AI Top or Slop: When Markets Reach Peak Magnificence

(True Partner Capital, September 2025, Chicago/Hong Kong)

The "Magnificent Ten" AI-focused stocks now command nearly 40% of the S&P 500's market capitalization, having doubled their weight from just 21% at the start of 2023. This extraordinary concentration tells a story of two markets: ten companies delivering annualized returns of 53.9% generating $15.85 trillion in added market value, and the remaining 490 companies returning just 11.3% annually, contributing only $9.04 trillion. This divide between what we call the "AI Top" and the "Slop 490" represents the most extreme market concentration in modern history.

What drives this unprecedented divergence? The Magnificent Ten share more than impressive returns; they share an all-consuming focus on artificial intelligence. Microsoft plans to spend $80 billion on AI data centers in 2025 alone, up from $50 billion in total capital expenditure in 2024. Meta's CEO has declared he would rather risk "misspending a couple of hundred billion" than miss superintelligence, a remarkable statement from a company that saw its shares crater 73% in 2022 over Metaverse spending concerns. Now markets reward this AI fervor.

Yet beneath this enthusiasm lie curious circular arrangements. In a well publized transaction, Nvidia invests USD 100 billion in open AI for the latter to buy processors at the former. Or even somewhat more curious, Nvdia has agreed to rent 18,000 of its own AI chips for $1.5 billion from Lambda, a company in which it holds an equity stake, essentially becoming its own largest customer through intermediaries. This pattern echoes the vendor financing arrangements that characterized the dot-com bubble's final stages, when companies like Nortel Networks provided financing that exceeded actual sales revenue, ultimately contributing to the firm's bankruptcy in 2009 after it had once represented a third of Canada's entire market capitalization.

The mathematics of the AI boom raise further questions. Bain Capital calculates that AI companies will need $2 trillion in combined annual revenue by 2030 just to fund the computing power for projected demand, yet current monetization efforts suggest revenue may fall $800 billion short. Meanwhile, competition emerges from unexpected quarters. China's DeepSeek demonstrates that nimbler open-source alternatives could commoditize large language models, while Chinese companies rapidly develop their own AI chips. The Chinese government now orders domestic firms to avoid Nvidia products entirely, suggesting confidence in homegrown alternatives that could reshape global markets as dramatically as Chinese competition reshaped solar and electric vehicle industries.

Against this backdrop, implied volatilities for US and European markets trade well below their long-term averages, suggesting remarkable complacency. While Asian markets show higher volatility reflecting their upside fervor, Western markets price in continued calm despite elevated valuations. The S&P 500 consensus forecasts project 13.6% earnings growth for 2026, nearly double the 7.3% annualized growth of the past decade, apparently dismissing tariff tensions as temporary noise.

Historical parallels emerge when examining current valuations. The Nifty Fifty era saw similar concentration in favored growth stocks, with Polaroid reaching a P/E ratio of 90 in 1971, not far from Broadcom's current 82 or AMD's 88. Those companies represented genuine innovation, yet their extreme valuations preceded decades of underperformance. Markets may not repeat, but as our analysis shows, they often rhyme.

For volatility specialists like True Partner, this environment of concentrated gains, circular financing, ambitious projections, and suppressed implied volatility creates a distinctive market structure. The firm's relative value volatility strategy, with its 14-year track record of positive performance despite negative correlation to equity markets, was designed for moments when market dynamics shift. Current conditions, with their echoes of past market extremes and historically low volatility pricing, present the kind of asymmetry that volatility strategies are positioned to navigate.

Our full analysis provides detailed examination of these market dynamics and their potential implications for understanding current market structures.

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