. We argue that this is due to the fact that the conditional mean parameters of realized regression models are …We study bootstrap methods for statistics that are a function of multivariate high frequency returns such as realized … regression coefficients and realized covariances and correlations. For these measures of covariation, the Monte Carlo simulation …

realized regression, covariance and correlation coefficients. We show that the finite sample performance of the bootstrap is … mean parameters of realized regression models are heterogeneous under stochastic volatility. …

A new approach to mean-variance efficient portfolio selection is introduced. The method is based on realized regression …

the multivariate realized regression principle, an omnibus noise ?filter and an adaptive long memory forecasting model …. While the multivariate realized regression approach allows for an accurate estimation of the betas also when more than a …