Research communities use the term Analytical Infrastructure (AI) to describe a vendor-agnostic data management platform that rests between data-intensive analytical tools and domain-specific data.
The systematic investment process involves the use of advanced analytical tools to consume data and quantitatively rank or score entities (such as stocks or bonds) based on algorithms written into the financial model. The primary goal behind the systematic investment process is to identify mispricing and manage overall portfolio risk; therefore, there are two primary dimensions: returns and risk. The systematic investment process is performed across various lines of the financial industry, including mutual funds, asset management, hedge funds, risk management, and funds of funds.
Having a data-intensive process doesn’t mean that you are consuming real-time tick data; instead, this means that you develop models that consume time-series data in order to make investment decisions.