> ## Documentation Index > Fetch the complete documentation index at: https://docs.cf0.ai/llms.txt > Use this file to discover all available pages before exploring further. # Bricks Beat Bytes > Walkthrough of the 2026 HALO thesis — a cf0 research note arguing physical infrastructure beats AI software, assembled end-to-end in Lab with cited figures. **By Filippo Cagliero** · cf0 Chief Strategy Officer\ **Published** 8 May 2026 · [cf0research.substack.com](https://cf0research.substack.com/p/bricks-beat-bytes-the-2026-halo-trade) This is a real cf0 research note, produced inside Lab by cf0's CSO and published on Substack. Filings, macro data, and market series all flowed through one thread; every figure carries a citation back to its source. **Conviction statement.** *"The physical infrastructure — power, cooling, aerospace, defense, rail — is underowned, undervalued, and entering a multi-year capex cycle with sovereign backing."* ## The HALO thesis in one chart A structural rotation toward companies whose moats rest on heavy physical assets — assets that take decades to replicate and cannot be coded away. The risk-return scatter below frames the case: HALO names cluster top-left (better risk-adjusted return than the AI basket), while a handful of AI names sit further right on the volatility axis. Risk-return scatter — HALO vs AI vs Market For portfolio managers, the basket offers valuation relief from stretched AI names while capturing the infrastructure tailwinds that underpin long-term productivity. Goldman Sachs' asset-heavy basket has outperformed asset-light peers by \~35% since the start of 2025, with the spread accelerating \~25 percentage points since November 2025. ## The six themes powering it The note decomposes the thesis into six themes, each with a near-term momentum score and a 2027 durability read. Concentration risk is flagged where a theme leans heavily on a single name. HALO themes — momentum / durability / concentration risk table The macro backdrop favours all six: $900.6B in authorised US defence spending for 2026, NATO's 5%-of-GDP-by-2035 commitment (~$2.7T cumulative), and \~\$1.5T of hyperscaler AI infrastructure capex through 2026 — which itself flows to power generation, cooling, land, and steel rather than software. ## How each name maps across themes The heatmap below scores fourteen HALO names against the six themes — useful for spotting where exposure concentrates (defence platforms is heavy across LMT / NOC / KTOS / AVAV / RTX / HII / GEA / LOAR / TDG) and where it doesn't (energy infra has one name; logistics & rail has three). HALO thematic exposure matrix — 14 names across 6 themes ## What this used This note used every part of cf0: * **SEC + global filings** — 10-Ks and 10-Qs for each HALO and AI name, pulled and parsed. * **Lab** — the surface where the thesis was framed; one thread held the macro setup, the screener output, the per-name tearsheets, the scenario sensitivity, and the chart inputs. * **Skills** — recurring research moves bound to a slug, so the same scenario / sensitivity passes can be re-run on a new ticker in one command. * **Reports** — the polished output exported as a branded PDF before publication to Substack. Every figure cites its source. Macro spending numbers trace to the NDAA appropriations text and NATO Hague Summit Declaration; ETF mechanics to the Roundhill prospectus on SEC EDGAR; per-name returns to public market data. ## Read the full note **Full report — 8 May 2026 · cf0 research** Conviction statement, macro setup, theme-by-theme deep dive, LOHA ETF mechanics, fourteen company tearsheets, scenario sensitivity, and follow-up questions. Open on Substack. ## Next walkthrough → [Fertilizer supply chain](/examples/fertilizer-supply-chain) — a sector ecosystem analysis from cf0 research.