A jump robust positive semidefinite rank-based estimator for the daily covariance matrix based on high-frequency intraday returns is proposed. It disentangles covariance estimation into variance and correlation components. This allows us to account for non-synchronous trading by estimating...

In the last decade, intensive studies on modeling high frequency financial data at the transaction level have been conducted. In the analysis of high-frequency duration data, it is often the first step to remove the intraday periodicity. Currently the most popular adjustment procedure is the...

We propose a new joint model of intraday returns and durations to study the dynamics of several Chinese stocks. We include three U.S. stocks for comparison. Flexible innovation distributions are used for durations and returns, and the total variance of returns is decomposed into different...

In this paper we examine the question of whether knowledge of the information contained in a limit order book helps to provide economic value in a simple trading scheme. Given the greater information content of the order book, over simple price information, it might naturally be expected that...

We use realized volatilities based on after-hours high frequency stock returns to predict next day stock volatility. We extend the GARCH model to include additional information: the whole after hours period, the preopen realized variance, the postclose realized variance, and the overnight...

This article highlights a comprehensive and approachable perspective to stochastic volatility models for financial time series analysis. Financial time series represent a distinctive category in the economic field, with highly dynamic characteristics, especially in times of financial crisis....