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Nvidia Stock Price Week Ahead: Friday’s 3% Slide Sets Up CPI, TSMC Sales and GTC Test
7 March 2026
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Nvidia Stock Price Week Ahead: Friday’s 3% Slide Sets Up CPI, TSMC Sales and GTC Test

New York, March 7, 2026, 2:06 PM EST — Market is closed

Nvidia ended Friday at $177.82, off 3.0%, after higher oil and a disappointing U.S. jobs number spooked growth stock holders. Wall Street stays closed Saturday, leaving investors to weigh whether Nvidia’s slide reflects broader macro jitters, or if expectations around the AI leader remain out of reach.

The market’s still watching for clarity on AI spending. Over the past two days, Broadcom and Marvell each flagged steady demand for AI chips and networking hardware. But with oil climbing past $90 a barrel, investors are also bracing for a new round of U.S. inflation data.

Nvidia managed to fuel both sides of the debate late last month. The company projected fiscal first-quarter revenue of $78 billion—topping Wall Street’s estimates—but shares slipped after the earnings release. Investors zeroed in on mounting competition from AMD and the push by major cloud players to develop their own chips, and also didn’t see the bigger shareholder payouts they’d hoped for. Ken Mahoney of Mahoney Asset Management noted the company’s beat-and-raise routine was nothing new; much of the optimism, he said, was “baked in to the cake.” Reuters

Nvidia tossed another detail into the mix late Friday: a fiscal 2027 compensation plan now links executive cash bonuses directly to revenue targets. CEO Jensen Huang stands to collect a $4 million cash bonus if the company hits its marks.

Peer commentary skewed upbeat. Broadcom CEO Hock Tan put a number on it: the company expects to see over $100 billion in AI chip revenue by 2027. D.A. Davidson’s Gil Luria called that level of foresight a sign of “significant growth” on the horizon. At Marvell, President and COO Chris Koopmans said AI infrastructure investment remains “still growing massively.” Reuters

The competitive landscape is murkier. Broadcom’s current strength has a lot to do with its push into ASICs—those application-specific integrated circuits—which are tailor-made for single tasks and in some cases step in for Nvidia’s pricier graphics chips. On Friday, selling pressure hit across the sector: AMD dipped 3.5%, U.S.-listed TSMC shares slid 4.2%. Marvell, on the other hand, jumped 18.3% after its outlook.

Still, risks linger. Bloomberg News said Friday that Oracle and OpenAI have scrapped plans to grow their major Texas AI data center, with expansion talks stalling over financing and shifting requirements. Yet, according to a Reuters source, that lost capacity is expected to be picked up elsewhere. Even with robust infrastructure growth, projects miss or get shuffled, and the dollars follow.

The next data points are just ahead. TSMC posts its February sales numbers March 10—another look at chip demand. On March 11, U.S. CPI figures arrive, bringing the next inflation check. Nvidia’s GTC gets underway March 16 in San Jose; Huang has promised updates there on the company’s CPU efforts. For the stock, watch March 11 for the macro pulse. March 16 then brings Nvidia’s turn in the spotlight.

Stock Market Today

  • Investors Favor Google's AI Spending Over Meta Despite Both Raising Capex Guidance
    April 29, 2026, 10:00 PM EDT. Alphabet and Meta both reported strong first-quarter earnings, raising capital expenditure (capex) forecasts to fuel AI infrastructure. Alphabet's shares jumped 7% post-earnings, while Meta's dropped 7%, reflecting investor trust in Google's AI strategy. Alphabet's cloud division grew 63%, bolstering revenue by 20%, with a capex guidance raised to $180-$190 billion through 2026. Meta increased its capex forecast to $125-$145 billion, citing component costs and data center investments. Wall Street favors Alphabet's cloud-driven AI growth, contrasting with skepticism over Meta's AI investments tied primarily to advertising. Alphabet's stock is up 118% over the past year compared to Meta's 21%, underscoring the market's preference for sustainable AI revenue models.

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