# Commodities Fundamentals > A Claude skill from brainbytes-dev/everything-claude-trading. - **Type:** Skill - **Install:** `agentstack add skill-brainbytes-dev-everything-claude-trading-commodities-fundamentals` - **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior - **Seller:** [brainbytes-dev](https://agentstack.voostack.com/s/brainbytes-dev) - **Installs:** 0 - **Category:** [Finance & Payments](https://agentstack.voostack.com/c/finance-and-payments) - **Latest version:** 0.1.0 - **License:** MIT - **Upstream author:** [brainbytes-dev](https://github.com/brainbytes-dev) - **Source:** https://github.com/brainbytes-dev/everything-claude-trading/tree/main/skills/macro/commodities-fundamentals ## Install ```sh agentstack add skill-brainbytes-dev-everything-claude-trading-commodities-fundamentals ``` Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent. ## About # Commodities Fundamental Analysis ## When to Activate - Analyzing commodity futures term structure (contango, backwardation) and roll yield - Evaluating supply-demand balances for energy, metals, or agricultural commodities - Understanding seasonal patterns and their trading implications - Assessing inventory data, OPEC dynamics, and production economics - Building commodity-based macro views or trading strategies ## Core Concepts ### Futures Term Structure **Contango:** - Longer-dated futures > near-term futures > spot price - Normal state for storable commodities (reflects storage costs + financing) - Rolling long positions incurs negative roll yield (sell cheap front, buy expensive back) - Example: WTI crude often in contango during oversupply (front month depressed) **Backwardation:** - Spot > near-term futures > longer-dated futures - Indicates tight current supply or strong immediate demand - Rolling long positions earns positive roll yield (sell expensive front, buy cheap back) - Historically, commodities in backwardation have higher total returns **Cost of Carry Model:** ``` F(T) = S * exp((r + c - y) * T) Where: F(T) = futures price at time T S = spot price r = risk-free rate c = storage cost (% of commodity value) y = convenience yield (benefit of holding physical) Contango when: r + c > y (storage costs exceed convenience yield) Backwardation when: y > r + c (strong convenience yield / tight supply) ``` **Convenience Yield:** - Benefit of holding physical commodity vs futures contract - High during supply disruptions, low inventories, strong immediate demand - Unobservable directly — implied from futures curve - Spikes during crises: oil refinery outages, grain droughts, metal supply shocks ### Roll Yield **Definition:** Profit or loss from rolling futures contracts before expiry. ``` Roll yield = (F_near - F_next) / F_near * (365 / days_between_contracts) Contango: roll yield is negative (rolling costs money) Backwardation: roll yield is positive (rolling earns money) Impact on total return: Total return = spot return + roll yield + collateral yield - Spot return: change in the front-month futures price - Roll yield: gain/loss from rolling contracts - Collateral yield: interest earned on margin collateral Example: If spot return = +10%, roll yield = -8%, collateral yield = +3% Total return = +5% (roll yield ate most of the spot appreciation) ``` ### Commodity-Specific Supply-Demand **Crude Oil:** ``` Supply sources: - OPEC production (voluntary quotas, spare capacity) - US shale (responsive to price, breakeven ~$40-60/bbl WTI) - Non-OPEC conventional (declining in many regions) - Strategic Petroleum Reserves (government releases) Demand drivers: - Global GDP growth (1% GDP growth ≈ 0.5% oil demand growth) - Transportation fuel (70% of demand) - Petrochemicals and industrial use - Seasonal: peak driving season (June-August), heating oil (winter) Key data releases: - EIA Weekly Petroleum Status Report (Wednesdays, 10:30 ET) - API Weekly Inventory Report (Tuesdays, 4:30 PM ET) - OPEC Monthly Oil Market Report - IEA Oil Market Report ``` **Gold:** ``` Drivers (not standard supply-demand): - Real interest rates (negative correlation: lower real rates -> higher gold) - USD strength (inverse relationship) - Central bank purchases (structural demand, particularly EM central banks) - Geopolitical risk / safe haven demand - Inflation expectations (gold as inflation hedge narrative) - Mine supply: ~3,500 tonnes/year, relatively stable (long lead times) - AISC (all-in sustaining cost): ~$1,200-1,400/oz