Managing Model Risk for Quants and Traders

Understand the most advanced approaches to detect and control critical risks related to the use of quantitative models for pricing, hedging and risk management.

This course updates principles of model validation in accordance with most recent evolutions in research and accounting & regulatory standards, covering a range of models commonly used for different asset classes.

From SABR and BGM in Interest Rates to local volatility, stochastic volatility and jump dynamics used in Equity and FX, moving through copulas, structural and reduced-form models used in credit, simple and advanced models are explained with a focus on the management of their hidden risks.

Practical prescriptions for comparing and choosing alternative models are given, including stress testing, scenario analysis, reverse engineering of models from counterparty quotes and consensus platforms, and monitoring of model evolution to minimise model losses.

The course also covers liquidity and discounting for different derivatives, statistical arbitrage with quantitative models, efficient modelling of correlation for various assets, an update of credit and counterparty risk models based on the analysis of the latest events, and the modelling and management of basis risk. Other points that are crucial for the validation of models and their practical applications are also analysed: hedging analysis, P&L analysis, calibration stability, and monitoring of the accuracy of approximations.

All delegates will receive a copy of Dr Morini's book, "Understanding and Managing Model Risk: A Practical Guide for Quants, Traders and Validators" published by Wiley Finance.

• Managers and Directors in Validation and Financial engineering
• Quants in Front Office and Risk management
• Derivatives Traders
• Regulators
• Structurers
• Exotic products managers (pricing strategy development)
• Portfolio managers

The foundations of derivatives pricing. Matlab will be used but prior knowledge is not essential.

Model risk and model validation outlook

• Managing model risk: value-based approach vs price-based approach. The credit crunch example
• Suggestions from model risk management in science. The real black swans
• Measuring model uncertainty. Practical meaning of no-arbitrage pricing and model completeness in liquid and illiquid markets
• Accounting standards (IAS/IFRS). Implications of fair value on model validation. Practical analysis of level 2 and 3 pricing. A case study on swaps and basis risk
• Market regulators: BIS, FSA, FED on stress testing, model risk and model validation. What changes after the crisis. Basel new principles
• From theory to practice: step-by-step building of a practical framework for model validation and the management of model risk

Comparing and using alternative models

• Model comparison methodology
• Calibration and realism assessment
• How to use alternative models to quantify model risk
• First example: gap risk computation in leveraged notes. Structurals vs reduced-form models and their hidden consequences on gap losses
• Second example: local vs stochastic volatility models on time-dependent equity derivatives. Smile dynamics
• Third example: BGM vs short rate models for Interest Rate American-Bermudan. Hidden role of correlations and common misunderstandings 

Stress-testing design and pitfalls

• Stress testing models and stress testing with models (scenario analysis for portfolios)
• What to test? Stressing model assumptions and stressing model implementation (approximations, analytics and numerics)
• First Example: stress-tests using market information. Improving correlation skew modelling for efficient portfolio scenario analysis
• Second Example: stress scenarios design using historical information. Validating and improving mapping for bespoke credit portfolios
• Third Example: stress-testing pitfalls. Detect copulas' weaknesses for forward correlations and improve on them