analyzing-commodity-derivatives
Structures commodity derivative pricing with forward curve construction and convenience yield estimation. Use when pricing commodity derivatives, analyzing forward curves, or modeling commodity markets.
Best use case
analyzing-commodity-derivatives is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Structures commodity derivative pricing with forward curve construction and convenience yield estimation. Use when pricing commodity derivatives, analyzing forward curves, or modeling commodity markets.
Teams using analyzing-commodity-derivatives should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/analyzing-commodity-derivatives/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How analyzing-commodity-derivatives Compares
| Feature / Agent | analyzing-commodity-derivatives | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Structures commodity derivative pricing with forward curve construction and convenience yield estimation. Use when pricing commodity derivatives, analyzing forward curves, or modeling commodity markets.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Analyzing Commodity Derivatives ## When To Use - Pricing commodity futures, options, or swaps on energy, metals, or agricultural underlyings - Constructing or validating a forward curve from observed futures prices and basis quotes - Estimating convenience yield for physical-delivery commodities (crude oil, natural gas, copper, grains) - Evaluating structured commodity products such as collars, accumulators, or storage deals - Assessing contango/backwardation dynamics and their implications for hedging or trading strategies ## Inputs To Gather - **Spot and futures prices**: Current spot price plus settlement prices across available contract maturities (source: exchange data, broker screens, or OTC quotes) - **Interest rate curve**: Risk-free rates (e.g., SOFR or Treasury curve) for corresponding tenors - **Storage and carry costs**: Warehousing fees, insurance, financing costs, and any applicable transport/delivery premiums [VERIFY against current exchange fee schedules] - **Historical volatility data**: Realized vol on the underlying commodity, implied vol surface if options are in scope - **Contract specifications**: Lot size, delivery location, quality grade, settlement method (physical vs. cash), and expiry calendar [VERIFY against exchange contract specs] - **Seasonal patterns**: Known demand/supply cycles (e.g., heating oil winter demand, grain harvest windows) ## Workflow 1. **Define the analysis scope** - Identify the commodity, exchange, and contract months in scope - Confirm whether the analysis covers futures only or includes options/structured products - Establish the pricing date and data snapshot time 2. **Construct the forward curve** - Collect settlement prices for all liquid contract months - Interpolate between observed points using cubic spline or piecewise-linear methods for illiquid tenors - Apply calendar-spread adjustments for roll periods - Validate curve shape: flag any inversions or discontinuities that may indicate stale data or market stress 3. **Estimate convenience yield** - Back out implied convenience yield from the cost-of-carry model: F(T) = S * exp((r + c - y) * T), solving for y - Compare implied convenience yield across tenors — typically higher at short maturities during supply tightness - Cross-check against physical market indicators: inventory levels, basis differentials, draw/injection rates - Note: convenience yield is not directly observable; always present as an estimate with stated assumptions 4. **Price the derivative instrument** - **Futures**: Mark-to-market using constructed forward curve; compute basis risk if hedging a non-standard delivery point - **Vanilla options**: Apply Black-76 model using forward price as underlying, with implied vol from the vol surface; report Greeks (delta, gamma, vega, theta) - **Swaps**: Calculate fixed-for-floating swap value by discounting the difference between the fixed price and the forward curve at each settlement date - **Structured products**: Decompose into component instruments (e.g., a collar = long put + short call on the commodity forward); price each leg independently, then aggregate 5. **Assess market structure and risk** - Characterize the term structure: contango (upward-sloping, storage costs dominate) vs. backwardation (downward-sloping, convenience yield dominates) - Quantify roll yield impact for positions held across contract rolls - Run sensitivity analysis: parallel shift in forward curve (+/- 5-10%), vol shock (+/- 20% relative), and interest rate bump - Identify key risk factors: liquidity concentration in specific tenors, delivery optionality, and regulatory position limits [VERIFY position limit rules per exchange and jurisdiction] ## Output - **Forward curve table and chart**: Observed prices, interpolated curve, and implied convenience yield by tenor - **Derivative valuation summary**: Fair value, mark-to-market P&L (if an existing position), and decomposition by component for structured products - **Greeks and sensitivities**: Delta, gamma, vega, theta for options; DV01/duration-equivalent for swaps; scenario-based P&L for all instruments - **Market structure commentary**: Contango/backwardation assessment, roll yield estimate, and comparison to historical term structure patterns - **Risk flags**: Any data gaps, illiquid tenors used in interpolation, large convenience yield deviations, or positions near regulatory limits ## Quality Checks - Verify forward curve is arbitrage-free: no negative calendar spreads in a full-carry market without a plausible convenience yield explanation - Confirm option pricing recovers observed market premiums within bid-ask spread tolerance - Ensure convenience yield estimates are consistent with physical market fundamentals (inventory reports, shipping rates) - Validate that swap valuations net to zero at inception for at-market swaps - Cross-check Greeks by bumping inputs numerically and comparing to analytical values - Flag any assumed correlations (e.g., between delivery locations or commodity grades) with [VERIFY] markers - Confirm all contract specifications match the relevant exchange rulebook [VERIFY expiry dates, delivery terms, and tick sizes]