commodity-analysis

Commodity market fundamentals analysis evaluates supply-demand balances, inventory cycles, and futures term structures to generate data-driven directional trading signals. It integrates macro-economic indicators and sector-specific data to synthesize fragmented market information into actionable composite scores.

Tracking inventory cycles for crude oil and copper futures involves identifying specific market stages like passive destocking to pinpoint optimal entry and exit points. This approach synthesizes disparate data points such as LME inventory levels and EIA data into a bullish or bearish composite score.

Macro-economic indicators like real interest rates and US 10Y TIPS yields are actively used for gold market analysis. The framework evaluates these specific fundamental indicators alongside inventory levels to determine the bullish or bearish bias for gold trading.

Backtesting trading strategies using EIA and OPEC production data requires a structured analytical approach to synthesize fragmented market data. This framework supports research workflows by integrating specific fundamental indicators into composite scores for evidence-based decision-making.

This commodity market analysis framework specifically supports research and backtesting workflows for crude oil, gold, and copper. It evaluates these specific assets using targeted fundamental indicators like OPEC production, real interest rates, and inventory levels.