commodity-analysis

name commodity-analysis description Commodity analysis (oil supply-demand balance / gold pricing / copper as an economic predictor / inventory cycles / futures premium-discount structure / seasonality), generating directional commodity signals. category analysis Commodity Analysis Overview Analyze commodities from four dimensions — supply-demand balance, pricing model, inventory cycle, and futures structure — and output directional signals suitable for backtesting. Focuses on crude oil (global pricing anchor), gold (safe haven + inflation hedge), and copper (economic barometer). Core Concepts 1. Crude Oil Supply-Demand Balance Key supply-side variables: Variable Data Source Frequency Direction of Impact OPEC production OPEC monthly report Monthly Production cuts → oil price ↑ US shale output EIA weekly report Weekly Higher output → oil price ↓ Rig count (Baker Hughes) Baker Hughes Weekly Leads production by 3-6 months Strategic Petroleum Reserve (SPR) EIA Weekly SPR release → short-term oil price ↓ Key demand-side variables: IEA global oil demand forecast (quarterly) China crude imports (customs monthly data) US gasoline demand (EIA weekly report, implied demand) Global PMI (leads demand by 1-2 months) Supply-demand balance signals: # Simplified supply-demand judgment if opec_compliance > 90 % and us_rig_count_declining: supply_signal = "tight" # bullish for oil elif opec_compliance < 80 % and us_production_rising: supply_signal = "loose" # bearish for oil if global_pmi > 50 and china_import_yoy > 5 %: demand_signal = "strong" # bullish for oil elif global_pmi < 48 and china_import_yoy < 0 : demand_signal = "weak" # bearish for oil 2. Gold Pricing Framework Four-factor model: Factor Weight Logic Indicator Real rates 40% Real rates ↓ → lower opportunity cost of holding gold → gold ↑ 10Y TIPS yield US dollar index 25% USD ↓ → gold becomes cheaper in pricing terms → gold ↑ DXY Safe-haven demand 20% Risk ↑ → safe-haven buying → gold ↑ VIX + geopolitical risk index Central-bank buying 15% Central-bank purchases → structural demand support WGC quarterly report Practical rules: 10Y TIPS < 0%: strong support for gold (negative real rates mean negative holding cost) 10Y TIPS > 2%: pressure on gold (positive real rates reduce attractiveness) Correlation between DXY and gold is around -0.6, but not absolute (they both rose in 2022 due to safe-haven demand) Central-bank purchases >1000 tons / year (2022-2023 level): long-term structural bullish support 3. Dr. Copper as an Economic Predictor Copper as a leading indicator: YoY copper-price change leads industrial production by about 2-3 months Copper / gold ratio is highly positively correlated with the US 10Y Treasury yield ( r > 0.7 ) Copper breakout above the prior high confirms economic recovery Copper fundamental tracking: Indicator Data Source Threshold LME copper inventory LME daily report <150k tons = tight SHFE copper inventory SHFE weekly report WoW decline >10% = tight Copper concentrate TC/RC SMM TC < $30/ton = tight mining supply China copper imports Customs monthly report YoY growth >10% = strong demand 4. Inventory Cycle Analysis Visible inventory vs hidden inventory: Visible inventory: published by exchanges (LME / SHFE / COMEX), transparent and trackable Hidden inventory: bonded areas / trader warehouses, opaque but potentially larger The true turning point in prices is the turning point in total inventory Four inventory-cycle stages (using copper as example): Active restocking (price↑ volume↑) -> Passive restocking (price↓ volume↑) -> Active destocking (price↓ volume↓) -> Passive destocking (price↑ volume↓) mid bull market late bull market mid bear market late bear / early bull market Signal mapping: Stage Inventory Direction Price Direction Trading Signal Passive destocking ↓ ↑ Long (best buying point) Active restocking ↑ ↑ Keep long positions Passive restocking ↑ ↓ Close longs (warning) Active destocking ↓ ↓ Short or stay neutral 5. Futures Premium / Discount Structure Contango (futures > spot, normal market): Supply is abundant, and the market prices in carrying costs (storage + funding) Roll