Abstract: Regime-switching stochastic differential equations are a class of models that incorporate both continuous and discrete sources of uncertainty. As such, they have a wide variety of applications in fields such as financial engineering, stochastic filtering, and control engineering. In this talk we will investigate the convergence of approximations to these models using the theory of rough paths, a modern field which has transformed the world of stochastic analysis. Specifically, we will introduce the probabilistic notion of strong convergence, discuss the basics of rough path theory, discover how we can acquire pathwise estimates of RSSDEs, and learn how these pieces fit together to establish convergence.

The Zoom link for this talk is available here.

If you are not currently affiliated with the ANU and wish to attend, please contact Po-Lam Yung.