International Merchandise Trade Statistics is a powerful dataset that can be used from a financial perspective to not only analyse historical markets, their volatility and evolution, but also used as a means to forecast commodity price movements. Global Trade Atlas (GTA) Research Paper was conceptualized to answer the below questions, with also the added intent of informing the industry of its potential use cases as well as to potentially drive innovation in this through the wider community:

1. Can Harmonised System codes be mapped against more traditional 'commodities'
2. Can any of the concepts found in Statistical Trade Data be correlated to spot prices
3. Could the data be used within the scope of predictive analytics to predict fluctuations in tradable commodity prices

We define the International Merchandise Trade Statistics which power the Global Trade Atlas utilised in this paper, scope the study to three reporter countries of interest: India, China and the United States - where for
each we select three/four commodities to focus on and analyse any statistical relationships against spot prices for the number of concepts that exist within the Statistical Trade Data, as well as discuss potential
applications within forecasting to provide short-term indications. We then use the US soybean trade as a case study to exemplify how the data can be used to generate insights into this commodity market and its short-term evolution.

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