Using Shipfix's global dataset on cargo orders, we prove our ability to predict physical trade flows quantitatively and objectively. In this article, we detail a few practical examples, starting with the Russian grains trade.
On 1 April 2020, the ministry of agriculture in Russia imposed an export quota on grains. This decision, amid the COVID 19 Crisis, highlighted the significance of the country's status as the largest wheat exporter worldwide. At Shipfix we decided to seize this hot market topic as a first opportunity to demonstrate the value of our data as a trade flow predictor for the grain trade.
The graph below illustrates a historical time series of all grain orders recorded out of Russia by Shipfix versus the official trade figures reported by established sources, in this case the UN's Comtrade database.
The plotted lines display a very significant predictive correlation which illustrate a simple market dynamic: grain shipping orders are circulated in the dry cargo market days, sometimes weeks before they are loaded onto a vessel and then that vessel spends weeks at sea before discharging the commodity and settling the trade.
Shipfix is the only market data provider that measures objectively through a data-driven approach the aggregate number and volume of order traded for over 460 products and commodities worldwide and over the major trading routes
Other examples of correlation analysis across other markets