Google (GOOGL.US) plummets 12% and Lily.US (LLY.US) hits a record high: AI capital expenditure ledgers trigger market revaluation

According to Woofun AI, the US stock market showed a sharp split on October 29. Google (GOOGL.US) plummeted 12.64% in a single day while LLY.US (LLY.US) bucked the trend and reached a record high. This contrast indicates that investors' valuation logic for artificial intelligence assets is shifting from a narrative of scale expansion to a strict examination of free cash flow.

Google's closing performance on October 29 was disastrous. The stock price fell 12.64%, causing its market value to evaporate about $500 billion in one day, setting the record for the biggest single-day decline since it went public in 2004. In stark contrast to the decline of tech giants, although the financial reports released later by Intel (INTC.US) and Amazon (AMZN.US) also triggered a post-market decline, Eli Lilly rose 6.57% and reached a new all-time high. At the index level, the Nasdaq Composite Index fell 1.38%, the S&P 500 fell 0.30%, and the Dow Jones Industrial Average fell 0.25%. The overall market did not fall into an overall panic, but structural changes in capital flows are clearly visible.

Market data compiled by CNN shows that this differentiation does not stem from questioning the demand for artificial intelligence, but rather from repricing the quality of profits. Google's third-quarter revenue reached $127.577 billion, up 25% year over year. This is the 13th consecutive quarter of double-digit growth, indicating that fundamentals are still strong. Among them, Google Cloud (GOOGL.US)'s revenue reached US$30.709 billion, a year-on-year surge of 103%, far exceeding market expectations, proving that demand for cloud computing and AI infrastructure from enterprise customers is still strong.

However, what is really causing concern in the market is the slowdown in the growth rate of the advertising business. Search and other ad revenue was $63.35 billion, up 12% year over year. Not only did it fall short of market expectations of nearly $65 billion, but the growth rate declined significantly from 17% in the previous quarter. Google revealed that the year-on-year growth rate of its search volume has reached the highest level in nearly five years, yet the increase in user search frequency has not translated into the same proportion of advertising revenue. The monetization efficiency of some AI models is lower than that of traditional search results pages, which reveals the challenge of maintaining advertising commercial value under new interactive methods.

The core driving force behind Google's stock price collapse was negative free cash flow due to a surge in capital expenditure. In the third quarter, Google's capital expenditure reached $51.355 billion, up about 114% year over year. This figure surpassed the quarter's operating cash flow of US$42.290 billion, resulting in a net free cash flow outflow of US$9.065 billion, while the market previously anticipated only a small net inflow of about US$2.7 billion.

This cash flow gap did not fluctuate by accident. Google's free cash flow had a net outflow of 5.855 billion US dollars in the second quarter, compared to a net inflow of 24.461 billion US dollars in the same period last year, and the gap is widening. Management made it clear that capital expenditure in 2027 will continue to be higher than 2026, but did not give a specific timeline for peak investment or peak spending. For cloud computing and AI infrastructure companies, building data centers and purchasing servers in advance is a necessary means to compete for long-term market share, but the key is whether additional investment can bring sufficient revenue and profit.

If the cloud business continues to grow rapidly and profit margins improve with scale, the current cash flow pressure may only be a phased phenomenon in the expansion cycle; however, if capital expenses outperform operating cash flow for a long time, and cloud business revenue cannot be converted into corresponding cash returns, investors must re-evaluate the free cash flow and return on capital of the enterprise. The valuation repricing experienced by Google this time is essentially aimed at the uncertainty of the AI payback cycle, rather than a denial of its AI capabilities.

Intel was hit hard in after-hours trading. At one point, the stock price fell by more than 20%, but its fundamental pressure was different from Google. Intel's third-quarter revenue was US$16.513 billion, up 21% year over year, in line with expectations. Among them, data center business revenue increased 78%, indicating that demand for AI inference server chips is being fulfilled.

What weighed down the stock price, however, was its fourth quarter guidance: revenue estimates were $15 billion to $16 billion, lower than Wall Street's estimate of about $17 billion, and gross margin guidance fell to 37%. Management explained that weak PC demand may continue until the first half of 2027, with rising memory chip prices driving up costs, and the Israeli factory accident impacted revenue of about $300 million in the fourth quarter.

