Magnificent Seven ETF Drops 7% as Microsoft, Google, and Amazon Face Earnings Outlook

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The Magnificent Seven ETF (MAGS.US) has fallen nearly 7% from its yearly high as ETF outflows accelerate amid earnings season. Meta (META.US) and Tesla (TSLA.US) led the decline following their earnings reports, with Meta down 18% due to negative free cash flow. Microsoft (MSFT.US) is expected to report $90 billion in revenue and $4.72 EPS, but market sentiment depends on returns from AI spending. Alphabet (GOOGL.US) projects $127 billion in revenue, while Amazon (AMZN.US) shares dropped to $248 as AWS revenue increases but free cash flow turns negative.

According to Woofun AI, as recent rebound momentum weakened and earnings season approached, the seven strongest-performing tech stocks collectively experienced a pullback over the past two weeks. The Roundhill Magnificent Seven ETF (MAGS.US) closed this week at $70.07, down nearly 7% from its year-to-date high.

This pullback trend accelerated after Meta (META.US) and Tesla (TSLA.US) released their earnings reports: Meta's stock dropped 18% from its yearly high due to negative free cash flow for the quarter, while Tesla faced pressure from declining revenue in its electric vehicle and energy businesses, though growth in its services and other segments partially offset the decline.

Woofun AI's compiled data shows that Microsoft (MSFT.US) closed last week at $524, slightly below its monthly high of $550 but still 50% higher than its yearly low. Analysts predict Microsoft's revenue will increase 17% year-over-year to $90 billion, with earnings per share rising from $4.13 to $4.72.

However, stock price fluctuations are more dependent on investors' scrutiny of AI capital expenditures and returns, particularly the performance of the Copilot product. Microsoft (MSFT.US) previously disclosed that its planned AI-related spending for 2026 will range between $175 billion and $190 billion.

Meanwhile, Alphabet (GOOGL.US) stock has declined to $317, a 22% drop from its intra-year high of $402. The market expects revenue to grow 25% to $127 billion, with earnings per share of $2.97. The performance of its core advertising business and free cash flow under continued AI investments will be key factors influencing the stock price. Alphabet’s (GOOGL.US) free cash flow for the second quarter was -$5.85 billion, and management has guided that AI spending between 2026 will range between $195 billion and $205 billion.

Additionally, BNP Paribas forecasts that its TPU (Tensor Processing Unit) business revenue will reach $40 billion by 2027, and the growth potential in this segment will be further clarified in this week’s earnings report.

Amazon (AMZN.US) stock has also experienced a significant correction, dropping from $287 in August to its current price of $248. Analysts expect revenue to grow 12.2% to $202 billion, with AWS being the key driver.

However, the deteriorating trend in free cash flow has raised market concerns, as Amazon's (AMZN.US) free cash flow turned negative in the second quarter, and this negative trend may persist as AI investments increase. Amazon (AMZN.US) expects its AI spending to reach $220 billion in 2026, higher than the previously reported $200 billion.

Structurally, the massive capital expenditures by these three tech giants on AI infrastructure are reshaping their financial models, with temporary pressure on free cash flow becoming a common trait. Microsoft (MSFT.US), Alphabet (GOOGL.US), and Amazon (AMZN.US) are expected to spend between $175 billion and $190 billion, $195 billion and $205 billion, and $220 billion on AI, respectively, highlighting the industry’s intense focus on the compute race.

This shift from pursuing short-term profits to long-term infrastructure investment has temporarily suppressed stock performance but laid the foundation for future technological moats. Notably, investors’ focus on earnings reports has moved beyond mere revenue growth to a deeper evaluation of capital efficiency and the commercialization of AI. This represents another stress test by the market on high-capital-expenditure models, following the last round of tech stock valuation reconfiguration; future performance will depend on whether these giants can demonstrate that their AI investments translate into sustainable profit growth.


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