Author(s)

Xuchang Chen, Guoqiang Tang, Yumei Ren, Xin Li

Faculty of Science, Guilin University of Technology, Guilin, China.

The low-frequency macroeconomic variables are applied to the risk prediction of the “belt and road” concept index. Firstly, the time-varying parameter vector autoregressive model (TVP-VAR) is used to calculate the Risk Spillover Effect of the “belt and road” concept index, and the improved adaptive noise complete set empirical mode decomposition (ICEEMDAN) is used to decompose the Risk Spillover index; Secondly, combined with permutation entropy and extreme gradient lifting tree model with Shapley value (XGBOOST), the characteristics of monthly macroeconomic variables were screened and the dimension was reduced by factor analysis, and the macroeconomic factors were extracted; Then the empirical mode component terms of macroeconomic factors and Risk Spillover index decomposition are reconstructed by using the mixing sampling model (CARCH-MIDAS); Finally, the reconstructed data and technical data are combined to use the depth autocorrelation network model (AUTOFORMER) for prediction, and the error is compared with other benchmark models. The empirical results show that this model has a higher accuracy in predicting the risk trend of the “belt and road” concept index. Therefore, investors should pay attention to the impact of macroeconomic variables when preventing the risk of the “belt and road” concept index.

Belt and Road, TVP-VAR, ICEEMDAN, AUTOFORMER

Chen, X. , Tang, G. , Ren, Y. and Li, X. (2023) An Analysis of the “Belt and Road” Concept Index’s Risk Alert Integrating Mixed-Frequency Macroeconomic Variables. Journal of Financial Risk Management, 12, 366-387. doi: 10.4236/jfrm.2023.124019.