# CommodityNode

> CommodityNode is an independent commodity intelligence platform that maps how raw material price movements ripple through industries, stocks, and ETFs. It covers 60+ commodities with interactive Impact Maps, quantified sensitivity scores, and Signal Reports published when price moves create actionable intelligence.

CommodityNode is built for equity investors, portfolio managers, macro traders, supply chain professionals, and researchers who need to understand the second-order effects of commodity price changes. Core content is free; advanced AI forecasting tools and the Scenario Simulator are available via Pro subscription.

## Key Pages

- [About CommodityNode](https://commoditynode.com/about/): Platform overview, founder credentials, editorial standards, and coverage scope
- [Methodology](https://commoditynode.com/methodology/): How impact scores, correlations, sensitivity ratings, and confidence levels are calculated
- [Pricing](https://commoditynode.com/pricing/): Free vs Pro subscription comparison
- [Contact](https://commoditynode.com/contact/): Editorial inquiries, corrections, and partnerships

## Commodity Hub Pages (Impact Maps)

Each commodity hub page includes: an interactive Impact Map (D3.js), quantified impact scores for related stocks and ETFs, correlation coefficients, a Key Impact Relationships table, and curated Signal Reports.

- [Gold](https://commoditynode.com/commodities/gold/): Safe-haven dynamics, miners (NEM, GOLD, AEM), GDX/GLD ETFs, central bank flows
- [Crude Oil](https://commoditynode.com/commodities/crude-oil/): OPEC policy, airline margins, refiner spreads, XLE/XOP ETFs
- [Copper](https://commoditynode.com/commodities/copper/): EV demand, infrastructure buildout, FCX/SCCO, COPX ETF
- [Silver](https://commoditynode.com/commodities/silver/): Solar panel demand, industrial use, SLV ETF
- [Natural Gas](https://commoditynode.com/commodities/natural-gas/): LNG exports, utility margins, UNG ETF
- [Lithium](https://commoditynode.com/commodities/lithium/): EV battery supply chain, Albemarle (ALB), SQM
- [Uranium](https://commoditynode.com/commodities/uranium/): Nuclear energy policy, Cameco (CCJ), URA ETF
- [Wheat](https://commoditynode.com/commodities/wheat/): Food inflation, agricultural supply chains, WEAT ETF
- [Aluminum](https://commoditynode.com/commodities/aluminum/): Automotive, packaging, Alcoa (AA), CENX
- [Steel](https://commoditynode.com/commodities/steel/): US tariff policy, Cleveland-Cliffs (CLF), Nucor (NUE), SLX ETF
- [Nickel](https://commoditynode.com/commodities/nickel/): EV battery cathodes, stainless steel, Indonesian supply
- [Cobalt](https://commoditynode.com/commodities/cobalt/): Battery supply chain, DRC concentration risk
- [Platinum](https://commoditynode.com/commodities/platinum/): Hydrogen fuel cells, autocatalysts, PPLT ETF
- [Palladium](https://commoditynode.com/commodities/palladium/): Gasoline autocatalysts, EV substitution risk
- [Iron Ore](https://commoditynode.com/commodities/iron-ore/): Steel production input, Vale (VALE), Rio Tinto (RIO)
- [Coal](https://commoditynode.com/commodities/coal/): Power generation, thermal vs metallurgical split
- [LNG](https://commoditynode.com/commodities/lng/): Global gas trade, European energy security
- [Corn](https://commoditynode.com/commodities/corn/): Ethanol demand, livestock feed, CORN ETF
- [Soybeans](https://commoditynode.com/commodities/soybeans/): China trade flows, oilseed crush margins, SOYB ETF
- [Coffee](https://commoditynode.com/commodities/coffee/): Climate supply risk, consumer staples margin impact
- [Iridium](https://commoditynode.com/commodities/iridium/): PEM electrolyzer catalyst, green hydrogen bottleneck
- [Rare Earth](https://commoditynode.com/commodities/rare-earth/): EV motors, defense electronics, China export controls
- [Graphite](https://commoditynode.com/commodities/graphite/): EV battery anodes, China supply dominance
- [Vanadium](https://commoditynode.com/commodities/vanadium/): Grid-scale energy storage, steel alloying

## Signal Reports (Recent)

Signal Reports are published when commodity price moves create actionable intelligence. Each report includes directional bias, sensitivity rating, confidence level, and sector ripple analysis.

- [Trump's 50% Metal Tariffs: Steel, Aluminum, Copper (April 2026)](https://commoditynode.com/trump-steel-aluminum-copper-tariffs-april-2026/): Section 232 restructuring analysis, winners (CLF, NUE, AA), losers (auto manufacturers), inflation implications
- [Iran-Hormuz Crisis: Oil's Biggest Supply Shock (April 2026)](https://commoditynode.com/iran-hormuz-oil-shock-global-markets/): WTI at $111/barrel, airline margin destruction, refiner dynamics, scenario probabilities
- [Iridium: The Rare PGM Green Hydrogen Cannot Ignore (April 2026)](https://commoditynode.com/iridium-green-hydrogen-pem-electrolyzer-supply/): 7-8 tonne annual supply vs. 12+ tonne demand implied by EU hydrogen targets
- [Gold Breaks $5,000: Mining Stocks Impact](https://commoditynode.com/gold-breaks-5000-mining-stocks/): Producer leverage, streaming company dynamics
- [Copper Structural Deficit Analysis](https://commoditynode.com/copper-structural-deficit/): Mine development lag vs. EV and data center demand
- [Natural Gas Storage Glut and Price Collapse](https://commoditynode.com/natural-gas-storage-glut-price-collapse/): Henry Hub dynamics, utility sector impact

## Tools

- [Scenario Simulator](https://commoditynode.com/simulator/): Model commodity price scenarios and project impacts on related equities (Pro)
- [Portfolio Stress Test](https://commoditynode.com/stress-test/): Assess commodity exposure across a portfolio (Pro)
- [Range Tracker](https://commoditynode.com/range-tracker/): Monitor commodities approaching historical price extremes
- [Correlation Explorer](https://commoditynode.com/correlation/): Cross-commodity and commodity-equity correlation data

## Methodology Summary

Impact scores represent the estimated percentage price response of a related asset to a 10% move in the underlying commodity, derived from:
- Level 1 (Direct): 5-year rolling regression using weekly returns data
- Level 2 (Secondary): Supply-chain input-output relationships with hedging adjustments
- Level 3 (Tertiary): Industry-level sensitivity models capturing substitution and demand effects
- Level 4 (Macro): Historical macro-commodity transmission coefficients

Correlations are Pearson coefficients over a rolling 3-year (156-week) window, recalculated quarterly. Only correlations with p-value < 0.05 are displayed. Full methodology: https://commoditynode.com/methodology/

## Licensing

Content on CommodityNode is provided for informational purposes. Signal Reports and Impact Map data may be cited with attribution to CommodityNode (https://commoditynode.com). Nothing on this site constitutes investment advice.