This 2 day workshop will be focusing on:

COURSE OBJECTIVE

• Learn how to use finite difference methods for option pricing in practice.
• Learn about discrete duality, stability, convergence, grid dimensioning, grid alignment, and how-to-do in practice.
• These concepts will be introduced through experiments with a self-coded one-dimensional PDE solver.
• Upon completion of the course, you will be ready to implement the finite difference method for standard 1D models such as

Black-Scholes, local volatility models, and the Hull-White model.

• … and be ready to go on to harder problems, such as: stochastic local volatility, Cheyette, hybrid models and models for
• option market making.
• In other words: From finite difference zero to hero in two days.

DAY 2: 09.00 – 17:00

• Code fdBwdRunner().
• Code fdFwdRunner().
• Work on exercises:
  • Time step convergence of the different theta schemes: implicit, explicit, crank-nicolson
  • Early exercise premium for American options: convergence and early exercise boundary.
  • Digital options.
  • Grid width and spatial convergence.
  • Discrete Dupire equation.
  • Barrier options.

• Collect results and experiences. Discuss in class.
• Discuss applications: traditional and some new ones.
• Including option market making and margin modeling.
• Have a look at a 2D solver.