This paper applies the Least Absolute Shrinkage and Selection Operator (LASSO) to make rolling one‐minute‐ahead return forecasts using the entire cross‐section of lagged returns as candidate predictors. The LASSO increases both out‐of‐sample fit and forecast‐implied Sharpe ratios. This out‐of‐sample success comes from identifying predictors that are unexpected, short‐lived, and sparse. Although the LASSO uses a statistical rule rather than economic intuition to identify predictors, the predictors it identifies are nevertheless associated with economically meaningful events: the LASSO tends to identify as predictors stocks with news about fundamentals.

Independent technological glitches forced two separate trading halts on different U.S. exchanges during the week of July 6, 2015. During each halt, all other exchanges remained open. We exploit exogenous variation provided by this unprecedented coincidence, in conjunction with a proprietary data set, to identify the causal impact of Designated Market Maker (DMM) participation on liquidity. When the voluntary liquidity providers on one exchange were removed, liquidity remained unchanged; when DMMs were removed, liquidity decreased market-wide. We find evidence consistent with the idea that these DMMs, despite facing only mild formal obligations, significantly improve liquidity in the modern electronic marketplace.