The S&P 500’s cap-weighted “parent” once again kept investors on their toes, navigating another bout of volatility as markets digested Google’s earnings release. Its equal-weighted “cousin,” meanwhile, continues to offer a reassuring counterpoint, suggesting that the market’s advance is gaining traction beyond its largest constituents. Sowell’s technical indicators remain cautiously favorable, reinforcing our disciplined, cautiously optimistic, and fully invested stance. While the market continues to test our patience, the fundamentals has not yet tested our conviction other than to adjust our sideview mirrors.
Artificial intelligence has developed an enormous appetite. This week, investors got a reminder that even extraordinary growth may not be enough to satisfy it. Record cloud demand is colliding with enormous infrastructure bills, while frontier-model developers must keep financing the next breakthrough. Two days of punishing technology selloffs brought the question into focus: when does the AI boom start paying for itself?
The Weekly Scoreboard
The S&P 500 fell 0.6% for the week, the Nasdaq lost 2.0%, and the Dow declined 0.9%, while the Russell 2000 gained 1.3%. Friday was especially brutal: the Nasdaq dropped 2.9% and the S&P 500 slid 1.8%.
The selling was not initially market-wide. On Thursday, more than 400 S&P 500 companies across 9 sectors advanced even as the capitalization-weighted index fell. The equal-weight S&P 500 ETF (RSP) gained roughly 0.8% for the week, but Friday's semiconductor rout showed how weakness in crowded technology trades could spread. Communication Services had the biggest drawdown effect for the S&P 500 index declining 8.4% led by Google and Meta.
Treasury yields declined as investors sought safety, with the 10-year near 4.95%. Brent crude finished near $118 a barrel, while gold futures fell 3.3% Friday to $3,898.90 an ounce.
Strong Earnings, Stronger Doubts
Alphabet provided Thursday's spark. Its shares plunged 12.6%, erasing roughly $475 billion in market value, even as Google Cloud revenue doubled to $30.7 billion. Investors focused instead on slower Google Search advertising growth, concerns that AI search may monetize less effectively than traditional queries, and quarterly free cash flow of negative $9.1 billion. Alphabet's operating profit actually rose 30%. The selloff reflected worries about its future economics, instead of a collapse in current demand.
The pressure intensified after Thursday's earnings. Amazon reported 39% AWS growth, yet its trailing twelve-month free cash flow swung from positive $14.8 billion to negative $42.4 billion, mainly as AI infrastructure spending accelerated. It still expects roughly $220 billion in capital expenditures this year. Amazon did not suffer a Google-sized collapse, but its spending outlook reinforced the same question: how much cash must be reinvested to maintain growth?
Intel delivered a different shock. Its shares sank 28.6% Friday after a weak fourth-quarter forecast and warnings that PC demand could remain soft into 2027. Its data-center business grew rapidly, but manufacturing costs, supply constraints, and expensive memory weighed on the outlook. The damage spread to chipmakers: AMD fell 10.9%, Nvidia 4.2%, and the semiconductor index 7.2%.
These were distinct disappointments, not proof that AI demand has vanished. Together, however, they pushed investors to reconsider valuations built on the assumption that AI investment would translate quickly into attractive returns.
The Race Behind the Bill
Even the huge data-center bills tell only part of the story. Anthropic's newly filed SEC prospectus reported $9.74 billion of research and development spending in the first half of 2026, versus $2.38 billion in direct costs to serve paying customers. R&D encompasses experimentation, personnel, training and other internal computing; it is not synonymous with training costs alone.
The distinction matters. Serving today's users may become cheaper as inference improves, while competing with tomorrow's models can demand another round of costly research. OpenAI, Anthropic, Google and their rivals face pressure to keep raising the performance bar. Nobody knows how many more rounds of capital-intensive competition will precede a more predictable, profitable industry structure.
Growth and the Fed
According to the Bureau of Economic Analysis, third-quarter GDP expanded at a 3.4% annualized rate, supported by investment. September PCE inflation was 3.6% year over year, with core inflation at 3.1%. The Federal Reserve held rates at 3.75%–4.00% in a 10–2 decision; both dissenters favored a hike. AI investment is supporting growth, but high financing costs make the eventual returns even more important.
The Week Ahead
Tuesday brings the midterm elections and JOLTS job openings; Friday's October employment report will test the Fed's assessment of the labor market. AMD reports Tuesday and Arm Wednesday, offering another test of demand after the chip selloff.
