Sphere: From Information Streams to a Liquidity Lake
Solutions Brief Sphere's Liquidity Lake: An AI/ML-Based Solution to overcome Information Fragementation in Hybrid Markets
In trading, the person with more information usually has a head start that is often difficult to overcome. This advantage, called information asymmetry, provides the ability to capture, structure, and store information so you can act on it quickly, which is vital across financial markets. However, many markets, especially in wholesale trading, have multiple execution channels (hybrid markets), each with its own information streams, including streaming data, voice, and instant messages.
Previously, traders did their best to ingest and remember all this information, especially the voice and message information not captured anywhere else. However, the sheer volume of data and venues makes doing so nearly impossible today. As a result, there are an increasing number of new tech-driven solutions to leverage these disparate data sources. Sphere is one such innovative solution, utilizing artificial intelligence (AI) and machine learning (ML) to combine the information in one application. While Sphere focuses on the commodities market, we see the potential for this solution in other markets, such as fixed income, with similar challenges around hybrid markets.
The Liquidity lake allows traders to go from a workflow that relies on memory to a technology-driven workflow with information at their fingertips.
The workflow originally looked like this:
Information Flows in Traditional Hybrid Markets:
While with the Liquidity Lake, the workflow could look like this: