The Double Gaussian Approximation for High Frequency Data

Abstract High frequency data have become an important feature of many areas of research. They permit the creation of estimators in highly non‐parametric classes of continuous‐time models. In the context of continuous semi‐martingale models, we here provide a locally parametric ‘double Gaussian’ approximation, to facilitate the analysis of estimators. As in Mykland and Zhang (Econometrica, 77, 2009, p. 1403), the error in the approximation can be offset with a postasymptotic likelihood correction. The current approximation is valid in large neighbourhoods, permitting a sharp analysis of estimators that use local behaviour over asymptotically increasing numbers of observations.