Medubaris Research

Truck & Van CapEx Inventory Pressure Index Methodology

Purpose

The Truck & Van CapEx Inventory Pressure Index (TVCI) measures physical inventory pressure across U.S. commercial vehicles. By isolating work-focused trims and configurations, the signal provides an observational framework for commercial asset inventory conditions that may indicate changes in capital expenditure (CapEx) patterns across construction, delivery, trades, logistics, and agriculture.

TVCI does not predict capital expenditure. It observes the accumulation and clearing of commercial capital assets. Any downstream CapEx implications are secondary research hypotheses requiring independent validation.

What TVCI Measures

TVCI tracks the physical residue of business capital investment decisions. In commercial operations, light-duty work trucks, heavy-duty utility trucks, and cargo vans are essential productive assets. When businesses delay or reduce capital investment, new vehicles accumulate on dealer lots, increasing inventory pressure. Conversely, during periods of business expansion, these assets clear quickly, reducing inventory pressure.

The framework enforces strict filters to isolate commercial-only demand:

  • Work-Only Pickups: Includes only base utility trims (e.g., Ford XL, Chevy WT, GMC Pro, Ram Tradesman). Excludes consumer-facing luxury and sport-themed trims (e.g., Lariat, Denali, High Country, Big Horn).
  • Cargo-Only Vans: Includes cargo configurations, cab chassis, and cutaways (e.g. Ford Transit Cargo, Mercedes-Benz Sprinter Cargo, Ram Promaster Cargo). Excludes passenger and crew configurations.
  • Heavy-Duty Aggregates: Heavy-duty trucks (F-250/350, 2500/3500) are included as entire model aggregates because their purchase behavior is overwhelmingly commercial.

Construction Process

TVCI converts raw inventory counts into a structured index through five stages:

  1. Ingestion & Registry Filtering: Raw observations are joined with a configuration-driven vehicle registry (tvci_vehicle_registry) containing start/end effective dates, sector mappings, and importance weights.
  2. Dynamic Source Blending: Observations from multiple sources (OEM, WTS API, Comvoy, MarketCheck, etc.) are combined using weights managed in a central source registry (tvci_source_registry).
  3. Statistical Normalization: Raw counts are transformed into standardized deviations (Z-scores) relative to their own rolling 8-week momentum and 52-week structural anchor baselines.
  4. Weighted Aggregation: Model-level consensus Z-scores are aggregated to composite and sector-level features using registry-defined importance weights.
  5. Observational Metadata: Exposes completeness indicators (coverage_ratio and sensor_availability_ratio) to ensure signal transparency.