Quant friendly index and market data with up to 30 years history

Our client is a large Investment Manager headquartered in the US, who promises to deliver superior, long-term investment performance and a client experience that exceeds expectations.

Mission critical data   

Their self-professed mission, to evaluate every investment decision to achieve superior performance, puts them under a lot of pressure to ensure they have on demand access to the highest quality data possible. For their research teams, this includes up to 30 years of daily snapshot history.

When RIMES met them, they either had gaps in the history they required, or they had the history but the quality was not fit-for-purpose. One of the major issues with historical data is maintaining it. For example, missed corporate actions often result in erroneous identifiers that break attempts to analyze historical data, resulting in hours of investigation and remediation at great cost to the business.

As a provider of Managed Data Services, RIMES’ reputation is based on the quality of the data we maintain for our clients. We have teams dedicated to ensuring the correct application of corporate actions and other revisions to the data. In addition, our client base is diverse in their requirements, for example, in the range of instrument identifiers they use. So not only must we maintain our instrument reference data, but we must cross-reference it across all our databases.

Data quality demonstrated

Using both our in-house Excel analysis tools and our API for Python tools, we showed, in a live demonstration to the quants and researchers, the depth, breadth and quality of the data we manage.

In the meeting, not only were the audience able to test and validate a range of sample data sets they were struggling with, but were shown how the data they needed could be linked using their preferred instrument identifier as the primary key.

Subsequently we provided historical data as part of a proof-of-concept exercise, which further highlighted errors in their existing data that we were able to correct.

Meeting their promises

Using the RIMES API for Python and our proprietary Excel analytical tools, the client’s equity and fixed income analysts have been able to update and correct their historical databases, facilitated by the specific primary key they wanted. Going forward, they can also maintain it without the costly resources required to manage all the changes and revisions in-house. The subsequent improvement in data quality has freed up their equity and fixed income analysts to concentrate on delivering long-term investment solutions to their clients, as they promised in their mission statement.

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