AbstractWe provide empirical evidence of directionality in high‐frequency multivariate time series of the five largest U.S. banks between 1999 and 2017. The directionality is more apparent during crisis periods than during noncrisis periods, and it has only a low association with volatility. We use directionality and volatility as a regime‐switching criterion between two‐regime threshold vector autoregressive (TVAR) models for forecasting share prices. We compare the forecasting performances using mean relative error squared, and a weighted average of the forecasting error, with weights based on the estimated conditional variance, for individual model components and as a group. We have demonstrated that moving directionality can provide early warning of increased volatility and crisis periods, and has potential for improving one‐step ahead forecasts using TVAR(1) models.