EDS Chief Data Scientist Ben Lieblich recently sat on a panel, along with Snowflake’s Bryan Lenker and FactSet’s Kellyn Cochell, discussing data trends among investment teams and how cloud-enabled capabilities can power quantitative research and investment analytics workflows.
For quantitative researchers and investment managers, streamlined access to data, integrated workflow tools, data transformation and sharing capabilities can accelerate their ability to perform faster research, run faster backtests, and generate alpha. However, for many asset managers and banks, legacy technology stacks and data silos provide slower processing engines with high maintenance costs, limited ability to enable ML-based strategies, and slower time to insight. During the webinar, hear from industry leaders on how technology can elevate their investment data and process management approach, as well as watch a brief demo on Snowflake. Some insights mentioned:
- In recent years, fundamental funds are becoming much more data-driven and bringing in factor-based risk management into their portfolios.
- Modern, sophisticated, flexible technology and cloud-native databases empower investment teams to have the freedom to choose how they consume data and insights, and simplify efforts in gaining transparency from their front office infrastructure.
- Quants are leveraging machine learning and large language models (LLMs) techniques which enables them to expand their reach of various data sets.