industry average Framework: Gold = f(real_rates, USD, risk_sentiment, CB_demand) ``` **Copper:** ``` "Dr. Copper" — proxy for global industrial activity Supply: concentrated in Chile, Peru, DRC (political risk) Demand: construction (25%), electronics (25%), transportation (12%) China accounts for ~55% of global copper demand Lead times: new mines take 10-15 years from discovery to production Key indicators: - China PMI (especially manufacturing) - LME warehouse inventories - Shanghai bonded warehouse stocks - TC/RC (treatment/refining charges) — smelter economics - Scrap availability and pricing ``` **Natural Gas:** ``` Highly seasonal and regional (not a global commodity): - Henry Hub (US): linked to domestic supply/demand - TTF (Europe): linked to LNG imports, pipeline flows, storage - JKM (Asia): linked to LNG spot market Storage cycle: - Injection season: April-October (build inventories) - Withdrawal season: November-March (draw inventories) - EIA storage report (Thursdays, 10:30 ET): key weekly catalyst US supply revolution: shale gas made US net exporter (LNG) Weather dominance: extreme cold/heat drives short-term price moves ``` ### Seasonal Patterns **Energy:** - Crude: tends to strengthen in spring (refinery maintenance ends, driving season approaches) - Natural gas: peaks in winter (heating demand), secondary peak in summer (cooling) - Gasoline: crack spread widens before Memorial Day, narrows after Labor Day **Agriculture:** - Grains: "sell in May, buy in November" reflects Northern Hemisphere planting/harvest cycle - Soybeans: weather market June-August (US growing season), South American harvest Jan-April - Weather premium builds during key growth periods (pollination for corn: mid-July) **Metals:** - Gold: tends to be strong in Q1 and Q3 (Indian wedding season, Chinese New Year demand) - Copper: seasonal strength in Q1 (Chinese restocking post-Lunar New Year) - Aluminum: relatively flat seasonality, driven more by energy costs ### Inventory Analysis **Interpretation Framework:** ``` Inventories falling + rising prices = demand-driven rally (bullish, sustainable) Inventories falling + falling prices = supply disruption being resolved (neutral) Inventories rising + falling prices = demand destruction (bearish) Inventories rising + rising prices = speculative hoarding (unstable, reversal risk) Key inventory data: - EIA crude inventories (US): weekly - LME warehouse stocks (metals): daily - COMEX warehouse stocks (gold, silver, copper): daily - USDA crop stocks reports (agriculture): quarterly - IEA OECD commercial inventories: monthly ``` ## Methodology ### Supply-Demand Balance Construction 1. **Map supply sources** — production by country/region, growth rates, spare capacity 2. **Estimate demand** — by sector and region, sensitivity to GDP and price 3. **Calculate balance** — surplus (supply > demand) or deficit (demand > supply) 4. **Project inventories** — cumulative balance shows inventory build or draw 5. **Compare with market pricing** — is the curve pricing in the fundamental balance? 6. **Identify catalysts** — what could shift the balance (weather, OPEC decision, sanctions)? ### Term Structure Trading ``` Strategies based on curve shape: 1. Calendar spread (time spread): - Long near-month, short deferred month (bullish on backwardation) - Risk-defined: max loss is spread between contracts - Lower margin than outright positions 2. Curve flattener/steepener: - Trade the shape of the curve beyond just front-back - Example: long 3-month, short 12-month if expecting tightening 3. Crack spread (oil): - Long crude, short refined products (gasoline, diesel) - Measures refining margin - 3:2:1 crack = 3 bbls crude vs 2 bbls gasoline + 1 bbl diesel 4. Crush spread (soybeans): - Long soybeans, short soybean meal + soybean oil - Measures processing margin ``` ### OPEC Analysis ``` Key variables: 1. Compliance with quotas (historically imperfect; cheat during low prices) 2. Spare capacity (meaningful only if >2 Mb/d; below that, market is tight) 3. Fiscal breakeven prices (Saudi: ~$80/bbl, Russia: ~$70/bbl, UAE: ~$65/bbl) 4. Internal politics (Saudi vs UAE on production levels) 5. OPEC+ cohesion (non-OPEC members like Russia have different incentives) Assessment framework: - If prices $100: pressure to increase production (but spare capacity limits response) - If non-OPEC supply growing fast: OPEC loses pricing power - Watch for: emergency