We present past results and future prospects inefficient evaluation of payoff functionals on randomly evolving dynamic quantities. In the presentation, we go through recent results in Fourier methods for exponential levy processes and derive an adaptive multi-level time stepper for simulating SDEs. We also discuss on-going research on optimal stopping for stochastic differential equations.
Carina Suciu has joined the Stochastic Numerics Group and SRI Uncertainty Quantification Center at KAUST. Carina is an Applied Mathematician and Computational Scientist specializing in numerical methods solving Populations Balance Systems (PBS). In 2007 she started to work in cooperation with chemical engineers and industrial partners, in the framework of a project “Coupled Simulations of Particle Populations in Turbulent Flows”.
Marco Ballesio successfully defended his Master Thesis "Indirect Inference for Scalar Time-homogeneous Stochastic Differential Equations Based on Moment Expansions" at Politecnico of Torino and Real Collegio Carlo Alberto. He wrote his Thesis at KAUST in the period July 2015 - January 2016 oriented by Raul Tempone, and Pedro Vilanova (Stochastic Numerics Research Group).