Our Man Group case study: Generating alpha and managing risk at petabyte scale using Python.

In the pursuit of alpha, leveraging cutting-edge database technology is essential to unlocking new data sets, markets, products, and opportunities. As real-world data continues to grow exponentially, legacy database approaches are no longer sufficient to overcome the deep-rooted challenges faced in quantitative research. Traditional infrastructures - burdened by complexity, high costs, and inefficiencies - often leave teams waiting on schema modifications, siloed across disparate data stores, and exposed to risks of data corruption or inconsistent trading outcomes. ArcticDB transforms this process by enabling firms to confidently store, analyse, and access real-world data at scale, all through familiar data science Python API. By streamlining quant operations, reducing risk, and eliminating technology bottlenecks, ArcticDB enables research teams to optimise their workflows and focus on what matters, generating alpha.

Customer story: Man Group

Man Group is a leading active investment management firm dedicated to delivering strong performance and tailored client portfolio solutions. They leverage cutting-edge technology across our operations to remain at the forefront of our dynamic industry. Currently, Man Group manages $168.6 billion in assets. Man Group relies on ArcticDB to help deliver value to a global client base.

Background

Searching for alpha and managing risk requires the ability to ingest, store, and analyse an ever-growing volume of complex, variable data across multiple asset classes. Flexible and adaptable data storage is also essential to accommodate schema changes, new data versions, and incomplete or missing data points. Additionally, the ability to time-travel through different versions of data is critical for auditing research models, ensuring that research remains accurate, reliable, and relevant.

As new trading strategies emerge, simultaneous data access across multiple teams becomes crucial. This drives the need for technology that fosters collaboration and moves away from traditional centralised approaches, which often lead to increased complexity, higher costs, and slower model production.

Challenge

While the importance of quantitative research and analysis is widely recognised, many financial services organizations struggle with the execution. They face several challenges and barriers:

• Managing ever-growing, diverse data sets spanning multiple asset classes

• Adapting to incomplete or outdated data, which can lead to inaccurate conclusions

• Empowering teams with familiar, user-friendly technology instead of restricting them with proprietary languages

• Fostering a collaborative culture where data is easily accessible and shared across teams

• Ensuring compliance with regulations by maintaining auditable records of data decisions over time

Overcoming these obstacles is critical to unlocking the full potential of quantitative research.

Strategy

Man Group implemented ArcticDB to support its Quant Research needs, supporting data across multiple asset classes on a highly flexible, scalable, and easily accessible time-series database. With ArcticDB, data sets can be accurately stored, quickly accessed by multiple teams using a Python API, and shared across multiple teams concurrently. Specifically, ArcticDB:

• Is fast, instantly queryable and optimised for huge Python dataframes, capable of processing up to billions of rows and hundreds of thousands of columns in seconds.

• Deployed effortlessly, and easy to adopt, with no sever infrastructure required, or staff trained on proprietary languages making it easy to roll out to teams.

• Setup to achieve savings through reduced infrastructure and change management.

ArcticDB has been used by leading financial services providers like Man Group for asset management due to its familiar Python interface, ability to scale, familiar API, and its ability to deliver tangible cost efficiencies.

Outcome

ArcticDB empowers firms to be "Quant Research Ready" by addressing key challenges in data management and collaboration. It provides a scalable, easy-to-adopt solution that adapts to business needs and growth, enabling teams to transform raw data into models faster, with less effort and reduced infrastructure costs.

If you are interested in using ArcticDB in a business setting, please contact us at info@arcticdb.io.