Construction of International Trade and Investment Platform Based on Artificial Intelligence Technology

Abstract

Abstract This paper completes the implementation of the risk control module of the international trade investment decision-making module through the construction process of the programmed international trade investment platform. Combining the decision tree algorithm and logistic regression algorithm to categorize and screen the factors affecting the fluctuation of international trade stock prices to obtain the international trade market fundamentals and technical factors that have a significant impact on international trade stock prices. The Kalman filter model is applied to improve the effective market factors screened so that the factor selection of the international trade investment model is more advantageous. After constructing the platform, in order to reflect its convenience, the RE, OLS, TI, TVD and BC models were used to analyze the export trade efficiency of the home country, respectively. The results show that the degree of facilitation of the host country’s trade and investment platform is positively correlated with the loss of the home country’s export trade efficiency (0.043), which is statistically significant at the 1% significance level, and that the loss of the home country’s export trade efficiency increases by 4.3% for every 1 unit increase in the degree of facilitation of the host country’s trade and investment platform. The construction of the international trade and investment platform increases the facilitation of export trade from trading partner countries to the host country, which indirectly increases the export trade efficiency loss of the home country.