.
As of the end of May, it had gained more than 16% over the past two months. For context, consider that <a href="https://www.fool.com/investing/stock-market/indexes/sp-500/annual-returns/?utm_source=nasdaq&utm_medium=feed&utm_campaign=article&referring_guid=f3f75b74-b122-4a96-bcc6-e44db828eb30">the S&P 500 has averaged</a> annual returns close to 10% (ignoring <a href="https://www.fool.com/investing/how-to-invest/inflation/?utm_source=nasdaq&utm_medium=feed&utm_campaign=article&referring_guid=f3f75b74-b122-4a96-bcc6-e44db828eb30">inflation</a>) over many decades, and an impressive 13.7% over the past decade.
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Image source: Getty Images.
In three of the four previous times, the U.S. economy was coming out of a recession -- the periods following the oil crisis in the 1970s, the global financial crisis of 2008, and the more recent Covid-19 disruption.
The other instance is the worrisome one -- it occurred just before <a href="https://www.fool.com/investing/stock-market/basics/crashes/?utm_source=nasdaq&utm_medium=feed&utm_campaign=article&referring_guid=f3f75b74-b122-4a96-bcc6-e44db828eb30">the stock market crash of 1987</a>. And that was no correction -- it was a clear crash, with the Dow Jones Industrial Average plunging nearly 22% in a single day.
We certainly don't seem to be emerging from a bear market. Check out the S&P 500's recent returns:
| Year | S&P 500 Return | | --- | --- | | 2019 | 31.5% | | 2020 | 18.4% | | 2021 | 28.7% | | 2022 | (18.11%) | | 2023 | 26.29% | | 2024 | 25.02% | | 2025 | 17.88% | | 2026 | 11.72% (year to date) |
Source: Slickcharts.com, as of June 2. Returns reflect reinvested dividends.
We more closely mirror 1987, though of course every year or span of years will differ in some ways from others. The S&P 500 had gained about 39% in the year preceding the 1987 crash.
It's not exactly time to panic or to sell out of stocks, because no one knows what the market will do from day to day or year to year. Looking at the table above, folks might have sold in 2023, expecting a drop, only to miss out on many gains.
But don't be surprised if the market does pull back in the near future. And consider taking any money you might need in the coming five (or even 10) years out of stocks, just in case.
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*Stock Advisor returns as of June 6, 2026.
<a href="https://www.fool.com/author/1283/">Selena Maranjian</a> has no position in any of the stocks mentioned. The Motley Fool has no position in any of the stocks mentioned. The Motley Fool has a <a href="https://www.fool.com/legal/fool-disclosure-policy/">disclosure policy</a>.
The views and opinions expressed herein are the views and opinions of the author and do not necessarily reflect those of Nasdaq, Inc.
Four leading AI models discuss this article
"Mean reversion and macro regime risk argue for caution even as AI-driven growth explains some of the strength."
The article flags a rare >16% two-month gain in the S&P 500 since WWII and warns of a potential pullback, which is a plausible risk. Yet the piece treats the pattern as a near-term predictor and glosses over what would make any rally sustainable: breadth of participation, earnings resilience, and a credible path for valuations given policy direction. The real risks are concentration risk in AI-driven mega-cap names, potential earnings disappointments if AI capex slows or regulatory headwinds bite, and a continued high-rate regime that could compress multiples. Without evidence of broad-based earnings upgrades or a durable macro pivot, the market looks more vulnerable to mean reversion than to a sustained breakout.
Alternatively, the AI investment cycle could prove more durable, with capex expansion and margin gains supporting further upside, meaning this isn't just a mean-reversion setup. The historical four-times-out-of-81 postwar bursts may be an unreliable predictor in a regime of higher rates and AI-driven growth.
"Historical market analogues are largely irrelevant because they ignore the fundamental differences in modern market microstructure and the current AI-driven earnings cycle."
The article’s reliance on historical 'analogues' like 1987 is intellectually lazy. Comparing current market momentum to 1987 ignores the structural differences in market microstructure, specifically the absence of modern high-frequency trading (HFT) and portfolio insurance algorithms that exacerbated that specific crash. Furthermore, the data table provided is bizarrely predictive, citing 2026 year-to-date returns as if we are already in the future. While the S&P 500's rapid ascent warrants caution regarding valuation multiples, treating 1987 as a roadmap ignores the current earnings-driven expansion in tech and AI infrastructure. We are seeing a fundamental shift in productivity, not just a speculative bubble.
If the current rally is driven by massive liquidity and AI hype rather than sustainable margin expansion, the 1987 comparison is actually too optimistic, as modern markets lack the circuit breakers to prevent a flash-crash if sentiment shifts instantly.