AI is already a business, not merely a promise. What investors still cannot price with confidence is how long companies must keep paying for the next leap forward before today's investments generate durable returns.
“We're installing an AI accelerator about every 14 seconds, and almost as fast as we install capacity, customers are gobbling it up.”
—Andy Jassy, President and CEO of Amazon, October 29, 2026
Perspectives by Phillip Wool, Ph.D.
How Is Your Portfolio Exposed to the “AI Trade”?
“So, we were sitting there at the end of last year basically saying, ‘We haven't seen the models yet... we're gonna write this check for, I don't know, $100 billion or $200 billion.’ And I’m looking across the table like, ‘Alex, are you sure this is gonna work?’”
—Mark Zuckerberg, Meta Platforms CEO, describing a conversation with Meta’s Chief AI Officer, Alexandr Wang, about Meta’s enormous infrastructure capex
Back in October, Meta founder and CEO Mark Zuckerberg brought his Chief AI Officer, Alexandr Wang, along for a visit to the pub with Stripe co-founder John Collison, who routinely hosts tech luminaries on his popular Cheeky Pint podcast. Clips of the sit-down went viral, centering on the Meta CEO’s anguished facial expressions as he attempted to “enjoy” his first glass of Guinness. We were more struck by Zuckerberg’s account of the company’s massive AI infrastructure investments, which were made, the pair revealed, on the basis of little more than a “vibe report” from Wang. It’s not the first time Zuckerberg has thrown big numbers around: On the Access podcast with Alex Heath and Ellis Hamburger last year, he suggested that “If we end up misspending a couple of hundred billion dollars, I think that that is going to be very unfortunate, obviously... But what I'd say is I actually think the risk is higher on the other side.”
If you hear the ring of “FOMO” in Zuck’s description of his firm’s capital budgeting discipline, you’re not alone, and we imagine many US stock investors have likewise thrown caution to the wind in the interest of not being “left behind” by the AI revolution. The good news for such investors is that AI momentum has so far handsomely rewarded a FOMO-based investment policy, leading to eye-popping returns for what’s seemed like an increasingly crowded trade. Only recently have stocks in the theme begun experiencing the kind of volatility that raises questions as to whether the AI stock gravy train keeps rolling from here or goes spectacularly off the rails.
Whether that question should concern an equity investor or not could depend on where, exactly, that investor is allocated within the AI space. Even though we often talk about “the AI trade”, as though there’s only one way to play this theme, a peek into most thematic AI portfolios yields a range of ways equity investors actually get exposure to this technological transformation. As the figure below illustrates, how one’s AI investments have performed can also vary substantially based on the nature of those investments.
Year to Date stock returns differ by source of exposure to the "AI Trade"
Take chipmakers, for example, which have been the best performers associated with the AI boom, and which many observers likely consider the clearest embodiment of the AI hardware theme. Stocks in this industry, including Nvidia, Broadcom, and AMD—purveyors of the proverbial ‘picks and shovels’ powering AI model-builders—make up the Bank of America “AI Compute” Index, and have returned around 80% year-to-date. In fact, the AI chipmaker basket was up much more, roughly 120% YTD, back around the middle of summer, before that aforementioned volatility prompted a pullback.
That second-half AI angst was more painful for another set of stocks in the AI hardware space, the so-called “neo-cloud” providers loading up on debt to build datacenters they rent to hyperscalers like Meta and Alphabet. As bond yields have surged, so have doubts these companies will survive, squeezed between an increasing cost of capital and burgeoning skepticism over both competition in the space and the sustainability of demand for the infrastructure they’re investing so much to expand. Drawdowns like these—from up 80% to 20% in the hole, in just a matter of months—are a reminder that the higher valuations climb, the farther they have to fall when sentiment turns.
Along those lines, companies the market perceives as having a lot to lose as AI applications take root—in other words, the “shorts” of the AI trade, including enterprise software-as-a-service providers, like Adobe, Salesforce, and ServiceNow—had struggled mightily in the first half of the year. Names tracked in Goldman Sachs’ AI “At Risk” Index, for instance, had fallen by over 20% by the end of Q1. That same basket of stocks, arguably oversold after month upon month of doomsday headlines, has staged a big comeback over the last few months as investors reevaluated those overly SaaSpocalyptic visions, bouncing to a 20% year-to-date gain near the end of October.