More importantly, Intel's earnings report has increased by more than 130% in 2026. Under high expectations, any guidance that falls short of expectations can easily trigger a return in profits. An after-hours terminal snapshot showed that the stock price was $70.87, about 25.8% lower than the closing price. This decline is more of a valuation adjustment due to shocks compounded by high expectations, rather than simply repricing AI capital expenditure, but it shows that the market's fault tolerance rate for AI industry chain assets is declining, and it is difficult to obtain a valuation premium based on AI concepts alone.

Amazon also faced a stress test of return on capital. After the market, the stock price once fell by more than 7%, and the media reported a decline of more than 12%. Amazon's total revenue for the third quarter of 2019 was USD billion, slightly lower than market expectations. AWS's revenue of $46 billion was up 39.3% year over year. Although it was higher than 37% in the previous quarter, it fell short of 40% expected by some organizations. Coupled with weak sales guidance during the holiday season, the market is concerned about its short-term revenue growth. More serious than revenue is the cash flow situation: operating cash flow in the past 12 months was $168.3 billion, up 29% year over year, but there was a net free cash flow outflow of $42.4 billion. The gap between the two is almost entirely due to the consumption of operating cash from capital investment such as data centers. Amazon is not shrinking its investment. CEO Jaxi said capital expenditure will increase significantly in 2027, and the company will maintain its 2026 billion dollar capital expenditure plan. An after-hours terminal snapshot showed that the stock price was $225.99, about 4.2% lower than the closing price. Revenue falling short of expectations, deep negative free cash flow, and expectations of continued expansion of capital expenditure combined to form the main pressure after the financial report.

Woofun AI collated data and showed that when Google, Amazon, Microsoft (MSFT.US), and Meta (META.US) were observed together, tech giants collectively fell into the plight of huge capital expenditure and uncertain return cycles. Together, the four companies spent more than $720 billion in 2026, about three times what they were two years ago. Among them, Google, Amazon, and Meta had negative free cash flow, and Meta had negative quarterly free cash flow for the first time since its listing. Upstream and cloud service providers are increasing their investment, and the market naturally wonders how much return such huge capital expenditure can ultimately generate for shareholders. There is nothing wrong with AI demand itself. The problem is that infrastructure construction may enter a stage where the scale of investment is getting larger and the payback cycle is unclear. This structural contradiction is reshaping the valuation logic of technology stocks.

While tech giants were busy explaining capital expenses, Eli Lilly bucked the trend and hit new highs with high-certainty cash flow driven by GLP-1 drugs. Eli Lilly's third-quarter revenue of $24.397 billion was up 39% year over year, higher than market expectations of approximately $22.6 billion; adjusted earnings per share were $7.48, exceeding expectations of $6.49. The core growth comes from GLP-1 drugs. Mounjaro's global revenue was US$10.72 billion, up 65% year over year, and Zepbound's revenue was US$5.35 billion, up 49% year over year. Together, the two products contributed about 66% of quarterly revenue. As sales continued to exceed expectations, the company raised its full-year revenue guidance from $85 billion to $87 billion to $91 billion to $92 billion, the third time in the year.

The fundamental difference between Eli Lilly and Google is the way growth is realized: Google first invests tens of billions of dollars to build infrastructure and then gradually recycle it, and Lilly's core revenue comes directly from drug sales that have already occurred. The company's net free cash flow for the third quarter was US$8.219 billion, and sales increased 53%. Although net sales prices fell by about 15% due to factors such as health insurance access, sales growth was enough to drive overall revenue growth of 39%. At the stage where the market re-examines return on capital, this business model, which can directly convert product demand into cash flow, is easier to get financial attention. Of course, Lilly's rolling price-earnings ratio is about 45 times, and valuations are not cheap. Health insurance access and market competition are still risks. Investors need to observe the growth rate of prescriptions, the rate of decline in net sales prices, and confirmation of revenue guidance and free cash flow.

