Commodity Risk Management AI — Hedging, VaR & Strategy

Commodity Risk: Where the Exposure Lives

Commodity price risk sits in four places: physical inventory, purchase commitments, sales contracts with fixed pricing, and derivative positions. A manufacturing company with $40M of copper inventory, $15M of forward purchase commitments, and no hedges is exposed to 100% of copper price moves on $55M of notional. Mapping and quantifying that exposure before designing a hedge program is where most corporate treasury teams underinvest — they hedge after the loss, not before.

ClaudeFinanceLab's commodities trading tools cover the full workflow: exposure mapping, hedge ratio calculation, instrument selection, basis risk quantification, and hedge effectiveness testing under ASC 815. The strategy is a human call. The math is not.

Commodity Exposure Mapping and Risk Quantification

Before any hedging decision, the exposure needs to be mapped: what commodity, what volume, what price reference, what tenor. A food manufacturer might have corn exposure across 6 different price indices (Chicago spot, Gulf basis, various delivered locations) with contract tenors from 30 days to 18 months. Getting this into a unified exposure report — notional, price sensitivity per unit, and total P&L impact per 10% price move — is the first and most important step.

• "Map and quantify commodity price exposure for a food manufacturer. Inputs: (1) Physical corn inventory: 500,000 bushels at average cost $4.20/bu. (2) Fixed-price purchase contracts: 200,000 bu per month for 6 months at $4.35/bu. (3) Fixed-price sales contracts: 150,000 bu per month for 3 months (to major retail customer at $5.10/bu including processing margin). (4) Open futures positions: short 100 CME corn futures contracts (5,000 bu each) at $4.50/bu, December delivery. Calculate: (a) Net unhedged corn exposure by month for the next 6 months; (b) Dollar P&L impact of a $0.50/bu adverse move on the unhedged position; (c) Current hedge ratio (hedged notional / total gross long exposure); (d) Recommend whether the hedge ratio is appropriate given that our board policy requires 60-80% of forward 90-day exposure to be hedged."
• "Quantify basis risk in my natural gas hedge program. We produce natural gas in the Permian Basin (priced at Waha Hub) but hedge using Henry Hub futures (the most liquid benchmark). Historical data over the past 24 months: average Waha-Henry Hub basis spread: -$0.85/MMBtu. Basis spread range: -$2.40 to +$0.15/MMBtu. Correlation between Waha price and Henry Hub price: 0.78. We have 50,000 MMBtu/day of production hedged with Henry Hub swaps at $3.20/MMBtu. (1) Calculate our effective realized price if the Waha-HH basis is: (a) -$0.85 (average), (b) -$2.00 (stressed), (c) -$0.30 (favorable). (2) What is the annual basis risk P&L impact at the stressed basis vs average? (3) Is there a Waha-specific derivative instrument we should consider, and when does basis risk justify the additional complexity and liquidity cost?"

Hedge Program Design and Instrument Selection

The choice between futures, swaps, options, and collars is a function of accounting treatment, credit capacity, basis risk, and the company's tolerance for upside participation. A collar costs nothing upfront but caps upside. A fixed-price swap eliminates variability but commits to a price that could look bad if markets move favorably. Claude models each instrument against the exposure and compares outcomes across price scenarios — the analysis most treasury teams do informally and should do rigorously.

• "Design a hedge program for a crude oil producer with 50,000 barrels/day of production for calendar year 2027. Board policy: hedge 50-70% of proved developed producing reserves for the next 12 months. Current WTI strip price for 2027: $72/bbl. Credit facility borrowing base requires maintaining a minimum of 50% hedged for the next 12 months. Analyze three instruments: (1) Fixed-price swaps at $71.50/bbl (current market), (2) Costless collars: sold call at $82/bbl, bought put at $64/bbl, (3) Three-way collars: sold call $85/bbl, bought put $65/bbl, sold put $55/bbl. For each instrument at 55% hedge ratio (27,500 bbl/day): (a) Realized price in scenarios: WTI at $55, $65, $72, $80, $90/bbl; (b) Annual revenue impact vs unhedged; (c) ASC 815 hedge accounting eligibility; (d) Credit exposure to counterparty (for swaps). Which structure do you recommend given the borrowing base requirement and a management view that prices will be rangebound $65-80?"