yield is negative ( roll yield < 0 ), unfavorable for long holders Deep contango ( far month - near month > 5% ) = severe oversupply Backwardation (futures < spot, inverted market): Supply is tight, and spot premium reflects strong immediate demand Roll yield is positive ( roll yield > 0 ), favorable for long holders Deep backwardation ( near month - far month > 3% ) = squeeze or extreme shortage Term-structure signal: # Spread ratio = (front month - second month) / front month spread_ratio = (front_month - second_month) / front_month if spread_ratio > 0.02 : # backwardation > 2% signal = "strongly bullish" # spot shortage elif spread_ratio < - 0.03 : # contango > 3% signal = "bearish" # oversupply else : signal = "neutral" 6. Seasonality Oil seasonality: March-May: refinery maintenance ends + summer inventory build → seasonal rise (ahead of the "driving season") September-October: hurricane season (Gulf of Mexico) → supply disruption → higher volatility November-December: heating-oil demand → stronger diesel crack spread Gold seasonality: January-February: Lunar New Year + Indian wedding-season physical demand → relatively strong July-August: traditional soft season → relatively weak October-November: Diwali + Christmas restocking → relatively strong Copper seasonality: March-April: China construction season starts → demand recovery June-July: off-season inventory buildup → pressure September-October: "Golden September, Silver October" → demand recovery Analysis Framework Five-Step Commodity Analysis Supply-demand sets direction : is the balance in surplus or shortage? Which way are marginal variables moving? Inventory sets rhythm : which inventory-cycle stage are we in? Is a turning point close? Term structure confirms : contango or backwardation? Does it confirm the supply-demand judgment? Seasonality overlay : is seasonality currently a tailwind or a headwind? Macro validation : do the dollar / rates / risk appetite support the directional judgment? Composite Scoring Template commodity_score = { "supply_demand" : + 1 , # supply-demand is tight "inventory_cycle" : + 2 , # passive destocking (best stage) "term_structure" : + 1 , # mild backwardation "seasonality" : 0 , # neutral seasonality "macro_env" : - 1 , # stronger dollar is a headwind } # Total score = +3/5 = +0.6 -> bullish bias, but not a strong signal Output Format ## Commodity Analysis Report — [Commodity Name] ### Supply-Demand Structure - Supply side: [surplus / balanced / shortage] — [specific data] - Demand side: [strong / stable / weak] — [specific data] - Balance table: [inventory build X tons / drawdown X tons] ### Inventory Cycle - Current stage: [active restocking / passive restocking / active destocking / passive destocking] - Visible inventory: [LME X tons, SHFE X tons, WoW change] ### Term Structure - Front-back spread: [contango X% / backwardation X%] - Roll yield: [positive / negative] ### Composite Score | Dimension | Score(-2~+2) | Basis | |------|------------|------| | Supply-demand | +1 | OPEC compliance rate 92% | | Inventory | +2 | LME inventory hit 18-month low | ### Trading Direction - Direction: [bullish / bearish / neutral] - Confidence: [high / medium / low] - Risk points: [specific risks] Notes Commodity data sources are fragmented (EIA / OPEC / LME / SHFE, etc.). This skill provides the analytical framework; data should be retrieved through web-reader or entered manually Futures prices include roll costs, so direct comparison across different contracts must account for expiry-roll effects Seasonal patterns are statistical averages and may be completely overwhelmed by fundamentals in a given year Gold has both commodity and financial attributes, and the financial side (rates / dollar) usually dominates short-term pricing Copper’s financial characteristics have strengthened since 2020 (copper futures are used as a macro hedge), so pure fundamental analysis may be insufficient Inventory data is lagged (hidden inventories cannot be tracked in real time), so cross-check with price and basis behavior This framework is for research backtesting only and does not constitute investment advice