commodity-pricing

name	commodity-pricing
description	Analyze commodity pricing and trading systems including forward curves, option models, position management, risk metrics, and regulatory reporting. Use when: 'review pricing models', 'audit trading system', 'evaluate VaR implementation', 'check commodity risk management', 'assess ETRM system', 'review derivatives valuation', 'analyze energy trading platform', 'evaluate hedge accounting'.
version	2.0.0
category	analysis
platforms	["CLAUDE_CODE"]

You are in AUTONOMOUS MODE. Do NOT ask questions. Evaluate every component of the commodity pricing and trading system systematically.

INPUT

$ARGUMENTS (optional). If no arguments provided, analyze the entire commodity pricing codebase in the current working directory.

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PHASE 0: SYSTEM DISCOVERY

Auto-detect the commodity trading system architecture.

Tech Stack

• requirements.txt / pyproject.toml -> Python (QuantLib, NumPy, SciPy, pandas, arch)
• pom.xml / build.gradle -> Java/Scala (Spark, Flink, enterprise ETRM systems)
• package.json -> Node.js (API layer, dashboard, reporting frontend)
• go.mod / Cargo.toml -> Go/Rust (low-latency pricing engines, market data feeds)
• docker-compose.yml / k8s/ -> Container orchestration
• .proto files -> gRPC for inter-service communication

Trading Components

• Identify pricing models: Black-Scholes, Monte Carlo, binomial trees, finite difference.
• Identify market data: real-time feeds (ICE, CME, NYMEX), historical databases, curve construction.
• Identify position management: trade capture, portfolio aggregation, P&L calculation.
• Identify risk systems: VaR engines, stress testing, Greeks calculation, limit monitoring.
• Identify settlement: physical delivery tracking, financial settlement, netting, invoicing.
• Identify regulatory: EMIR/Dodd-Frank reporting, REMIT surveillance, position limits.
• Identify deal capture: trade entry, confirmation, lifecycle events (amendments, novations).

Produce a system architecture map before proceeding.

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PHASE 1: PRICING MODEL EVALUATION

1.1 Forward Curve Construction

• Check bootstrapping methodology (piecewise, spline, monotone convex).
• Verify curve input sources: exchange settlements, broker quotes, bilateral trades.
• Check for seasonal shaping in power and gas curves (monthly, daily, hourly granularity).
• Verify basis differential modeling between delivery points.
• Check curve storage and versioning (end-of-day, intraday, real-time).
• Verify curve staleness detection and fallback logic for missing market data.

1.2 Option Pricing

• Identify option models: Black-76, Bachelier, local volatility, stochastic volatility.
• Check implied volatility surface construction and interpolation.
• Verify smile/skew handling in energy options (mean-reverting models).
• Check Asian option pricing (arithmetic average, geometric approximation).
• Verify spread option pricing: Kirk approximation, Margrabe, or Monte Carlo.
• Check swing/storage option valuation: least-squares Monte Carlo, dynamic programming.
• Verify calendar spread and time spread option handling.

1.3 Monte Carlo Simulation

• Check variance reduction techniques: antithetic variates, control variates, stratification.
• Verify random number generation quality (Mersenne Twister, Sobol sequences).
• Check convergence monitoring and adaptive sample sizing.
• Verify correlation structure in multi-factor simulations (Cholesky decomposition).
• Check simulation performance: GPU acceleration, parallel processing.
• Verify path generation respects mean reversion and jump-diffusion if applicable.

1.4 Physical Asset Valuation

• Check real option valuation of physical assets (tolling agreements, storage, transport).
• Verify intrinsic vs extrinsic value decomposition.
• Check operational constraint modeling (ramp rates, minimum run times, efficiency curves).
• Verify seasonal storage optimization (injection/withdrawal scheduling).
• Check transportation and pipeline capacity valuation.

For each finding: file path, model component, severity, description, recommendation.

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PHASE 2: MARKET DATA MANAGEMENT

2.1 Real-Time Feeds

• Identify exchange feed handlers: CME MDP, ICE iMpact, NYMEX, EEX, NBP.
• Check feed redundancy and failover between primary and backup feeds.
• Verify message processing latency monitoring.
• Check sequence number gap detection and recovery.
• Verify time synchronization accuracy for market data timestamps.
• Check throttling and backpressure handling during high-volume periods.

2.2 Historical Data

• Check tick data storage and retrieval performance.
• Verify end-of-day settlement price capture and validation.
• Check corporate action and contract rollover handling.
• Verify data quality validation: price bounds, stale data detection, outlier filtering.
• Check gap filling methodology for illiquid products.
• Verify historical data retention meets regulatory requirements (5-7 years minimum).

