The Trump‑Era Rally Keeps Extending, and 2 Stocks Still Look Undervalued

Alphabet is described as trading within 3% of new highs at under 30x P/E, while Microsoft trades at 24.6x trailing P/E and may benefit from a larger OpenAI investment and Azure strength. The piece argues both names remain attractive relative-value plays versus more parabolic AI/semiconductor winners, but urges caution amid overheated tech sentiment. Overall tone is constructive on large-cap AI leaders, especially Alphabet and Microsoft.

Analysis

The important read-through is not simply that AI remains bid, but that the market is starting to discriminate between AI capex intensity and AI monetization quality. That favors platforms with distribution, data, and pricing power over pure-model or hardware-exposure names; in other words, the next leg of AI returns is likely to come from software and cloud attach rather than another round of semiconductor multiple expansion. If that happens, the relative performance gap between mega-cap “buyers of AI” and “sellers of AI” should widen over the next 1-2 quarters.

GOOG looks better positioned as a second-order beneficiary because it can convert AI into search, ads, cloud, and security without needing the market to underwrite a standalone AI story. The contrarian point is that this is still under-owned as an AI expression versus the more crowded semi trade, so the stock can compound even if broad tech consolidates. The risk is execution slippage in product monetization or any sign that AI responses erode search economics faster than they expand cloud margins; that would matter over months, not days.

MSFT is the cleaner “quality catch-up” setup. The market is implicitly discounting ongoing deal complexity and a slower product cycle, but that creates room for multiple expansion if enterprise Copilot adoption reaccelerates and Azure growth inflects off an easier comp in the second half. The bigger asymmetric risk is that Microsoft proves to be the most durable monetizer of AI in enterprise while the rest of the market is forced to pay up for lower-quality growth, which would make the current relative discount look like a mistake rather than a value opportunity.

The main macro wildcard is sentiment rotation: if the market starts penalizing long-duration AI beneficiaries and rewarding cash-generative compounders, both GOOG and MSFT should outperform on a relative basis even in a choppy tape. If semis de-rate 10-15% from stretched positioning, that likely becomes a source of support for these two names rather than a sign of broader AI fatigue.

Key Decisions for Investors

• Go long GOOG / short SMH for 1-3 months: express the view that monetization winners will outperform capex beneficiaries as AI spend quality becomes the key differentiator; target 8-12% relative outperformance, stop if semis continue to lead on fresh AI enthusiasm.
• Add MSFT on weakness versus QQQ over the next 2-6 weeks: use it as a relative-value catch-up trade, not an absolute momentum chase; upside is multiple re-rate if enterprise AI traction becomes visible, downside is lower beta if the market rotates out of expensive growth.
• Pair trade long GOOG / short a basket of parabolic semi leaders over 1-2 quarters: hedge market beta and isolate the thesis that AI monetization is shifting from picks-and-shovels to platforms; risk is another leg of speculative hardware exuberance.
• Buy 3-6 month MSFT call spreads financed partially by selling out-of-the-money calls: attractive if you expect a slow grind higher rather than a breakout; best risk/reward if Azure/Copilot data improves before the market fully re-prices the stock.
• Trim or avoid adding to high-multiple AI infrastructure names into strength: the asymmetric risk/reward is worsening as positioning becomes crowded and the market starts demanding evidence of monetization, not narrative.