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The leading knowledge platform for the financial technology industry

A-Team Insight Blogs

AIM Software Automates Data Prep for Quant Modelling with Gain Quant DB

AIM Software has secured an initial three customers for it Gain Quant DB application that was originally designed to help its first customer automate data preparation for quant modelling. This customer, a large asset manager, is in production with the solution, while the second will be in production in the first quarter of next year and the third is starting work on implementation.

The asset manager needed a solution that would easily aggregate index and market data from multiple sources, including Thomson Reuters QA Direct and stock exchanges, and feed it into MatLab. It ran a selection process involving US and European software vendors in search of a solution, before asking AIM Software to develop a new business application on its Gain enterprise data management platform.

The resulting Quant DB application acts as a central research database that automatically collects and cross-references data from various sources, eliminating the risks of manual consolidation. Snapshots of market data are created several times a day using a vendor agnostic approach and are stored centrally and made available to all quants for the development and validation of models.

Vincent Goubert, lead business development, front office at AIM Software, explains: “Quant teams use a minimum of 10 different data sources for their research and these are expensive. They often design and develop their own tools using three or four data sources specific to a particular strategy. Each quant spends up to four hours every day running scripts on a desktop computer to acquire and cross-reference just the data he needs. This means that in a firm with a number of quants, no-one has a view across all the data sources. One quant may fix a problem in a data source and other quants may see the problem, but not know that it has been fixed.

“We have developed Quant DB as a central research database that can be shared between quants and used to feed data into MatLab where models can be back-tested. It helps firms gain efficiencies and reduce research time, it improves the accuracy of data used by quants in models and it keeps quants’ know-how in house, reducing operational risk if a quant leaves the firm.”

From an operational perspective, the asset manager in production with Quant DB says its quants are getting the data they need faster and can focus on creating better investment strategies. The manager also has less reliance on quants’ individual knowledge through the use of a shared solution.

Martin Buchberger, CEO of AIM Software, concludes: “There s a trend towards optimising front-office data tools. Gain Quant DB helps asset managers industrialise processes, launch new models faster and keep know-how inside.”

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