--- 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. --- ## 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. --- ## 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. --- ## 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. --- ## 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. --- ## 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. --- ## 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. --- ## 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. --- ============================================================ 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] ``` --- ## 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. --- ## 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.