Data & Methodology
CommodityNode combines public market data, commodity reference datasets, supply-chain context, and AI-assisted research workflows to produce market intelligence and scenario analytics.
Data sources
Sources may include exchange-traded futures references, Yahoo Finance market data, government datasets such as EIA/FRED/USDA/BLS, company filings, and curated public news references.
Update cadence
Prices and model artifacts are typically refreshed daily when data providers are available. Some macro or fundamental datasets update weekly, monthly, quarterly, or irregularly.
Model outputs
Forecast ranges and consensus estimates are probabilistic scenario inputs, not instructions or promises. Model versions and source data can change over time.
Forecast horizon and uncertainty
CommodityNode may display 30/60/90-day model horizons, uncertainty bands, consensus blends, or scenario ranges. These are designed to help users frame risk and business planning questions, not to predict guaranteed market outcomes.
Data quality handling
Missing, stale, sparse, or proxy-priced data can occur. Where possible, CommodityNode labels proxy series, suppresses unreliable moves, and shows timestamps so users can evaluate freshness.
Backtests and historical context
Historical relationships are used for research context. Past performance, historical correlation, or previous scenario behavior does not guarantee future behavior.