Quantitative Analytics Database

LSEG Quantitative Analytics Database empowers you to unlock an unrivalled range of ready-to-use content. Quants and data scientists spend a staggering 40%-80% of their average day gathering, cleansing and normalising data from disparate sources. Only then can this data be used to power machine learning or traditional statistical models. At the same time, the search for differentiated strategies demands new and innovative data sets – but turning around proprietary or niche third-party data for analysis is a challenge, especially when this needs to be done at speed.

Our ready-to-use content and advanced tools to integrate proprietary data free up valuable time that can be used to develop and test ideas, optimise portfolios, manage risk and ultimately create alpha. We manage the database and update content 24/7.

Key benefits of LSEG Quantitative Analytics Database:

- Eliminate the effort of addressing different time frequencies, currencies and units, or adjusting data for corporate actions.

- Access point-in-time values and data for delisted companies.

- Enjoy a seamless user experience featuring programming languages such as Python and C# and a database that integrates with statistical packages, including R, SAS, MATLAB and S-PLUS.

- Easily map and analyse all securities associated with a single entity and build factors using data from different sources.

- Shorten time to market and reduce your workload by syncing proprietary data with our time series data sets spanning a range of identifiers – including SEDOL and RIC.

- Gain access to an unrivalled library of multi-asset securities pricing, company data and historical constituent lists.

- Back-test over multiple economic cycles and variable market conditions with trusted timestamps and point-in-time data that helps you avoid look-ahead and survivorship biases.

- Leverage our partnership with Snowflake to begin your quant or machine learning initiatives without the capital lock-in associated with deployed quantitative data solutions.

- Access quantitative analytics data as a service in the cloud and leverage Snowflake’s data sharing capabilities to combine data sets in your Snowflake account and run queries on the full content set.

- Utilise select, preloaded third-party data integrated into Quantitative Analytics, and seamlessly access information that is concorded and historically mapped.