Why Daniel Ives is getting more bullish on Nvidia after GTC?

Nvidia moved higher in pre-market trading after CEO Jensen Huang’s GTC keynote presented a larger-than-expected view of the AI infrastructure market. Prominent analysts, including Wedbush's Daniel Ives, echoed the bullish stance, saying Nvidia sits at the center of an accelerating AI spending cycle, supporting upside for the stock and the AI infrastructure segment.

Analysis

Nvidia’s bigger-than-expected TAM reframing accelerates an already tight cascade: more GPU orders -> TSMC/ASML wafer priority -> higher lead times and pricing power for cutting-edge node capacity. Expect a 3–9 month cadence effect where foundry allocation shifts materially toward Nvidia-led designs, crowding out other compute-hungry customers and increasing spot prices for advanced packaging and HBM memory by ~10–20% versus non-AI baselines.

Second-order winners include advanced toolmakers and memory suppliers (ASML, LRCX, MU) and networking/telemetry stacks that convert GPU racks into usable clusters (Mellanox-like IP, DPUs). Conversely, laggards are companies relying on general-purpose x86 scale-up rather than scale-out GPU economics—large legacy CPU vendors and some software vendors with heavy on-prem CPU licensing exposure will face margin compression as customers accelerate cloud/GPU migrations.

Key risks: (1) demand pull-forward/inventory correction over 3–9 months if enterprises overbuy in H1 and later right-size; (2) model-level efficiency gains (quantization, sparsity) that can reduce GPU requirements over 12–36 months; (3) geopolitical export controls that cap addressable China revenue and could bifurcate supply chains within 6–18 months. Any of these can flip sentiment rapidly and compress multiples that currently price near convex growth assumptions.

From a time-horizon lens, tradeable alpha concentrates in the 3–12 month window (supply-cycle & order visibility), while position-making for fabs and tools is a 12–36 month structural call. Monitor weekly foundry allocation signals, HBM spot spreads, and cloud vendors’ capex commentary as proximal catalysts.

Key Decisions for Investors

• Long NVDA via a 9–12 month call spread (buy 12-month ATM call, sell 12-month 30–40% OTM call) sized to 1–2% AUM. Rationale: captures continued TAM re-rating while capping premium paid; target 2.5x upside if GPU orders sustain, max loss = premium (~1% AUM).
• Pair trade: go long NVDA (cash or Jan-2027 LEAP) and short INTC (equal dollar notional) over 6–12 months. Rationale: captures node/time-to-market advantage and cloud GPU mix; stop-loss if NVDA underperforms S&P by >15% in 30 days. Expect 1.5–3x asymmetric payoff if Nvidia demand persists, limited by macro risk.
• Initiate a 12–24 month overweight in ASML (or TSMC/TSM) via 18-month calls or cash, 1–2% AUM. Rationale: tool/foundry capacity is the choke point; upside if node allocation stays skewed. Hedge with a 6–12 month put on NVDA equal to 30% notional to protect against demand pull-forward shock.
• Tactical hedge: buy 2–3 month NVDA puts (5–10% notional) or an S&P tail hedge into the next quarterly earnings/capex cycle to protect against rapid sentiment reversal driven by inventory corrections or export-control headlines.