Inference for Multi-Dimensional High-Frequency Data

Markus Bibinger & Per A. Mykland
We find the asymptotic distribution of the multi-dimensional multi-scale and kernel estimators for high-frequency financial data with microstructure. Sampling times are allowed to be asynchronous. The central limit theorem is shown to have a feasible version. In the process, we show that the classes of multi-scale and kernel estimators for smoothing noise perturbation are asymptotically equivalent in the sense of having the same asymptotic distribution for corresponding kernel and weight functions. We also include the...
This data repository is not currently reporting usage information. For information on how your repository can submit usage information, please see our documentation.