Clare Pleydell-Bouverie 3.7 3 ideas

UBS raised its worst-case default scenario for private credit to 15%. Approximately one-third of private credit exposure is to the software sector. If AI disrupts legacy software cash flows (as per the SaaS thesis above), the lenders to these software companies (Private Credit/BDCs) will face massive impairments. Software is "asset-light," meaning recovery rates in bankruptcy will be near zero. SHORT. The "wheels are coming off" the asset class due to its exposure to disrupted tech. M&A activity picks up, allowing distressed software firms to be acquired rather than defaulting.

Hyperscaler capital expenditure growth is significantly outpacing estimates (67% actual vs. 19% estimated). Additionally, "Physical AI" (robotics, autonomous driving) is emerging as a new demand layer not yet priced in. The market views NVDA primarily as a data center stock, ignoring the "Physical AI" cycle (robots/cars needing silicon). As autonomous driving (e.g., Wayve) and robotics scale, NVDA's addressable market expands beyond just LLM training. LONG. 2026 will be a year of accelerating "beat and raise" cycles for NVDA. Supply chain constraints (sold out) or a faster-than-expected drop in software ROI.

AI allows for "Software 2.0" (accelerated compute) to displace "Software 1.0" (legacy code). New AI-native startups can compete with lower costs. Legacy SaaS companies historically commanded premium valuations (10x revenue) due to "recurring revenue" safety. AI destroys this moat, leading to margin compression (pricing power loss) and multiple compression (re-rating to 3-4x revenue). SHORT/AVOID. 90% of the software sector faces further de-rating. Indiscriminate selling creates value traps where quality proprietary data companies are oversold.