This paper develops the idea of renewal time sampling, a novel sampling scheme constructed from stopping times of semimartingales. Based on this new sampling scheme we propose a class of volatility estimators named renewal based volatility estimators. In this paper we show that: (1) The spot...

In this paper we examine the relative importance of trading volume, bid-ask spread, order flow, order imbalance, total quote depth, quote depth difference and trading intensity for high-frequency volatility estimation. By using a best subset regression approach, we fi nd that contemporaneous...

This paper studies the theoretical properties and implementation issues with the risk-neutral density (RND) estimator based on the mixture-of-lognormal (MLN) approach. First, we establish the consistency and asymptotic normality of the MLN method under the correct choice of mixtures and propose...

We introduce a novel weighted least squares approach to estimate daily realized covariation and microstructure noise variance using high-frequency data. We provide an asymptotic theory and conduct a comprehensive Monte Carlo simulation to demonstrate the desirable statistical properties of the...

Statistical disclosure limitation is widely used by data collecting institutions to provide safe individual data. However, the choice of the disclosure limitation method severely affects the quality of the data and limit their use for empirical research. In particular, estimators for nonlinear...

We derive the finite sample bias of the sample cross-covariance estimator based on a stationary vector-valued time series with an unknown mean. This result leads to a bias-corrected estimator of cross-covariances constructed from linear combinations of sample cross-covariances, which can in...