How a start-up hedge fund leveraged the BMLL data science platform to reduce set up costs and shorten time to market
To develop effective investment and trading strategies, quantitative or systematic hedge funds must carry out extensive research and run complex computation and continuous model calibrations. They require robust infrastructure in place to do this. Building such a data engineering infrastructure in-house can be a significant investment for early-stage hedge funds, since it requires substantial financial resources to acquire the necessary hardware, software and associated technical support resources prior to generating any potential returns.
Aleto (formerly Magma Capital Funds) is a start-up Hedge Fund that delivers cutting-edge product and technology offerings to empower RIAs. Gershie Vann, CEO and Founder speaks to BMLL about the complexities and challenges of setting up a new systematic hedge fund, and how Aleto was able to overcome these challenges.
“BMLL allowed us to bypass the complex and costly process of obtaining data from exchanges. As a result, we could focus our efforts on conducting research to determine usefulness and relevance of data to our specific needs. Having immediate access to the data eliminated any delays that would have otherwise hindered our research efforts. By removing these barriers, our team could dive straight into analyzing the data and extracting results.”
- Gershie Vann, CEO and Founder, Aleto.
