Will conflict in Iran weigh on markets long-term?

Key Concepts

• Geopolitical Drawdowns: Market declines triggered by international conflicts, historically short-lived (weeks rather than months).
• AI Ecosystem Investing: A strategy of diversifying across various sectors (infrastructure, utilities, construction) rather than betting on a single tech winner.
• "Boring" Industrial Stocks: Traditional companies (construction, utilities) that are experiencing high growth due to the physical requirements of AI data centers.
• Valuation Multiples: The ratio of a company's stock price to its earnings (P/E ratio), used to determine if a stock is "on sale" or overvalued.
• Data Center Infrastructure: The physical components—power, cooling, and construction—necessary to support AI hardware.

1. Market Outlook and Geopolitical Strategy

Ian Shaffer, President and CIO of Gallant Advisors, maintains a bullish long-term outlook on equities despite ongoing tensions in the Middle East.

• Historical Precedent: Shaffer argues that investors should look past geopolitical disruptions. Citing the 2022 Russian invasion of Ukraine and the 2023 Israel war, he notes that market drawdowns during these events are typically measured in weeks, not months.
• Investment Philosophy: He advocates for a "buy low, sell high" approach, using market sell-offs to acquire quality companies at a discount. He suggests that as the market moves into the April earnings season, investors are increasingly "shrugging off" macro-news in favor of fundamental company performance.

2. The "Skilled Trades" AI Thesis

Shaffer highlights a shift in the AI narrative, referencing Nvidia CEO Jensen Huang’s observation that the next generation of millionaires may emerge from skilled trades (plumbing, electrical work).

• The "Nuts and Bolts" of AI: While AI is often viewed as a software or chip-centric industry, Shaffer emphasizes that the physical infrastructure required to power AI—data centers, cooling systems, and electrical grids—creates massive upside for industrial companies.
• Diversification Strategy: Rather than trying to pick the next "Nvidia," Shaffer recommends taking positions across the entire AI ecosystem to mitigate the risk of picking a single winner or loser.

3. Specific Investment Case Studies

Shaffer identifies two primary areas of opportunity: construction/engineering and utilities.

Emcor (EME) vs. Comfort Systems (FIX)

• The Comparison: Both companies provide engineering, construction, and maintenance services for data centers.
• The Strategy: Shaffer prefers Emcor (EME) over Comfort Systems (FIX). While FIX has performed exceptionally well, Shaffer views its current valuation as too high.
• Valuation Logic: He notes that EME trades at approximately 25x earnings, while its AI-related segments are growing at rates exceeding 30%. He advises waiting for a pullback before entering, noting that he successfully bought EME when it dipped due to missed buy-side estimates.

American Electric Power (AEP)

• The Utility Play: Shaffer describes AEP as a "boring" utility company that is uniquely positioned to build the "AI grid of the future."
• The Catalyst: AEP is securing power contracts through 2030 and partnering with companies like Bloom Energy to expand capacity.
• The Value Proposition: Investors gain exposure to AI-driven growth while receiving a 3% dividend, providing a defensive yet high-upside investment.

4. Synthesis and Conclusion

The core takeaway from the discussion is that the AI boom is creating significant, often overlooked opportunities in traditional industrial sectors. Shaffer’s framework relies on:

1. Patience: Maintaining a watchlist and waiting for market volatility to buy quality names at a discount.
2. Fundamental Analysis: Prioritizing companies with strong growth in AI-related segments that are not yet priced at "rocket ship" valuations.
3. Infrastructure Focus: Recognizing that the physical requirements of AI (power, cooling, construction) are as critical to the industry's success as the chips themselves.

Shaffer concludes that while the market may face short-term noise, the long-term trajectory for companies building the physical backbone of the AI economy remains robust.