This is a course on estimation in high frequency data. It is intended for an
audience that includes people interested in finance, econometrics, statistics, probability and financial engineering.
There has in recent years been a vast increase in the amount of high frequency data available. There has also been an explosion in the literature on the subject.
In this course, we start from scratch, introducing the probabilistic model
for such data, and then turn to the estimation question in this model. We shall be focused on the (for this area) emblematic problem of estimating volatility. Similar techniques to those we present can be applied to estimating leverage effects, realized regressions, semivariances, doing analyses of variance, detecting jumps, measuring liquidity by measuring the size of the microstructure noise, and many other objects of interest.
The applications are mainly in finance, ranging from risk management to options hedging, execution of...