The compute, networking, memory, storage, and power layer of the AI buildout. Owners of the bottlenecks: accelerators, custom silicon, switching, optics, HBM, fab equipment, test, and the server/power chain that turns capex into installed compute.
Basket total returns · Annualized using 252 trading sessions · 0% risk-free rate and downside target. As of 2026-10-21 · close.
How these statistics are calculated
Risk methodology
Sharpe: average daily simple return divided by its sample standard deviation, multiplied by √252. The risk-free rate is assumed to be 0%; this is not a cash-adjusted ratio.
Sortino: average daily simple return divided by downside deviation, multiplied by √252. Downside deviation is the square root of the average squared shortfall below 0%, counting all sessions, including zeros for gains.
Historical volatility: √(252 × average squared daily log return), matching the Vol page’s realized-volatility convention. This differs from the sample standard deviation used in Sharpe.
Each period requires complete history and at least 5 sessions. MTD and YTD follow the calendar; 1y is 252 sessions. Missing data or an undefined ratio displays — with a reason. Short periods can produce unstable ratios; intraday snapshots include a partial session. History before this basket’s creation is backtested. If a new basket has no stored daily return series yet, estimates from its rounded published chart levels are marked ≈.
Basket returns include dividends. “vs FW 3000” compares the basket’s compounded growth with the benchmark’s. Green means positive; red means negative.
Cross-checked against SMH. Daily return correlation: 0.94 across 1710 sessions. semiconductor-only proxy; the basket’s networking, storage, and power names sit outside it
Membership history & changes
Membership history
expand
MRVL joined the S&P 500 and moves from broad-only to both universes (reverse of the ZION/MOH/MHK pattern): broad entry closed, untagged entry added same-day. The S&P version gains a member; the FW 3000 version is unchanged.
correction
FN and CRDO removed — never FW 3000 constituents (offshore-domiciled, screened out of the universe), so the 2026-06-12 broad pass added them in error; the pipeline has flagged both as missing/ex-universe since. Entries deleted outright rather than closed with a removed date: neither ever had tape, so no computed history is restated. Optics coverage continues via COHR, CIEN, GLW, MTSI and the new optics-memory basket.
expand
FW 3000 pass: added MRVL, CRWV, ALAB, CRDO, MOD, ONTO, MTSI, FN — names outside the S&P 500 but inside our broad universe; they count only in the FW 3000 version of this basket. Effective-dated to creation so the broad backtest covers the full set. The S&P 500 basket is unchanged.
expand
Widening pass: added the optics/networking leg (COHR, CIEN, GLW), storage (WDC, STX), test and materials (TER, Q), power silicon (MPWR), and server manufacturing (SMCI, JBL). Reference pinned to SMH — semis-only, so expect high but not perfect tracking. New members are effective-dated to basket creation so the backtest and the reference correlation cover the widened set (the basket was one day old, with no meaningful live history to restate).
correction
MRVL removed: not an S&P 500 constituent (basket rule violation at creation); custom-silicon exposure remains via AVGO.
create
Initial composition: 12 names across compute, networking, memory, equipment, power.
The optical layer of the AI buildout: datacom transceivers, the lasers and photonic components inside them, optical transport and data-center interconnect, and the fiber it all runs on. Every networking generation pushes optics deeper into the rack, so unit growth compounds even when GPU spend plateaus — the volume trade next to Memory & Storage's price trade.
Where AI capex meets the tightest physical supply limit: HBM/DRAM, NAND and data-center disk. Sold-out capacity, multi-year supply agreements and an oligopoly structure concentrate pricing power in the memory makers — the shortage trade inside the AI buildout, tracked separately from the optical chain so each supply cycle reads clean.
S&P 500 business models on the wrong side of AI: seat-based IT services and outsourcing, ad agencies, and data/research vendors whose products LLMs increasingly substitute. A monitoring basket (potential underperformers / hedge candidates), not a buy list. Small by design — most pure displacement stories live outside the index.