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#ShareYourUSStocksWinNvidia Can AI Stocks Outperform in H2 2026?
Format: Scenario Analysis with Probability Weighting
H2 2026 AI STOCK OUTLOOK: THREE SCENARIOS FOR THE SECOND HALF
The first half of 2026 has delivered extraordinary returns for AI infrastructure names, with memory chip suppliers leading gains exceeding 300% in some cases. As we enter the second half, three distinct scenarios frame the risk-reward calculus for AI equity exposure.
**SCENARIO A: CONTINUED DOMINANCE (Probability: 45%)**
AI stocks maintain outperformance through sustained earnings beats and upward guidance revisions. Supporting factors include:
- Corporate AI adoption accelerating beyond pilot phases into production deployment
- Hyperscaler capex commitments remaining elevated ($500+ billion industry-wide per Goldman Sachs estimates)
- Memory supply constraints (HBM, DDR5) persisting through 2027, supporting pricing power
Under this scenario, AI infrastructure names deliver 20-35% additional returns in H2, though volatility increases as valuations compress marginal upside.
SCENARIO B: ROTATION & CONSOLIDATION (Probability: 40%)
The June 2026 selloff marks the beginning of a broader rotation rather than a temporary pullback. Characteristics include:
- Profit-taking in extended hardware names flows into AI application/software layers
- Valuation compression as earnings growth fails to match elevated multiples
- Institutional rebalancing toward "AI beneficiaries" rather than "AI enablers"
This scenario implies flat to +10% returns for hardware-centric AI names, with significant dispersion based on individual execution.
SCENARIO C: CORRECTION ACCELERATION (Probability: 15%)
A more severe repricing occurs if:
- Evidence emerges that AI capex is generating insufficient revenue returns
- Macroeconomic conditions (rates, dollar strength) deteriorate disproportionately impacting growth multiples
- Regulatory developments constrain AI deployment timelines
This tail risk scenario implies 15-25% drawdowns from June levels for the most extended names.
Positioning Implication: The probability-weighted expected return remains positive, but risk-adjusted position sizing and selective exposure to names with near-term earnings catalysts becomes critical.
Format: Supply Chain Architecture Diagram + Tier Analysis
BEYOND NVIDIA: THE AI INFRASTRUCTURE ECOSYSTEM EXPANDING IN 2026
As the AI trade broadens beyond the headline GPU leader, sophisticated investors are mapping the complete infrastructure stack to identify underappreciated beneficiaries. The June 2026 market dynamics have accelerated rotation into these five critical ecosystem players.
BROADCOM (AVGO) — Custom Silicon Leadership
Broadcom's custom AI chip business represents the most direct threat to Nvidia's dominance. The company's partnerships with Google (TPU v6/v7), Meta, and Microsoft position it as the architect of hyperscaler-specific silicon. Goldman Sachs estimates 70% cost-per-token reduction as Google's TPU evolves, directly challenging Nvidia's pricing power. With 60% projected market share in AI Server Compute ASIC design by 2027, Broadcom's moat extends beyond commodity components.
ADVANCED MICRO DEVICES (AMD) — The Alternative Compute Layer
AMD's MI300X accelerators have gained meaningful traction against Nvidia's H100/H200 series, particularly among cost-conscious cloud providers. The company's CPU-GPU integration strategy and open software ecosystem (ROCm) appeal to customers seeking vendor diversification. Year-to-date outperformance reflects institutional recognition of AMD's execution improvement.
SUPER MICRO COMPUTER (SMCI) — AI Server Assembly
As the leading AI-optimized server manufacturer, Super Micro captures value from the physical infrastructure buildout. The company's liquid-cooling leadership and rapid product cycles align with hyperscaler demand for dense, efficient compute deployments. Revenue growth has outpaced traditional server OEMs by multiples.
TAIWAN SEMICONDUCTOR (TSM) — The Foundry Bottleneck
TSMC manufactures virtually all leading-edge AI chips, including Nvidia's GPUs, AMD's accelerators, and Broadcom's custom silicon. The company's 3nm and advanced packaging capacity constraints create pricing power and visibility through 2027. While local competitors like MediaTek have outperformed recently, TSMC's technology leadership in sub-3nm nodes remains unchallenged.
ARISTA NETWORKS (ANET) — Data Center Connectivity
Arista's ethernet switching dominance in AI training clusters addresses the critical interconnect bottleneck as model sizes scale. The company's 400G/800G deployment momentum with hyperscalers positions it as the networking layer beneficiary of AI infrastructure expansion.
Investment Thesis: These five names represent the "picks and shovels" infrastructure layer companies enabling AI deployment regardless of which algorithmic approaches ultimately dominate.