GAIN Quant DB is a highly configurable aggregation database designed to accelerate the development of models and testing of strategies in MatLab, R or other analytics platforms. The system helps speed up research processes by automating tedious data preparation tasks. GAIN Quant DB aggregates and cross-references data from multiple sources (including Thomson Reuters QA, Bloomberg and stock exchanges) and creates reports that are seamlessly integrated into numerical computing environments, such as MATLAB.

Industrializing the research process

GAIN Quant DB helps investment and wealth managers to industrialize the data preparation processes and expedite the testing of new models and new investment strategies, ultimately enabling them to be more efficient in launching new funds.

GAIN Quant DB provides quant teams with a shared knowledgebase, while making the research process completely auditable. As a result, researchers get the data they need more quickly, allowing them to develop more accurate investment strategies in shorter timeframes.

The problems with manual data preparation

Effective data preparation is crucial for ensuring the accuracy of the data underlying new quantitative models before launching new funds.

However, at several firms, this data preparation process is manually-intensive, time-consuming and error-prone, as each quant develops their own tools, scripts, databases, and spreadsheets. Not only is this approach highly inefficient, it also leaves the firm open to high levels of operational and reputational risk.

The key to solving this issue is to automate the data aggregation process.

Central Aggregation Database

GAIN Quant DB is a central data repository that automatically collects and cross-references data from multiple sources (including Thomson Reuters Quantitative Analytics, Thomson Reuters DataStream, Worldscope, IBES, FTSE, MSCI), eliminating problems associated with staff developing their own scripts.

Snapshots of market data can be requested on demand by end users or generated automatically. GAIN Quant DB also supports “point in time” functionality, reducing the risk of “look-ahead-bias ”. The product provides quants staff with accurate time series data, which can be fully traced back.

With GAIN Quant DB, researchers can access the data they need more quickly. They can develop more accurate investment strategies with less effort, while full transparency and data control increase the trust of institutional investors. 

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