Evidence of sector rotation shows that capital is flowing to sectors with high profit visibility, such as healthcare, finance, and energy. The healthcare sector showed outstanding performance, with Moderna (MRNA.US) up 4.01%, Merck (MRK.US) up 3.83%, and AMGN.US (AMGN.US) up 1.97%. Most financial stocks closed higher, and JPMorgan Chase (JPM.US) rose 1.26%. Energy stocks rose slightly, with ExxonMobil (XOM.US) up 0.70% and Chevron (CVX.US) up 0.99%. Brent crude oil remained at $114, and WTI crude oil was around $102, but energy stocks did not see a sharp rise in line with oil prices, indicating that the capital is focused on operating cash flow that energy companies have already realized rather than geographical premiums.

Goldman Sachs (GS.US) position tracking shows that hedge funds have increased their holdings in the medical sector by $1.69 billion in the past two weeks while reducing their semiconductor holdings. According to EPFR data, the net inflow of US medical-themed funds in the last two weeks was US$4.72 billion, and the return intensity was at a high level in 2026. Strategist Baird pointed out that AI narrative fluctuations do not disrupt growth logic, and capital may spread from a few giants that rely on high capital expenditure to support valuations to assets with more diverse sources of profit. Although there are different ways to make money in healthcare, finance, and energy, the sources of income and cash flow are relatively clear. This “can see clearly” characteristic is very attractive at the stage where investors pay attention to current cash flow.

Future key nodes will determine how the market continues to screen AI assets. The first is Nvidia's (NVDA.US) earnings report for mid-November, which will directly test whether AI computing power demand is strong, and should focus on data center revenue, orders, deliveries, and gross margin stability. If revenue and orders continue to exceed expectations, AI infrastructure demand is still supported; if order growth slows or gross margins are pressured, the market may lower AI hardware growth expectations. The second is the next round of capital expenditure guidelines for cloud giants. For Google, Amazon, Microsoft, and Meta, investors need to look at capital expenses, cloud business revenue, operating margins, and free cash flow in combination.

If cloud revenue increases and capital expenditure growth slows, operating cash flow begins to cover investment expenses, indicating that AI infrastructure is moving from investment to return; conversely, if capital expenditure support continues to rise and the growth rate of cloud business does not improve, the free cash flow gap widens, and valuation pressure is difficult to resolve. The third point is the Federal Reserve interest rate meeting on December 9. Interest rate decisions, bitmap, Powell's speech, and changes in US bond yields will affect the relative valuation of cash flow over different periods. Under high interest rates, highly valued growth stocks that rely on forward returns are under pressure, and companies with stable profits gain an advantage; however, if interest rate cuts are caused by a weakening economy and corporate profit expectations are lowered simultaneously, improvements in valuation may not offset the deterioration in fundamentals.

The investment logic is being restructured from scale expansion to final verification of free cash flow. Nvidia and AMD (AMD.US) need to verify orders, data center revenue, and gross profit margins; cloud giants need to track cloud business revenue growth, profit margins, capital expenses, and free cash flow. Healthcare Assets focuses on prescription volumes, net sales prices, and year-round guidance for GLP-1 products. Among financial and energy assets, JPMorgan Chase (JPM.US) is required to track net interest spreads, credit losses, and transaction income, while traditional energy focuses on oil prices, production, capital discipline, and free cash flow. These directions are not simple defensive allocations. Eli Lilly still has valuation and competition risks. Banks face credit cycles, and energy is affected by fluctuations in oil prices.

A more reasonable approach is to establish an observation list based on each profit driver and determine allocation weights based on financial reports and changes in capital flows. The core of this market round is that investors are increasing their demand for AI commercial returns. The capital has not abandoned AI. As long as demand for computing power grows, there are still long-term opportunities. However, for companies whose capital expenditure support continues to expand and cash flow has not improved, the market is no longer willing to overvalue companies based on long-term stories alone. Conversely, sectors with clear profit paths, such as healthcare, finance, and energy, may continue to receive financial attention. What's really worth tracking next is who can take the lead in turning investment into profit and free cash flow, not who announces larger AI investment plans.