Stock return forecast is of great importance to trading, hedging, and portfolio management. In this article, we apply LASSO and random forest to make rolling one-minute-ahead return forecasts of Dow Jones stocks, using the cross-section of lagged returns of S&P 500 components as candidate predictors. Although the number of candidate variables is large, the negative out-of-sample R2 suggests that the predictions from LASSO and random forest give larger mean-squared error than the historical average. So, there is no evidence of predictability in the cross-sectional returns of large stocks in high frequency. The predictability presented by Chinco et al. (2019) might be due to the interaction between large and small stocks.