Commodities & Futures Screener

The Commodities Rotation Model tracks the relative performance of four commodity sectors — Industrial Metals, Energy, Agriculture, and Precious Metals — to identify the current phase of the commodity supercycle. The model uses Z-score normalized relative strength against both the broad commodity index (DBC) and equities (SPY), combined with sector momentum and cross-sector correlation analysis.

Phase 1: Reflation

Industrial metals lead as economic activity begins to recover. Central banks typically maintain accommodative policy, credit conditions ease, and manufacturing PMIs inflect higher. Copper and aluminium outperform gold and energy. This phase favors cyclical equity sectors (Industrials, Materials) and emerging market currencies.

Key signals: Rising copper/gold ratio, improving Dr. Copper index, industrial metals relative strength turning positive while energy lags.

Phase 2: Expansion

Broad-based commodity demand accelerates. Energy joins the rally as economic growth becomes self-sustaining. Agricultural commodities benefit from rising input costs and consumption. Inflationary pressures build, but equities can still advance as earnings growth outpaces cost increases.

Key signals: All four sectors show positive relative strength, energy and agriculture outperform, rising crude oil prices, increasing commodity index breadth.

Phase 3: Late Cycle

Cost pressures accelerate and begin to compress margins. Energy prices spike as supply constraints bind, precious metals rally as inflation hedges, and central banks shift toward tightening. Equity markets face headwinds from rising input costs and tighter financial conditions.

Key signals: Precious metals outperform, energy remains strong but volatile, industrial metals decelerate, rising commodity/equity correlation.

Phase 4: Slowdown

Demand destruction sets in. Industrial metals decline sharply, energy corrects, and the commodity cycle resets. Precious metals may continue to outperform as safe havens. Central banks face the dilemma between fighting inflation and supporting growth. Defensive equity positioning is warranted.

Key signals: Falling copper/gold ratio, negative Dr. Copper index, industrial metals and energy underperform, declining commodity index breadth, rising gold/commodity ratio.

Confidence & Transition Risk: The model calculates a confidence score based on cross-sector agreement and momentum persistence. When sector signals diverge or momentum decelerates, transition risk increases — indicating a potential phase change within the next 4–8 weeks.

Copper is called “Dr. Copper” because of its ability to “diagnose” the health of the global economy. As a critical input for construction, manufacturing, electronics, and infrastructure, copper demand directly reflects industrial activity. Unlike gold (which rises on fear) or oil (which is supply-constrained), copper is the purest demand-side indicator among major commodities.

Rather than using raw copper prices (which are distorted by dollar strength, supply disruptions, and speculative flows), the Dr. Copper indicator uses three ratios that isolate the economic signal:

Copper / Gold Ratio

This is the most important ratio. Gold represents fear and monetary uncertainty, while copper represents industrial optimism. A rising ratio signals that growth expectations are improving relative to risk aversion. Historically, a sustained decline in this ratio has preceded every U.S. recession since 1970 by 3–9 months. The Z-score normalization captures how extreme the current reading is relative to its own history.

Copper / S&P 500 Ratio

This ratio compares physical economy demand (copper) against financial economy performance (equities). When copper outperforms equities, the real economy is strong relative to financial assets — a hallmark of genuine economic expansion rather than liquidity-driven rallies. Divergences where equities rise but copper/SPX falls often precede corrections.

Copper / Oil Ratio

Both copper and oil are industrial commodities, but oil is heavily influenced by OPEC supply decisions and geopolitics. A rising copper/oil ratio suggests demand-pull strength (real economic activity) rather than supply-push inflation. When this ratio falls, it indicates that commodity strength is driven by supply constraints rather than genuine demand growth.

Composite Dr. Copper Index

The three Z-scored ratios are combined into a composite index. Positive values indicate economic expansion, while negative values signal contraction risk. Extreme readings (>1.5 or <-1.5) historically correspond to major economic turning points. The economic signal derived from this index has correctly identified the onset of every recession and most major expansions since 2010.

COT Regime

Derived from the CFTC Commitment of Traders report. Classifies the positioning of commercial hedgers, asset managers, and leveraged funds into regimes: Risk-On (smart money building longs, speculative conviction rising), Bull (trend confirmed by positioning), Distribution (smart money reducing exposure while price remains elevated), and Liquidation (broad position unwinding, typically marking bottoms or accelerating selloffs).

Uncertainty Regime

Measures price uncertainty using a proprietary volatility model. Bullish/Bearish Trend (low uncertainty, directional conviction), Accumulation/Distribution (moderate uncertainty, transitional), Extreme Uncertainty (high volatility, avoid or reduce position size).

Market Phase

Combines price trend, momentum, and volatility into a single phase label. Identifies whether a commodity is in a trending, consolidating, or transitional state. Useful for determining which strategy (trend-following vs. mean-reversion) is appropriate.

AM & LF Percentiles

AM %ile (Asset Managers) and LF %ile (Leveraged Funds) show the current net positioning of these trader groups relative to the past 52 weeks. Extreme readings (>90th or <10th percentile) indicate crowded trades that are vulnerable to reversal.