2.3 Curve Management

• Check official end-of-day curve publication workflow.
• Verify curve approval and sign-off process.
• Check curve override capability with audit trail.
• Verify multi-curve support: bid, ask, mid, settlement, internal marks.
• Check curve comparison and variance reporting.
• Verify curve data distribution to downstream consumers (risk, P&L, settlement).

2.4 Reference Data

• Check contract specification management (lot sizes, delivery points, expiry dates).
• Verify product master data consistency across systems.
• Check calendar management (exchange holidays, delivery calendars).
• Verify counterparty and broker reference data management.

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PHASE 3: POSITION MANAGEMENT AND P&L

3.1 Trade Capture

• Check trade entry validation (limit checks, product eligibility, counterparty credit).
• Verify trade lifecycle event handling: new, amend, cancel, novation, exercise, assignment.
• Check trade confirmation matching and exception handling.
• Verify deal ticket completeness (all required fields populated).
• Check bulk trade import capability and validation.
• Verify trade audit trail (every change tracked with user, timestamp, before/after).

3.2 Position Aggregation

• Check real-time position aggregation by: book, trader, desk, commodity, delivery period.
• Verify netting logic: delivery point, counterparty, product type.
• Check physical vs financial position separation.
• Verify time-bucketed position reporting (daily, monthly, quarterly, annual).
• Check position limit monitoring against regulatory and internal limits.
• Verify position reconciliation between front-office and back-office systems.

3.3 P&L Calculation

• Check mark-to-market P&L methodology (daily revaluation against curves).
• Verify realized vs unrealized P&L separation.
• Check P&L attribution: price change, volume change, new deals, curve roll.
• Verify P&L explain capability (breakdown of daily P&L movement drivers).
• Check accounting P&L vs trading P&L reconciliation.
• Verify multi-currency P&L with FX rate handling.
• Check accrual accounting treatment where required (hedge accounting, ASC 815).

3.4 Hedge Accounting

• Check hedge designation and documentation workflow.
• Verify hedge effectiveness testing: prospective and retrospective.
• Check fair value vs cash flow hedge classification.
• Verify de-designation and reclassification handling.
• Check ASC 815 / IFRS 9 compliance in hedge accounting logic.

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PHASE 4: RISK MANAGEMENT

4.1 Value at Risk (VaR)

• Identify VaR methodology: historical simulation, parametric, Monte Carlo.
• Check VaR confidence levels and holding periods (95%/99%, 1-day/10-day).
• Verify VaR backtesting: exceptions tracking, Kupiec test, Christoffersen test.
• Check conditional VaR (CVaR / Expected Shortfall) calculation.
• Verify component VaR and incremental VaR for portfolio decomposition.
• Check VaR limit monitoring and breach notification.

4.2 Greeks Calculation

• Check delta, gamma, vega, theta, rho calculation on all derivative positions.
• Verify Greeks are computed using appropriate bump sizes (1% price, 1% vol, 1 day).
• Check cross-gamma and correlation sensitivity.
• Verify Greeks aggregation across portfolios.
• Check Greeks-based hedging recommendations.

4.3 Stress Testing

• Check historical stress scenarios (energy crises, weather events, geopolitical shocks).
• Verify hypothetical stress scenario construction capability.
• Check reverse stress testing (what scenario causes a given loss threshold).
• Verify stress test coverage of all material risk factors.
• Check stress test reporting and governance workflow.

4.4 Credit Risk

• Check counterparty credit exposure calculation (current and potential future exposure).
• Verify credit limit monitoring and breach alerting.
• Check collateral management: margin calls, ISDA CSA threshold tracking.
• Verify netting agreement application in exposure calculation.
• Check credit valuation adjustment (CVA) computation.

4.5 Limit Management

• Check multi-level limit framework: VaR, position, Greeks, notional, tenor.
• Verify limit breach detection is real-time or near-real-time.
• Check pre-trade limit checking capability.
• Verify limit override workflow with approval and audit trail.
• Check limit utilization reporting and trending.

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PHASE 5: REGULATORY REPORTING AND COMPLIANCE

5.1 EMIR / Dodd-Frank Reporting

• Check trade reporting to registered trade repositories.
• Verify Unique Transaction Identifier (UTI) generation and sharing.
• Check Legal Entity Identifier (LEI) management.
• Verify reporting field completeness against regulatory technical standards.
• Check lifecycle event reporting (modifications, terminations, valuations).
• Verify daily valuation reporting for outstanding derivatives.
• Check reporting reconciliation and error correction workflow.

5.2 REMIT (EU Energy Market)

• Check REMIT transaction reporting (standard and non-standard contracts).
• Verify fundamental data reporting (generation outages, capacity availability).
• Check inside information disclosure procedures.
• Verify market manipulation surveillance (wash trades, spoofing detection).
• Check ACER reporting format compliance.

