The article presents a model for predicting daily highs and lows of US stock indexes. The researchers found that highs and lows of these indexes are closely related over time. By analyzing data on openings, closings, and trading volume, they were able to explain 40% to 50% of the variations in daily highs and lows. The study shows that including these variables in the analysis affects how highs and lows respond to market shocks.