If hardware stocks sitting on massive gains and increasingly lofty expectations are most exposed to a reversal in AI sentiment and software stocks have already begun to rebound, where might investors search for the next set of opportunities—or, at the very least, a tech ‘safe haven’ to weather setbacks in the AI theme? Hyperscalers could merit a look. Investors’ ambivalence toward big capex outlays has kept these stocks’ valuations in check, and diversified businesses throwing off loads of cash do tend to provide a buffer when the mood goes to ‘risk off’. Companies in the “AI adopters” category, which benefit most from applying AI to reduce costs and boost profitability, have also seen much more muted performance thus far and could provide another good pool of prospects for stock-pickers who view the “AI trade” as encompassing more than just hardware.
Disclosure: This material is for informational purposes only and should not be considered investment advice. An investor should consult with their financial professional before making any investment decisions. The opinions contained herein are subject to change without notice and do not necessarily reflect the opinions of Rayliant Investment Research. Indices cannot be invested in directly and are unmanaged. Past performance is not indicative of future results.
Advisory services offered through Sowell Management, a Registered Investment Advisor. The views expressed represent the opinion of Sowell Management. The views are subject to change and are not intended as a forecast or guarantee of future results. This material is for informational purposes only. It does not constitute investment advice and is not intended as an endorsement of any specific investment. Stated information is derived from proprietary and non-proprietary sources that have not been independently verified for accuracy or completeness. While Sowell Management believes the information to be accurate and reliable, we do not claim or have responsibility for its completeness, accuracy, or reliability. Statements of future expectations, estimates, projections, and other forward-looking statements are based on available information and Sowell Management’s view as of the time of these statements. Accordingly, such statements are inherently speculative as they are based on assumptions that may involve known and unknown risks and uncertainties. Actual results, performance or events may differ materially from those expressed or implied in such statements. Investing in securities involves risks, including the potential loss of principal. While equities may offer the potential for greater long-term growth than most debt securities, they generally have higher volatility. International investments may involve risk of capital loss from unfavorable fluctuation in currency values, from differences in generally accepted accounting principles, or from economic or political instability in other nations. Past performance is not indicative of future results.
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WEEK AHEAD
November 2-6, 2026
The S&P 500’s cap-weighted “parent” once again kept investors on their toes, navigating another bout of volatility as markets digested Google’s earnings release. Its equal-weighted “cousin,” meanwhile, continues to offer a reassuring counterpoint, suggesting that the market’s advance is gaining traction beyond its largest constituents. Sowell’s technical indicators remain cautiously favorable, reinforcing our disciplined, cautiously optimistic, and fully invested stance. While the market continues to test our patience, the fundamentals has not yet tested our conviction other than to adjust our sideview mirrors.
Weekly Market Commentary:
Can We Afford to Feed the AI Beast?
Artificial intelligence has developed an enormous appetite. This week, investors got a reminder that even extraordinary growth may not be enough to satisfy it. Record cloud demand is colliding with enormous infrastructure bills, while frontier-model developers must keep financing the next breakthrough. Two days of punishing technology selloffs brought the question into focus: when does the AI boom start paying for itself?
The Weekly Scoreboard
The S&P 500 fell 0.6% for the week, the Nasdaq lost 2.0%, and the Dow declined 0.9%, while the Russell 2000 gained 1.3%. Friday was especially brutal: the Nasdaq dropped 2.9% and the S&P 500 slid 1.8%.
The selling was not initially market-wide. On Thursday, more than 400 S&P 500 companies across 9 sectors advanced even as the capitalization-weighted index fell. The equal-weight S&P 500 ETF (RSP) gained roughly 0.8% for the week, but Friday's semiconductor rout showed how weakness in crowded technology trades could spread. Communication Services had the biggest drawdown effect for the S&P 500 index declining 8.4% led by Google and Meta.
Treasury yields declined as investors sought safety, with the 10-year near 4.95%. Brent crude finished near $118 a barrel, while gold futures fell 3.3% Friday to $3,898.90 an ounce.
Strong Earnings, Stronger Doubts
Alphabet provided Thursday's spark. Its shares plunged 12.6%, erasing roughly $475 billion in market value, even as Google Cloud revenue doubled to $30.7 billion. Investors focused instead on slower Google Search advertising growth, concerns that AI search may monetize less effectively than traditional queries, and quarterly free cash flow of negative $9.1 billion. Alphabet's operating profit actually rose 30%. The selloff reflected worries about its future economics, instead of a collapse in current demand.