5.3 Position Limits

• Check exchange position limit monitoring (CFTC, ESMA).
• Verify position aggregation across accounts and entities for limit purposes.
• Check large trader reporting threshold monitoring.
• Verify exemption tracking (bona fide hedging, risk management).
• Check speculative position limit compliance.

5.4 Settlement and Delivery

• Check physical delivery scheduling and nomination.
• Verify financial settlement calculation and netting.
• Check invoice generation and reconciliation.
• Verify settlement calendar management per exchange and jurisdiction.
• Check settlement dispute handling and resolution workflow.

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PHASE 6: SYSTEM OPERATIONS AND DATA INTEGRITY

6.1 End-of-Day Processing

• Check EOD batch processing pipeline: curve publication, P&L, risk, reporting.
• Verify batch job dependency management and failure handling.
• Check EOD reconciliation checkpoints.
• Verify EOD completion monitoring and SLA tracking.
• Check month-end and year-end close processing.

6.2 Data Integrity

• Check trade data reconciliation between systems (front/mid/back office).
• Verify position reconciliation with exchange clearing statements.
• Check cash reconciliation with bank statements.
• Verify data lineage tracking from source to report.
• Check data quality monitoring and alerting.

6.3 Audit and Controls

• Check segregation of duties: trading vs risk vs settlement vs IT.
• Verify four-eyes principle on trade amendments and limit changes.
• Check system access controls and role-based permissions.
• Verify regulatory audit trail retention (7 years for CFTC, 5 years for EMIR).
• Check change management controls on pricing models and risk parameters.

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============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

1. Verify all output sections have substantive content (not just headers).
2. Verify every finding references a specific file, code location, or data point.
3. Verify recommendations are actionable and evidence-based.
4. If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

• Identify which sections are incomplete or lack evidence
• Re-analyze the deficient areas with expanded search patterns
• Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

• Flag specific gaps in the output
• Note what data would be needed to complete the analysis

OUTPUT FORMAT

## Commodity Pricing and Trading System Analysis Report

**System:** [name/description]
**Stack:** [detected technologies]
**Commodity Markets:** [detected: power, gas, oil, metals, agricultural]
**Trading Types:** [physical, financial, derivatives]

### Summary

| Category | Status | Findings | Critical |
|----------|--------|----------|----------|
| Pricing Models | [PASS/WARN/FAIL] | N | N |
| Market Data | [PASS/WARN/FAIL] | N | N |
| Position/P&L | [PASS/WARN/FAIL] | N | N |
| Risk Management | [PASS/WARN/FAIL] | N | N |
| Regulatory Reporting | [PASS/WARN/FAIL] | N | N |
| Operations/Integrity | [PASS/WARN/FAIL] | N | N |

### Pricing Model Coverage

| Product Type | Model | Validation | Greeks | Status |
|-------------|-------|------------|--------|--------|
| Forwards/Futures | | | | |
| European options | | | | |
| Asian options | | | | |
| Spread options | | | | |
| Swing/storage | | | | |

### Risk Coverage Matrix

| Risk Metric | Implemented | Validated | Monitored | Gap |
|-------------|-------------|-----------|-----------|-----|
| VaR (historical) | | | | |
| VaR (Monte Carlo) | | | | |
| CVaR / ES | | | | |
| Greeks | | | | |
| Stress testing | | | | |
| Credit exposure | | | | |

### Detailed Findings

For each category with WARN or FAIL:

| # | Severity | File | Description | Impact | Recommendation |
|---|----------|------|-------------|--------|----------------|

### Remediation Priority
[Ordered list by financial exposure and regulatory risk]

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RULES

• Do NOT modify any pricing models, risk parameters, or trading limits.
• Do NOT execute trades, submit orders, or interact with exchange APIs.
• Do NOT access or display actual trade data, counterparty names, or portfolio positions.
• Do NOT expose pricing model parameters, VaR figures, or limit thresholds that are commercially sensitive.
• Do NOT skip regulatory reporting analysis even for internal or proprietary trading systems.
• Do NOT assume model accuracy without checking backtesting and validation results.
• Do NOT conflate theoretical model outputs with production calibrated results -- verify calibration.

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NEXT STEPS

• "Run /fraud-detection to evaluate trade surveillance and market manipulation detection."
• "Run /security-review to audit trading platform APIs and access controls."
• "Run /compliance-ops to review broader financial regulatory requirements."

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

• Look for the project path in ~/.claude/projects/
• If found, append to skill-telemetry.md in that memory directory

Entry format:

### /commodity-pricing — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.