Asymptotic equivalence of discretely observed diffusion processes and their Euler scheme: small variance case

Abstract

This paper establishes the global asymptotic equivalence, in the sense of the Le Cam $\Delta$-distance, between scalar diffusion models with unknown drift function and small variance on the one side, and nonparametric autoregressive models on the other side. The time horizon $T$ is kept fixed and both the cases of discrete and continuous observation of the path are treated. We allow non constant diffusion coefficient, bounded but possibly tending to zero. The asymptotic equivalences are established by constructing explicit equivalence mappings.

21 pages

References in corpus (2)

• Asymptotic Equivalence for Nonparametric Regression
• Asymptotic equivalence of nonparametric autoregression and nonparametric regression