meetings, bilateral discussions, ministerial statements ``` ## Examples ### Example 1: Crude Oil Contango Trade (Storage Play) ``` Situation: - WTI front month: $45/bbl - WTI 12-month: $55/bbl - Contango: $10/bbl (22% annualized) - Storage cost: $5/bbl for 12 months (tank space available) - Financing: $2/bbl (interest on commodity value) Trade: Cash-and-carry arbitrage - Buy physical crude at $45 - Store for 12 months (cost: $5) - Sell 12-month futures at $55 - Total cost: $45 + $5 + $2 = $52 - Guaranteed profit: $55 - $52 = $3/bbl (6.7% on capital, risk-free) Constraint: requires physical storage access (tank farms, tankers) At scale: this trade was massively profitable in 2020 COVID oversupply ``` ### Example 2: Copper Demand Signal ``` Indicators: - China manufacturing PMI: 52.5 (expansionary, rising) - LME copper inventories: declining for 8 consecutive weeks - Shanghai bonded warehouse stocks: near 5-year lows - Copper term structure: shifting from contango to backwardation - Chile production: -5% YoY (water restrictions, grade decline) Assessment: - Strong demand (China PMI) + constrained supply (Chile) + low inventories - Fundamental deficit emerging - Backwardation confirms physical tightness Trade: Long copper futures (3-month LME or COMEX) Entry: $8,500/tonne Target: $9,500/tonne (supply deficit pricing) Stop: $8,000/tonne (demand slowdown invalidation) Roll yield: positive (backwardation) ``` ### Example 3: Natural Gas Seasonal Trade ``` Setup (September): - Henry Hub: $2.50/MMBtu - Storage: 3,200 Bcf (5% above 5-year average) - Weather forecast: La Nina pattern (colder than normal winter expected) - Production: flat YoY (drilling activity stable) Historical pattern: - Gas rallies Oct-Jan 65% of years - La Nina winters produce 10-15% above-average heating demand - Average Oct-Jan rally: +25% Trade: Long January natural gas futures Entry: $2.50 Target: $3.50 (40% upside if cold winter materializes) Stop: $2.20 (warm forecast shift, bearish for position) Size: 2% portfolio risk (volatile market, wide stops needed) Risk: above-average storage provides buffer against supply tightness Mild winter would cap upside and potentially break support ``` ## Quality Gate Before trading commodities on fundamentals, verify: - [ ] Supply-demand balance is sourced from multiple data providers (IEA, EIA, OPEC, USDA, industry reports) - [ ] Inventory data is current and correctly interpreted (absolute level vs rate of change vs seasonal norm) - [ ] Term structure shape is understood and roll yield is factored into expected return - [ ] Seasonal patterns are contextualized — do fundamentals support or contradict the seasonal tendency? - [ ] OPEC or cartel dynamics assessed — for energy, OPEC decisions can override fundamentals - [ ] Weather risk is acknowledged — agricultural and gas trades are heavily weather-dependent - [ ] Position sizing accounts for commodity volatility (crude: ~30% annualized, nat gas: ~50%, grains: ~25%) - [ ] Physical market nuances understood — grades, delivery points, quality premiums, transportation costs - [ ] Geopolitical risk priced in — sanctions, wars, export bans can disrupt supply suddenly - [ ] Correlation with macro portfolio considered — commodities often correlate with inflation and growth expectations ## Source & license This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code. - **Author:** [brainbytes-dev](https://github.com/brainbytes-dev) - **Source:** [brainbytes-dev/everything-claude-trading](https://github.com/brainbytes-dev/everything-claude-trading) - **License:** MIT Install and usage instructions live in the source repository linked above. ## Pricing - **Free** — Free ## Security capabilities Automated source analysis of v0.1.0 — what this tool can access: - **Network access:** no - **Filesystem access:** no - **Shell / process execution:** no - **Environment & secrets:** no - **Dynamic code execution:** no *"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.* ## Versions - **0.1.0** — security scan: passed — Imported from the upstream source. ## Links - Listing page: https://agentstack.voostack.com/l/skill-brainbytes-dev-everything-claude-trading-commodities-fundamentals - Seller: https://agentstack.voostack.com/s/brainbytes-dev - Browse the marketplace: https://agentstack.voostack.com/browse --- Listed on AgentStack — the marketplace for AI agent skills and MCP servers. 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