This paper proposes a new intraday volatility forecasting model, particularly suitable for modeling a large number of assets. We decompose volatility of high-frequency returns into components that may be easily interpreted and estimated. The conditional variance is a product of daily, diurnal,...

We propose a dynamic econometric microstructure model of trading, and we investigate how the dynamics of trades and trade composition interact with the evolution of market liquidity, market depth, and order flow. We estimate a bivariate generalized autoregressive intensity process for the...

This article formulates a bivariate point process to jointly analyze trade and quote arrivals. In microstructure models, trades may reveal private information that is then incorporated into new price quotes. This article examines the speed of this information flow and the circumstances that...

This paper proposes a new intraday volatility forecasting model, particularly suitable for modeling a large number of assets. We decompose volatility of high-frequency returns into components that may be easily interpreted and estimated. The conditional variance is a product of daily, diurnal,...

Financial risk management has generally focused on short-term risks rather than long-term risks, and arguably this was an important component of the recent financial crisis. Econometric approaches to measuring long-term risk are developed in order to estimate the term structure of value at risk...

This paper proposes a new generalized autoregressive conditionally heteroskedastic (GARCH) process, the asymmetric generalized dynamic conditional correlation (AG-DCC) model. The AG-DCC process extends previous specifications along two dimensions: it allows for series-specific news impact and...