GAIN Quant DB
GAIN Quant DB helps asset management firms to accelerate the research process by automating the tedious task of data preparation. It easily aggregates index and market data from multiple sources including Thomson Reuters QA Direct and stock exchanges to feed MatLab. Market data snapshots are created, stored centrally, and made available to all the quants for the development and validation of their models.
The issue of data preparation
Data preparation is a crucial step to guarantee best possible accuracy of the data underlying of new quantitative models before new funds are launched. In numerous cases, each quant is developing its own tools, scripts, databases, spreadsheets, meaning manually intensive, time-consuming and error-prone data preparation work. In worst cases, the know-how on datasets and tools leaves upon individual’s departure, leading to high operational risk for the institution.
Central data repository
GAIN Quant DB is a central data repository that automatically collects and cross-references data from various sources (e.g. Thomson Reuters Quantitative Analytics, Thomson Reuters DataStream, Worldscope, IBES, FTSE, MSCI), eliminating problems of staff developing their own scripts.
Snapshots of market data can be requested on demand by end users or generated automatically. GAIN Quant also supports "point in time"-functionality which reduces the risk of “look-ahead-bias” – a known issue in commercial databases happening when historical facts such as returns are revised under the light of new facts not known at the initial time of writing. Consequently, the time series available to the quants are more accurate and can be traced back.
Industrializing the research process
GAIN Quant DB helps asset managers to industrialize the data preparation processes in order to be faster in testing new models and new and investment strategies and therefore more efficient to launch funds.
This way, Quant DB enables the team to have a shared know-how and making the research process truly auditable even in the case after a team member decides to depart. As a result, researchers are faster in getting the data they need and can develop more accurate investment strategies with less effort.
Of course, full transparency as well as data control increase the trust of institutional investors and therefore the business of our clients.