High frequency trading (HFT) depends on sophisticated algorithms to closely monitor price changes across securities. Theory predicts this technological advantage should translate into market-wide liquidity co-variation, by transmitting information-based liquidity shocks. Using a dataset of...

High-frequency trading has become a dominant force in the U.S. capital market, accounting for over 70% of dollar trading volume. This study examines the implication of high-frequency trading for stock price volatility and price discovery. I find that high-frequency trading is positively...

This paper shows that intensity of high-frequency trading (HFT) in stocks held by mutual funds is negatively related to fund performance. This negative relation can largely be explained by the illiquidity premium: HFT-intensive stocks provide lower returns because the majority of these stocks...

We propose a novel high-frequency decomposition of daily stock returns into news- and non-news-driven components, and uncover evidence of pervasive stock market underreaction to firm news. Prices tend to drift in the same direction as the initial market response for several days after the news...

We study the consequences of high-frequency trading (HFT) — and potential policy responses — via the tradeoff between liquidity and information production. Faster speeds facilitate HFT with consequences for this tradeoff: information production diminishes because informed traders have less...

This paper studies the predictability of ultra high-frequency stock returns and durations to relevant price, volume and transactions events, using machine learning methods. We find that, contrary to low frequency and long horizon returns, where predictability is rare and inconsistent,...