A leading clearing house faced the challenge of a significant number of untraded options, which led to inefficiencies and limited revenue potential.
To address this challenge, DataCRaiM partnered with the clearing house to leverage the power of the Databricks platform. We analysed over a billion historical trading records to identify patterns that make certain options more likely to be traded. Our team employed a Random Forest predictive AI model to uncover key predictors of trade volume.
Our analysis revealed that a significant number (41%) of listed options had never been traded. This analysis enabled the customer to: