| Summary: | This year marks the 10th anniversary of the Belt and Road Initiative, and relevant theme indexes have attracted market attention. As a characteristic policy of China’s foreign trade, it is of great significance to study the development situation of its related stocks for the progress and future development of the Belt and Road. In this paper, EMD method and ARMA model are adopted. Taking the SSE One Belt & One Road Index as the representative of the Belt and Road Theme Index, the paper analyzes the price influencing factors of the Belt and Road theme stocks and predicts the future trend of their volatility. It believes that the price of the Belt and Road theme index is mainly affected by three parts: market supply relationship, short-term common influencing factors and long-term major event impact. Making EMDARMA prediction on its volatility and finds it to be more accurate than using the ARMA model directly.r load forecasting is very important for power dispatching. Accurate load forecasting is of great significance for saving energy, reducing generating cost and improving social and economic benefits. In order to accurately predict the power load, based on BP neural network theory, combined with the advantages of Clementine in dealing with big data and preventing overfitting, a neural network prediction model for large data is constructed.
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