AI stocks: Dip buying, opportunities, and how to play the AI trade

Here's a detailed summary of the YouTube video transcript:

Key Concepts

• AI Trade: The current market trend driven by investments in artificial intelligence and its related infrastructure.
• Earnings Season: The period when publicly traded companies release their financial results.
• Valuation: The assessment of a company's worth, often expressed as a price-to-earnings (P/E) ratio or other multiples.
• Beat/Miss: When a company's reported earnings or revenue are higher (beat) or lower (miss) than analyst expectations.
• FOMO (Fear Of Missing Out): The anxiety that arises from the belief that others are having rewarding experiences from which one is absent.
• Buying the Dip: A strategy of purchasing an asset after its price has fallen, anticipating a rebound.
• Multiple Expansion/Contraction: The change in a valuation multiple (e.g., P/E ratio) based on market sentiment and company performance.
• Second and Third Derivatives of AI: Looking beyond the immediate AI chips and infrastructure to related industries and technologies that will be impacted by AI's growth.
• AI Infrastructure: The physical and software components necessary to support AI development and deployment, including networking and power generation.
• M&A (Mergers and Acquisitions): The consolidation of companies or assets through various types of financial transactions.

Summary

The Paradox of Tech Earnings: Beating Estimates, Yet Stocks Fall

The current earnings season has presented a peculiar pattern: technology companies are consistently exceeding analyst expectations and even raising their future forecasts, yet their stock prices are declining. This phenomenon was observed with Qualcomm and is a recurring theme across the semiconductor sector.

Key Points:

• Positioning Over Performance: According to Ivana Dilvka, founder and CIO of Spear Invest, the market's reaction is less about the reported numbers and more about how investors were positioned going into the earnings.
• Qualcomm Example: Qualcomm's stock fell despite a seemingly good quarter because the market had already priced in positive news, particularly regarding their new data center chip announced weeks prior. The lack of additional details on this chip during the earnings call, with more promised for next year, led to a muted reaction.
• High Expectations and Overvaluation Concerns: Sylvia Jablonsky, CEO and CIO of Defiance ETFs, attributes the stock drops to exceptionally high market expectations. Even minor deviations from a "perfect" report can trigger investors to take profits or reduce positions due to concerns about overvaluation.
• FOMO and Buying the Dip: Despite the sell-offs, there's a significant "FOMO" sentiment among investors who missed out on earlier gains. Jablonsky suggests that for those who believe in the long-term AI thesis and the continued growth of companies like Qualcomm, Broadcom, Super Micro, AMD, and Nvidia, dips present potential buying opportunities.

Valuations and the Importance of Consistent Beats

The discussion delves into whether current valuations are truly high and the role of earnings beats in justifying them.

Key Points:

• Valuations Not Necessarily High: Ivana Dilvka argues that valuations are not necessarily high because the consistent earnings beats are driving down the multiples. When a company beats expectations but its stock doesn't react positively, its P/E ratio (or other multiples) effectively decreases. This makes dips attractive as investors aren't "chasing" higher multiples.
• Long-Term Performance Requires Consistent Beats: While quarter-by-quarter reactions might be less critical for short-term trading, consistent, multi-quarter beats are essential for long-term stock appreciation. Companies that fail to consistently deliver strong numbers will struggle to maintain upward price momentum.
• Justifying Multiples: Sylvia Jablonsky emphasizes that the numbers are crucial for justifying current multiples and attracting buyers. Dips are only good buying opportunities if the underlying news and numbers remain positive.

Case Study: Super Micro Computer

Super Micro Computer serves as another example of a company experiencing a stock decline despite being a significant player in the AI build-out.

Key Points:

• Design Issues and Quarter-over-Quarter Decline: Super Micro reported design issues, leading to a 15% quarter-over-quarter decline in their performance, contrasting with the overall semiconductor industry's 15.8% growth.
• Pure AI Play with Leadership Potential: Despite the recent setback, Super Micro is considered a pure AI play with potential leadership in data centers, edge computing, and 5G.
• Historical "Buy the Dip" Trend: Historically, buying Super Micro on dips has been a successful strategy. However, Ivana Dilvka reiterates that the numbers still matter, and for Super Micro, investors will need to wait and see how the design issues are resolved.

Mergers and Acquisitions (M&A) in the Semiconductor Space

A recent report about SoftBank considering the acquisition of Marvell Technology and its potential combination with ARM is discussed.

Key Points:

• Marvell's Undervaluation: Ivana Dilvka notes that Marvell has been undervalued, particularly compared to its peers, which makes a SoftBank acquisition logical.
• Long-Term Fundamentals: Dilvka believes Marvell has a strong long-term story, especially its leverage to Amazon. With Amazon's custom silicon (Trainium) showing improvement, the fundamentals for companies exposed to Amazon are strengthening towards 2026.
• Potential for Consolidation: The discussion implies that M&A activity might increase in the sector.

The Next Catalysts for AI Growth

The conversation shifts to identifying future growth drivers and catalysts in the AI space.

Key Points:

• Nvidia's Upcoming Earnings: Nvidia's earnings report on November 19th is a key event, though its impact (positive or negative) is debated given recent market reactions.
• Beyond the Chips: Second and Third Derivatives of AI: Sylvia Jablonsky suggests looking beyond the immediate AI chips and infrastructure to the "second and third derivatives of AI." This involves identifying hyper-growth opportunities in related sectors.
• AI-Powered Infrastructure: Jablonsky highlights AI-powered infrastructure, including energy and the broader ecosystem supporting AI, as a promising area. She points to energy companies performing well due to their role in powering the AI phenomenon.
• Physical and Software Infrastructure: Ivana Dilvka agrees, stating that the market is heading towards the next wave of AI investments, specifically targeting infrastructure. This includes opportunities in networking and power generation, encompassing both physical and software infrastructure.

Conclusion/Synthesis

The current market environment for AI-related stocks is characterized by a disconnect between strong company performance and declining stock prices. This is largely attributed to high investor expectations, pre-earnings positioning, and concerns about valuations. While "buying the dip" can be a viable strategy for long-term believers in the AI thesis, consistent financial performance remains crucial for sustained growth. Looking ahead, the focus is shifting beyond the core AI chips to the broader infrastructure and secondary/tertiary impacts of AI, presenting new avenues for investment in areas like networking and power generation. M&A activity is also a potential factor to watch in the semiconductor landscape.