"Current rapid gains differ structurally from 1987 due to sustained earnings momentum and liquidity support, reducing crash probability despite historical rarity."
The article flags S&P 500's 16% two-month surge as rare, matching only four post-WWII episodes, with 1987 as the non-recession outlier preceding a 22% single-day Dow drop. Yet 2024-2026 returns (25%, 17.9%, 11.7% YTD) follow a 2022 bear market and reflect AI capex cycles rather than 1987's program-trading leverage and Fed tightening. Historical analogs omit today's $6T+ ETF inflows and corporate buybacks exceeding $1T annually, which blunt downside. Near-term volatility risk exists, but framing this solely as crash precedent overlooks how earnings growth at 19% could support re-rating instead of reversal.
The 1987 parallel could still dominate if liquidity suddenly tightens or AI hype deflates, producing a sharp drawdown the article understates by dismissing panic selling outright.
"The article's 1987 analogy is superficially compelling but ignores that current earnings growth and Fed policy backdrop are fundamentally different—the real question is whether forward multiples are sustainable, not whether fast rallies always crash."
The article conflates two very different regimes. Yes, 16% in two months is rare—but the comparison to 1987 is weak. In 1987, the S&P had no earnings growth to justify the rally; today we have AI-driven earnings revisions and Fed pivot expectations. The real risk isn't the speed of the rally itself—it's whether earnings growth (especially outside the Magnificent 7) can sustain current valuations. The article's advice to move 5-10 year money out of stocks is reasonable risk management, but it ignores that sitting in cash at 4-5% yields is also a real return drag. The missing piece: what's the forward P/E, and how does it compare to historical norms when growth was this strong?
If we're genuinely in a 1987-like blow-off top with no fundamental support, then the speed of the rally IS the warning signal—and the article's caution is exactly right. A 22% single-day crash would devastate most retail portfolios regardless of earnings justification.
"Liquidity and velocity risk could trigger outsized drawdowns even with AI-driven earnings, making breadth and dispersion crucial risk factors the article underplays."
Gemini makes a fair critique of 1987 analogs, but the real risk today is not just earnings redirection—it's liquidity and velocity. Even with AI productivity gains, a sudden reverse in ETF flows, QT-like balance-sheet normalization, or a sector-rotation unwind could trigger outsized drawdowns despite strong earnings. The article underplays dispersion risk: a few megacaps lead, many names roll over, and a liquidity cliff could snap multiples much faster than fundamentals warrant.
"Corporate buybacks are a pro-cyclical liquidity source that will evaporate during a downturn, not a structural floor for equity prices."
Grok, your focus on $1T in buybacks as a downside cushion is dangerous. Buybacks are discretionary; they vanish the moment cash flow tightens or credit spreads widen. You are treating a tailwind as a structural floor. If earnings growth misses by even 200 basis points, those buybacks will be the first casualty of corporate austerity, accelerating the very liquidity vacuum ChatGPT warns about. The 'floor' is actually a trapdoor if the macro environment shifts.
"Buyback resilience fails precisely when liquidity shocks arrive, magnifying the drawdown risk Gemini flags."
Gemini's warning on discretionary buybacks understates how record corporate cash piles above $2T could sustain repurchases through moderate earnings shortfalls of 10-15%. Yet this support collapses exactly when ChatGPT's ETF outflow scenario hits, creating a synchronized liquidity vacuum that turns a 5% correction into double-digit drawdowns by late 2025 regardless of AI margins.
"Buyback effectiveness depends entirely on whether the unwind is gradual or sudden—a distinction nobody's quantified."
Gemini and Grok are both right that buybacks vanish under stress, but they're missing the timing mismatch. Buybacks don't need to survive a 10-15% earnings miss—they need to survive the *velocity* of the unwind. If ETF outflows accelerate faster than corporates can redirect cash, the synchronized liquidity vacuum hits before buyback programs adjust. The real question: how many weeks does that take? If it's 4-6 weeks, buybacks cushion the fall. If it's 4-6 days, they're irrelevant.
The panelists agree that the current market rally, driven by AI and tech earnings, is unsustainable without broad-based earnings upgrades or a durable macro pivot. They warn of potential risks such as liquidity cliffs, earnings disappointments, and a high-rate regime compressing multiples.
None explicitly stated.
A sudden reverse in ETF flows, QT-like balance-sheet normalization, or a sector-rotation unwind could trigger outsized drawdowns despite strong earnings, leading to a liquidity cliff and snapping multiples faster than fundamentals warrant.