We characterize how informed investors trade in the options market ahead of corporate news when they receive private, but noisy, information about (i) the timing of the announcement and (ii) its impact on stock prices. Our theoretical framework generates a rich set of predictions about the...

We reconsider the issue of price discovery in spot and futures markets. We use a threshold error correction model to allow for arbitrage operations to have an impact on the return dynamics. We estimate the model using quote midpoints, and we modify the model to account for time-varying...

We extend the classical "martingale-plus-noise" model for high-frequency prices by an error correction mechanism originating from prevailing mispricing. The speed of price reversal is a natural measure for informational efficiency. The strength of the price reversal relative to the...

Using merger announcements and applying methods from computational linguistics we find strong evidence that stock prices underreact to information in financial media. A one standard deviation increase in the media-implied probability of merger completion increases the subsequent 12-day return of...

We argue for incorporating the financial economics of market microstructure into the financial econometrics of asset return volatility estimation. In particular, we use market microstructure theory to derive the cross-correlation function between latent returns and market microstructure noise,...

We assess the quality of opening and closing prices for Nasdaq stocks by examining the effect that opening and closing call auctions (introduced in 2004) have had on price formation. Our use of measurement intervals of one minute or less sharpens the picture of intra-day volatility...

We study the impact of the arrival of macroeconomic news on the informational and noise-driven components in high-frequency quote processes and their conditional variances. Bid and ask returns are decomposed into a common ("efficient return") factor and two market-side-specific components...

Trading under limited pre-trade transparency becomes increasingly popular on financial markets. We provide first evidence on traders' use of (completely) hidden orders which might be placed even inside of the (displayed) bid-ask spread. Employing TotalView-ITCH data on order messages at NASDAQ,...

Alternative strategies for predicting stock market volatility are examined. In out-of-sample forecasting experiments implied-volatility information, derived from contemporaneously observed option prices or history-based volatility predictors, such as GARCH models, are investigated, to determine...

We report evidence that the presence of hidden liquidity is associated with greater liquidity in the order books, greater trading volume, and smaller price impact. Limit and market order submission behavior changes when hidden liquidity is present consistent with at least some traders being able...