In this study, we adjust the hierarchical risk parity (HRP) model by introducing hierarchical information on assets to help manage portfolio risk. The adjusted HRP model with hierarchical information considers both correlation and hierarchical information. Compared with other models, the HRP model with hierarchical information has better out-of-sample robustness for simulation data. Moreover, this model achieves better out-of-sample performance using Chinese industry indices data. The results reveal that the adjusted HRP model is an efficient tool to control out-of-sample portfolio risk.