Crowded

Flags when either asset managers or leveraged funds hold an extreme net position. Crowded longs tend to precede pullbacks; crowded shorts tend to precede short squeezes. This is a contrarian indicator best used in conjunction with other signals.

Seasonality (Season 1M)

Shows the historically expected return over the next 21 trading days, based on calendar patterns. Includes win rate and sample count for statistical reliability. Seasonal patterns are strongest in agricultural commodities (planting/harvest cycles) and energy (heating/driving seasons).

Darkpool & Short Activity

For ETF-linked contracts, shows dark pool activity ratio. Elevated dark pool activity combined with declining price can indicate institutional accumulation. High short interest creates potential for short-squeeze rallies.

Tightness

Derived from the inventory/demand balance in the Commodity Fundamentals section. Tight markets (low inventories relative to demand) support prices, while loose markets (surplus inventory) create downward pressure. Tightness is the most fundamental supply/demand indicator for physical commodities.

Pattern & Win Probability

Detects candlestick and price action patterns on the futures contract. The win probability is calculated from historical pattern performance on the specific commodity, accounting for the commodity’s unique volatility and seasonal characteristics.

Individual signals are informative but not sufficient for trade decisions. The real edge comes from signal convergence — when multiple independent data sources point in the same direction.

Step 1: Macro Filter — Rotation Phase

Start with the Commodities Rotation Model to identify which sector is in a favorable phase. Trading with the rotation cycle (e.g., buying industrial metals in Reflation, energy in Expansion) provides a structural tailwind. Avoid counter-cycle trades unless other signals are extremely compelling.

Step 2: Regime Alignment

Filter for contracts where COT Regime and Uncertainty Regime agree. A “Risk-On” COT regime combined with “Bullish Trend” uncertainty is the strongest long setup. Conversely, “Distribution” COT with “Bearish Trend” uncertainty confirms shorts. Conflicting regimes (e.g., bullish COT but high uncertainty) suggest waiting.

Step 3: Positioning & Crowding Check

Ensure the trade is not crowded against you. The highest-probability longs occur when the COT regime is bullish but positioning is not yet extreme (<80th percentile). Once AM or LF percentiles exceed 90%, the trade is consensus and vulnerable to reversal. Use crowding as a timing filter, not a direction filter.

Step 4: Seasonal Confirmation

Check whether seasonality supports the trade direction. A bullish setup with a positive seasonal pattern (especially >60% win rate over ≥15 years) adds a statistically validated tailwind. Counter-seasonal trades require stronger signals from other indicators to justify.

Step 5: Fundamentals & Tightness

For physical commodities, verify the supply/demand picture using the Commodity Fundamentals chart. Tight inventories combined with rising demand provide the fundamental underpinning for sustained rallies. Trades backed by both technical signals and fundamental tightness have the highest expected value.

Signal Convergence Scoring

A practical approach is to count the number of aligned signals:

• 5+ signals aligned: Highest conviction — full position size, wider stops
• 3–4 signals aligned: Standard setup — normal position size
• 1–2 signals aligned: Low conviction — reduced size or pass
• Conflicting signals: No trade — wait for clarity

• COT Positioning: CFTC Commitment of Traders (Traders in Financial Futures & Disaggregated reports), published weekly with a 3-day lag. Source: cftc.gov
• Futures Prices: Continuous front-month contracts from TradeNavigator (end-of-day, updated daily) with Stooq as historical backup. Source: stooq.com
• ETF Prices & Darkpool: Tiingo end-of-day data for ETF proxies; FINRA dark pool volume data. Sources: tiingo.com, finra.org
• Inventory & Supply Data: EIA weekly petroleum stocks (crude, gasoline, distillate) and EIA STEO monthly demand forecasts. USDA PSD (Production, Supply & Distribution) for agricultural commodities (corn, wheat, soybeans, cotton). Sources: eia.gov, usda.gov
• Demand Data: EIA STEO monthly demand estimates for energy (crude, natural gas, gasoline), USDA domestic consumption for agriculture, FRED Industrial Production Index (INDPRO) as demand proxy for metals (gold, silver, copper, platinum, palladium). Source: fred.stlouisfed.org
• Tightness Indicators (3 tiers):
  • Supply/Demand Tightness (Tier 1): Stocks-to-use ratio Z-score. Only for commodities with physical inventory data (energy, agriculture).
  • COT Tightness (Tier 2): Composite of COT commercial positioning Z-score (40%), price Z-score (40%), and price momentum (20%). Available for all futures with COT data.
  • Price Tightness (Tier 3): Price-only Z-score (60%) + momentum (40%). Available for all commodities as fallback.
• Commodities Rotation: Proprietary model using Z-score normalized relative strength of 4 sector sub-indices against DBC and SPY
• Dr. Copper: Proprietary composite of Copper/Gold, Copper/S&P 500, and Copper/Oil Z-scored ratios
• Uncertainty & Regime Models: Proprietary volatility-regime classification using realized volatility, trend persistence, and momentum dispersion
• Seasonality: Calculated from 15+ years of historical calendar returns per commodity