Lund U
Stochastic differential equations is an important class of models with a wide range of applications, commonly used in finance. Pricing of exotic financial derivatives is often a very computationally intensive process, emphasizing the need to simulate models as time-efficient as possible. The general experience though, is that fast often means less flexible. With this in mind I developed SDEModels.jl, a package dedicated to simulation of stochastic differential equations. Using features available in Julia, such as metaprogramming and a very fast RNG, I was able to achieve both lightning-fast simulation with barely any overhead, and managed to make it very simple to define and switch models. Together with additional package OptionPrice.jl, which implements fast and accurate state-of-the-art pricing algorithms, the goal is to give you a great toolbox for pricing derivatives in Julia both easy and fast for a wide variety of models and contracts.
Carl is doing his PhD studies in mathematical statistics at Lund University, Sweden. The focus of his research is inference methods for stochastic models used in mathematical finance, with a strong aspect of compuational methods and computational efficency. He has a strong interest of writing highly performant code, squeezing out every possible flop.