The pressure intensified after Thursday's earnings. Amazon reported 39% AWS growth, yet its trailing twelve-month free cash flow swung from positive $14.8 billion to negative $42.4 billion, mainly as AI infrastructure spending accelerated. It still expects roughly $220 billion in capital expenditures this year. Amazon did not suffer a Google-sized collapse, but its spending outlook reinforced the same question: how much cash must be reinvested to maintain growth?
Intel delivered a different shock. Its shares sank 28.6% Friday after a weak fourth-quarter forecast and warnings that PC demand could remain soft into 2027. Its data-center business grew rapidly, but manufacturing costs, supply constraints, and expensive memory weighed on the outlook. The damage spread to chipmakers: AMD fell 10.9%, Nvidia 4.2%, and the semiconductor index 7.2%.
These were distinct disappointments, not proof that AI demand has vanished. Together, however, they pushed investors to reconsider valuations built on the assumption that AI investment would translate quickly into attractive returns.
The Race Behind the Bill
Even the huge data-center bills tell only part of the story. Anthropic's newly filed SEC prospectus reported $9.74 billion of research and development spending in the first half of 2026, versus $2.38 billion in direct costs to serve paying customers. R&D encompasses experimentation, personnel, training and other internal computing; it is not synonymous with training costs alone.
The distinction matters. Serving today's users may become cheaper as inference improves, while competing with tomorrow's models can demand another round of costly research. OpenAI, Anthropic, Google and their rivals face pressure to keep raising the performance bar. Nobody knows how many more rounds of capital-intensive competition will precede a more predictable, profitable industry structure.
Growth and the Fed
According to the Bureau of Economic Analysis, third-quarter GDP expanded at a 3.4% annualized rate, supported by investment. September PCE inflation was 3.6% year over year, with core inflation at 3.1%. The Federal Reserve held rates at 3.75%–4.00% in a 10–2 decision; both dissenters favored a hike. AI investment is supporting growth, but high financing costs make the eventual returns even more important.
The Week Ahead
Tuesday brings the midterm elections and JOLTS job openings; Friday's October employment report will test the Fed's assessment of the labor market. AMD reports Tuesday and Arm Wednesday, offering another test of demand after the chip selloff.
AI is already a business, not merely a promise. What investors still cannot price with confidence is how long companies must keep paying for the next leap forward before today's investments generate durable returns.
—Andy Jassy, President and CEO of Amazon, October 29, 2026
Perspectives by Phillip Wool, Ph.D.
How Is Your Portfolio Exposed to the “AI Trade”?
“So, we were sitting there at the end of last year basically saying, ‘We haven't seen the models yet... we're gonna write this check for, I don't know, $100 billion or $200 billion.’ And I’m looking across the table like, ‘Alex, are you sure this is gonna work?’”
—Mark Zuckerberg, Meta Platforms CEO, describing a conversation with Meta’s Chief AI Officer, Alexandr Wang, about Meta’s enormous infrastructure capex
Back in October, Meta founder and CEO Mark Zuckerberg brought his Chief AI Officer, Alexandr Wang, along for a visit to the pub with Stripe co-founder John Collison, who routinely hosts tech luminaries on his popular Cheeky Pint podcast. Clips of the sit-down went viral, centering on the Meta CEO’s anguished facial expressions as he attempted to “enjoy” his first glass of Guinness. We were more struck by Zuckerberg’s account of the company’s massive AI infrastructure investments, which were made, the pair revealed, on the basis of little more than a “vibe report” from Wang. It’s not the first time Zuckerberg has thrown big numbers around: On the Access podcast with Alex Heath and Ellis Hamburger last year, he suggested that “If we end up misspending a couple of hundred billion dollars, I think that that is going to be very unfortunate, obviously... But what I'd say is I actually think the risk is higher on the other side.”
If you hear the ring of “FOMO” in Zuck’s description of his firm’s capital budgeting discipline, you’re not alone, and we imagine many US stock investors have likewise thrown caution to the wind in the interest of not being “left behind” by the AI revolution. The good news for such investors is that AI momentum has so far handsomely rewarded a FOMO-based investment policy, leading to eye-popping returns for what’s seemed like an increasingly crowded trade. Only recently have stocks in the theme begun experiencing the kind of volatility that raises questions as to whether the AI stock gravy train keeps rolling from here or goes spectacularly off the rails.
