In the previous posts, we saw that it is easy to create a PDE solver for pricing options. But, what happens if one likes to price more complex structures like convertible bonds or variable annuities?

All posts in this series:

• Basics of a PDE solver in Matlab
• Pricing American options with a PDE solver
• Efficient pricing of barrier options
• Complex pricing models for PDE solver

An efficient way of describing an options payoff is ThetaML. In many cases, ThetaML is used as a configuration for Monte Carlo Simulations. Now, Stefanie Schraufsetter presents a new book on PDE methods based on ThetaML:

A Pricing Framework for the Efficient Evaluation of Financial Derivatives based on Theta Calculus and Adaptive Sparse Grids

More info at Amazon: Stefanie Schraufstetter: A Pricing Framework for the Efficient Evaluation of Financial Derivatives based on Theta Calculus and Adaptive Sparse Grids

For examples on ThetaML in the context of PDE solver see the presentations from Stefanie Schraufstetter and Janos Benk at  the PRMIA Workshop on Variable Annuities.