ABSTRACT
In modern finance theory, asset prices are typically modeled as a semimartingale. In addition, recent technological developments have made financial high frequency data commonly available. These motivate researchers to develop statistical inference for semimartingales based on high-frequency observation data. In this paper we give a brief review on this topic with emphasis on non-parametric estimation of quadratic covariation matrices and quasi likelihood analysis of stochastic processes.
