Today was the first real “air pocket” of November. All the major US indexes finished in the red, with the Dow off roughly half a percent, the S&P 500 down a bit more than one percent, and the Nasdaq sliding about two percent as traders finally pushed back against the AI melt-up. The selling lined up with the news tape: headlines framed the session as a broad de-risking on stretched valuations, with AI leaders and high-beta tech taking the hardest hit while bitcoin briefly fell below 100,000 and risk appetite cooled across assets.

Earnings gave the day its texture. Palantir and Uber had both reported strong third-quarter numbers but traded lower as investors focused on how much future growth was already priced in. Uber posted a huge jump in net income, helped by a one-off tax benefit, and continued to show solid growth in trips and bookings, yet the stock faded into the close. Pfizer, by contrast, managed to rally at points after beating on earnings and raising its full-year profit outlook, even while it juggled a revenue decline and an increasingly messy obesity-drug bidding war.

By the bell, the message from the tape was pretty simple. This was not a macro panic or a liquidity event, it was a repricing of “how much AI and growth we want to pay for” after a very fast run. The shutdown-skewed data backdrop means nobody is sure where the real economy sits, so traders chose the one lever they control in real time, which is how much risk they are willing to carry in the most crowded trades on the board.

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This article from Morningstar takes a clear-eyed look at a popular myth: that growth stocks are the only way to riches. The article argues that while growth names certainly dominate headlines, they are not a reliable stand-alone path to strategy success. With valuations stretched and leadership narrowly concentrated, the broader market is signalling that diversification, not devotion, is the smarter play.

The piece points out that growth sectors have delivered remarkable returns, but at the cost of high risk and limited breadth. Over the past decade, many investors forgot that value, income, and smaller-cap segments also contribute to portfolio resilience. Now, with AI hype baked in and capex heavy, the margin for error is thinner. The emphasis shifts from “which growth story will win” to “which growth story can sustain.”

For traders and long-term investors alike, the takeaway is subtle but actionable: don’t outsource your portfolio to the handful of mega-caps. Stay exposed to growth, yes, but make room for rotation-ready value plays, international exposure, and quality cyclicals that can act as ballast when the next leg of market leadership evolves. The road to riches may still include growth, but it won’t be paved by it alone.

On this recent Odd Lots, Hudson River Trading’s head of AI research, Iain Dunning, takes listeners inside how the firm uses artificial intelligence not just to speed up execution, but to generate ultra-short-term price predictions that edging past classical algorithmic methods.

Dunning explains that the margin for error in high-frequency markets demands models that learn in real time, ingest global micro-data and adapt to structural shifts like filings, natural-language signals and even power-grid anomalies. He emphasises that the constraints aren’t just math—they’re labour (researchers), compute (chips) and latency (microseconds)—and argues that the “AI” used in trading is often closer to advanced engineering than the large language-models driving the buzz.

For investors and traders the key takeaway is not “buy the firm that beats with AI” but “recognise the risk-curve is changing.” If one player tightens its latency and information edge, entire market microstructure flows shift. Even if all of this feels rather too nuanced, it’s a fascinating look at the guts of the market’s algorithmic machinery.

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Tomorrow the market gets its first real look at the economy after today’s reset. The morning features ADP employment and ISM services for October, two private and survey-based reads that have become stand-ins while official releases are delayed by the government shutdown. A softer ADP print or a dip in services activity would quickly revive talk of additional Fed cuts, while anything resilient would validate Powell’s recent “no promises on more easing” message and keep yields underpinned.

On the earnings side, the spotlight tilts from software toward chips and consumer goods. Qualcomm reports after the close, and the street is treating it as a verdict on the next leg of the AI hardware trade, especially at the edge and on devices rather than in data centers. Expectations call for another solid quarter and upbeat commentary on on-device AI, which means the bar is not low. A clean beat and confident guide could help repair some of today’s tech damage, while a wobble would confirm that investors have become much more selective about which AI stories they are willing to fund.

In short, Wednesday is set up as a tone check rather than a binary event. If the data look “good enough” and Qualcomm reassures, today’s selloff can be framed as a healthy shakeout. If the numbers or guidance disappoint, traders will head into the back half of the week treating last month’s highs as a ceiling rather than a floor.