We compare the optimal trading strategy of an informed speculator when he can trade ahead of incoming news (is "fast"), versus when he cannot (is "slow"). We find that speed matters: the fast speculator's trades account for a larger fraction of trading volume, and are more correlated with...

Information processing filters out the noise in data but it takes time. Hence, low precision signals are available before high precision signals. To capture this feature, we develop a model of securities trading in which investors can acquire signals (about future cash flows) of increasing...

We use clickstream data to show that investors' demand for information about macroeconomic factors affecting the path of future interest rates is a measure of their uncertainty about this path. In particular, an increase in information demand ahead of influential economic announcements affecting...

We analyze how computing power and data abundance affect speculators' search for predictors. In our model, speculators search for predictors through trials and optimally stop searching when they find a predictor with a signal-to-noise ratio larger than an endogenous threshold. Greater computing...