SpaceX's listing did not drain the well, the tech rally will continue - broker

Wedbush’s Dan Ives says the recent chip-stock weakness was positioning ahead of the SpaceX listing, not a demand breakdown, and calls the outcome a Goldilocks signal for the AI trade. He sees strong demand across Asia and expects OpenAI and Anthropic to move toward listings before year-end, reinforcing the AI capital-spending flywheel into chips, energy and data-center infrastructure. Ives also highlights Palantir, Snowflake, Datadog and Innodata as preferred data-layer names, with Wedbush price targets of $230, $280, $260 and $120, respectively.

Analysis

The important read-through is not that AI demand is healthy; it is that capital is still rotating within the same ecosystem rather than leaving it. If private-market listings keep absorbing liquidity without breaking the public complex, that signals a broader re-rating regime where investors are willing to finance the full stack — compute, networking, power, storage, and software — instead of forcing a zero-sum trade. That should help the most levered enablers, especially names with direct exposure to enterprise AI deployment and recurring usage expansion.

The second-order beneficiary set is better than the obvious chip basket. If model access commoditizes, value migrates to proprietary data, workflow integration, and observability, which supports platforms that sit inside customer operations and become harder to displace once embedded. That creates a barbell: infrastructure still participates, but the higher-quality compounding likely comes from data moat names with pricing power and multi-year expansion runway.

The key risk is timing mismatch. The narrative can stay bullish for months even if near-term hardware orders wobble, but if enterprise adoption fails to translate into budgeted spend by late 2H26, the market will punish the highest-multiple AI beneficiaries first. Macro softness is the cleanest reversal catalyst because it would hit the “monetization next” thesis before the full capex cycle is visible in reported numbers.

Consensus is probably underestimating how much of this move is a positioning event rather than a fundamental all-clear. If investors have already de-risked chips ahead of new listings, the next leg may be less about chasing semis and more about rotating into the names where AI spending becomes measurable in revenue retention, cloud consumption, and workflow expansion. That argues for selective longs over broad-beta exposure.

Key Decisions for Investors

• Long MSFT into the next 3-6 months: use any post-listing softness to add, because Azure AI monetization should show up earlier in revenue growth than most peers; target a 1.5-2.0x upside to downside over 6-9 months.
• Long AMZN on weakness over the next 1-2 quarters: AWS is the cleanest operating leverage expression if AI spend shifts from experimentation to production; favor call spreads to cap time decay while keeping convexity.
• Build a basket long PLTR/SNOW/DDOG/INOD versus a semiconductor proxy over 2H26: the pair expresses the view that data/workflow monetization outlasts model commoditization and reduces reliance on cyclical hardware multiples.
• Use a short-dated hedge on the crowded AI chip complex if positioning remains extended: if the market is front-running capital rotation, a 1-2 month put spread can protect against a second leg of de-grossing without betting against the full AI cycle.
• If entering PLTR or SNOW, size for a 6-12 month hold and expect volatility: these are not near-term earnings trades but compounding data-layer winners; risk/reward is best on pullbacks rather than breakout chasing.