Processing Knowledge

A critical component of financial research is sourcing the data. One of my previous post highlighted the importance of data mining for investing. A meaty amount of this data is present in the internet, however there are other offline sources of data which many a times is not easily accessible. The dearth of time has motivated many fund managers and financial analysts to outsource the work of mining not only the data available online but also the data available offlineto KPOs such as SG Analytics.

Mining Online Data:

Mining online data requires a lot of artifical intelligence and a flair for the mathematical tools used to get something meaningul from the data. The problem is partially solved by storing the data in custom databases the data as data presentation is a critical component of data mining. Once the raw data is stored in a structured format, a user interface is required to ontain the required subset of the data required for the mathematical analysis.

Mining EDGAR data

The problem is aggrevated when the data is present offline in the form of financial statements. Such data has to be first converted into a structured form in some database. This is a non trivial task as offline data is usually heavily unstructured and many a times requires multiple iterations if the data is poorly presented.

Mining and Presenting the Data:

Mining and Presenting Offline and Online Data

KPOs have lately mastered the art of not only mining the data and storing them in structured and custom databases but also in providing some user interfaces to easily access this data. This activity is a real timesaver for many financial researchers who previously had to manually mine the data.