Hedgeye is taking Google (GOOGL) off its highest-conviction list after a powerful run that it says arrived far earlier than anticipated.
In a new post on X, Andrew Freedman, the firm’s head of communications and software research, says the major drivers they outlined coming into the year have already materialized.
He names five bullish catalysts that fueled GOOGL’s run to a new all-time high of $328.83 earlier this week.
“I removed Google from our ‘Top Picks’ list yesterday, as the catalysts we flagged coming into 2025 have largely played out — and faster than expected. Search stabilization, policy tailwinds, Cloud acceleration, Gemini 3.0, TPU momentum. All delivered.”
While Freedman says it is within the realm of possibility for GOOGL to continue its ascent, he notes that further rallies would have to be supported by a massive amount of investor inflow.
“Could the stock go to $400 or higher? Sure. But that’s another $1T in market cap. At this scale, you have to start framing upside differently.”
For Freedman, the original valuation gap that motivated the top-pick call is now gone, and the remaining upside depends on forecasts for bigger future profits. At current valuations, he says Google has been rerated to fair value, and the easy money is gone.
“On valuation (risk/reward), we are staying disciplined:
Our ~$325 fair value is based on ~$20 EPS × 25x = $500 in ’29/’30, discounted back at 10%.
We think $20 EPS could arrive in CY29 (→ $342) vs. Street at CY30 (→ $310). Either way, the mispricing we saw entering 2025 has largely closed.
What’s left to drive upside from here?
1) Multiple expansion
2) More aggressive modeling assumptions.”
Freedman stresses that he is still optimistic about Google’s long-term direction but says discipline requires shifting focus as growth comparisons turn more difficult in the second half of 2026.
Hedgeye’s decision to cut GOOGL from its top picks comes as institutions take note of Google’s full-stack AI approach. Cathie Wood’s ARK Invest recently put out a note, saying that Google can be a dominant force in the AI model race, as it is the only hyperscaler that controls its own frontier models, agentic layer, training infrastructure, compiler and software stack, data centers, accelerators and cloud distribution.
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