Equity Derivatives and Market Risk Models

Content

• The Authors
• Notation
• Introduction
• Part I. Modelling Framework
  • 1. The Black-Scholes Framework
  • 1.1 The Black-Scholes equity model
  • 1.2 Extentions to Black-Scholes
  • 2. Skew Models
  • 2.1 Introduction
  • 2.2 Volatility surface generation
  • 2.3 Volatility smile model
  • 2.4 Volatility surface dynamics
  • 3. Jump-Diffusion Models
  • 3.1 Model Description
  • 3.2 Options pricing
  • 3.3 Fitting the smile
  • 4. Deterministic Volatility Models
  • 4.1 Introduction
  • 4.2 Calibration techniques
  • 4.3 Hedging
  • 5. Stochastic Volatility Models
  • 5.1 The Hull-White model
  • 5.2 The Heston Model
  • 5.3 Calibration
  • 5.4 Hedging
  • 5.5 Introduction to Arch and Garch
  • 6. Credit Spread Models
  • 6.1 Merton's model
  • 6.2 Structural models
  • 6.3 Intensity models
  • 6.4 Convertible bonds with credit risk
• Part II. Numerical Techniques
  • 7. Trees
  • 7.1 Thich tree
  • 7.2 Implied trees
  • 7.3 Stochastic trees
  • 7.4 Generic tree framework
  • 8. Finite Difference
  • 8.1 One-dimensional techniques
  • 8.2 Path-dependant options
  • 8.3 Two-dimensional techniques
  • 8.4 Generic finite difference
  • 9. Monte Carlo
  • 9.1 Local volatility in Monte Carlo
  • 9.2 It-Taylor expansion
  • 9.3 Greeks in Monte Carlo
  • 9.4 Generic Monte Carlo framework
  • 10. Alternative Approaches
  • 10.1 Fourier transforms
  • 10.2 Laplace transforms
  • 10.3 Path integral
• Part III. Market Products
  • 11. American Options on Multi Assets
  • 11.1 Markov chain method
  • 11.2 Regression for continuation method
  • 11.3 Simulated tree
  • 11.4 Stochastic mesh
  • 12. Volatility Contracts
  • 12.1 Variance swaps
  • 12.2 Covariance swaps
  • 12.3 Volatility swaps
  • 13. Discrete Sampling Options
  • 13.1 Barriers
  • 13.2 Lookbacks
  • 14. Additional Products
  • 14.1 Cliquet with smile - analytical approximation
  • 14.2 Barrier options with a smile
  • 14.3 Passport options
• Part IV. Risk Management
  • 15. Introduction to Risk Management
  • 15.2 Credit Risk
  • 15.3 Raroc
  • 16. Value-at-Risk
  • 16.1 The VaR approach
  • 16.2 VaR methodologies
  • 16.3 Simulated VaR
  • 16.4 Analytical VaR
  • 16.5 Correlation concepts
  • 17. Extreme Value Theory
  • 17.1 The domain of attraction
  • 17.2 A central limit theorem for maxima
  • 17.3 Point process approach
  • 17.4 Estimation of the tail distribution
  • 17.5 A limit theorem for the excess distribution
  • 17.6 The peaks over threshold (POT) method
  • 17.7 Dynamic extreme value theory
  • 17.8 Multi-day returns
  • 17.9 Multivariate EVT
  • 17.10 Hill estimation
  • 18. Coherent Risk Measures
  • 18.1 Axioms for acceptance sets
  • 18.2 Correspondence between acceptance sets and risk measures
  • 18.3 Axioms for risk measures
  • 18.4 Correspondence between the axioms on acceptance sets and risk measures
  • 18.5 Value-at-risk and expected shortfall
  • 18.6 Model-free risk measures
  • 18.7 Generalised senarios
  • 19. Credit Risk Management
  • 19.1 The asset value model
  • 19.2 The credit quality migration model
  • 19.2 Credit Risk+
• Bibliography