Equity Derivatives: Advanced Models

 

"The course material and the tutor were excellent. I can recommend this course to any quants."

Frederic Marechal - Quantitative Analyst
Click for more comments

Course Outline

This course introduces and applies advanced models for the pricing of equity derivatives. The objective of the workshop is to develop a solid understanding of the current frameworks for pricing equity derivatives and to give participants the mathematical and practical background necessary to apply the various pricing methodologies to the market.

Delegates are entitled to a 30% discount on Schoutens's book, Lévy Processes in Finance: Pricing Financial Derivatives

View a course sample

Who The Course is For

  • Quantitative analysts
  • Risk managers
  • Fund managers
  • Financial engineers
  • Researchers
  • Credit managers
  • Accountants
  • Corporate and financial consultants
  • Treasury managers
  • Portfolio managers
  • Venture Capital executives

Tell a colleague about this course

Prior Knowledge

Probability theory, basics of stochastic processes, basic concepts of financial products, bionomial tree modelling and the Black-Scholes setting, a good maths background and knowledge of basic maths models, knowledge of basic programming.


This program is eligible for 24 Continuing Education credit hours from the CFA Institute. If you are a CFA Institute member, CE credit for your participation in this program will be automatically recorded in your CE Diary.


photos Brochure with Booking Form   |   Register to Receive Updates

Day One

Shortfalls of the Black-Scholes Model

  • Problems with the Normal Distribution
  • The need for stochastic volatility
  • Fat tails and extreme events
  • Implied volatility
  • Stylised features of financial returns

An Introduction to Jump Processes

  • Skewed and fat tailed distribution
  • Jump processes; the state-of-the art
  • Details of popular examples
  • The Variance Gamma model

Workshop: PC-based implementation of the VG model (Matlab)

  • Implementation of density function
  • Simulation of Variance Gamma random variables
  • Parameter intuition

Day Two

Stochastic Volatility

  • Stylised features of volatility
  • The Heston model
  • Heston with jumps
  • Jump models with stochastic volatility

Pricing European Options using Characteristic Functions

  • The basics of characteristic functions and Fast Fourier Techniques
  • The generic pricing formula for vanilla option
  • Full details of how to implement the fast generic option pricer
  • Calculation of Greeks and other vanilla payoffs

Calibration

  • Basic concepts of calibration
  • Search algorithms
  • Rule of thumb in choosing good starting values

Workshop: PC-based implementation of FFT pricing and calibration algorithm (Matlab)

  • Hands-on- implementation of the fast vanilla pricer
  • Detailed implementation of Heston and/or VG vanilla pricers
  • Testing of the models, and producing implied vol surfaces

Day Three

Monte Carlo Simulations: Theory

  • General Concepts
  • Sampling of Heston paths
  • Simulated correlated variables
  • Sampling jumps
  • Sampling skewed and fat-tailed distributions
  • Advanced sampling methods: Milstein's scheme

Exotic Option Pricing

  • Pricing European options using Monte Carlo simulation
  • Exotic option pricing
  • Structured Products
  • Model Risk

Workshop: PC-based implementation of Monte Carlo Simulations and Exotic Option pricing (Matlab):

  • Heston Monte Carlo implementation
  • barrier products
  • Cliquets
  • Reverse Ciliquets
  • Asians

At the end of the course delegates will have running on their machines (Matlab):

  • FFT pricer for vanillas for VG and/or Heston
  • Calibration algorithm for VG and/or Heston
  • Monte Carlo Pricers for VG and/or Heston for a range of exotic options
Copyright © London Financial Studies