Sannolikhet, statistik och kombinatorik: Bayesian sequential least-squares estimation for the drift of a Wiener process
- Plats: Ångströmlaboratoriet 64119
- Föreläsare: Erik Ekström
- Kontaktperson: Fiona Skerman
Abstract: Given a Wiener process with unknown and unobservable drift, we seek to estimate this drift as effectively but also as quickly as possible, in the presence of a quadratic penalty for the estimation error and of a linearly growing cost for the observation duration. In a Bayesian framework, this question reduces to choosing judiciously a stopping time for an appropriate diffusion process in natural scale; we provide structural properties of the solution for the corresponding problem of optimal stopping. This is joint work with Ioannis Karatzas and Juozas Vaicenavicius.