User Login

Error
Home Courses Course Calendar Teaching Team About Us Resources Contact
Close
Course Calendar Course Calendar

Managing Model Risk for Quants, Traders and Validators

Day One

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

Day Two

Understanding model evolution to prevent model losses

  • Bringing hidden model assumptions to light and monitoring when they break down
  • Example 1: how interest-rate consensus model broke down when the basis spreads exploded. How to find an analytical model that explains the new market. Consequences for term-structure building
  • Example 2: modelling liquidity risk and liquidity charges. Funding liquidity and interactions with credit and discounting. Market liquidity and bid-ask. How changes in market fundamentals can shake the foundations of pricing

Hedging Analysis and P&L Analysis

  • Limits of pricing models when applied to hedging. How models are modified for efficient hedging. Validation of a real hedging strategy
  • Practical example: Local volatility models vs stochastic volatility models in options hedging. The case of SABR and the shadow delta for the swaptions smile
  • What we can get from P&L analysis and the delusions about it. The effect of model recalibration. The real cost of hedging and the charging of hedging costs

Correlation

  • The risk of wrong correlation assumptions and technical difficulties in modelling interdependencies
  • Three tools to overcome technical difficulties. Examples: FX correlations, interest rate correlation parameterisations, correlation of stochastic volatility with the underlying
  • Controlling model dimensionality and correlation rank
  • Wrong correlation assumptions. 1-correlation risk with example on multifactor models. 0-correlation risk with example on counterparty risk. Correlation vs dependency

Calibration

  • Assessing calibration stability through comparison with market variability and analysis of the implied evolution of term structure of volatilities
  • The effect of calibration instability on hedging
  • Practical examples in dynamic hedging and pricing of American options
  • Reverse engineering of counterparty quotes, consensus platforms, collateral regulations. Examples

MatLab workshop


Day Three

Approximations

  • Validating an approximation. The operative steps. Monitoring market features that affect the reliability of approximations. Setting quantitative triggers
  • Validation against Monte Carlo methods. Methodology. Examples from interest rates: the swaption approximation and the convexity adjustments for CMS
  • Validating against analytic methods. SABR approximation vs the SABR model

Extrapolations

  • Interpolation and extrapolations. Dangers of extrapolations and how to avoid them
  • Turning extrapolation into interpolation by adding data: example from volatility smile
  • Turning extrapolation into interpolation by changing variable: example from correlation skew

Arbitrage

  • The practical meaning of arbitrage trading and statistical arbitrage. Risks of hedge funds and proprietary desks. Models' limitations in detecting arbitrage
  • Analysing and validating arbitrage strategies by revealing their nature of directional trades on market uncertainty
  • Practical example on the Equity/Bond capital-structure arbitrage
  • Cap-swaption arbitrage and how it broke down

Payoff Errors

  • Last but not least: are we sure the payoff is right? Mathematical errors and legal errors
  • Examples of payoff errors widely common in the market: index options and bilateral counterparty risk

A final synthesis with practical MatLab workshops on model risk and model validation

 



Keep me updated about this course

Submit