Wall Street stock picks highlight Oracle, Rocket Lab and Meta for long-term growth

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Highlights

Oracle receives a buy rating and $400 price target from Guggenheim, driven by strong cloud infrastructure revenue and declining OpenAI concentration.
Rocket Lab initiated at buy with an $80 price target by Raymond James, citing a $3 billion constellation via Iridium, 59% revenue growth in 2026, and a $2.4 billion backlog.
J.P. Morgan upgrades Meta Platforms to buy with a raised $820 price target, citing rapid frontier AI model development and monetization beyond core advertising.

Analyst calls center on cloud, space and AI growth

As reported by CNBC, the stock selections are drawn from analyst recommendations highlighted by TipRanks, which ranks Wall Street analysts by past performance. The list focuses on companies that analysts say are positioned to benefit from structural growth trends rather than near-term market swings.

Oracle is attracting support after reporting better-than-expected first-quarter fiscal 2027 results, helped by strong cloud infrastructure revenue. Guggenheim analyst John DiFucci reiterates a buy rating and a $400 price target after investor meetings with Oracle head of investor relations Ken Bond, arguing that demand for AI training, inferencing, public cloud services and AI-enabled database and application products can accelerate revenue and profit over the next few years.

DiFucci also says concerns about customer concentration are easing. He notes that OpenAI's share of Oracle's remaining performance obligations has fallen from 80% last June to about 50% now and is expected to decline further as Oracle signs additional contracts.

Rocket Lab is also winning support after Raymond James analyst Brian Gesuale initiates coverage with a buy rating and an $80 price target. He says the company is building a vertically integrated space platform spanning launch, spacecraft, components, payloads and optical communications, with the Iridium acquisition and Neutron program expected to broaden its medium-lift and applications position in 2027.

Gesuale says the Iridium deal adds a deployed constellation valued at more than $3 billion, globally coordinated L-band spectrum, about $500 million in EBITDA and $300 million in free cash flow. He also points to revenue growth of 59% in 2026, a backlog that has risen to nearly $2.4 billion from $1.1 billion in the third quarter of 2025, and improving profitability as Rocket Lab moves from investment to monetization.

Meta Platforms rounds out the list after J.P. Morgan analyst Doug Anmuth upgrades the stock to buy from hold and raises his price target to $820 from $640. He argues that Meta remains in the early stages of monetizing frontier AI models and products beyond advertising, including the Muse AI agent and Meta Model API access.

Industry implications for investors and sectors

Across the three picks, the common theme is that analysts are favoring companies with scalable platforms and expanding exposure to AI-driven or infrastructure-heavy markets. Oracle represents enterprise software and cloud capacity growth, Rocket Lab reflects investor interest in commercial space and satellite services, and Meta shows how large digital platforms are being revalued for AI product development as well as advertising resilience.

Anmuth says Meta's push into frontier models is advancing quickly, with the company moving from Muse Spark 1.1 in July to Muse Spark 1.3, which he says is competitive with Claude and GPT models. He also sees Watermelon expanding Meta's opportunity in consumer products, business intelligence and engagement across its Family of Apps, while AI infrastructure investment supports future computing demand.

For investors, the recommendations underscore a preference for companies that can translate heavy capital spending into revenue acceleration and margin expansion over several years. That approach stands out at a time when short-term macro risks continue to cloud broader market direction.

We previously reported on how major technology companies are using residual value guarantees and special-purpose vehicles to fund AI infrastructure such as data centres and advanced chips, often keeping much of the exposure off their balance sheets. The piece highlighted that these structures can reduce funding costs but add complexity to corporate credit risk, especially as AI spending outpaces cash flow and off-balance-sheet commitments grow across the sector.

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