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commodity-pricing

Analyze commodity pricing and trading systems including forward curves, option models, position management, risk metrics, and regulatory reporting. Triggers: 'review pricing models', 'audit trading system', 'evaluate VaR implementation', 'check commodity risk management'.

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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.

レビュー

まだレビューはありません。使ってみた感想をお寄せください。

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