The Small Cap Swing Trader Alert Archive
Below you'll find The Small Cap Swing Trader setups stacked up and ordered chronologically.Nvidia Slips Ahead of Earnings
Nvidia Slips Ahead of Earnings as AI Sentiment Weakens — What Traders Should Watch
Nvidia stock began Tuesday’s session under pressure once again, falling more than 2% in early trading as Wall Street continued rotating out of mega-cap technology and AI leaders ahead of Wednesday’s earnings. The move followed Monday’s broad tech selloff and came amid rising concerns that the economics of generative AI may not be as strong—or as immediate—as once believed. Redburn and Rothschild & Co. issued fresh downgrades of Microsoft and Amazon, two of Nvidia’s largest customers, citing skepticism around AI monetization. This shift in tone has injected volatility directly into the Nvidia AI earnings outlook.
Nvidia attempted to soften the blow on Tuesday morning by announcing up to $10 billion in new investment in Anthropic. Microsoft will also contribute up to $5 billion, and Anthropic will scale its Claude models on Microsoft cloud infrastructure powered by Nvidia GPUs. The companies emphasized a new collaboration to optimize Anthropic workloads for future Nvidia architectures. While strategically important, the news wasn’t strong enough to fully reverse early selling pressure.
Other chip stocks also declined sharply—AMD fell nearly 6%, Broadcom slipped 1.5%, and the VanEck Semiconductor ETF dropped 2.8%. This widespread weakness underscores the importance of Wednesday’s earnings announcement to Nvidia’s AI earnings outlook.
What Wall Street Expects on Wednesday
Analysts project Nvidia will report:
- Revenue: $54.8 billion
- EPS: $1.23
These expectations remain historically high, but after two consecutive down days, Nvidia now faces a slightly lower hurdle than usual. Still, traders will scrutinize far more than top-line numbers. The Nvidia AI earnings outlook hinges on:
- Competition from AMD, cloud ASICs, and custom hyperscaler silicon
- Chip depreciation cycles are affecting spending timelines
- Management commentary surrounding AI demand durability
Morningstar strategist Dave Sekera notes that traders want clarity on shifting competitive dynamics because Nvidia’s first-mover advantage—while massive—is not permanent.
What Today’s Price Action Means for Traders
Tuesday’s decline wasn’t random—it was a repricing of expectations for the Nvidia AI earnings outlook ahead of a major catalyst. This gives traders several clear setups going into Wednesday.
Day Trading Outlook
Bullish Intraday Scenario
- Holding above $182–184 → VWAP reclaim long setups
- Break above $188–190 → momentum continuation
- Possible short–covering rally into earnings
Bearish Intraday Scenario
- Lose $180 → flush toward $176–178
- Watch sympathy weakness in AMD, AVGO, SMH
- “Sell the rumor” pressure into the close
Swing Trading Outlook (1–5 Days)
Bullish (Post-Earnings Beat)
If Nvidia beats and guides higher, upside targets include:
- $195
- $203
- $210 on a full squeeze
This scenario requires stabilizing margins and improving tone in Nvidia’s AI earnings outlook.
Bearish (Miss or Weak Guidance)
Downside targets include:
- $170–175 primary support
- $165 if AI sector selling accelerates
Bottom Line
Tuesday’s selloff reflected the market adjusting to uncertainty surrounding Nvidia’s AI earnings outlook. With tech downgrades, AI-monetization concerns, and a cautious tone across the sector, Nvidia enters its earnings report facing more pressure—and more opportunity—than at any point in the past year.
The company’s multibillion-dollar investment in Anthropic reinforces its deep position at the core of AI infrastructure. Now, the question is whether earnings can calm concerns about competition, margins, and long-term chip demand. Traders should prepare for volatility—and for the possibility that Wednesday marks the beginning of Nvidia’s next major trend.
AI Chip Race Heats Up
AI Chip Race Heats Up as Tech Giants Build Their Own Silicon
Apple set the precedent in 2010 with its custom A4 chip for the iPhone 4, demonstrating that controlling silicon could enhance performance and profitability. Now, with Nvidia valued at $4.6 trillion and maintaining near-monopoly margins of 74% in its data center business, every major player wants a piece of the hardware stack. The AI chip race is no longer about innovation—it’s about control.
From Dependence to Diversification
Companies have realized that outsourcing chip design leaves them at the mercy of Nvidia’s pricing and production cycles. Training frontier AI models is becoming prohibitively expensive—costs have risen 2.4 times per year since 2016, and could exceed $1 billion per model by 2027. To stay competitive, tech giants are turning to custom application-specific integrated circuits (ASICs), which can be optimized for their cloud and AI workloads.
Google’s Tensor Processing Units (TPUs), Microsoft’s Azure Maia and Cobalt chips, Amazon’s Trainium processors, and Meta’s in-house silicon strategy all illustrate how the AI chip race is reshaping data center infrastructure. These chips are designed to strike a balance between performance and energy efficiency, thereby reducing dependence on Nvidia while lowering long-term costs.
Winners and Wild Cards
Suppliers like Broadcom, Marvell Technology, and MediaTek stand to gain from this build-it-yourself movement, handling the engineering and manufacturing for cloud giants. Bernstein estimates that the ASIC market could grow at a 55% annual rate to reach $60 billion by 2028. Meanwhile, Nvidia still dominates with projected sales of $375 billion in the same period—proof that it will remain at the center of the AI chip race for years to come.
Outside the U.S., China’s Alibaba and Baidu are developing their own chips to cut reliance on Western technology. Even automakers are joining the fray, betting that custom silicon will accelerate their self-driving ambitions. The AI boom has even inspired Japan’s SoftBank to explore acquisitions, such as Marvell, positioning itself as a global enabler of next-generation chip production.
Trading Insights and Market Impact
- Nvidia (NVDA): Despite competition, it remains the cornerstone of AI infrastructure. Pullbacks below $185 could offer long entries toward $200–205 ahead of Q4 guidance.
- Broadcom (AVGO): The biggest near-term beneficiary of ASIC contracts. Support sits near $1,200; a breakout above $1,330 targets $1,400 in the short term.
- Marvell (MRVL): Speculative buy for traders anticipating M&A activity or rising custom chip demand. Watch $67 as the next pivot resistance.
- Microsoft (MSFT): Short-term volatility expected as investors digest capex growth for in-house silicon. Look for entries on dips toward $400 support.
For active traders, the near-term setups hinge on capital expenditures (capex) guidance and chip cost efficiency. If these firms can demonstrate that in-house designs lower total AI training costs, we could see a shift toward cloud infrastructure providers that control their own hardware destiny. Conversely, any delays in rollout could spark profit-taking across the AI chip race sector.
Bottom Line
The AI chip race is transforming the global semiconductor ecosystem and reshaping the landscape of technological power. Whether it leads to independence or inefficiency depends on execution. For now, Nvidia remains the benchmark—but every custom chip announcement chips away at that dominance. Traders should keep an eye on hardware efficiency metrics, production timelines, and margin guidance as key catalysts into 2026.