Literature Review in International Trade Forecasting Based in Machine Learning Method

Author:

Tong Ye

Abstract

In recent years, with the intricacy of international politics and economic situation and the anti-globalization trend, China’s trade with world is facing many serious challenges. There are more factors that effects China export and import. Because of that, high-precision forecasting for international trade is beneficial for nation’s government, guild and export and import enterprise that need a judgement or decision for future. To better promote future research, the paper reviews the paper written by experts from world in trade forecasting field, classifies and summarizes their opinion according in their adopting machine learning method.

Publisher

EDP Sciences

Subject

General Medicine

Reference25 articles.

1. Huang Y.. China’s export forecast based on quantile diffusion index autoregressive model. Lanzhou University[D],2022

2. Wang PL. Time series analysis of China’s service trade based on ARIMA model, International Conference on Economics,Finance and Statistics(ICEFS), JAN 14-15, 2017

3. Li Z..ARIMA quarterly model of China’s international trade imports[C],Beijing,2016.

4. Mei M.. The Reasearch about the Potential of Oil Trade between China and Africa, Ocean University of China[D],2015.

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