‘INCREDIBLE’: Sector specialist on NVIDIA’s economic returns

Key Concepts

• CFROI (Cash Flow Return on Investment): A valuation framework used to compare companies on a "like-for-like" basis by adjusting for accounting differences (e.g., R&D capitalization).
• Economic Profit: A measure of value creation that goes beyond traditional accounting earnings to determine if a company is generating returns above its cost of capital.
• Hyperscalers: Large-scale cloud infrastructure providers (e.g., Amazon, Google) whose massive capital expenditures in AI are currently under scrutiny for their return on investment.
• AI Cycle: The current technological era characterized by significant capital investment in infrastructure, which is being compared to previous eras like the PC, networking, and mobile cycles.

---

1. The HOLT Framework and Economic Returns

John Tolbert of UBS HOLT explains that the primary goal of their methodology is to calculate the "true economic returns" of a business. The framework addresses inconsistencies in financial reporting—such as how different companies treat R&D expenses—to create a standardized metric for global comparison. By normalizing these metrics, investors can better assess whether a company’s recent performance is sustainable or if it is merely a result of accounting choices.

2. The AI Investment Cycle and Hyperscalers

A central debate in the market is whether the massive capital expenditures by hyperscalers will yield sufficient returns.

• The Concern: Investors worry that while growth is high, the return on capital for these near-term investments is declining.
• The Perspective: Despite falling returns on capital, the absolute dollar value of economic profit remains high. Tolbert argues that the trend for value creation remains positive for the next few years, suggesting that the "AI era" is a continuation of a long-term technological arc rather than a bubble.

3. Market Valuation and "Fair Value"

Tolbert addresses the skepticism surrounding tech stocks, noting that many investors are prone to "betting against" the long-term momentum of the sector.

• Fair Valuation: Despite recent underperformance in certain areas, the HOLT framework suggests that many tech stocks are currently "fairly valued" relative to the broader market when accounting for economic adjustments.
• The "This Time is Different" Argument: While many analysts argue that the current tech cycle is overextended, the fundamental data suggests that the market has already priced in a degree of skepticism. If these companies can maintain their current levels of performance, they remain attractive investment opportunities.

4. Methodology and Back-Testing

The HOLT framework is designed to be a predictive tool for investment processes.

• Process: The system screens for companies with strong fundamentals and high potential for economic profit.
• Validation: Tolbert confirms that the system has been back-tested and consistently identifies attractive investment opportunities.
• Application: The framework is used by global institutional clients to navigate uncertainty, particularly regarding how AI will impact corporate earnings in 2026 and 2027.

5. Key Takeaways and Synthesis

The discussion highlights a disconnect between market sentiment and fundamental data. While the market often fears that AI investments are "overdone" or represent a "dead cat bounce," the HOLT analysis suggests that the tech sector is supported by strong economic profit generation.

Conclusion: The primary takeaway is that investors should shift their focus from traditional earnings metrics to Economic Profit and CFROI. By doing so, they can look past the volatility of the current AI cycle and identify companies that are genuinely creating value. As long as software growth re-accelerates and disruption fears are managed, the long-term outlook for the tech sector remains robust, with current valuations appearing reasonable rather than inflated.