BST Awards 2020: Best buy-side commodities trading platform—Barchart

Chicago-based Barchart takes home the gold this year as the best buy-side commodity trading platform, thanks to its cmdtyView offering. 

Mark Haraburda, CEO at Barchart, says the platform helps clients simplify complex and cumbersome workflows. Through a single platform, Barchart provides global exchange data, physical commodity prices, futures and physical execution, and advanced analytics to commodities market participants within agriculture, energy, and metals.

Over the past year, the firm has invested in a number of different areas. These include the development of geospatial tools to analyze commodity data, including prices and fundamentals like supply and demand, production and consumption. 

“Commodities naturally have local factors impacting them, so tying this data into mapping technologies and creating localized indexes provides enhanced analytical capabilities as well as more precise price assessments,” Haraburda says. 

Barchart is also continuing its work on developing more proprietary data sets, such as localized indexes for commodities like corn and soybeans, as well as commodity production and yields. Haraburda says these models utilize satellite imagery, advanced weather data collection, and other big data aggregations overlaid with cloud-based data processing routines and technologies like artificial intelligence (AI) to produce actionable information for decision-making. 

“We are expanding the scope and reach of our physical commodity trading capabilities by providing commodity producers with the ability to connect with our commodity-buyer community through mobile apps. In addition, we are expanding further into additional commodity sectors like energy and metals,” he says.    

Aside from adding new asset classes and multi-language support, a big part of the firm’s roadmap is creating proprietary data sets outside the US, often in the form of local and regional indexes. 

“The predictive models we have built for commodities in the US are easily replicable to other areas of the globe, and that is exactly what we plan to do … take our proprietary data sets global,” he says.