Whether that question should concern an equity investor or not could depend on where, exactly, that investor is allocated within the AI space. Even though we often talk about “the AI trade”, as though there’s only one way to play this theme, a peek into most thematic AI portfolios yields a range of ways equity investors actually get exposure to this technological transformation. As the figure below illustrates, how one’s AI investments have performed can also vary substantially based on the nature of those investments.
Take chipmakers, for example, which have been the best performers associated with the AI boom, and which many observers likely consider the clearest embodiment of the AI hardware theme. Stocks in this industry, including Nvidia, Broadcom, and AMD—purveyors of the proverbial ‘picks and shovels’ powering AI model-builders—make up the Bank of America “AI Compute” Index, and have returned around 80% year-to-date. In fact, the AI chipmaker basket was up much more, roughly 120% YTD, back around the middle of summer, before that aforementioned volatility prompted a pullback.
That second-half AI angst was more painful for another set of stocks in the AI hardware space, the so-called “neo-cloud” providers loading up on debt to build datacenters they rent to hyperscalers like Meta and Alphabet. As bond yields have surged, so have doubts these companies will survive, squeezed between an increasing cost of capital and burgeoning skepticism over both competition in the space and the sustainability of demand for the infrastructure they’re investing so much to expand. Drawdowns like these—from up 80% to 20% in the hole, in just a matter of months—are a reminder that the higher valuations climb, the farther they have to fall when sentiment turns.
Along those lines, companies the market perceives as having a lot to lose as AI applications take root—in other words, the “shorts” of the AI trade, including enterprise software-as-a-service providers, like Adobe, Salesforce, and ServiceNow—had struggled mightily in the first half of the year. Names tracked in Goldman Sachs’ AI “At Risk” Index, for instance, had fallen by over 20% by the end of Q1. That same basket of stocks, arguably oversold after month upon month of doomsday headlines, has staged a big comeback over the last few months as investors reevaluated those overly SaaSpocalyptic visions, bouncing to a 20% year-to-date gain near the end of October.
If hardware stocks sitting on massive gains and increasingly lofty expectations are most exposed to a reversal in AI sentiment and software stocks have already begun to rebound, where might investors search for the next set of opportunities—or, at the very least, a tech ‘safe haven’ to weather setbacks in the AI theme? Hyperscalers could merit a look. Investors’ ambivalence toward big capex outlays has kept these stocks’ valuations in check, and diversified businesses throwing off loads of cash do tend to provide a buffer when the mood goes to ‘risk off’. Companies in the “AI adopters” category, which benefit most from applying AI to reduce costs and boost profitability, have also seen much more muted performance thus far and could provide another good pool of prospects for stock-pickers who view the “AI trade” as encompassing more than just hardware.
Disclosure: This material is for informational purposes only and should not be considered investment advice. An investor should consult with their financial professional before making any investment decisions. The opinions contained herein are subject to change without notice and do not necessarily reflect the opinions of Rayliant Investment Research. Indices cannot be invested in directly and are unmanaged. Past performance is not indicative of future results.
Advisory services offered through Sowell Management, a Registered Investment Advisor. The views expressed represent the opinion of Sowell Management. The views are subject to change and are not intended as a forecast or guarantee of future results. This material is for informational purposes only. It does not constitute investment advice and is not intended as an endorsement of any specific investment. Stated information is derived from proprietary and non-proprietary sources that have not been independently verified for accuracy or completeness. While Sowell Management believes the information to be accurate and reliable, we do not claim or have responsibility for its completeness, accuracy, or reliability. Statements of future expectations, estimates, projections, and other forward-looking statements are based on available information and Sowell Management’s view as of the time of these statements. Accordingly, such statements are inherently speculative as they are based on assumptions that may involve known and unknown risks and uncertainties. Actual results, performance or events may differ materially from those expressed or implied in such statements. Investing in securities involves risks, including the potential loss of principal. While equities may offer the potential for greater long-term growth than most debt securities, they generally have higher volatility. International investments may involve risk of capital loss from unfavorable fluctuation in currency values, from differences in generally accepted accounting principles, or from economic or political instability in other nations. Past performance is not indicative of future results.