Bilateral Trade Flow Prediction Models Enhanced By Wavelet and Machine Learning Algorithms

International economy promotes a sense of global interdependence and offers mutual benefits to countries around the world through the system of imports and exports. In this study, we have utilized economic indicators as inputs in an algorithm scheme that is based on Machine Learning methods combined with Wavelet Transforms to predict the bilateral trade flow between pairs of trading countries. Utilizing this methodology will allow countries to strike more successful trade deals, and increase a nation’s estimated Gross Domestic Product (GDP) per capita. This will ultimately help reduce poverty as governments reallocate funds to serve struggling populations and target the 2030 United Nations Agenda (UNA) [1].