Commodity VaR and Stress Testing

Commodity VaR uses the same framework as financial asset VaR (parametric, historical simulation, or Monte Carlo) but requires commodity-specific considerations: mean-reversion in some markets, seasonality in energy and agricultural commodities, and the skewed distribution of commodity returns during supply shocks. Historical simulation captures these non-normalities better than parametric VaR for commodities.

• "Calculate 10-day 99% historical simulation VaR for a commodity portfolio. Portfolio: (1) Long 10,000 MT copper at $9,200/MT; (2) Short 500,000 MMBtu natural gas at $2.85/MMBtu; (3) Long 15,000 barrels crude oil at $72/bbl. Historical daily price return data for the past 500 trading days (use representative simulated returns for the model): assume copper daily return σ = 1.2%, natural gas daily return σ = 2.8%, crude oil daily return σ = 1.6%. Correlation matrix: copper-crude 0.45, copper-gas 0.20, crude-gas 0.35. (1) Calculate individual position 10-day 99% parametric VaR. (2) Calculate portfolio VaR with correlations. (3) Calculate diversification benefit. (4) Stress test the portfolio under: (a) energy crisis scenario: gas +40%, crude +25%, copper flat; (b) global recession scenario: copper -20%, crude -30%, gas -15%."
• "Design a commodity risk report for the CFO's monthly risk committee. Our commodity exposure: agriculture (corn, soybeans, wheat inputs), natural gas (plant energy), and diesel (logistics fleet). Total notional exposure: $85M. Current hedging: 65% of 90-day forward corn, 40% of 90-day natural gas, 0% diesel. Structure the report to include: (1) Exposure dashboard — notional by commodity, hedge ratio, unhedged exposure; (2) Sensitivity table — P&L impact per 10% adverse move per commodity; (3) Total portfolio VaR (parametric, 95%, 10-day); (4) Hedge effectiveness summary by commodity (is the hedge ratio within policy?); (5) Market commentary — 2 sentences each on corn, gas, and diesel market outlook; (6) Recommended actions if any hedge ratios are outside policy. Format it so a non-specialist CFO can read the first page and understand the company's risk position in 60 seconds."

Hedge Effectiveness Testing Under ASC 815

Hedge accounting under ASC 815 requires prospective and retrospective effectiveness testing. Failing effectiveness means gains and losses on the hedging instrument flow through earnings immediately rather than matching the hedged item — the opposite of the risk management intent. The dollar-offset method and regression analysis are the two most common approaches. Claude builds both, compares results, and identifies whether the hedge relationship is at risk of dedesignation.

• "Test hedge effectiveness for a copper forward contract designated as a cash flow hedge under ASC 815. Hedging instrument: forward purchase of 500 MT copper at $9,150/MT for delivery in 90 days. Hedged item: forecasted purchase of 500 MT copper. Data for the past 8 quarters: changes in fair value of forward contract vs changes in fair value of the hedged item (the hypothetical perfect hedge). Dollar-offset ratios (actual/hypothetical): Q1: 0.94, Q2: 1.03, Q3: 0.97, Q4: 1.05, Q5: 0.92, Q6: 1.08, Q7: 0.99, Q8: 1.02. (1) Apply the dollar-offset method — is the hedge highly effective in all quarters (80-125% range)? (2) Run a regression analysis of the cumulative data — what is R², slope, and does the regression meet ASC 815 qualitative criteria? (3) Is there any quarter where the hedge is at risk of failing effectiveness? (4) What documentation is required at inception and quarterly under ASC 815 for this hedge relationship?"

Where to Start

Related reading: Commodities Trading AI — Market Analysis & Strategy, FX Risk Management AI — Currency Hedging & Exposure, Portfolio VaR — Value at Risk Formula & Claude Prompts, Corporate Treasury AI.