Derivative Pricing Model Validator
Validate derivative pricing models with analytical and numerical stress-testing
What You Can Do
You can systematically validate derivative pricing models before deployment by comparing analytical solutions against numerical methods, detecting arbitrage opportunities and calibration issues, and performing sensitivity analysis across market conditions. Claude orchestrates multi-framework validation workflows that stress-test exotic options under extreme scenarios, optimize computational efficiency, and generate audit-ready documentation for model governance—catching model errors before they propagate to trading systems.
Features
Compare Black-Scholes variants, local volatility, stochastic volatility (Heston, SABR), interest rate models (Hull-White, CIR), and jump-diffusion frameworks
Identify parameter instability across volatility surfaces and detect when models diverge from market prices
Benchmark analytical solutions against Monte Carlo simulations, finite difference methods, and lattice approaches
Test exotic options under extreme market conditions, parameter shifts, and regime changes with systematic scenario generation
Verify delta, gamma, vega, theta calculations for hedging accuracy and identify computational errors
Identify pricing inconsistencies, violations of no-arbitrage conditions, and mispricing patterns
Generate audit-ready validation reports with consistency checks, model limitations, and governance documentation
Compare computational efficiency across pricing methodologies with runtime and accuracy trade-off analysis
Example Output
Example 1: Heston Model Validation Report
- Calibration Status: ✓ Stable across 30-day to 2-year maturity range
- Comparison vs. Market: Max deviation 2.3% (within acceptable tolerance)
- Greeks Validation: Delta matches finite difference benchmark within 0.001
- Stress Test Results: Model remains stable under 50% volatility spike; Greeks smooth across strikes
- Recommendation: Approved for production use with daily recalibration
Example 2: Monte Carlo vs. Analytical Benchmark
- European Call (S=100, K=100, T=1Y): Analytical $10.45 vs. MC $10.48 (95% CI: $10.42-$10.54)
- Barrier Option Pricing Discrepancy: Analytical $8.23 vs. MC $7.91 (3.8% difference flagged for investigation)
- Computational Cost: Analytical 0.002s vs. MC 2.4s for equivalent accuracy
- Recommendation: Use analytical for European vanilla; Monte Carlo required for path-dependent exotics
Example 3: Calibration Issue Detection
- Parameter stability across term structure: ✗ Mean reversion jumps 200bps at 5Y tenor
- Volatility smile fit: ✗ Systematic overpricing of 10% OTM calls
- Root cause: Identified as market data outlier on 2024-01-15; recommend data cleaning
- Impact: Recalibration reduces hedging error by 45%
What's Included
- SKILL.md: Complete validation framework with model taxonomy and workflow orchestration
- Validation Template: Structured checklist for comparing analytical vs. numerical pricing methods
- Stress-Test Scenario Generator: Pre-built market regime definitions and extreme scenario matrices
- Calibration Diagnostic Worksheet: Parameter stability analysis framework and drift detection criteria
- Audit Report Template: Regulatory-compliant validation documentation with sign-off checkpoints
Who It's For
- Quantitative analysts — Building, validating, and deploying new pricing models in production environments
- Risk managers — Stress-testing existing models and identifying model limitations under extreme conditions
- Model validators — Performing independent validation of pricing methodologies for model governance
- Trading desk engineers — Optimizing computational efficiency and comparing pricing methodologies
- Compliance officers — Generating audit documentation and ensuring model validation governance standards are met
Best For
- Pre-deployment validation of new pricing models before production use
- Calibration diagnostics and parameter stability analysis across market conditions
- Benchmarking analytical solutions against numerical methods (Monte Carlo, PDE, lattice)
- Stress-testing exotic options and structured products under extreme market scenarios
- Greeks validation and hedging accuracy verification for risk management
- Arbitrage detection and pricing consistency checking across models
- Regulatory and internal audit documentation for model governance
- Computational efficiency optimization and runtime comparison across pricing methods
You might also like
You can analyze equity charts to identify continuation patterns (flags, pennants, triangles), reversal patterns (head-and-shoulders, double tops/bottoms), and momentum breakouts using rule-based frameworks. Claude applies consistent validation criteria to assess pattern strength, calculate precise risk/reward ratios based on pattern geometry, and identify early invalidation signals that trigger stop-loss placement—transforming subjective chart reading into systematic, probability-weighted trading decisions.
by steelmorgan
You can conduct deep-dive REIT financial analysis by translating GAAP accounting into real estate-specific valuation frameworks. The skill helps you calculate Funds From Operations, compare price-to-NAV ratios across property sectors, assess distribution sustainability, identify red flags in quarterly earnings, and evaluate comparable company multiples within residential, office, retail, industrial, or healthcare property segments. You'll produce institutional-grade investment recommendations backed by quantified risk metrics and confidence intervals.
by steelmorgan
You can transform fragmented ESG data from multiple vendors (MSCI, Sustainalytics, Bloomberg) into cohesive integration frameworks that clearly map ESG factors to investment thesis and financial outcomes. This skill helps you identify data conflicts, resolve vendor discrepancies, establish materiality-weighted scoring systems, and document audit trails that demonstrate defensible ESG integration decisions to institutional investors and regulators.
by steelmorgan
This skill accelerates your alternative asset evaluation by organizing complex fund assessments across hedge funds, private equity, real assets, and structured products into standardized, comparable frameworks. You can evaluate manager capability, operational infrastructure, fee alignment, and risk exposure while automatically flagging red flags—reducing cognitive load and maintaining institutional-grade rigor across disparate asset classes.
by steelmorgan
You can rigorously validate algorithmic trading strategies by decomposing backtest performance, identifying which components drive returns, and stress-testing robustness across market regimes. This skill exposes hidden validation gaps—like curve-fitting bias and survivorship errors—that cause live trading failures, helping you separate genuine alpha from statistical artifacts before deploying capital.
by steelmorgan
You can construct institutional-grade healthcare valuation models that properly weight clinical and regulatory event risk. This skill teaches you to integrate disease-state economics (market sizing, competitive positioning), probability-adjusted NPV calculations for clinical programs, and financial runway analysis into cohesive price targets. You'll generate transparent bull/base/bear scenarios tied to specific clinical readout dates and regulatory milestones that institutional investors expect.
by steelmorgan
You can architect and implement pricing models for vanilla and exotic derivatives, including options, swaps, and structured products. Claude helps you design Monte Carlo simulation frameworks, calibrate model parameters to market instruments, validate implementations against benchmarks, and stress-test pricing across extreme market scenarios. The result is production-ready code that passes governance checks and aligns pricing with market reality.
by skillslib
You can rapidly analyze corporate catalysts—mergers, bankruptcies, restructurings, regulatory decisions, and special situations—to uncover price dislocations and asymmetric payoff opportunities. This skill structures your catalyst research, quantifies probability-weighted outcomes, assesses execution risk and deal mechanics, and identifies mispriced event risk before consensus recognition. You'll synthesize multi-source event information and stress-test your investment thesis against alternative scenarios.
by steelmorgan