Mathematical Finance, Stochastic Analysis, and Machine Learning Seminar by Yuan Yin: Convergence of a Branching Particle Filtering Algorithm for Partially Observed Diffusions, with Application in Market Microstructure Modeling

Speaker: Yuan Yin, Illinois Institute of Technology

Title: Convergence of a Branching Particle Filtering Algorithm for Partially Observed Diffusions, with Application in Market Microstructure Modeling

Abstract: In this talk I will present a thorough analysis of the particle filtering algorithm for estimating the conditional distribution in partially observed diffusion models. Specifically, it focuses on estimating the distribution of unobserved processes using observed data. The algorithm involves several steps and assumptions, which are described in detail. We also examine the convergence of the algorithm and identify sufficient conditions under which it converges. Finally, we derive an explicit upper bound on the convergence rate of the algorithm, which depends on the set of parameters and the choice of time frequency. This bound provides a measure of the algorithm's performance and can be used to optimize its parameters to achieve faster convergence. This is a joint work with Sergey Nadtochiy.

 

Mathematical Finance, Stochastic Analysis, and Machine Learning