This is the first paper about the high dimensional beta tests with high frequency financial data, which allowing that the number of regressors can be larger than the number of observations within each estimation block and can also grow to infinity in asymptotics. In this paper, the sum-type test...

High-frequency financial data are not only discretely sampled in time but the time separating successive observations is often random. We analyze the consequences of this dual feature of the data when estimating a continuous-time model. In particular, we measure the additional effects of the...

This paper shows that the asymptotic normal approximation is often insufficiently accurate for volatility estimators based on high frequency data. To remedy this, we compute Edgeworth expansions for such estimators. Unlike the usual expansions, we have found that in order to obtain meaningful...