There are many approaches for estimating an integrated variance and covariance in the presence of market microstructure noise. It is important to know a dependence of noise to construct the integrated variance and covariance estimators. We study a time dependence of bivariate noise processes in...

The cumulative covariance estimator in Hayashi and Yoshida (2005) which suits for non-synchronous observations possibly has a bias in the presence of the observational noise. We propose the test statistic to detect whether the observational noise causes a measurable bias in the estimator of...

The cumulative covariance estimator in Hayashi and Yoshida (2005b) which suits for non-synchronous observations possibly has a bias in the presence of the observational noise. We propose the test statistic to detect whether the observational noise causes a measurable bias in the estimator of...

This paper proposes new test statistics for the dependence and cross and auto covariance estimators of bivariate noise processes. It derives their asymptotic distributions and provides additional tests for the statistical significance of covariance estimators. Monte Carlo simulation shows that...

For the linear hypothesis in a strucural equation model, the properties of test statistics based on the two stage least squares estimator (2SLSE) have been examined since these test statistics are easily derived in the instrumental variable estimation framework. Savin (1976) has shown that...