Uniform Central Limit Theorems for Multidimensional Diffusions
Angelika Rohde, Claudia Strauch

TL;DR
This paper explores the regularity and convergence properties of empirical processes based on multidimensional diffusions, revealing enhanced regularity under certain conditions and extending classical empirical process theory to diffusion settings.
Contribution
It establishes uniform CLTs for multidimensional diffusions, demonstrating increased regularity compared to classical iid processes, and characterizes conditions for weak convergence of smoothed empirical diffusion processes.
Findings
Enhanced regularity for multivariate ergodic diffusions with finite invariant measure
Uniform weak convergence possible with exponentially small bandwidth in 2D
Strong undersmoothing conditions for higher dimensions with Hölder continuous coefficients
Abstract
It has recently been shown that there are substantial differences in the regularity behavior of the empirical process based on scalar diffusions as compared to the classical empirical process, due to the existence of diffusion local time. Besides establishing strong parallels to classical theory such as Ossiander's bracketing CLT and the general Gin\'e-Zinn CLT for uniformly bounded families of functions, we find increased regularity also for multivariate ergodic diffusions, assuming that the invariant measure is finite with Lebesgue density . The effect is diminishing for growing dimension but always present. The fine differences to the classical iid setting are worked out using exponential inequalities for martingales and additive functionals of continuous Markov processes as well as the characterization of the sample path behavior of Gaussian processes by means of the generic…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStochastic processes and financial applications · Markov Chains and Monte Carlo Methods · Statistical Methods and Inference
