# Market Thesis Research Bundle

Question: Given the AI-led equity wealth effect and still-low household savings, will U.S. luxury and high-end discretionary spending stay resilient enough to offset fuel and borrowing-cost pressure through the next two earnings cycles?

What this bundle is: a reasoning and monitoring scaffold. It organizes public evidence into observations, claims, uncertainty branches, thresholds, and a watch plan.

What this bundle is not: primary evidence, live market data, trade advice, or a substitute for official, live, or current web sources.

Core tension: Given the AI-led equity wealth effect and still-low household savings, will U.S. luxury and high-end discretionary spending stay resilient enough to offset fuel and borrowing-cost pressure through the next two earnings cycles?

Current inference to verify: {'stance': 'conditional_yes', 'summary': 'The current inference is that premium-end spending can likely remain resilient enough to partially offset fuel and borrowing-cost pressure through the next two earnings cycles, but not with enough breadth to make the category fully insulated. The support is concentrated in higher-income, market-exposed households and in a handful of strong category leaders, so the thesis depends on continued equity strength and the absence of a new fuel or credit shock.', 'confidence': 0.66, 'verification_boundary': 'next retail-sales releases, luxury/discretionary earnings, and consumer-spending commentary over the next two earnings cycles', 'basis_claim_ids': ['nc_1', 'nc_2', 'nc_3', 'nc_4', 'nc_5']} Treat this as a hypothesis that must be refreshed against live official sources, not as a signal.

How to use: read `source_priority.json` first, refresh sources in `live_verification_plan.json`, then use `fact_inference_split.json`, `thresholds.json`, and `watch_schedule.json` to decide what changed. Do not infer buy/sell/hold, position sizing, execution, or asset-price direction from this artifact.